In this paper, we study the scaling for the mean first-passage time （MFPT） of the random walks on a generalized Koch network with a trap. Through the network construction, where the initial state is transformed from...In this paper, we study the scaling for the mean first-passage time （MFPT） of the random walks on a generalized Koch network with a trap. Through the network construction, where the initial state is transformed from a triangle to a polygon, we obtain the exact scaling for the MFPT. We show that the MFPT grows linearly with the number of nodes and the dimensions of the polygon in the large limit of the network order. In addition, we determine the exponents of scaling efficiency characterizing the random walks. Our results are the generalizations of those derived for the Koch network, which shed light on the analysis of random walks over various fractal networks.展开更多
Studies on first-passage failure are extended to the multi-degree-of-freedom quasi-non-integrable-Hamiltonian systems under parametric excitations of Gaussian white noises in this paper. By the stochastic averaging me...Studies on first-passage failure are extended to the multi-degree-of-freedom quasi-non-integrable-Hamiltonian systems under parametric excitations of Gaussian white noises in this paper. By the stochastic averaging method of energy envelope, the system's energy can be modeled as a one-dimensional approximate diffusion process by which the classical Pontryagin equation with suitable boundary conditions is applicable to analyzing the statistical moments of the first-passage time of an arbitrary order. An example is studied in detail and some numerical results are given to illustrate the above procedure.展开更多
The mean first-passage time of a bistable system with time-delayed feedback driven by multiplicative non-Gaussian noise and additive Gaussian white noise is investigated. Firstly, the non-Markov process is reduced to ...The mean first-passage time of a bistable system with time-delayed feedback driven by multiplicative non-Gaussian noise and additive Gaussian white noise is investigated. Firstly, the non-Markov process is reduced to the Markov process through a path-integral approach; Secondly, the approximate Fokker-Planck equation is obtained by applying the unified coloured noise approximation, the small time delay approximation and the Novikov Theorem. The functional analysis and simplification are employed to obtain the approximate expressions of MFPT. The effects of non-Gaussian parameter （measures deviation from Gaussian character） r, the delay time τ, the noise correlation time to, the intensities D and a of noise on the MFPT are discussed. It is found that the escape time could be reduced by increasing the delay time τ, the noise correlation time τ0, or by reducing the intensities D and α. As far as we know, this is the first time to consider the effect of delay time on the mean first-passage time in the stochastic dynamical system.展开更多
In this paper, we consider the stationary probability and first-passage time of biased random walk on 1D chain, where at each step the walker moves to the left and right with probabilities p and q respectively(0 p, q ...In this paper, we consider the stationary probability and first-passage time of biased random walk on 1D chain, where at each step the walker moves to the left and right with probabilities p and q respectively(0 p, q 1,p + q = 1). We derive exact analytical results for the stationary probability and first-passage time as a function of p and q for the first time. Our results suggest that the first-passage time shows a double power-law F ^(N-1)~γ, where the exponent γ = 2 for N < |p-q|^(-1) and γ = 1 for N > |p-q|^(-1). Our study sheds useful insights into the biased random-walk process.展开更多
The mean first-passage time （MFPT） of an asymmetric bistable system between multiplicative non-Gaussian noise and additive Gaussian white noise with nonzero cross-correlation time is investigated. Firstly, the non-M...The mean first-passage time （MFPT） of an asymmetric bistable system between multiplicative non-Gaussian noise and additive Gaussian white noise with nonzero cross-correlation time is investigated. Firstly, the non-Markov process is reduced to the Markov process through a path-integral approach; Secondly, the approximate Fokker Planck equation is obtained by applying the unified colored noise approximation and the.Novikov Theorem. The steady-state probability distribution （SPD） is also obtained. The basal functional analysis and simplification are employed to obtain the approximate expressions of MFPT T^±. The effects of the asymmetry parameter β, the non-Gaussian parameter （measures deviation from Gaussian character） r, the noise correlation times τ and τ2, the coupling coefficient A, the intensities D and a of noise on the MFPT are discussed. It is found that the asymmetry parameter β, the non-Gaussian parameter r and the coupling coefficient A can induce phase transition. Moreover, the main findings are that the effect of self-existent parameters （D, α, and τ） of noise and cross-correlation parameters （A, 7-2） between noises on MFPT T^± is different.展开更多
In this paper, the effect of every parameter （including p, q, r, λ, τ） on the mean first-passage time （MFPT） is investigated in an asymmetric bistable system driven by colour-correlated noise. The expression of ...In this paper, the effect of every parameter （including p, q, r, λ, τ） on the mean first-passage time （MFPT） is investigated in an asymmetric bistable system driven by colour-correlated noise. The expression of MFPT has been obtained by applying the steepest-descent approximation. Numerical results show that （1） the intensity of multiplicative noise p and the intensity of additive noise q play different roles in the MFPT of the system, （2） suppression appears on the curve of the MFPT with small λ （e.g. λ 〈 0.5） but there is a peak on the curve of the MFPT when λ is big （e.g. λ 〉 0.5）, and （3） with different values of r （e.g. r = 0.1, 0.5, 1.5）, the effort of τ on the MFPT is diverse.展开更多
How to balance the size of exponentially growing cells has always been a focus of biologists.Recent experiments have uncovered that the cell is divided into two daughter cells only when the level of time-keeper protei...How to balance the size of exponentially growing cells has always been a focus of biologists.Recent experiments have uncovered that the cell is divided into two daughter cells only when the level of time-keeper protein reaches a fixed threshold and cell divi-sion in prokaryote is not completely symmetric.The timing of cell division is essentially random because gene expression is stochastic,but cells seen to manage to have precise timing of cell division events.Although the inter cellular variability of gene expression has attracted much attention,the randomness of event timing has been rarely studied.In our analysis,the timing of cell division is formulated as the first-passage time (denoted hy FPT) for time-keeper protein’s level to cross a critical threshold firstly,we derive exact analytical formulae for the mean and noise of FPT based on stochastic gene expression model with asymmetric cell division.The results of numerical simulation show that the regulatory factors (division rate,newborn cell size,exponential growth rate and threshold) have significant influence on the mean and noise of FPT.We also show that both the increase of division rate and newborn cell size could reduce the mean of FPT and increase the noise of FPT,the larger the exponential growth rate is,the smaller the mean and noise of FPT will be;and the larger the threshold value is,the higher the mean of FPT is and the lower the noise is.In addition,compared with symmetric divi sion,asymmetric division can reduce the mean of FPT and improve the noise of FPT.In summary,our results provide insight into the relationship between regulatory factors and FPT and reveal that asymmetric division is an effective mechanism to shorten the mean of FPT.展开更多
This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relativ...This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.展开更多
Hard disk drives(HDDs)serve as the primary storage devices in modern data centers.Once a failure occurs,it often leads to severe data loss,significantly degrading the reliability of storage systems.Numerous studies ha...Hard disk drives(HDDs)serve as the primary storage devices in modern data centers.Once a failure occurs,it often leads to severe data loss,significantly degrading the reliability of storage systems.Numerous studies have proposed machine learning-based HDD failure prediction models.However,the Self-Monitoring,Analysis,and Reporting Technology(SMART)attributes differ across HDD manufacturers.We define hard drives of the same brand and model as homogeneous HDD groups,and those from different brands or models as heterogeneous HDD groups.In practical engineering scenarios,a data center is often composed of a heterogeneous population of HDDs,spanning multiple vendors and models.Existing research predominantly focuses on homogeneous datasets,ignoring the model’s generalization capability across heterogeneous HDDs.As a result,HDD models with limited samples often suffer from poor training effectiveness and prediction performance.To address this issue,we investigate generalizable SMART predictors across heterogeneous HDD groups.By extracting time-series features within a fixed sliding time window,we propose a Heterogeneous Disk Failure Prediction Method based on Time Series Features(HDFPM)framework.This method is adaptable to HDD models with limited sample sizes,thereby enhancing its applicability and robustness across diverse drive populations.Experimental results show that the proposed model achieves an F1-score of 0.9518 when applied to two different Seagate HDD models,while maintaining the False Positive Rate(FPR)below 1%.After incorporating the Complexity-Ratio Dynamic Time Warping(CDTW)based feature enhancement method,the best prediction model achieves a True Positive Rate(TPR)of up to 0.93 between the two models.For next-day failure prediction across various Seagate models,the model achieves an F1-score of up to 0.8792.Moreover,the experimental results also show that within the same brand,the higher the proportion of shared SMART attributes across different models,the better the prediction performance.In addition,HDFPMdemonstrates the best stability andmost significant performance in heterogeneous environments.展开更多
This research is focused on the calculation of a reasonable detonator delay time for realizing cut blast vibration control.First,the viscoelastic rock mass parameters corresponding to the engineering rock mass quality...This research is focused on the calculation of a reasonable detonator delay time for realizing cut blast vibration control.First,the viscoelastic rock mass parameters corresponding to the engineering rock mass quality classification were determined based on wave theory of Kelvin medium.Then,a calculation model was obtained for the millisecond-delay cut blast vibration in Kelvin media using the Starfield charge superposition principle.Further,the influence of the delay time on the cut blast vibration was quantitatively analyzed and a method for calculating the reasonable cut blasting millisecond delay time is proposed according to the principle of dimensional analysis.Finally,field tests were used to verify the applicability of the method.The results show that 5 ms to 20 ms is a better detonator delay time range and cut blasting vibration can be effectively controlled using the delay time calculated by the calculation model described in this paper.展开更多
Flowering time is a critical agronomic trait with a profound effect on the productivity and adaptabillity of rapeseed(Brassica napus L.).Strategically advancing flowering time can reduce the risk of yield losses due t...Flowering time is a critical agronomic trait with a profound effect on the productivity and adaptabillity of rapeseed(Brassica napus L.).Strategically advancing flowering time can reduce the risk of yield losses due to extreme climatic conditions and facilitate the cultivation of subsequent crops on the same land,thereby enhancing overall agricultural efficiency.In this review,we synthesize current information on flowering time regulation in rapeseed through an integrated analysis of its genetic,hormonal,and environmental dimensions,emphasizing their crosstalk and implications for yield.We consolidate multi-omics evidence from population genetics,functional genomics,and systems biology to create a haplotype-based framework that overcomes the trade-off between flowering time and yield,providing support for the precision breeding of early-maturing cultivars.The insights presented here could inform future research on flowering time regulation and guide strategies for increasing rapeseed productivity.展开更多
Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative con...Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative control guidance law(ITCCG)that combines the optimal error dynamics with an improved adaptive cubature Kalman filter(IACKF)algorithm.First,a terminal impact time feedback term is introduced into proportional navigation guidance based on the relative virtual guidance model,and terminal time control is achieved through optimal error dynamics.Then,the Huber loss function is used to reduce the impact of measurement outliers,and the diagonal decomposition is applied to address the issue of non-positive definite matrices that cannot undergo Cholesky decomposition.Finally,the ITCCG and IACKF algorithms combined achieve multi-UAV time-cooperated guidance based on maneuvering target state estimation.Simulation results show that the proposed algorithm effectively reduces the target state estimation error and achieves cooperative guidance within the desired time frame.展开更多
To address the insufficient prediction accuracy of multi-state parameters in electro-hydraulic servo material fatigue testing machines under complex loading and nonlinear coupling conditions,this paper proposes a mult...To address the insufficient prediction accuracy of multi-state parameters in electro-hydraulic servo material fatigue testing machines under complex loading and nonlinear coupling conditions,this paper proposes a multivariate sequence-to-sequence prediction model integrating a Long Short-Term Memory(LSTM)encoder,a Gated Recurrent Unit(GRU)decoder,and a multi-head attention mechanism.This approach enhances prediction accuracy and robustness across different control modes and load spectra by leveraging multi-channel inputs and cross-variable feature interactions,thereby capturing both short-term high-frequency dynamics and long-term slow drift characteristics.Experiments using long-term data from real test benches demonstrate that the model achieves a stable MSE below 0.01 on the validation set,with MAE and RMSE of approximately 0.018 and 0.052,respectively,and a coefficient of determination reaching 0.98.This significantly outperforms traditional identification methods and single RNN models.Sensitivity analysis indicates that a prediction stride of 10 achieves an optimal balance between accuracy and computational overhead.Ablation experiments validated the contribution of multi-head attention and decoder architecture to enhancing cross-variable coupling modeling capabilities.This model can be applied to residualdriven early warning in health monitoring,and risk assessment with scheme optimization in test design.It enables near-real-time deployment feasibility,providing a practical data-driven technical pathway for reliability assurance in advanced equipment.展开更多
Severe trauma often involves complex injuries,leading to high disability and fatality rates.Effective treatment requires prompt and coordinated efforts across multiple disciplines to enhance success rates.Time-based c...Severe trauma often involves complex injuries,leading to high disability and fatality rates.Effective treatment requires prompt and coordinated efforts across multiple disciplines to enhance success rates.Time-based chain rescue is crucial in managing severe trauma.A patient with chest and abdominal injuries and hemorrhagic shock was transferred from an ambulance to our hospital.Our trauma team-initiated pre-hospital first aid,utilized an emergency green channel,and conducted rapid ultrasound,collaborating across disciplines.The patient eventually recovered and was discharged.展开更多
This article studies the consensus problem with directed graphs for general linear multi-agent systems.New distributed state-feedback protocols with dynamic event-triggered(DET)mechanisms are proposed for directed gra...This article studies the consensus problem with directed graphs for general linear multi-agent systems.New distributed state-feedback protocols with dynamic event-triggered(DET)mechanisms are proposed for directed graphs that are strongly connected and weight-balanced,general strongly connected,and have spanning trees,respectively.It is proven that strictly positive minimum inter-event times(MIETs)are ensured using the designed DET mechanisms.Several numerical examples are presented to illustrate the effectiveness of the theoretical results.Compared with existing results,our results have the following merits:1)DET mechanisms are designed to determine the sampling instants,which can reduce the communication frequency between agents compared with static mechanisms;2)We focus on the consensus problem on directed graphs,which is more general than existing related results on undirected graphs;3)The existence of positive MIETs is shown to be guaranteed by the designed DET sampling strategies while existing related results can only exclude Zeno behavior.展开更多
Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learni...Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learning tasks.To address this issue,a novel time-frequency-assisted deep feature enhancement(TFE)mechanism is proposed.Unlike traditional methods that integrate time-frequency analysis with deep neural networks,TFE employs a wavelet scattering transform to establish a parallel time-frequency feature space,where a dual interaction strategy facilitates collaboration between deep feature and time-frequency spaces through two operations:1)Enhancement,where a frequency-importance-driven contrastive learning(FICL)network transfers physically-aware information from wavelet scattering features to deep features,and 2)Feedback,which uses a detection rule adaptation module to minimize bias in wavelet scattering features based on deep feature performance.TFE is applied to a domain-adversarial anomaly detection framework and,through alternating training,significantly enhances both deep feature discriminative power and few-shot anomaly detection.Theoretical analysis confirms that the proposed dual interaction strategy reduces the upper bound of classification error.Experiments on benchmark datasets and a real-world industrial dataset from a large steel factory demonstrate TFE's superior performance and highlight the importance of frequency saliency in transfer learning.Thus,collaboration is shown to outperform integration for few-shot transfer learning in anomaly detection.展开更多
基金Project supported by the Research Foundation of Hangzhou Dianzi University,China (Grant Nos. KYF075610032 andzx100204004-7)the Hong Kong Research Grants Council,China (Grant No. CityU 1114/11E)
文摘In this paper, we study the scaling for the mean first-passage time （MFPT） of the random walks on a generalized Koch network with a trap. Through the network construction, where the initial state is transformed from a triangle to a polygon, we obtain the exact scaling for the MFPT. We show that the MFPT grows linearly with the number of nodes and the dimensions of the polygon in the large limit of the network order. In addition, we determine the exponents of scaling efficiency characterizing the random walks. Our results are the generalizations of those derived for the Koch network, which shed light on the analysis of random walks over various fractal networks.
基金The project supported by the Post-Doctoral Foundation of China
文摘Studies on first-passage failure are extended to the multi-degree-of-freedom quasi-non-integrable-Hamiltonian systems under parametric excitations of Gaussian white noises in this paper. By the stochastic averaging method of energy envelope, the system's energy can be modeled as a one-dimensional approximate diffusion process by which the classical Pontryagin equation with suitable boundary conditions is applicable to analyzing the statistical moments of the first-passage time of an arbitrary order. An example is studied in detail and some numerical results are given to illustrate the above procedure.
基金National Natural Science Foundation of China under Grant Nos.10472091,10332030,and 10502042
文摘The mean first-passage time of a bistable system with time-delayed feedback driven by multiplicative non-Gaussian noise and additive Gaussian white noise is investigated. Firstly, the non-Markov process is reduced to the Markov process through a path-integral approach; Secondly, the approximate Fokker-Planck equation is obtained by applying the unified coloured noise approximation, the small time delay approximation and the Novikov Theorem. The functional analysis and simplification are employed to obtain the approximate expressions of MFPT. The effects of non-Gaussian parameter （measures deviation from Gaussian character） r, the delay time τ, the noise correlation time to, the intensities D and a of noise on the MFPT are discussed. It is found that the escape time could be reduced by increasing the delay time τ, the noise correlation time τ0, or by reducing the intensities D and α. As far as we know, this is the first time to consider the effect of delay time on the mean first-passage time in the stochastic dynamical system.
基金Supported by the National Natural Science Foundation of China under Grant No.11205110Shanghai Key Laboratory of Intelligent Information Processing(IIPL-2011-009)Innovative Training Program for College Students under Grant No.2015xj070
文摘In this paper, we consider the stationary probability and first-passage time of biased random walk on 1D chain, where at each step the walker moves to the left and right with probabilities p and q respectively(0 p, q 1,p + q = 1). We derive exact analytical results for the stationary probability and first-passage time as a function of p and q for the first time. Our results suggest that the first-passage time shows a double power-law F ^(N-1)~γ, where the exponent γ = 2 for N < |p-q|^(-1) and γ = 1 for N > |p-q|^(-1). Our study sheds useful insights into the biased random-walk process.
基金supported by National Natural Science Foundation of China under Grant Nos.10472091,10332030,and 10502042
文摘The mean first-passage time （MFPT） of an asymmetric bistable system between multiplicative non-Gaussian noise and additive Gaussian white noise with nonzero cross-correlation time is investigated. Firstly, the non-Markov process is reduced to the Markov process through a path-integral approach; Secondly, the approximate Fokker Planck equation is obtained by applying the unified colored noise approximation and the.Novikov Theorem. The steady-state probability distribution （SPD） is also obtained. The basal functional analysis and simplification are employed to obtain the approximate expressions of MFPT T^±. The effects of the asymmetry parameter β, the non-Gaussian parameter （measures deviation from Gaussian character） r, the noise correlation times τ and τ2, the coupling coefficient A, the intensities D and a of noise on the MFPT are discussed. It is found that the asymmetry parameter β, the non-Gaussian parameter r and the coupling coefficient A can induce phase transition. Moreover, the main findings are that the effect of self-existent parameters （D, α, and τ） of noise and cross-correlation parameters （A, 7-2） between noises on MFPT T^± is different.
基金Project supported by the National Natural Science Foundation of China （Grants Nos 10472091, 10332030 and 10502042） and the Graduate Starting Seed Fund of Northwestern Polytechnical University （Grant No Z200655）.
文摘In this paper, the effect of every parameter （including p, q, r, λ, τ） on the mean first-passage time （MFPT） is investigated in an asymmetric bistable system driven by colour-correlated noise. The expression of MFPT has been obtained by applying the steepest-descent approximation. Numerical results show that （1） the intensity of multiplicative noise p and the intensity of additive noise q play different roles in the MFPT of the system, （2） suppression appears on the curve of the MFPT with small λ （e.g. λ 〈 0.5） but there is a peak on the curve of the MFPT when λ is big （e.g. λ 〉 0.5）, and （3） with different values of r （e.g. r = 0.1, 0.5, 1.5）, the effort of τ on the MFPT is diverse.
基金This work was supported by Natural Science Foundation of China Grants Nos. 11631005 (J.Y.), 11526203 (J.Y.), 11471085 (J.Y.), 11701117 (L.H.)2017A030310590 (L.H.)Key Research Platform and Research Project of Universities in Guangdong Province Grants Nos. 2018KQNCX244 (K.W.).
文摘How to balance the size of exponentially growing cells has always been a focus of biologists.Recent experiments have uncovered that the cell is divided into two daughter cells only when the level of time-keeper protein reaches a fixed threshold and cell divi-sion in prokaryote is not completely symmetric.The timing of cell division is essentially random because gene expression is stochastic,but cells seen to manage to have precise timing of cell division events.Although the inter cellular variability of gene expression has attracted much attention,the randomness of event timing has been rarely studied.In our analysis,the timing of cell division is formulated as the first-passage time (denoted hy FPT) for time-keeper protein’s level to cross a critical threshold firstly,we derive exact analytical formulae for the mean and noise of FPT based on stochastic gene expression model with asymmetric cell division.The results of numerical simulation show that the regulatory factors (division rate,newborn cell size,exponential growth rate and threshold) have significant influence on the mean and noise of FPT.We also show that both the increase of division rate and newborn cell size could reduce the mean of FPT and increase the noise of FPT,the larger the exponential growth rate is,the smaller the mean and noise of FPT will be;and the larger the threshold value is,the higher the mean of FPT is and the lower the noise is.In addition,compared with symmetric divi sion,asymmetric division can reduce the mean of FPT and improve the noise of FPT.In summary,our results provide insight into the relationship between regulatory factors and FPT and reveal that asymmetric division is an effective mechanism to shorten the mean of FPT.
文摘This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.
基金supported by the Tianjin Manufacturing High Quality Development Special Foundation(No.20232185)the Roycom Foundation(No.70306901).
文摘Hard disk drives(HDDs)serve as the primary storage devices in modern data centers.Once a failure occurs,it often leads to severe data loss,significantly degrading the reliability of storage systems.Numerous studies have proposed machine learning-based HDD failure prediction models.However,the Self-Monitoring,Analysis,and Reporting Technology(SMART)attributes differ across HDD manufacturers.We define hard drives of the same brand and model as homogeneous HDD groups,and those from different brands or models as heterogeneous HDD groups.In practical engineering scenarios,a data center is often composed of a heterogeneous population of HDDs,spanning multiple vendors and models.Existing research predominantly focuses on homogeneous datasets,ignoring the model’s generalization capability across heterogeneous HDDs.As a result,HDD models with limited samples often suffer from poor training effectiveness and prediction performance.To address this issue,we investigate generalizable SMART predictors across heterogeneous HDD groups.By extracting time-series features within a fixed sliding time window,we propose a Heterogeneous Disk Failure Prediction Method based on Time Series Features(HDFPM)framework.This method is adaptable to HDD models with limited sample sizes,thereby enhancing its applicability and robustness across diverse drive populations.Experimental results show that the proposed model achieves an F1-score of 0.9518 when applied to two different Seagate HDD models,while maintaining the False Positive Rate(FPR)below 1%.After incorporating the Complexity-Ratio Dynamic Time Warping(CDTW)based feature enhancement method,the best prediction model achieves a True Positive Rate(TPR)of up to 0.93 between the two models.For next-day failure prediction across various Seagate models,the model achieves an F1-score of up to 0.8792.Moreover,the experimental results also show that within the same brand,the higher the proportion of shared SMART attributes across different models,the better the prediction performance.In addition,HDFPMdemonstrates the best stability andmost significant performance in heterogeneous environments.
基金National Natural Science Foundation of China under Grant Nos.51979205 and 51939008。
文摘This research is focused on the calculation of a reasonable detonator delay time for realizing cut blast vibration control.First,the viscoelastic rock mass parameters corresponding to the engineering rock mass quality classification were determined based on wave theory of Kelvin medium.Then,a calculation model was obtained for the millisecond-delay cut blast vibration in Kelvin media using the Starfield charge superposition principle.Further,the influence of the delay time on the cut blast vibration was quantitatively analyzed and a method for calculating the reasonable cut blasting millisecond delay time is proposed according to the principle of dimensional analysis.Finally,field tests were used to verify the applicability of the method.The results show that 5 ms to 20 ms is a better detonator delay time range and cut blasting vibration can be effectively controlled using the delay time calculated by the calculation model described in this paper.
基金supported by the National Key Research and Development Program of China(2022YFD1200400)the National Natural Science Foundation of China(32272111)+4 种基金Special fund for youth team of the Southwest Universities(SWU-XJPY202306)Chongqing Natural Science Foundation(CSTB2024NSCQLZX0012)Modern Agro-industry Technology Research System(CARS-12)Chongqing Modern Agricultural Industry Technology System(COMAITS202504)Biological Breeding-National Science and Technology Major Project(2022ZD04008).We sincerely appreciate the Plant Editors team for English language editing of the manuscript,which significantly improved its clarity and overall quality.
文摘Flowering time is a critical agronomic trait with a profound effect on the productivity and adaptabillity of rapeseed(Brassica napus L.).Strategically advancing flowering time can reduce the risk of yield losses due to extreme climatic conditions and facilitate the cultivation of subsequent crops on the same land,thereby enhancing overall agricultural efficiency.In this review,we synthesize current information on flowering time regulation in rapeseed through an integrated analysis of its genetic,hormonal,and environmental dimensions,emphasizing their crosstalk and implications for yield.We consolidate multi-omics evidence from population genetics,functional genomics,and systems biology to create a haplotype-based framework that overcomes the trade-off between flowering time and yield,providing support for the precision breeding of early-maturing cultivars.The insights presented here could inform future research on flowering time regulation and guide strategies for increasing rapeseed productivity.
基金supported by the Fundamental Research Funds for the Central Universities of China(FRF-TP-24-058A)with additional support from the National Key Laboratory of Helicopter Aeromechanics(2024-ZSJ-LB-02-02).
文摘Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative control guidance law(ITCCG)that combines the optimal error dynamics with an improved adaptive cubature Kalman filter(IACKF)algorithm.First,a terminal impact time feedback term is introduced into proportional navigation guidance based on the relative virtual guidance model,and terminal time control is achieved through optimal error dynamics.Then,the Huber loss function is used to reduce the impact of measurement outliers,and the diagonal decomposition is applied to address the issue of non-positive definite matrices that cannot undergo Cholesky decomposition.Finally,the ITCCG and IACKF algorithms combined achieve multi-UAV time-cooperated guidance based on maneuvering target state estimation.Simulation results show that the proposed algorithm effectively reduces the target state estimation error and achieves cooperative guidance within the desired time frame.
基金supported by Natural Science Foundation of China(NSFC),Grant number 5247052693.
文摘To address the insufficient prediction accuracy of multi-state parameters in electro-hydraulic servo material fatigue testing machines under complex loading and nonlinear coupling conditions,this paper proposes a multivariate sequence-to-sequence prediction model integrating a Long Short-Term Memory(LSTM)encoder,a Gated Recurrent Unit(GRU)decoder,and a multi-head attention mechanism.This approach enhances prediction accuracy and robustness across different control modes and load spectra by leveraging multi-channel inputs and cross-variable feature interactions,thereby capturing both short-term high-frequency dynamics and long-term slow drift characteristics.Experiments using long-term data from real test benches demonstrate that the model achieves a stable MSE below 0.01 on the validation set,with MAE and RMSE of approximately 0.018 and 0.052,respectively,and a coefficient of determination reaching 0.98.This significantly outperforms traditional identification methods and single RNN models.Sensitivity analysis indicates that a prediction stride of 10 achieves an optimal balance between accuracy and computational overhead.Ablation experiments validated the contribution of multi-head attention and decoder architecture to enhancing cross-variable coupling modeling capabilities.This model can be applied to residualdriven early warning in health monitoring,and risk assessment with scheme optimization in test design.It enables near-real-time deployment feasibility,providing a practical data-driven technical pathway for reliability assurance in advanced equipment.
基金Jiangsu Provincial Hospital Association Hospital Management Innovation Research Fund(Project Ni.:JSYGY-3-2025-267)。
文摘Severe trauma often involves complex injuries,leading to high disability and fatality rates.Effective treatment requires prompt and coordinated efforts across multiple disciplines to enhance success rates.Time-based chain rescue is crucial in managing severe trauma.A patient with chest and abdominal injuries and hemorrhagic shock was transferred from an ambulance to our hospital.Our trauma team-initiated pre-hospital first aid,utilized an emergency green channel,and conducted rapid ultrasound,collaborating across disciplines.The patient eventually recovered and was discharged.
基金supported in part by the Natural Science Foundation of China(62273227,92367203)the Open Research Project of the State Key Laboratory of Industrial Control Technology,China(ICT2024B68)。
文摘This article studies the consensus problem with directed graphs for general linear multi-agent systems.New distributed state-feedback protocols with dynamic event-triggered(DET)mechanisms are proposed for directed graphs that are strongly connected and weight-balanced,general strongly connected,and have spanning trees,respectively.It is proven that strictly positive minimum inter-event times(MIETs)are ensured using the designed DET mechanisms.Several numerical examples are presented to illustrate the effectiveness of the theoretical results.Compared with existing results,our results have the following merits:1)DET mechanisms are designed to determine the sampling instants,which can reduce the communication frequency between agents compared with static mechanisms;2)We focus on the consensus problem on directed graphs,which is more general than existing related results on undirected graphs;3)The existence of positive MIETs is shown to be guaranteed by the designed DET sampling strategies while existing related results can only exclude Zeno behavior.
基金supported in part by the National Natural Science Foundation of China(62472146)the Key Technologies Research Development Joint Foundation of Henan Province of China(225101610001)。
文摘Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learning tasks.To address this issue,a novel time-frequency-assisted deep feature enhancement(TFE)mechanism is proposed.Unlike traditional methods that integrate time-frequency analysis with deep neural networks,TFE employs a wavelet scattering transform to establish a parallel time-frequency feature space,where a dual interaction strategy facilitates collaboration between deep feature and time-frequency spaces through two operations:1)Enhancement,where a frequency-importance-driven contrastive learning(FICL)network transfers physically-aware information from wavelet scattering features to deep features,and 2)Feedback,which uses a detection rule adaptation module to minimize bias in wavelet scattering features based on deep feature performance.TFE is applied to a domain-adversarial anomaly detection framework and,through alternating training,significantly enhances both deep feature discriminative power and few-shot anomaly detection.Theoretical analysis confirms that the proposed dual interaction strategy reduces the upper bound of classification error.Experiments on benchmark datasets and a real-world industrial dataset from a large steel factory demonstrate TFE's superior performance and highlight the importance of frequency saliency in transfer learning.Thus,collaboration is shown to outperform integration for few-shot transfer learning in anomaly detection.
