In order to study the universality of the interactions among different markets, we analyze the cross-correlation matrix of the price of the Chinese and American bank stocks. We then find that the stock prices of the e...In order to study the universality of the interactions among different markets, we analyze the cross-correlation matrix of the price of the Chinese and American bank stocks. We then find that the stock prices of the emerging market are more correlated than that of the developed market. Considering that the values of the components for the eigenvector may be positive or negative, we analyze the differences between two markets in combination with the endogenous and exogenous events which influence the financial markets. We find that the sparse pattern of components of eigenvectors out of the threshold value has no change in American bank stocks before and after the subprime crisis. However, it changes from sparse to dense for Chinese bank stocks. By using the threshold value to exclude the external factors, we simulate the interactions in financial markets.展开更多
Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with ot...Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.展开更多
To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ens...To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ensemble empirical mode decomposition(EEMD)and cross-correlation algorithm was proposed.Firstly,a fast Fourier transform(FFT)spectrum analysis was utilized to ascertain the frequency range of the signal.Secondly,data acquisition was conducted at an appropriate sampling frequency,and the acquired Doppler flow rate signal was then decomposed into a series of intrinsic mode functions(IMFs)by EEMD.Subsequently,these decomposed IMFs were recombined based on their energy entropy,and then the noise of the recombined Doppler flow rate signal was removed by cross-correlation filtering.Finally,an ideal ultrasonic Doppler flow rate signal was extracted.Simulation and experimental verification show that the proposed Doppler flow signal processing method can effectively enhance the signal-to-noise ratio(SNR)and extend the lower limit of measurement of the ultrasonic Doppler flow meter.展开更多
The improved cross-correlation algorithm for the strain demodulation of Vernier-effect-based optical fiber sensor(VE-OFS)is proposed in this article.The algorithm identifies the most similar spectrum to the measured o...The improved cross-correlation algorithm for the strain demodulation of Vernier-effect-based optical fiber sensor(VE-OFS)is proposed in this article.The algorithm identifies the most similar spectrum to the measured one from the database of the collected spectra by employing the cross-correlation operation,subsequently deriving the predicted value via weighted calculation.As the algorithm uses the complete information in the measured raw spectrum,more accurate results and larger measurement range can be obtained.Additionally,the improved cross-correlation algorithm also has the potential to improve the measurement speed compared to current standards due to the possibility for the collection using low sampling rate.This work presents an important algorithm towards a simpler,faster way to improve the demodulation performance of VE-OFS.展开更多
Traditional cross-correlation algorithms are prone to time-of-flight(TOF)calculation errors under conditions of strong noise interference and complex temperature gradients,resulting in a decline in the accuracy of ult...Traditional cross-correlation algorithms are prone to time-of-flight(TOF)calculation errors under conditions of strong noise interference and complex temperature gradients,resulting in a decline in the accuracy of ultrasonic temperature measurement.To this end,this paper proposes an ultrasonic temperature measurement method that combines YOLOv11 target detection with energy-type weighted cross-correlation algorithm.The YOLOv11 model is utilized to conduct target detection and key area positioning on the ultrasonic signal waveform diagram,automatically identifying characteristic waveforms such as node waves and end face waves,and achieving adaptive extraction of the effective signal interval.Further introduce the energy-based weighted cross-correlation algorithm.Based on the signal energy distribution,the cross-correlation results are weighted and processed to enhance the main wave response and suppress noise interference.Experiments show that the YOLOv11 model has high detection accuracy(Precision=0.987,Recall=0.958,mAP@50=0.988);The proposed method maintains the stability of time delay estimation under strong noise and high temperature(>1200℃),with the average time delay error reduced by approximately 35%to 50%compared to traditional algorithms.This verifies its high robustness and temperature measurement accuracy in complex environments,and it has a promising engineering application prospect.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
Driven by advancements in mobile internet technology,images have become a crucial data medium.Ensuring the security of image information during transmission has thus emerged as an urgent challenge.This study proposes ...Driven by advancements in mobile internet technology,images have become a crucial data medium.Ensuring the security of image information during transmission has thus emerged as an urgent challenge.This study proposes a novel image encryption algorithm specifically designed for grayscale image security.This research introduces a new Cantor diagonal matrix permutation method.The proposed permutation method uses row and column index sequences to control the Cantor diagonal matrix,where the row and column index sequences are generated by a spatiotemporal chaotic system named coupled map lattice(CML).The high initial value sensitivity of the CML system makes the permutation method highly sensitive and secure.Additionally,leveraging fractal theory,this study introduces a chaotic fractal matrix and applies this matrix in the diffusion process.This chaotic fractal matrix exhibits selfsimilarity and irregularity.Using the Cantor diagonal matrix and chaotic fractal matrix,this paper introduces a fast image encryption algorithm involving two diffusion steps and one permutation step.Moreover,the algorithm achieves robust security with only a single encryption round,ensuring high operational efficiency.Experimental results show that the proposed algorithm features an expansive key space,robust security,high sensitivity,high efficiency,and superior statistical properties for the ciphered images.Thus,the proposed algorithm not only provides a practical solution for secure image transmission but also bridges fractal theory with image encryption techniques,thereby opening new research avenues in chaotic cryptography and advancing the development of information security technology.展开更多
Generative steganography uses generative stego images to transmit secret message.It also effectively defends against statistical steganalysis.However,most existing methods focus primarily on matching the feature distr...Generative steganography uses generative stego images to transmit secret message.It also effectively defends against statistical steganalysis.However,most existing methods focus primarily on matching the feature distribution of training data,often neglecting the sequential continuity between moves in the game.This oversight can result in unnatural patterns that deviate from real user behavior,thereby reducing the security of the hidden communication.To address this issue,we design a Gomoku agent based on the AlphaZero algorithm.The model engages in self-play to generate a sequence of plausible moves.These moves formthe basis of the stego images.We then apply an attractionmatrix at each step.It guides themove selection so that themoves appearmore natural.Thismethod helps maintain logical flow between moves.It also extends the game length,which increases the embedding capacity.Next,we filter and prioritize the generated moves.The selected moves are embedded into a move pool.Secret message is mapped to thesemoves.It is then embedded step by step as the game progresses.The finalmove sequence constitutes a complete steganographic game record.The receiver can extract the secret message using this record and a predefined mapping rule.Experiments show that our method reaches a maximum embedding capacity of 223 bits per carrier.Detection accuracy is 0.500 under XuNet and 0.498 under YeNet.These results are equal to random guessing,showing strong imperceptibility.The proposed method demonstrates superior concealment,higher embedding capacity,and greater robustness against common image distortions and steganalysis attacks.展开更多
Traditional nerve repair methods,such as autologous nerve grafting and allogeneic nerve grafting,face issues such as donor shortage,functional loss,and immune rejection.Decellularized extracellular matrix-based grafts...Traditional nerve repair methods,such as autologous nerve grafting and allogeneic nerve grafting,face issues such as donor shortage,functional loss,and immune rejection.Decellularized extracellular matrix-based grafts have emerged as highly promising alternatives,capable of uniquely recreating the natural neural mic roenvironment,promoting host cell remodeling,and ultimately enhancing functional neural regeneration.This review comprehensively analyzes the key mechanisms of peripheral nerve injury and regeneration,focusing on contemporary therapeutic strategies for key aspects such as axonal apoptosis inhibition,enhanced intrinsic regenerative capacity,construction of regenerative microenvironment,and prevention of target organ atrophy.Findings from this review has shown that decellularized extra cellular matrix grafts can promote the migration,prolife ration,and differentiation of nerve cells by providing physical suppo rt,chemical signals,and mechanical stability.Decellularized extracellular matrix grafts are mainly used as ne rve conduits,scaffolds,hydrogels,and3D printing inks.Decellularized extra cellular matrix grafts have demonstrated significant advantages in promoting nerve regeneration by regulating the prolife ration and differentiation of Schwann cells,improving the neural microenvironment,reducing inflammato ry responses,and promoting angiogenesis.Additionally,decellularized extracellular matrix grafts can se rve as drug carrie rs,enabling the controlled release of growth factors,which further enhances nerve regeneration.However,these grafts also have some limitations,including the presence of immunogenic residues,inadequate mechanical prope rties,inter-batch variability,and uncontrollable degradation rates.Future research should focus on optimizing the decellularization process,enhancing the mechanical prope rties of decellularized extracellular matrix grafts,reducing immunogenicity,improving biocompatibility and safety,and developing new composite mate rials.Furthermore,exploring their application potential in complex nerve injuries,such as diabetic neuropathy,is crucial to meet the needs of peripheral nerve regeneration and repair.展开更多
We read with the great interest the study by Ababneh et al in which inducedmesenchymal stem cell-derived exosomes were shown to exhibit a stronger andmore sustained anti-proliferative effect by inducing a senescence-l...We read with the great interest the study by Ababneh et al in which inducedmesenchymal stem cell-derived exosomes were shown to exhibit a stronger andmore sustained anti-proliferative effect by inducing a senescence-like state withoutapoptosis.The results obtained by the authors highlight the features of theeffects of senescent drift induction in surrounding tissues.In the light of thesefindings,the role of the properties of extracellular matrix and cellular glycocalyxin responses of human tumors to therapy remain uninvestigated.These extracellularbarriers appear to be significant obstacles to effective cancer therapy,especiallyin relation to the use of unique properties of tumor microenvironment forthe immunotherapy-resistant cancer treatment.展开更多
The effect of adding hydroxycinnamic acids(caffeic acid,sinapic acid,p-coumaric acid and chlorogenic acid)in Cabernet Sauvignon dry red wine before and after fermentation was investigated,taking into account the color...The effect of adding hydroxycinnamic acids(caffeic acid,sinapic acid,p-coumaric acid and chlorogenic acid)in Cabernet Sauvignon dry red wine before and after fermentation was investigated,taking into account the color parameters,anthocyanin content,and overall polyphenol levels in the wine samples.The copigmentation effect of malvidin-3-Oglucoside and sinapic acid was further explored in model solution and through theoretical calculations.The results indicated that the addition of hydroxycinnamic acids significantly enhanced the wine's color with sinapic acid(before the fermentation)showing the most pronounced color protection effect.Compared to control samples,the addition of hydroxycinnamic acids resulted in a 36%increase in total phenolic content and a 28% increase in total anthocyanin content.Thermodynamic analysis revealed that the interaction between sinapic acid and malvidin-3-O-glucoside was spontaneous and exothermic.Theoretical studies identified hydrogen bonding(HB)and dispersion forces as the main primary stabilizing forces,with the carboxyl group of sinapic acid playing a critical role while the anthocyanin backbone also influenced the interaction.展开更多
The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix sp...The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix splitting methods.Taking the decomposition of the diagonal elements for coefficient matrix as the key point,some new preconditioners are constructed.Taking the tri-diagonal coefficient matrix as an example,the convergence domains and optimal relaxation factor of the new method are analyzed theoretically.The presented new iteration methods are applied to solve linear algebraic equations,even 2D and 3D diffusion problems with the fully implicit discretization.The results of numerical experiments are matched with the theoretical analysis,and show that the iteration numbers are reduced greatly.The superiorities of presented iteration methods exceed some classical iteration methods dramatically.展开更多
With the rapid advancement of electromagnetic launch technology,enhancing the structural stability and thermal resistance of armatures has become essential for improving the overall efficiency and reliability of railg...With the rapid advancement of electromagnetic launch technology,enhancing the structural stability and thermal resistance of armatures has become essential for improving the overall efficiency and reliability of railgun systems.Traditional aluminum alloy armatures often suffer from severe ablation,deformation,and uneven current distribution under high pulsed currents,which limit their performance and service life.To address these challenges,this study employs the Johnson–Cook constitutive model and the finite element method to develop armature models of aluminum matrix composites with varying heterogeneous graphene volume fractions.The temperature,stress,and strain of the armatures during operation were analyzed to investigate the effects of different graphene volume fractions on the deformation and damage behavior of aluminum matrix composite armatures under the multi-field coupling of electromagnetic,thermal,and structural interactions.The results indicate that,compared to the 6061 aluminum alloy matrix,the graphene-reinforced aluminum matrix composite armature significantly suppresses ablation damage at the tail and throat edges.The incorporation of graphene notably reduces the temperature rise during the armature emission process,increases the muzzle velocity under identical current excitation,and mitigates directional deformation of the armature.The 1 wt.% graphene-reinforced aluminum matrix composite armature demonstrates better agreement with experimental results at a strain rate of 2000 s^(-1),while simultaneously improving stress-strain response,reducing temperature rise,and improving velocity performance.展开更多
Mg alloys have garnered significant attention in advanced engineering applications due to their exceptional combination of specificstrength and lightweight properties.Theα-Mg solid solution,which constitutes the core...Mg alloys have garnered significant attention in advanced engineering applications due to their exceptional combination of specificstrength and lightweight properties.Theα-Mg solid solution,which constitutes the core component of Mg alloys,directly governs the alloy’sthermodynamic behavior,kinetic response,and overall performance.This paper systematically reviews the effects of theα-Mg matrix phase onmechanical properties(e.g.,when the average grain size of pure Mg is refined from 59.7μm to 1.57μm,the alloy’s yield strength increasesby 122 MPa),corrosion resistance(e.g.,adding 0.5%Gd and 0.5%Sc to pure Mg reduces the alloy’s weight loss rate from 208.71 mm/yearto 0.29 mm/year),damping properties,electromagnetic shielding properties,and flame retardancy,and reveals the microscopic interactionmechanisms between the matrix phase,solute atoms,crystal defects,and second phases.Furthermore,this paper critically analyzes the keyrole of the matrix phase in emerging fields such as bio-Mg alloys(e.g.,controlled degradation rate design),Mg-air batteries(e.g.,anodeefficiency optimization),and Mg-based hydrogen storage materials(e.g.,enhancement of hydrogen absorption/desorption kinetics).Finally,this paper explores the significant potential of data-driven methods in the design and development of next-generation high-performance Mgalloys.展开更多
Efficient implementation of fundamental matrix operations on quantum computers,such as matrix products and Hadamard operations,holds significant potential for accelerating machine learning algorithms.A critical prereq...Efficient implementation of fundamental matrix operations on quantum computers,such as matrix products and Hadamard operations,holds significant potential for accelerating machine learning algorithms.A critical prerequisite for quantum implementations is the effective encoding of classical data into quantum states.We propose two quantum computing frameworks for preparing the distinct encoded states corresponding to matrix operations,including the matrix product,matrix sum,matrix Hadamard product and division.Quantum algorithms based on the digital encoding computing framework are capable of implementing the matrix Hadamard operation with a time complexity of O(poly log(mn/ε))and the matrix product with a time complexity of O(poly log(mnl/ε)),achieving an exponential speedup in contrast to the classical methods of O(mn)and O(mnl).Quantum algorithms based on the analog-encoding framework are capable of implementing the matrix Hadamard operation with a time complexity of O(k_(1)√mn·poly log(mn/ε))and the matrix product with a time complexity of O(k_(2)√1·poly log(mnl/ε)),where k_(1)and k_(2)are coefficients correlated with the elements of the matrix,achieving a square speedup in contrast to the classical counterparts.As applications,we construct an oracle that can access the trace of a matrix within logarithmic time,and propose several algorithms to respectively estimate the trace of a matrix,the trace of the product of two matrices,and the trace inner product of two matrices within logarithmic time.展开更多
Evaluating the adversarial robustness of classification algorithms in machine learning is a crucial domain.However,current methods lack measurable and interpretable metrics.To address this issue,this paper introduces ...Evaluating the adversarial robustness of classification algorithms in machine learning is a crucial domain.However,current methods lack measurable and interpretable metrics.To address this issue,this paper introduces a visual evaluation index named confidence centroid skewing quadrilateral,which is based on a classification confidence-based confusion matrix,offering a quantitative and visual comparison of the adversarial robustness among different classification algorithms,and enhances intuitiveness and interpretability of attack impacts.We first conduct a validity test and sensitive analysis of the method.Then,prove its effectiveness through the experiments of five classification algorithms including artificial neural network(ANN),logistic regression(LR),support vector machine(SVM),convolutional neural network(CNN)and transformer against three adversarial attacks such as fast gradient sign method(FGSM),DeepFool,and projected gradient descent(PGD)attack.展开更多
This study investigates the anisotropic thermal conductivity of aluminum matrix composites reinforced with graphene nano-plates(GNPs)and in situ ZrB_(2) nanoparticles,while simultaneously maintaining high strength and...This study investigates the anisotropic thermal conductivity of aluminum matrix composites reinforced with graphene nano-plates(GNPs)and in situ ZrB_(2) nanoparticles,while simultaneously maintaining high strength and toughness.A discontinuous layered GNPs-ZrB_(2)/AA6111 composite was prepared using in situ melt reactions and semi-solid stirring casting technology,combined with hot rolling deformation processing.Microstructural analysis revealed that the GNPs were aligned parallel to the rolling direction-transverse direction(RD-TD)plane,whereas the ZrB_(2) nanoparticles aggregated into cluster strips,collectively forming a discontinuous layered structure.This multilayer arrangement maximized the in-plane thermal conductivity of the GNPs.The tightly bonded GNP/Al interfaces with the locking of CuAl_(2) nanoparticles ensured that the GNPs fully exploited their high thermal conductivity.Therefore,the GNPs-ZrB_(2)/AA6111 composite achieved high in-plane thermal conductivity(230 W/(m·K)),which is higher than that of the matrix(206 W/(m·K)).The improved in-plane thermal conductivity is primarily attributed to the exceptionally high intrinsic in-plane thermal conductivity of the GNPs and their two-dimensional layered structure.However,the composite exhibited pronounced thermal conductivity anisotropy in the in-plane and through-plane directions.The reduced through-plane thermal conductivity is predominantly caused by the intrinsically low through-plane thermal conductivity of the GNPs and the increased interfacial thermal resistance from the additional grain boundaries.展开更多
In the present work,the porous Ti particle reinforced Mg-based bulk metallic glass matrix composites(BMGCs)have been successfully fabricated via a novel in-situ dealloying method in metallic melt.A dual reinforcing st...In the present work,the porous Ti particle reinforced Mg-based bulk metallic glass matrix composites(BMGCs)have been successfully fabricated via a novel in-situ dealloying method in metallic melt.A dual reinforcing structure,including large-scale between porous particles and fine-scale inside one particle,was induced to further overcome the strength-plasticity tradeoff.The microstructure and mechanical properties of such dual-scale structure-reinforced BMGCs with various volume fractions and diameters of porous Ti particles were investigated in detail.It is found that with more and finer porous Ti particles,the BMGC showed both high fracture strength(1131.9±39.1 MPa)and good plastic deformability(1.48±0.38%).The characteristic of the reinforcing structure(0.48μm)inside the porous particles was close to the plastic processing zone size of the matrix(0.1~0.2μm),which generated a locally ideal reinforcing structure.Such dual-scale reinforcing structures with more interfaces can effectively promote the multiplication of shear bands at the interfaces.Due to the size effect,the refined submicron matrix between the Ti ligaments inside the porous particles should exhibit homogeneous shearing events.Such delocalization behavior from the dual-scale reinforcing structures should help to enhance the role of the interactions between shear bands,thus improving the yield strength of the composites.Based on the in-situ dealloying method,the dual-scale structure design provides a novel approach to fabricate various BMGCs with both high strength and good plasticity.展开更多
Polymer matrix composites with high dielectric constants and low dielectric losses are in high demand for flexible electronics.However,simultaneously satisfying these requirements poses a significant scientific challe...Polymer matrix composites with high dielectric constants and low dielectric losses are in high demand for flexible electronics.However,simultaneously satisfying these requirements poses a significant scientific challenge owing to the intrinsic trade-off relationship.Herein,we utilized the in situ controllable reduction of graphene oxide(GO)within a poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene)(P(VDF-Tr FE-CFE))matrix to regulate the dielectric properties.The as-obtained composite exhibited a high relative dielectric constant of 1415coupled with a low loss tangent of 0.380 at 100 Hz.Experimental and theoretical studies indicate that the increased degree of electron conjugation and conductivity of the reduced GO(RGO)are responsible for the high-k.The constrained reduction degree of GO,combined with its homogeneous dispersion in the polymer matrix,effectively suppresses long-range charge carrier migration,thereby minimizing dielectric loss.This novel strategy could be successfully applied to both organic and aqueous systems.Furthermore,a high-performance flexible capacitive proximity sensor was exemplified by the optimization of both the dielectric layer and electrode pattern,exhibiting excellent sensitivity and stability.The fundamental mechanisms elucidated in this study provide crucial design principles for developing dielectric PMCs with tailored properties,thereby opening new avenues for advanced flexible electronic applications.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.11275186,91024026,and FOM2014OF001)the University of Shanghai for Science and Technology(USST)of Humanities and Social Sciences,China(Grant Nos.USST13XSZ05 and 11YJA790231)
文摘In order to study the universality of the interactions among different markets, we analyze the cross-correlation matrix of the price of the Chinese and American bank stocks. We then find that the stock prices of the emerging market are more correlated than that of the developed market. Considering that the values of the components for the eigenvector may be positive or negative, we analyze the differences between two markets in combination with the endogenous and exogenous events which influence the financial markets. We find that the sparse pattern of components of eigenvectors out of the threshold value has no change in American bank stocks before and after the subprime crisis. However, it changes from sparse to dense for Chinese bank stocks. By using the threshold value to exclude the external factors, we simulate the interactions in financial markets.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 11875042 and 11505114)the Shanghai Project for Construction of Top Disciplines (Grant No. USST-SYS-01)。
文摘Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.
基金supported by National Natural Science Foundation of China(No.61973234)Tianjin Science and Technology Plan Project(No.22YDTPJC00090)。
文摘To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ensemble empirical mode decomposition(EEMD)and cross-correlation algorithm was proposed.Firstly,a fast Fourier transform(FFT)spectrum analysis was utilized to ascertain the frequency range of the signal.Secondly,data acquisition was conducted at an appropriate sampling frequency,and the acquired Doppler flow rate signal was then decomposed into a series of intrinsic mode functions(IMFs)by EEMD.Subsequently,these decomposed IMFs were recombined based on their energy entropy,and then the noise of the recombined Doppler flow rate signal was removed by cross-correlation filtering.Finally,an ideal ultrasonic Doppler flow rate signal was extracted.Simulation and experimental verification show that the proposed Doppler flow signal processing method can effectively enhance the signal-to-noise ratio(SNR)and extend the lower limit of measurement of the ultrasonic Doppler flow meter.
文摘The improved cross-correlation algorithm for the strain demodulation of Vernier-effect-based optical fiber sensor(VE-OFS)is proposed in this article.The algorithm identifies the most similar spectrum to the measured one from the database of the collected spectra by employing the cross-correlation operation,subsequently deriving the predicted value via weighted calculation.As the algorithm uses the complete information in the measured raw spectrum,more accurate results and larger measurement range can be obtained.Additionally,the improved cross-correlation algorithm also has the potential to improve the measurement speed compared to current standards due to the possibility for the collection using low sampling rate.This work presents an important algorithm towards a simpler,faster way to improve the demodulation performance of VE-OFS.
文摘Traditional cross-correlation algorithms are prone to time-of-flight(TOF)calculation errors under conditions of strong noise interference and complex temperature gradients,resulting in a decline in the accuracy of ultrasonic temperature measurement.To this end,this paper proposes an ultrasonic temperature measurement method that combines YOLOv11 target detection with energy-type weighted cross-correlation algorithm.The YOLOv11 model is utilized to conduct target detection and key area positioning on the ultrasonic signal waveform diagram,automatically identifying characteristic waveforms such as node waves and end face waves,and achieving adaptive extraction of the effective signal interval.Further introduce the energy-based weighted cross-correlation algorithm.Based on the signal energy distribution,the cross-correlation results are weighted and processed to enhance the main wave response and suppress noise interference.Experiments show that the YOLOv11 model has high detection accuracy(Precision=0.987,Recall=0.958,mAP@50=0.988);The proposed method maintains the stability of time delay estimation under strong noise and high temperature(>1200℃),with the average time delay error reduced by approximately 35%to 50%compared to traditional algorithms.This verifies its high robustness and temperature measurement accuracy in complex environments,and it has a promising engineering application prospect.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(62376106)The Science and Technology Development Plan of Jilin Province(20250102212JC).
文摘Driven by advancements in mobile internet technology,images have become a crucial data medium.Ensuring the security of image information during transmission has thus emerged as an urgent challenge.This study proposes a novel image encryption algorithm specifically designed for grayscale image security.This research introduces a new Cantor diagonal matrix permutation method.The proposed permutation method uses row and column index sequences to control the Cantor diagonal matrix,where the row and column index sequences are generated by a spatiotemporal chaotic system named coupled map lattice(CML).The high initial value sensitivity of the CML system makes the permutation method highly sensitive and secure.Additionally,leveraging fractal theory,this study introduces a chaotic fractal matrix and applies this matrix in the diffusion process.This chaotic fractal matrix exhibits selfsimilarity and irregularity.Using the Cantor diagonal matrix and chaotic fractal matrix,this paper introduces a fast image encryption algorithm involving two diffusion steps and one permutation step.Moreover,the algorithm achieves robust security with only a single encryption round,ensuring high operational efficiency.Experimental results show that the proposed algorithm features an expansive key space,robust security,high sensitivity,high efficiency,and superior statistical properties for the ciphered images.Thus,the proposed algorithm not only provides a practical solution for secure image transmission but also bridges fractal theory with image encryption techniques,thereby opening new research avenues in chaotic cryptography and advancing the development of information security technology.
基金funded by theWuxi“Taihu Light”Science and Technology Key Project(Basic Research)(K20241046)the National Natural Science Foundation of China(Grant Nos.62102189,62122032,42305158)+1 种基金the Open Project of the National Engineering Research Center for Sensor Networks(2024YJZXKFKT02)Wuxi University Research Start-up Fund for High-Level Talents(No.2022r043).
文摘Generative steganography uses generative stego images to transmit secret message.It also effectively defends against statistical steganalysis.However,most existing methods focus primarily on matching the feature distribution of training data,often neglecting the sequential continuity between moves in the game.This oversight can result in unnatural patterns that deviate from real user behavior,thereby reducing the security of the hidden communication.To address this issue,we design a Gomoku agent based on the AlphaZero algorithm.The model engages in self-play to generate a sequence of plausible moves.These moves formthe basis of the stego images.We then apply an attractionmatrix at each step.It guides themove selection so that themoves appearmore natural.Thismethod helps maintain logical flow between moves.It also extends the game length,which increases the embedding capacity.Next,we filter and prioritize the generated moves.The selected moves are embedded into a move pool.Secret message is mapped to thesemoves.It is then embedded step by step as the game progresses.The finalmove sequence constitutes a complete steganographic game record.The receiver can extract the secret message using this record and a predefined mapping rule.Experiments show that our method reaches a maximum embedding capacity of 223 bits per carrier.Detection accuracy is 0.500 under XuNet and 0.498 under YeNet.These results are equal to random guessing,showing strong imperceptibility.The proposed method demonstrates superior concealment,higher embedding capacity,and greater robustness against common image distortions and steganalysis attacks.
基金National Natural Science Foundation of China,No.32130060,No.81901256Jiangsu College Students Innovation and En trepreneurship Training Program,No.202310304120Y,No.202313993004Y2024 Medical Research Project by the Jiangsu Commission of Health,No.M2024009。
文摘Traditional nerve repair methods,such as autologous nerve grafting and allogeneic nerve grafting,face issues such as donor shortage,functional loss,and immune rejection.Decellularized extracellular matrix-based grafts have emerged as highly promising alternatives,capable of uniquely recreating the natural neural mic roenvironment,promoting host cell remodeling,and ultimately enhancing functional neural regeneration.This review comprehensively analyzes the key mechanisms of peripheral nerve injury and regeneration,focusing on contemporary therapeutic strategies for key aspects such as axonal apoptosis inhibition,enhanced intrinsic regenerative capacity,construction of regenerative microenvironment,and prevention of target organ atrophy.Findings from this review has shown that decellularized extra cellular matrix grafts can promote the migration,prolife ration,and differentiation of nerve cells by providing physical suppo rt,chemical signals,and mechanical stability.Decellularized extracellular matrix grafts are mainly used as ne rve conduits,scaffolds,hydrogels,and3D printing inks.Decellularized extra cellular matrix grafts have demonstrated significant advantages in promoting nerve regeneration by regulating the prolife ration and differentiation of Schwann cells,improving the neural microenvironment,reducing inflammato ry responses,and promoting angiogenesis.Additionally,decellularized extracellular matrix grafts can se rve as drug carrie rs,enabling the controlled release of growth factors,which further enhances nerve regeneration.However,these grafts also have some limitations,including the presence of immunogenic residues,inadequate mechanical prope rties,inter-batch variability,and uncontrollable degradation rates.Future research should focus on optimizing the decellularization process,enhancing the mechanical prope rties of decellularized extracellular matrix grafts,reducing immunogenicity,improving biocompatibility and safety,and developing new composite mate rials.Furthermore,exploring their application potential in complex nerve injuries,such as diabetic neuropathy,is crucial to meet the needs of peripheral nerve regeneration and repair.
文摘We read with the great interest the study by Ababneh et al in which inducedmesenchymal stem cell-derived exosomes were shown to exhibit a stronger andmore sustained anti-proliferative effect by inducing a senescence-like state withoutapoptosis.The results obtained by the authors highlight the features of theeffects of senescent drift induction in surrounding tissues.In the light of thesefindings,the role of the properties of extracellular matrix and cellular glycocalyxin responses of human tumors to therapy remain uninvestigated.These extracellularbarriers appear to be significant obstacles to effective cancer therapy,especiallyin relation to the use of unique properties of tumor microenvironment forthe immunotherapy-resistant cancer treatment.
基金supported by the Key R&D Program of Shaanxi Province,China(2024NC-YBXM-146)the Xi’an Agricultural Technology Research and Development Project,China(24NYGG0048)+1 种基金the Key R&D Program of Xianyang,China(L2024-ZDYF-ZDYF-NY-0028)the National Foreign Expert Project of China(G2023172002L)。
文摘The effect of adding hydroxycinnamic acids(caffeic acid,sinapic acid,p-coumaric acid and chlorogenic acid)in Cabernet Sauvignon dry red wine before and after fermentation was investigated,taking into account the color parameters,anthocyanin content,and overall polyphenol levels in the wine samples.The copigmentation effect of malvidin-3-Oglucoside and sinapic acid was further explored in model solution and through theoretical calculations.The results indicated that the addition of hydroxycinnamic acids significantly enhanced the wine's color with sinapic acid(before the fermentation)showing the most pronounced color protection effect.Compared to control samples,the addition of hydroxycinnamic acids resulted in a 36%increase in total phenolic content and a 28% increase in total anthocyanin content.Thermodynamic analysis revealed that the interaction between sinapic acid and malvidin-3-O-glucoside was spontaneous and exothermic.Theoretical studies identified hydrogen bonding(HB)and dispersion forces as the main primary stabilizing forces,with the carboxyl group of sinapic acid playing a critical role while the anthocyanin backbone also influenced the interaction.
基金The National Natural Science Foundations of China (12202219)the Natural Science Foundations of Ningxia (2024AAC02009, 2023AAC05001)the Ningxia Youth Top Talents Training Project。
文摘The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix splitting methods.Taking the decomposition of the diagonal elements for coefficient matrix as the key point,some new preconditioners are constructed.Taking the tri-diagonal coefficient matrix as an example,the convergence domains and optimal relaxation factor of the new method are analyzed theoretically.The presented new iteration methods are applied to solve linear algebraic equations,even 2D and 3D diffusion problems with the fully implicit discretization.The results of numerical experiments are matched with the theoretical analysis,and show that the iteration numbers are reduced greatly.The superiorities of presented iteration methods exceed some classical iteration methods dramatically.
基金funded Basic Research Projects of Higher Education Institutions in Liaoning Province(JYTZD20230004)Future Industry Frontier Technology Project in Liaoning Province in 2025(2025JH2/101330141)Key Research and Development Program of Liaoning Province in 2025.
文摘With the rapid advancement of electromagnetic launch technology,enhancing the structural stability and thermal resistance of armatures has become essential for improving the overall efficiency and reliability of railgun systems.Traditional aluminum alloy armatures often suffer from severe ablation,deformation,and uneven current distribution under high pulsed currents,which limit their performance and service life.To address these challenges,this study employs the Johnson–Cook constitutive model and the finite element method to develop armature models of aluminum matrix composites with varying heterogeneous graphene volume fractions.The temperature,stress,and strain of the armatures during operation were analyzed to investigate the effects of different graphene volume fractions on the deformation and damage behavior of aluminum matrix composite armatures under the multi-field coupling of electromagnetic,thermal,and structural interactions.The results indicate that,compared to the 6061 aluminum alloy matrix,the graphene-reinforced aluminum matrix composite armature significantly suppresses ablation damage at the tail and throat edges.The incorporation of graphene notably reduces the temperature rise during the armature emission process,increases the muzzle velocity under identical current excitation,and mitigates directional deformation of the armature.The 1 wt.% graphene-reinforced aluminum matrix composite armature demonstrates better agreement with experimental results at a strain rate of 2000 s^(-1),while simultaneously improving stress-strain response,reducing temperature rise,and improving velocity performance.
基金supported by Advanced Materials-National Science and Technology Major Project(No.:2025ZD0619700)National Natural Science Foundation of China(No.:U24A2035,52225101&52171100).
文摘Mg alloys have garnered significant attention in advanced engineering applications due to their exceptional combination of specificstrength and lightweight properties.Theα-Mg solid solution,which constitutes the core component of Mg alloys,directly governs the alloy’sthermodynamic behavior,kinetic response,and overall performance.This paper systematically reviews the effects of theα-Mg matrix phase onmechanical properties(e.g.,when the average grain size of pure Mg is refined from 59.7μm to 1.57μm,the alloy’s yield strength increasesby 122 MPa),corrosion resistance(e.g.,adding 0.5%Gd and 0.5%Sc to pure Mg reduces the alloy’s weight loss rate from 208.71 mm/yearto 0.29 mm/year),damping properties,electromagnetic shielding properties,and flame retardancy,and reveals the microscopic interactionmechanisms between the matrix phase,solute atoms,crystal defects,and second phases.Furthermore,this paper critically analyzes the keyrole of the matrix phase in emerging fields such as bio-Mg alloys(e.g.,controlled degradation rate design),Mg-air batteries(e.g.,anodeefficiency optimization),and Mg-based hydrogen storage materials(e.g.,enhancement of hydrogen absorption/desorption kinetics).Finally,this paper explores the significant potential of data-driven methods in the design and development of next-generation high-performance Mgalloys.
基金Project supported by the National Natural Science Foundation of China(Grant No.61573266)the Natural Science Basic Research Program of Shaanxi(Grant No.2021JM-133)the Fundamental Research Funds for the Central Universities and the Innovation Fund of Xidian University(Grant No.YJSJ25009)。
文摘Efficient implementation of fundamental matrix operations on quantum computers,such as matrix products and Hadamard operations,holds significant potential for accelerating machine learning algorithms.A critical prerequisite for quantum implementations is the effective encoding of classical data into quantum states.We propose two quantum computing frameworks for preparing the distinct encoded states corresponding to matrix operations,including the matrix product,matrix sum,matrix Hadamard product and division.Quantum algorithms based on the digital encoding computing framework are capable of implementing the matrix Hadamard operation with a time complexity of O(poly log(mn/ε))and the matrix product with a time complexity of O(poly log(mnl/ε)),achieving an exponential speedup in contrast to the classical methods of O(mn)and O(mnl).Quantum algorithms based on the analog-encoding framework are capable of implementing the matrix Hadamard operation with a time complexity of O(k_(1)√mn·poly log(mn/ε))and the matrix product with a time complexity of O(k_(2)√1·poly log(mnl/ε)),where k_(1)and k_(2)are coefficients correlated with the elements of the matrix,achieving a square speedup in contrast to the classical counterparts.As applications,we construct an oracle that can access the trace of a matrix within logarithmic time,and propose several algorithms to respectively estimate the trace of a matrix,the trace of the product of two matrices,and the trace inner product of two matrices within logarithmic time.
文摘Evaluating the adversarial robustness of classification algorithms in machine learning is a crucial domain.However,current methods lack measurable and interpretable metrics.To address this issue,this paper introduces a visual evaluation index named confidence centroid skewing quadrilateral,which is based on a classification confidence-based confusion matrix,offering a quantitative and visual comparison of the adversarial robustness among different classification algorithms,and enhances intuitiveness and interpretability of attack impacts.We first conduct a validity test and sensitive analysis of the method.Then,prove its effectiveness through the experiments of five classification algorithms including artificial neural network(ANN),logistic regression(LR),support vector machine(SVM),convolutional neural network(CNN)and transformer against three adversarial attacks such as fast gradient sign method(FGSM),DeepFool,and projected gradient descent(PGD)attack.
基金supported by the National Natural Science Foundation of China(Nos.52471156,U20A20274,and 52071158)the China Postdoctoral Science Foundation(Nos.2024M751173 and 2024M752703)+1 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent,China(No.2024ZB229)the Natural Science Foundation of Jiangsu Higher Education Institutions,China(No.24KJB430012).
文摘This study investigates the anisotropic thermal conductivity of aluminum matrix composites reinforced with graphene nano-plates(GNPs)and in situ ZrB_(2) nanoparticles,while simultaneously maintaining high strength and toughness.A discontinuous layered GNPs-ZrB_(2)/AA6111 composite was prepared using in situ melt reactions and semi-solid stirring casting technology,combined with hot rolling deformation processing.Microstructural analysis revealed that the GNPs were aligned parallel to the rolling direction-transverse direction(RD-TD)plane,whereas the ZrB_(2) nanoparticles aggregated into cluster strips,collectively forming a discontinuous layered structure.This multilayer arrangement maximized the in-plane thermal conductivity of the GNPs.The tightly bonded GNP/Al interfaces with the locking of CuAl_(2) nanoparticles ensured that the GNPs fully exploited their high thermal conductivity.Therefore,the GNPs-ZrB_(2)/AA6111 composite achieved high in-plane thermal conductivity(230 W/(m·K)),which is higher than that of the matrix(206 W/(m·K)).The improved in-plane thermal conductivity is primarily attributed to the exceptionally high intrinsic in-plane thermal conductivity of the GNPs and their two-dimensional layered structure.However,the composite exhibited pronounced thermal conductivity anisotropy in the in-plane and through-plane directions.The reduced through-plane thermal conductivity is predominantly caused by the intrinsically low through-plane thermal conductivity of the GNPs and the increased interfacial thermal resistance from the additional grain boundaries.
基金supported by National Natural Science Foundation of China(No.52101138)Natural Science Foundation of Hubei Province(No.2023AFB798)+1 种基金Shenzhen Science and Technology Program(No.JCYJ20220530160813032)State Key Laboratory of Solidification Processing in NWPU(No.SKLSP202309).
文摘In the present work,the porous Ti particle reinforced Mg-based bulk metallic glass matrix composites(BMGCs)have been successfully fabricated via a novel in-situ dealloying method in metallic melt.A dual reinforcing structure,including large-scale between porous particles and fine-scale inside one particle,was induced to further overcome the strength-plasticity tradeoff.The microstructure and mechanical properties of such dual-scale structure-reinforced BMGCs with various volume fractions and diameters of porous Ti particles were investigated in detail.It is found that with more and finer porous Ti particles,the BMGC showed both high fracture strength(1131.9±39.1 MPa)and good plastic deformability(1.48±0.38%).The characteristic of the reinforcing structure(0.48μm)inside the porous particles was close to the plastic processing zone size of the matrix(0.1~0.2μm),which generated a locally ideal reinforcing structure.Such dual-scale reinforcing structures with more interfaces can effectively promote the multiplication of shear bands at the interfaces.Due to the size effect,the refined submicron matrix between the Ti ligaments inside the porous particles should exhibit homogeneous shearing events.Such delocalization behavior from the dual-scale reinforcing structures should help to enhance the role of the interactions between shear bands,thus improving the yield strength of the composites.Based on the in-situ dealloying method,the dual-scale structure design provides a novel approach to fabricate various BMGCs with both high strength and good plasticity.
基金financially supported by the Innovation and Technology Commission of the Hong Kong SAR Government(No.MRP/020/21)Hong Kong Polytechnic University(No.847A)+1 种基金RI-Wear Seed Fund of Poly U(1-CD8J)Start-up Fund of Poly U(1-BD49)。
文摘Polymer matrix composites with high dielectric constants and low dielectric losses are in high demand for flexible electronics.However,simultaneously satisfying these requirements poses a significant scientific challenge owing to the intrinsic trade-off relationship.Herein,we utilized the in situ controllable reduction of graphene oxide(GO)within a poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene)(P(VDF-Tr FE-CFE))matrix to regulate the dielectric properties.The as-obtained composite exhibited a high relative dielectric constant of 1415coupled with a low loss tangent of 0.380 at 100 Hz.Experimental and theoretical studies indicate that the increased degree of electron conjugation and conductivity of the reduced GO(RGO)are responsible for the high-k.The constrained reduction degree of GO,combined with its homogeneous dispersion in the polymer matrix,effectively suppresses long-range charge carrier migration,thereby minimizing dielectric loss.This novel strategy could be successfully applied to both organic and aqueous systems.Furthermore,a high-performance flexible capacitive proximity sensor was exemplified by the optimization of both the dielectric layer and electrode pattern,exhibiting excellent sensitivity and stability.The fundamental mechanisms elucidated in this study provide crucial design principles for developing dielectric PMCs with tailored properties,thereby opening new avenues for advanced flexible electronic applications.
