The practical predictability of hail precipitation rates is significantly influenced by initial meteorological perturbations,stemming from various uncertainty sources.This study thoroughly assessed the predictability ...The practical predictability of hail precipitation rates is significantly influenced by initial meteorological perturbations,stemming from various uncertainty sources.This study thoroughly assessed the predictability of hail precipitation rates in both climatologically and flow-dependent perturbed ensembles(CEns and FEns).These ensembles incorporated initial meteorological uncertainties derived separately from two operational ensembles.Leveraging the Weather Research and Forecasting model,we conducted cloud-resolving simulations of an idealized hailstorm.The practical predictability of hail responded comparably to both climatological and flow-dependent uncertainties,which was revealed across the entire ensemble of 50 members.However,a notable difference emerged when comparing the peak hail precipitation rates among the top 10 and bottom 10 members.From a thermodynamic perspective,the primary source of uncertainty in hail precipitation lay in the significant variations in temperature stratification,particularly at-20℃and-40℃.On the microphysical front,perturbations within CEns generated greater uncertainty in the process of rainwater collection by hail,contributing significantly to the microphysical growth mechanisms of hail.Furthermore,the findings reveal a stronger dependency of hail precipitation uncertainty on thermodynamic perturbations compared to kinematic perturbations.These insights enhance the comprehension of the practical predictability of hail and contribute significantly to the understanding of ensemble forecasting for hail events.展开更多
Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-targe...Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the“therapeutic module”of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.展开更多
In recent years,universal adversarial per-turbation(UAP)has attracted the attention of many re-searchers due to its good generalization.However,in order to generate an appropriate UAP,current methods usually require e...In recent years,universal adversarial per-turbation(UAP)has attracted the attention of many re-searchers due to its good generalization.However,in order to generate an appropriate UAP,current methods usually require either accessing the original dataset or meticulously constructing optimization functions and proxy datasets.In this paper,we aim to elimi-nate any dependency on proxy datasets and explore a method for generating Universal Adversarial Pertur-bations(UAP)on a single image.After revisiting re-search on UAP,we discovered that the key to gener-ating UAP lies in the accumulation of Individual Ad-versarial Perturbation(IAP)gradient,which prompted us to study the method of accumulating gradients from an IAP.We designed a simple and effective process to generate UAP,which only includes three steps:pre-cessing,generating an IAP and scaling the perturba-tions.Through our proposed process,any IAP gener-ated on an image can be constructed into a UAP with comparable performance,indicating that UAP can be generated free of data.Extensive experiments on var-ious classifiers and attack approaches demonstrate the superiority of our method on efficiency and aggressiveness.展开更多
Pangu-Weather(PGW),trained with deep learning–based methods(DL-based model),shows significant potential for global medium-range weather forecasting.However,the interpretability and trustworthiness of global medium-ra...Pangu-Weather(PGW),trained with deep learning–based methods(DL-based model),shows significant potential for global medium-range weather forecasting.However,the interpretability and trustworthiness of global medium-range DLbased models raise many concerns.This study uses the singular vector(SV)initial condition(IC)perturbations of the China Meteorological Administration's Global Ensemble Prediction System(CMA-GEPS)as inputs of PGW for global ensemble prediction(PGW-GEPS)to investigate the ensemble forecast sensitivity of DL-based models to the IC errors.Meanwhile,the CMA-GEPS forecasts serve as benchmarks for comparison and verification.The spatial structures and prediction performance of PGW-GEPS are discussed and compared to CMA-GEPS based on seasonal ensemble experiments.The results show that the ensemble mean and dispersion of PGW-GEPS are similar to those of CMA-GEPS in the medium range but with smoother forecasts.Meanwhile,PGW-GEPS is sensitive to the SV IC perturbations.Specifically,PGWGEPS can generate realistic ensemble spread beyond the sub-synoptic scale(wavenumbers≤64)with SV IC perturbations.However,PGW's kinetic energy is significantly reduced at the sub-synoptic scale,leading to error growth behavior inconsistent with CMA-GEPS at that scale.Thus,this behavior indicates that the effective resolution of PGW-GEPS is beyond the sub-synoptic scale and is limited to predicting mesoscale atmospheric motions.In terms of the global mediumrange ensemble prediction performance,the probability prediction skill of PGW-GEPS is comparable to CMA-GEPS in the extratropic when they use the same IC perturbations.That means that PGW has a general ability to provide skillful global medium-range forecasts with different ICs from numerical weather prediction.展开更多
This study rigorously examines the interplay between viscous dissipation,magnetic effects,and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro...This study rigorously examines the interplay between viscous dissipation,magnetic effects,and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro cantilever channel,aiming to deepen our understanding of heat transport processes in complex fluid dynamics scenarios.The primary objective is to elucidate how physical operational parameters influence both the velocity of fluid flow and its temperature distribution,utilizing a comprehensive numerical approach.Employing a combination of mathematical modeling techniques,including similarity transformation,this investigation transforms complex partial differential equations into more manageable ordinary ones,subsequently solving them using the homotopy perturbation method.By analyzing the obtained solutions and presenting them graphically,alongside detailed analysis,the study sheds light on the pivotal role of significant parameters in shaping fluid movement and energy distribution.Noteworthy observations reveal a substantial increase in fluid velocity with escalating magnetic parameters,while conversely,a contrasting trend emerges in the temperature distribution,highlighting the intricate relationship between magnetic effects,flow dynamics,and thermal behavior in non-Newtonian fluids.Further,the suction velocity enhance both the local skin friction and Nusselt numbers,whereas theWeissenberg number reduces them,opposite to the effect of the power-law index.展开更多
Hydraulic fracturing then fluid circulation in enhanced geothermal system(EGS)reservoirs have been shown to induce seismicity remote from the stimulation-potentially generated by the distal projection of thermoporoela...Hydraulic fracturing then fluid circulation in enhanced geothermal system(EGS)reservoirs have been shown to induce seismicity remote from the stimulation-potentially generated by the distal projection of thermoporoelastic stresses.We explore this phenomenon by evaluating stress perturbations resulting from stimulation of a single stage of hydraulic fracturing that is followed by thermal depletion of a prismatic zone adjacent to the hydraulic fracture.We use Coulomb failure stress to assess the effect of resulting stress perturbations on instability on adjacent critically-stressed faults.Results show that hydraulic fracturing in a single stage is capable of creating stress perturbations at distances to 1000 m that reach 10^(-5)-10^(-4)MPa.At a closer distance,the magnitude of stress perturbations increases even further.The stress perturbation induced by temperature depletion could also reach 10^(-3)-10^(-2)MPa within 1000 m-much higher than that by hydraulic fracturing.Considering that a critical change in Coulomb failure stress for fault instability is 10^(-2)MPa,a single stage of hydraulic fracturing and thermal drawdown are capable of reactivating critically-stressed faults at distances within 200 m and 1000 m,respectively.These results have important implications for understanding the distribution and magnitudes of stress perturbations driven by thermoporoelastic effects and the associated seismicity during the simulation and early production of EGS reservoirs.展开更多
Recent advances in wearable devices have enabled large-scale collection of sensor data across healthcare,sports,and other domains but this has also raised critical privacy concerns,especially under tightening regulati...Recent advances in wearable devices have enabled large-scale collection of sensor data across healthcare,sports,and other domains but this has also raised critical privacy concerns,especially under tightening regulations such as the General Data Protection Regulation(GDPR),which explicitly restrict the processing of data that can re-identify individuals.Although existing anonymization approaches such as the AnonymizingAutoEncoder(AAE)can reduce the risk of re-identification,they often introduce substantial waveform distortions and fail to preserve information beyond a single classification task(e.g.,human activity recognition).This study proposes a novel sensor data anonymization method based onAdversarial Perturbations(AP)to address these limitations.By generating minimal yet targeted noise,the proposed method significantly degrades the accuracy of identity classification while retaining essential features for multiple tasks such as activity,gender,or device-position recognition.Moreover,to enhance robustness against frequency-domain analysis,additional models trained on transformed(e.g.,short-time Fourier transform(STFT))representations are incorporated into the perturbation process.A multi-task formulation is introduced that selectively suppresses person-identifying features while reinforcing those relevant to other desired tasks without retraining large autoencoder-based architectures.The proposed framework is,to our knowledge,the first AP-based anonymization technique that(i)defends simultaneously against time-and frequency-domain attacks and(ii)allows per-task trade-off control on a single forward-back-propagation run,enabling real-time,on-device deployment on commodity hardware.On three public datasets,the proposed method reduces person-identification accuracy from 60–90%to near-chance levels(≤5%)while preserving the original activity-recognition F1 both in the time and frequency domains.Compared with the baseline AAE,the proposed method improves downstream task F1 and lowers waveform mean squared error,demonstrating a better privacy-utility trade-off without additional model retraining.These findings underscore the effectiveness and flexibility of AP in privacy-preserving sensor-data processing,offering a practical solution that safeguards user identity while retaining rich,application-critical information.展开更多
Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly effi...Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly efficient calculations for O-CNOPs are still challenging in the field of ensemble forecasting.In this study,we combine a gradient-based iterative idea with the Gram‒Schmidt orthogonalization,and propose an iterative optimization method to compute O-CNOPs.This method is different from the original sequential optimization method,and allows parallel computations of O-CNOPs,thus saving a large amount of computational time.We evaluate this method by using the Lorenz-96 model on the basis of the ensemble forecasting ability achieved and on the time consumed for computing O-CNOPs.The results demonstrate that the parallel iterative method causes O-CNOPs to yield reliable ensemble members and to achieve ensemble forecasting skills similar to or even slightly higher than those produced by the sequential method.Moreover,the parallel method significantly reduces the computational time for O-CNOPs.Therefore,the parallel iterative method provides a highly effective and efficient approach for calculating O-CNOPs for ensemble forecasts.Expectedly,it can play an important role in the application of the O-CNOPs to realistic ensemble forecasts for high-impact weather and climate events.展开更多
Toroidal torques,generated by the resonant magnetic perturbation(RMP)and acting on the plasma column,are numerically systematically investigated for an ITER baseline scenario.The neoclassical toroidal viscosity(NTV),i...Toroidal torques,generated by the resonant magnetic perturbation(RMP)and acting on the plasma column,are numerically systematically investigated for an ITER baseline scenario.The neoclassical toroidal viscosity(NTV),in particular the resonant portion,is found to provide the dominant contribution to the total toroidal torque under the slow plasma flow regime in ITER.While the electromagnetic torque always opposes the plasma flow,the toroidal torque associated with the Reynolds stress enhances the plasma flow independent of the flow direction.A peculiar double-peak structure for the net NTV torque is robustly computed for ITER,as the toroidal rotation frequency is scanned near the zero value.This structure is found to be ultimately due to a non-monotonic behavior of the wave-particle resonance integral(over the particle pitch angle)in the superbanana plateau NTV regime in ITER.These findings are qualitatively insensitive to variations of a range of factors including the wall resistivity,the plasma pedestal flow and the assumed frequency of the rotating RMP field.展开更多
The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typic...The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typically input multiple time slices without deterministic dependencies.In this study,the CNOP for DLMs(CNOP-DL)is proposed as an extension of the CNOP in the time dimension.This method is useful for targeted observations as it indicates not only where but also when to deploy additional observations.The CNOP-DL is calculated for a forecast case of sea surface temperature in the South China Sea with a DLM.The CNOP-DL identifies a sensitive area northwest of Palawan Island at the last input time.Sensitivity experiments demonstrate that the sensitive area identified by the CNOP-DL is effective not only for the CNOP-DL itself,but also for random perturbations.Therefore,this approach holds potential for guiding practical field campaigns.Notably,forecast errors are more sensitive to time than to location in the sensitive area.It highlights the crucial role of identifying the time of the sensitive area in targeted observations,corroborating the usefulness of extending the CNOP in the time dimension.展开更多
A large number of runaway electrons(REs)generated during disruption can cause significant damage to next-generation large-scale tokamaks.The influence of three-dimensional(3D)helical magnetic perturbations on the supp...A large number of runaway electrons(REs)generated during disruption can cause significant damage to next-generation large-scale tokamaks.The influence of three-dimensional(3D)helical magnetic perturbations on the suppression of RE generation was explored using a set of 3D helical coils in J-TEXT tokamak,which can excite m/n=-2/2 helical magnetic perturbations.Experimental evidence shows that the-2/2 magnetic perturbations caused by the opposite coil current direct plasma toward the high-field side,simultaneously enhancing the magnetic fluctuations,which would enhance the radial loss of REs and even prevent RE generation.On the other hand,-2/2 magnetic perturbations can also reduce the cooling time during the disruption phase and generate a population of high-energy REs,which can interact with high-frequency magnetic fluctuations and in turn suppress RE generation.The critical helical coil current was found to correlate with electron density,requiring higher coil currents at higher densities.According to the statistical analysis of RE generation at different electron densities,the applied-2/2 magnetic perturbations can increase the magnetic fluctuations to the same level at lower electron densities,which can decrease the threshold electron density for RE suppression.This will be beneficial for RE mitigation in future large tokamak devices.展开更多
This paper deals with the monotonicity of limit wave speed c0(h)to a perturbed g KdV equation.We show the decrease of c0(h)by combining the analytic method and the numerical technique.Our results solve a special case ...This paper deals with the monotonicity of limit wave speed c0(h)to a perturbed g KdV equation.We show the decrease of c0(h)by combining the analytic method and the numerical technique.Our results solve a special case of the open question presented by Yan et al.,and the method potentially provides a way to study the monotonicity of c0(h)for general m∈N^(+).展开更多
Due to uncertainties in initial conditions and parameters, the stability and uncertainty of grassland ecosystem simulations using ecosystem models are issues of concern. Our objective is to determine the types and pat...Due to uncertainties in initial conditions and parameters, the stability and uncertainty of grassland ecosystem simulations using ecosystem models are issues of concern. Our objective is to determine the types and patterns of initial and parameter perturbations that yield the greatest instability and uncertainty in simulated grassland ecosystems using theoretical models. We used a nonlinear optimization approach, i.e., a conditional nonlinear optimal perturbation related to initial and parameter perturbations （CNOP） approach, in our work. Numerical results indicated that the CNOP showed a special and nonlinear optimal pattern when the initial state variables and multiple parameters were considered simultaneously. A visibly different complex optimal pattern characterizing the CNOPs was obtained by choosing different combinations of initial state variables and multiple parameters in different physical processes. We propose that the grassland modeled ecosystem caused by the CNOP-type perturbation is unstable and exhibits two aspects： abrupt change and the time needed for the abrupt change from a grassland equilibrium state to a desert equilibrium state when the initial state variables and multiple parameters are considered simultaneously. We compared these findings with results affected by the CNOPs obtained by considering only uncertainties in initial state variables and in a single parameter. The numerical results imply that the nonlinear optimal pattern of initial perturbations and parameter perturbations, especially for more parameters or when special parameters are involved, plays a key role in determining stabilities and uncertainties associated with a simulated or predicted grassland ecosystem.展开更多
Making exact approximations to solve equations distinguishes applied mathematicians from pure mathematicians, physicists, and engineers. Perturbation problems, both regular and singular, are pervasive in diverse field...Making exact approximations to solve equations distinguishes applied mathematicians from pure mathematicians, physicists, and engineers. Perturbation problems, both regular and singular, are pervasive in diverse fields of applied mathematics and engineering. This research paper provides a comprehensive overview of algebraic methods for solving perturbation problems, featuring a comparative analysis of their strengths and limitations. Serving as a valuable resource for researchers and practitioners, it offers insights and guidance for tackling perturbation problems in various disciplines, facilitating the advancement of applied mathematics and engineering.展开更多
We used high-pass filtering and the Fourier transform to analyze tidal gravity data prior to five earthquakes from four superconducting gravity stations around the world. A stable gravitational perturbation signal is ...We used high-pass filtering and the Fourier transform to analyze tidal gravity data prior to five earthquakes from four superconducting gravity stations around the world. A stable gravitational perturbation signal is received within a few days before the earthquakes. The gravitational perturbation signal before the Wenchuan earthquake on May 12, 2008 has main frequency of 0.1–0.3 Hz, and the other four have frequency bands of 0.12-0.17 Hz and 0.06-0.085 Hz. For earthquakes in continental and oceanic plate fault zones, gravity anomalies often appear on the superconducting gravimeters away from the epicenter, whereas the stations near the epicenter record small or no anomalies. The results suggest that this kind of gravitational perturbation signals correlate with earthquake occurrence, making them potentially useful earthquake predictors. The far-field effect of the gravitational perturbation signals may reveal the interaction mechanisms of the Earth’s tectonic plates. However, owing to the uneven distribution of gravity tide stations, the results need to be further confirmed in the future.展开更多
In this paper,making use of upper and lower solutions,we first prove the existence of the solu tion for integral differential equation of Volterra type.Then applying the theory of differential in equalities obtained,u...In this paper,making use of upper and lower solutions,we first prove the existence of the solu tion for integral differential equation of Volterra type.Then applying the theory of differential in equalities obtained,under the appropriate assumptions,by constructing the special function of upper and lower solutions,we demonstrate the existence of the solution for singularly preturbed integral differential equation of Volterra type,and give the uniformly valid approximate estimation.展开更多
In this paper, a class of nonlinear singularly perturbed initial boundary value problems for reaction diffusion equations with boundary perturbation are considered under suitable conditions. Firstly, by dint of the re...In this paper, a class of nonlinear singularly perturbed initial boundary value problems for reaction diffusion equations with boundary perturbation are considered under suitable conditions. Firstly, by dint of the regular perturbation method, the outer solution of the original problem is obtained. Secondly, by using the stretched variable and the expansion theory of power series the initial layer of the solution is constructed. And then, by using the theory of differential inequalities, the asymptotic behavior of the solution for the initial boundary value problems is studied. Finally, using some relational inequalities the existence and uniqueness of solution for the original problem and the uniformly valid asymptotic estimation are discussed.展开更多
In this paper, we study a class singular perturbed elliptic equation boundary value problem with a super surface of turning point in n-dimensional space by using the method of multiple scales and the comparison theore...In this paper, we study a class singular perturbed elliptic equation boundary value problem with a super surface of turning point in n-dimensional space by using the method of multiple scales and the comparison theorem. The uniformly valid asymptotic approxmations of solutions for the boundary value problem is constructed.展开更多
The current paper establishes the analytical models of the long-term evolution and perturbation compensation strategy for Medium Earth Orbits（MEO）shallow-resonant navigation constellation,with application to the Chi...The current paper establishes the analytical models of the long-term evolution and perturbation compensation strategy for Medium Earth Orbits（MEO）shallow-resonant navigation constellation,with application to the Chinese Bei Dou Navigation Satellite System（BDS）.The long-term perturbation model for the relative motion is developed based on the Hamiltonian model,and the long-term evolution law is analyzed.The relationship between the control boundary of the constellation and the offset of the orbital elements is analyzed,and a general analytical method for calculating the offset of the orbit elements is proposed.The analytical model is further improved when the luni-solar perturbations are included.The long-term evolutions of the BDS MEO constellation within 10 years are illustrated,and the effectiveness of the proposed analytical perturbation compensation calculation approach is compared with the traditional numerical results.We found the fundamental reason for the nonlinear variations of the relative longitude of ascending node and the mean argument of latitude is the long-periodic variations of the orbital inclination due to the luni-solar perturbations.The proposed analytical approach can avoid the numerical iterations,and reveal the essential relationship between the orbital element offsets and the secular drifts of the constellation configuration.Moreover,there is no need for maintaining the BDS MEO constellation within 10 years while using the perturbation compensation method.展开更多
The singularly perturbed elliptic equation boundary value problem with turning point is considered. Using the method of multiple scales and the comparison theorem, the asymptotic behavior of solution for the boundary ...The singularly perturbed elliptic equation boundary value problem with turning point is considered. Using the method of multiple scales and the comparison theorem, the asymptotic behavior of solution for the boundary value problem is studied.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42005005 and 42030607)the Science and Technology Department of Shaanxi Province(Grant No.2024JC-YBQN-0248)+2 种基金the Education Department of Shaanxi Province(Grant No.23JK0686)a Xi'an Science and Technology Project(Grant No.22GXFW0131)the Young Talent fund of the University Association for Science and Technology in Shaanxi(Grant No.20210706)。
文摘The practical predictability of hail precipitation rates is significantly influenced by initial meteorological perturbations,stemming from various uncertainty sources.This study thoroughly assessed the predictability of hail precipitation rates in both climatologically and flow-dependent perturbed ensembles(CEns and FEns).These ensembles incorporated initial meteorological uncertainties derived separately from two operational ensembles.Leveraging the Weather Research and Forecasting model,we conducted cloud-resolving simulations of an idealized hailstorm.The practical predictability of hail responded comparably to both climatological and flow-dependent uncertainties,which was revealed across the entire ensemble of 50 members.However,a notable difference emerged when comparing the peak hail precipitation rates among the top 10 and bottom 10 members.From a thermodynamic perspective,the primary source of uncertainty in hail precipitation lay in the significant variations in temperature stratification,particularly at-20℃and-40℃.On the microphysical front,perturbations within CEns generated greater uncertainty in the process of rainwater collection by hail,contributing significantly to the microphysical growth mechanisms of hail.Furthermore,the findings reveal a stronger dependency of hail precipitation uncertainty on thermodynamic perturbations compared to kinematic perturbations.These insights enhance the comprehension of the practical predictability of hail and contribute significantly to the understanding of ensemble forecasting for hail events.
基金supported by the National Natural Science Foundation of China(Grant Nos.:32271292,31872723,32200778,and 22377089)the Jiangsu Students Innovation and Entrepre-neurship Training Program,China(Program No.:202210285081Z)+6 种基金the Project of MOE Key Laboratory of Geriatric Diseases and Immunology,China(Project No.:JYN202404)Proj-ect Funded by the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions,Natural Science Foundation of Jiangsu Province,China(Project No.:BK20220494)Suzhou Medical and Health Technology Innovation Project,China(Grant No.:SKY2022107)the Clinical Research Center of Neuro-logical Disease in The Second Affiliated Hospital of Soochow University,China(Grant No.:ND2022A04)State Key Laboratory of Drug Research(Grant No.:SKLDR-2023-KF-05)Jiangsu Shuang-chuang Program for Doctor,Young Science Talents Promotion Project of Jiangsu Science and Technology Association(Program No.:TJ-2023-019)Young Science Talents Promotion Project of Suzhou Science and Technology Association,Suzhou International Joint Laboratory for Diagnosis and Treatment of Brain Diseases,and startup funding(Grant Nos.:NH21500221,NH21500122,and NH21500123)to Qifei Cong.
文摘Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the“therapeutic module”of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.
基金supported in part by the Natural Science Foundation of China under Grant 62372395in part by the Research Foundation of Education Bureau of Hunan Province under Grant No.24A0105in part by the Postgraduate Scientific Research Innovation Project of Hunan Province(Grant No.CX20230546).
文摘In recent years,universal adversarial per-turbation(UAP)has attracted the attention of many re-searchers due to its good generalization.However,in order to generate an appropriate UAP,current methods usually require either accessing the original dataset or meticulously constructing optimization functions and proxy datasets.In this paper,we aim to elimi-nate any dependency on proxy datasets and explore a method for generating Universal Adversarial Pertur-bations(UAP)on a single image.After revisiting re-search on UAP,we discovered that the key to gener-ating UAP lies in the accumulation of Individual Ad-versarial Perturbation(IAP)gradient,which prompted us to study the method of accumulating gradients from an IAP.We designed a simple and effective process to generate UAP,which only includes three steps:pre-cessing,generating an IAP and scaling the perturba-tions.Through our proposed process,any IAP gener-ated on an image can be constructed into a UAP with comparable performance,indicating that UAP can be generated free of data.Extensive experiments on var-ious classifiers and attack approaches demonstrate the superiority of our method on efficiency and aggressiveness.
基金supported by the joint funds of the Chinese National Natural Science Foundation(NSFC)(Grant No.U2242213)the funds of the NSFC(Grant No.42341209)+2 种基金the National Key Research and Development(R&D)Program of the Ministry of Science and Technology of China(Grant No.2021YFC3000902)the National Science Foundation for Young Scholars(Grant No.42205166)the Joint Research Project for Meteorological Capacity Improvement(Grant No.22NLTSQ008)。
文摘Pangu-Weather(PGW),trained with deep learning–based methods(DL-based model),shows significant potential for global medium-range weather forecasting.However,the interpretability and trustworthiness of global medium-range DLbased models raise many concerns.This study uses the singular vector(SV)initial condition(IC)perturbations of the China Meteorological Administration's Global Ensemble Prediction System(CMA-GEPS)as inputs of PGW for global ensemble prediction(PGW-GEPS)to investigate the ensemble forecast sensitivity of DL-based models to the IC errors.Meanwhile,the CMA-GEPS forecasts serve as benchmarks for comparison and verification.The spatial structures and prediction performance of PGW-GEPS are discussed and compared to CMA-GEPS based on seasonal ensemble experiments.The results show that the ensemble mean and dispersion of PGW-GEPS are similar to those of CMA-GEPS in the medium range but with smoother forecasts.Meanwhile,PGW-GEPS is sensitive to the SV IC perturbations.Specifically,PGWGEPS can generate realistic ensemble spread beyond the sub-synoptic scale(wavenumbers≤64)with SV IC perturbations.However,PGW's kinetic energy is significantly reduced at the sub-synoptic scale,leading to error growth behavior inconsistent with CMA-GEPS at that scale.Thus,this behavior indicates that the effective resolution of PGW-GEPS is beyond the sub-synoptic scale and is limited to predicting mesoscale atmospheric motions.In terms of the global mediumrange ensemble prediction performance,the probability prediction skill of PGW-GEPS is comparable to CMA-GEPS in the extratropic when they use the same IC perturbations.That means that PGW has a general ability to provide skillful global medium-range forecasts with different ICs from numerical weather prediction.
文摘This study rigorously examines the interplay between viscous dissipation,magnetic effects,and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro cantilever channel,aiming to deepen our understanding of heat transport processes in complex fluid dynamics scenarios.The primary objective is to elucidate how physical operational parameters influence both the velocity of fluid flow and its temperature distribution,utilizing a comprehensive numerical approach.Employing a combination of mathematical modeling techniques,including similarity transformation,this investigation transforms complex partial differential equations into more manageable ordinary ones,subsequently solving them using the homotopy perturbation method.By analyzing the obtained solutions and presenting them graphically,alongside detailed analysis,the study sheds light on the pivotal role of significant parameters in shaping fluid movement and energy distribution.Noteworthy observations reveal a substantial increase in fluid velocity with escalating magnetic parameters,while conversely,a contrasting trend emerges in the temperature distribution,highlighting the intricate relationship between magnetic effects,flow dynamics,and thermal behavior in non-Newtonian fluids.Further,the suction velocity enhance both the local skin friction and Nusselt numbers,whereas theWeissenberg number reduces them,opposite to the effect of the power-law index.
基金funded by the National Natural Science Foundation of China(Grant Nos.42107163 and 42320104003)support from the G.Albert Shoemaker endowment.
文摘Hydraulic fracturing then fluid circulation in enhanced geothermal system(EGS)reservoirs have been shown to induce seismicity remote from the stimulation-potentially generated by the distal projection of thermoporoelastic stresses.We explore this phenomenon by evaluating stress perturbations resulting from stimulation of a single stage of hydraulic fracturing that is followed by thermal depletion of a prismatic zone adjacent to the hydraulic fracture.We use Coulomb failure stress to assess the effect of resulting stress perturbations on instability on adjacent critically-stressed faults.Results show that hydraulic fracturing in a single stage is capable of creating stress perturbations at distances to 1000 m that reach 10^(-5)-10^(-4)MPa.At a closer distance,the magnitude of stress perturbations increases even further.The stress perturbation induced by temperature depletion could also reach 10^(-3)-10^(-2)MPa within 1000 m-much higher than that by hydraulic fracturing.Considering that a critical change in Coulomb failure stress for fault instability is 10^(-2)MPa,a single stage of hydraulic fracturing and thermal drawdown are capable of reactivating critically-stressed faults at distances within 200 m and 1000 m,respectively.These results have important implications for understanding the distribution and magnitudes of stress perturbations driven by thermoporoelastic effects and the associated seismicity during the simulation and early production of EGS reservoirs.
基金supported in part by the Japan Society for the Promotion of Science(JSPS)KAKENHI Grant-in-Aid for Scientific Research(C)under Grants 23K11164.
文摘Recent advances in wearable devices have enabled large-scale collection of sensor data across healthcare,sports,and other domains but this has also raised critical privacy concerns,especially under tightening regulations such as the General Data Protection Regulation(GDPR),which explicitly restrict the processing of data that can re-identify individuals.Although existing anonymization approaches such as the AnonymizingAutoEncoder(AAE)can reduce the risk of re-identification,they often introduce substantial waveform distortions and fail to preserve information beyond a single classification task(e.g.,human activity recognition).This study proposes a novel sensor data anonymization method based onAdversarial Perturbations(AP)to address these limitations.By generating minimal yet targeted noise,the proposed method significantly degrades the accuracy of identity classification while retaining essential features for multiple tasks such as activity,gender,or device-position recognition.Moreover,to enhance robustness against frequency-domain analysis,additional models trained on transformed(e.g.,short-time Fourier transform(STFT))representations are incorporated into the perturbation process.A multi-task formulation is introduced that selectively suppresses person-identifying features while reinforcing those relevant to other desired tasks without retraining large autoencoder-based architectures.The proposed framework is,to our knowledge,the first AP-based anonymization technique that(i)defends simultaneously against time-and frequency-domain attacks and(ii)allows per-task trade-off control on a single forward-back-propagation run,enabling real-time,on-device deployment on commodity hardware.On three public datasets,the proposed method reduces person-identification accuracy from 60–90%to near-chance levels(≤5%)while preserving the original activity-recognition F1 both in the time and frequency domains.Compared with the baseline AAE,the proposed method improves downstream task F1 and lowers waveform mean squared error,demonstrating a better privacy-utility trade-off without additional model retraining.These findings underscore the effectiveness and flexibility of AP in privacy-preserving sensor-data processing,offering a practical solution that safeguards user identity while retaining rich,application-critical information.
基金sponsored by the National Natural Science Foundation of China(Grant Nos.41930971,42330111,and 42405061)the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(Earth Lab).
文摘Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly efficient calculations for O-CNOPs are still challenging in the field of ensemble forecasting.In this study,we combine a gradient-based iterative idea with the Gram‒Schmidt orthogonalization,and propose an iterative optimization method to compute O-CNOPs.This method is different from the original sequential optimization method,and allows parallel computations of O-CNOPs,thus saving a large amount of computational time.We evaluate this method by using the Lorenz-96 model on the basis of the ensemble forecasting ability achieved and on the time consumed for computing O-CNOPs.The results demonstrate that the parallel iterative method causes O-CNOPs to yield reliable ensemble members and to achieve ensemble forecasting skills similar to or even slightly higher than those produced by the sequential method.Moreover,the parallel method significantly reduces the computational time for O-CNOPs.Therefore,the parallel iterative method provides a highly effective and efficient approach for calculating O-CNOPs for ensemble forecasts.Expectedly,it can play an important role in the application of the O-CNOPs to realistic ensemble forecasts for high-impact weather and climate events.
基金funded by National Natural Science Foundation of China(NSFC)(Nos.12075053,11505021 and 11975068)by National Key R&D Program of China(No.2022YFE 03060002)+1 种基金by Fundamental Research Funds for the Central Universities(No.2232024G-10)supported by the U.S.DoE Office of Science(No.DE-FG02–95ER54309)。
文摘Toroidal torques,generated by the resonant magnetic perturbation(RMP)and acting on the plasma column,are numerically systematically investigated for an ITER baseline scenario.The neoclassical toroidal viscosity(NTV),in particular the resonant portion,is found to provide the dominant contribution to the total toroidal torque under the slow plasma flow regime in ITER.While the electromagnetic torque always opposes the plasma flow,the toroidal torque associated with the Reynolds stress enhances the plasma flow independent of the flow direction.A peculiar double-peak structure for the net NTV torque is robustly computed for ITER,as the toroidal rotation frequency is scanned near the zero value.This structure is found to be ultimately due to a non-monotonic behavior of the wave-particle resonance integral(over the particle pitch angle)in the superbanana plateau NTV regime in ITER.These findings are qualitatively insensitive to variations of a range of factors including the wall resistivity,the plasma pedestal flow and the assumed frequency of the rotating RMP field.
基金supported by the National Natural Science Foundation of China (Grant No. 42288101, 42375062, 42476192, 42275158)the National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (Earth Lab)the GHfund C (202407036001)
文摘The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typically input multiple time slices without deterministic dependencies.In this study,the CNOP for DLMs(CNOP-DL)is proposed as an extension of the CNOP in the time dimension.This method is useful for targeted observations as it indicates not only where but also when to deploy additional observations.The CNOP-DL is calculated for a forecast case of sea surface temperature in the South China Sea with a DLM.The CNOP-DL identifies a sensitive area northwest of Palawan Island at the last input time.Sensitivity experiments demonstrate that the sensitive area identified by the CNOP-DL is effective not only for the CNOP-DL itself,but also for random perturbations.Therefore,this approach holds potential for guiding practical field campaigns.Notably,forecast errors are more sensitive to time than to location in the sensitive area.It highlights the crucial role of identifying the time of the sensitive area in targeted observations,corroborating the usefulness of extending the CNOP in the time dimension.
基金supported by the National Magnetic Confinement Fusion Energy R&D Program of China (Nos.2018YFE0309103 and 2019YFE03010004)National Natural Science Foundation of China (Nos.12475222,12205122,and 51821005)Hubei International Science and Technology Cooperation Projects (No.2022EHB003)。
文摘A large number of runaway electrons(REs)generated during disruption can cause significant damage to next-generation large-scale tokamaks.The influence of three-dimensional(3D)helical magnetic perturbations on the suppression of RE generation was explored using a set of 3D helical coils in J-TEXT tokamak,which can excite m/n=-2/2 helical magnetic perturbations.Experimental evidence shows that the-2/2 magnetic perturbations caused by the opposite coil current direct plasma toward the high-field side,simultaneously enhancing the magnetic fluctuations,which would enhance the radial loss of REs and even prevent RE generation.On the other hand,-2/2 magnetic perturbations can also reduce the cooling time during the disruption phase and generate a population of high-energy REs,which can interact with high-frequency magnetic fluctuations and in turn suppress RE generation.The critical helical coil current was found to correlate with electron density,requiring higher coil currents at higher densities.According to the statistical analysis of RE generation at different electron densities,the applied-2/2 magnetic perturbations can increase the magnetic fluctuations to the same level at lower electron densities,which can decrease the threshold electron density for RE suppression.This will be beneficial for RE mitigation in future large tokamak devices.
基金Supported by the National Natural Science Foundation of China(12071162)the Natural Science Foundation of Fujian Province(2021J01302)the Fundamental Research Funds for the Central Universities(ZQN-802)。
文摘This paper deals with the monotonicity of limit wave speed c0(h)to a perturbed g KdV equation.We show the decrease of c0(h)by combining the analytic method and the numerical technique.Our results solve a special case of the open question presented by Yan et al.,and the method potentially provides a way to study the monotonicity of c0(h)for general m∈N^(+).
基金provided by grants from National Natural Science Foundation of China (Grant Nos. 40905050and 40830955)the Chinese Academy of Sciences (CASGrant No. KZCX3-SW-230)
文摘Due to uncertainties in initial conditions and parameters, the stability and uncertainty of grassland ecosystem simulations using ecosystem models are issues of concern. Our objective is to determine the types and patterns of initial and parameter perturbations that yield the greatest instability and uncertainty in simulated grassland ecosystems using theoretical models. We used a nonlinear optimization approach, i.e., a conditional nonlinear optimal perturbation related to initial and parameter perturbations （CNOP） approach, in our work. Numerical results indicated that the CNOP showed a special and nonlinear optimal pattern when the initial state variables and multiple parameters were considered simultaneously. A visibly different complex optimal pattern characterizing the CNOPs was obtained by choosing different combinations of initial state variables and multiple parameters in different physical processes. We propose that the grassland modeled ecosystem caused by the CNOP-type perturbation is unstable and exhibits two aspects： abrupt change and the time needed for the abrupt change from a grassland equilibrium state to a desert equilibrium state when the initial state variables and multiple parameters are considered simultaneously. We compared these findings with results affected by the CNOPs obtained by considering only uncertainties in initial state variables and in a single parameter. The numerical results imply that the nonlinear optimal pattern of initial perturbations and parameter perturbations, especially for more parameters or when special parameters are involved, plays a key role in determining stabilities and uncertainties associated with a simulated or predicted grassland ecosystem.
文摘Making exact approximations to solve equations distinguishes applied mathematicians from pure mathematicians, physicists, and engineers. Perturbation problems, both regular and singular, are pervasive in diverse fields of applied mathematics and engineering. This research paper provides a comprehensive overview of algebraic methods for solving perturbation problems, featuring a comparative analysis of their strengths and limitations. Serving as a valuable resource for researchers and practitioners, it offers insights and guidance for tackling perturbation problems in various disciplines, facilitating the advancement of applied mathematics and engineering.
基金supported by the National Science Fund of China Project(Nos.41174104 and 41472301)the Project of Innovation-driven Plan in Central South University(No.2015CX008)
文摘We used high-pass filtering and the Fourier transform to analyze tidal gravity data prior to five earthquakes from four superconducting gravity stations around the world. A stable gravitational perturbation signal is received within a few days before the earthquakes. The gravitational perturbation signal before the Wenchuan earthquake on May 12, 2008 has main frequency of 0.1–0.3 Hz, and the other four have frequency bands of 0.12-0.17 Hz and 0.06-0.085 Hz. For earthquakes in continental and oceanic plate fault zones, gravity anomalies often appear on the superconducting gravimeters away from the epicenter, whereas the stations near the epicenter record small or no anomalies. The results suggest that this kind of gravitational perturbation signals correlate with earthquake occurrence, making them potentially useful earthquake predictors. The far-field effect of the gravitational perturbation signals may reveal the interaction mechanisms of the Earth’s tectonic plates. However, owing to the uneven distribution of gravity tide stations, the results need to be further confirmed in the future.
文摘In this paper,making use of upper and lower solutions,we first prove the existence of the solu tion for integral differential equation of Volterra type.Then applying the theory of differential in equalities obtained,under the appropriate assumptions,by constructing the special function of upper and lower solutions,we demonstrate the existence of the solution for singularly preturbed integral differential equation of Volterra type,and give the uniformly valid approximate estimation.
基金Project supported by the National Natural Science Foundation of China （Nos. 40676016, 10471039）, the National Key Basic Research Special Foundation of China （No. 2004CB418304）, the Key Basic Research Foundation of the Chinese Academy of Sciences （No. KZCX3-SW-221） and in part by EInstitutes of Shanghai Municipal Education Commission （No. E03004）
文摘In this paper, a class of nonlinear singularly perturbed initial boundary value problems for reaction diffusion equations with boundary perturbation are considered under suitable conditions. Firstly, by dint of the regular perturbation method, the outer solution of the original problem is obtained. Secondly, by using the stretched variable and the expansion theory of power series the initial layer of the solution is constructed. And then, by using the theory of differential inequalities, the asymptotic behavior of the solution for the initial boundary value problems is studied. Finally, using some relational inequalities the existence and uniqueness of solution for the original problem and the uniformly valid asymptotic estimation are discussed.
文摘In this paper, we study a class singular perturbed elliptic equation boundary value problem with a super surface of turning point in n-dimensional space by using the method of multiple scales and the comparison theorem. The uniformly valid asymptotic approxmations of solutions for the boundary value problem is constructed.
基金supported by the National Natural Science Foundation of China (No. 61403416)
文摘The current paper establishes the analytical models of the long-term evolution and perturbation compensation strategy for Medium Earth Orbits（MEO）shallow-resonant navigation constellation,with application to the Chinese Bei Dou Navigation Satellite System（BDS）.The long-term perturbation model for the relative motion is developed based on the Hamiltonian model,and the long-term evolution law is analyzed.The relationship between the control boundary of the constellation and the offset of the orbital elements is analyzed,and a general analytical method for calculating the offset of the orbit elements is proposed.The analytical model is further improved when the luni-solar perturbations are included.The long-term evolutions of the BDS MEO constellation within 10 years are illustrated,and the effectiveness of the proposed analytical perturbation compensation calculation approach is compared with the traditional numerical results.We found the fundamental reason for the nonlinear variations of the relative longitude of ascending node and the mean argument of latitude is the long-periodic variations of the orbital inclination due to the luni-solar perturbations.The proposed analytical approach can avoid the numerical iterations,and reveal the essential relationship between the orbital element offsets and the secular drifts of the constellation configuration.Moreover,there is no need for maintaining the BDS MEO constellation within 10 years while using the perturbation compensation method.
文摘The singularly perturbed elliptic equation boundary value problem with turning point is considered. Using the method of multiple scales and the comparison theorem, the asymptotic behavior of solution for the boundary value problem is studied.
