Arrhythmias are a frequently occurring phenomenon in clinical practice,but how to accurately dis-tinguish subtle rhythm abnormalities remains an ongoing difficulty faced by the entire research community when conductin...Arrhythmias are a frequently occurring phenomenon in clinical practice,but how to accurately dis-tinguish subtle rhythm abnormalities remains an ongoing difficulty faced by the entire research community when conducting ECG-based studies.From a review of existing studies,two main factors appear to contribute to this problem:the uneven distribution of arrhythmia classes and the limited expressiveness of features learned by current models.To overcome these limitations,this study proposes a dual-path multimodal framework,termed DM-EHC(Dual-Path Multimodal ECG Heartbeat Classifier),for ECG-based heartbeat classification.The proposed framework links 1D ECG temporal features with 2D time–frequency features.By setting up the dual paths described above,the model can process more dimensions of feature information.The MIT-BIH arrhythmia database was selected as the baseline dataset for the experiments.Experimental results show that the proposed method outperforms single modalities and performs better for certain specific types of arrhythmias.The model achieved mean precision,recall,and F1 score of 95.14%,92.26%,and 93.65%,respectively.These results indicate that the framework is robust and has potential value in automated arrhythmia classification.展开更多
High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an eff...High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.展开更多
With the increasingly complex and changeable electromagnetic environment,wireless communication systems are facing jamming and abnormal signal injection,which significantly affects the normal operation of a communicat...With the increasingly complex and changeable electromagnetic environment,wireless communication systems are facing jamming and abnormal signal injection,which significantly affects the normal operation of a communication system.In particular,the abnormal signals may emulate the normal signals,which makes it very challenging for abnormal signal recognition.In this paper,we propose a new abnormal signal recognition scheme,which combines time-frequency analysis with deep learning to effectively identify synthetic abnormal communication signals.Firstly,we emulate synthetic abnormal communication signals including seven jamming patterns.Then,we model an abnormal communication signals recognition system based on the communication protocol between the transmitter and the receiver.To improve the performance,we convert the original signal into the time-frequency spectrogram to develop an image classification algorithm.Simulation results demonstrate that the proposed method can effectively recognize the abnormal signals under various parameter configurations,even under low signal-to-noise ratio(SNR)and low jamming-to-signal ratio(JSR)conditions.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
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
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
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
Peripheral nerve injury causes severe neuroinflammation and has become a global medical challenge.Previous research has demonstrated that porcine decellularized nerve matrix hydrogel exhibits excellent biological prop...Peripheral nerve injury causes severe neuroinflammation and has become a global medical challenge.Previous research has demonstrated that porcine decellularized nerve matrix hydrogel exhibits excellent biological properties and tissue specificity,highlighting its potential as a biomedical material for the repair of severe peripheral nerve injury;however,its role in modulating neuroinflammation post-peripheral nerve injury remains unknown.Here,we aimed to characterize the anti-inflammatory properties of porcine decellularized nerve matrix hydrogel and their underlying molecular mechanisms.Using peripheral nerve injury model rats treated with porcine decellularized nerve matrix hydrogel,we evaluated structural and functional recovery,macrophage phenotype alteration,specific cytokine expression,and changes in related signaling molecules in vivo.Similar parameters were evaluated in vitro using monocyte/macrophage cell lines stimulated with lipopolysaccharide and cultured on porcine decellularized nerve matrix hydrogel-coated plates in complete medium.These comprehensive analyses revealed that porcine decellularized nerve matrix hydrogel attenuated the activation of excessive inflammation at the early stage of peripheral nerve injury and increased the proportion of the M2 subtype in monocytes/macrophages.Additionally,porcine decellularized nerve matrix hydrogel negatively regulated the Toll-like receptor 4/myeloid differentiation factor 88/nuclear factor-κB axis both in vivo and in vitro.Our findings suggest that the efficacious anti-inflammatory properties of porcine decellularized nerve matrix hydrogel induce M2 macrophage polarization via suppression of the Toll-like receptor 4/myeloid differentiation factor 88/nuclear factor-κB pathway,providing new insights into the therapeutic mechanism of porcine decellularized nerve matrix hydrogel in peripheral nerve injury.展开更多
The development of shape-customizable and bulk flexible electrochemical devices through processing technologies as versatile as those used for plastics promises to revolutionize the future of battery technology.Howeve...The development of shape-customizable and bulk flexible electrochemical devices through processing technologies as versatile as those used for plastics promises to revolutionize the future of battery technology.However,this pursuit has been fundamentally hindered by the absence of transformative battery materials capable of delivering the necessary electrochemical functions,robust interface adhesion,and,crucially,the suitable rheological properties required for on-demand shaping.In this work,we introduce a concept of a multifunctional plasticine electrode matrix(PEM)featuring nano-interpenetrating networks(nano-IPN)to address this challenge.Utilizing the nonflammable liquid-electrolyte hydration combined with conductive nanomaterials,we have realized a PEM in the form of a multifunctional nanocomposite that integrates ion and electron conduction,component binding,non-flammability,and plasticine-like moldability.With this PEM,we have successfully fabricated a variety of bulk-flexible electrodes with high mass loading of active material(AM)(>70 wt%)using industry-friendly extrusion and compression molding techniques.Moreover,these high AM-loading composite electrodes achieve an unparalleled bulk conformability and flexibility,remaining structurally intact even under severe mechanical stress.Ultimately,we have successfully produced shape-patternable and flexible batteries via extrusion molding.This study underscores the potential of the PEM to revolutionize battery microstructures,interfaces,manufacturing processes,and performance characteristics.展开更多
Objective:Osteoarthritis(OA)is a degenerative joint disease characterized by extracellular matrix(ECM)degradation,chondrocyte apoptosis,and chronic inflammation.Cartilage destruction and ECM degeneration contribute to...Objective:Osteoarthritis(OA)is a degenerative joint disease characterized by extracellular matrix(ECM)degradation,chondrocyte apoptosis,and chronic inflammation.Cartilage destruction and ECM degeneration contribute to joint function loss and disability.Signal transducer and activator of transcription 3(STAT3)up-regulates the expression of MMP-13,which degrades collagen Ⅱ.Our previous study found that 5,7,3',4'-tetramethoxyflavone(TMF)exhibited protective effects on OA chondrocytes.This study aims to investigate the protective role of TMF in inhibiting ECM degradation by mediating the Sirt1/STAT3 signaling pathway.Methods:Rat OA models were established by the injection of monosodium iodoacetate(MIA).Hematoxylin&eosin(HE)staining and immunohistochemistry(IHC)analysis were performed.IL-1β stimulated C28/I2 cells were used as OA-like chondrocyte cell model.Western blotting assays were used to determine the protein expression.Results:The expression of MMP-13 was upregulated while type Ⅱ collagen expression is downregulated,and the phosphorylation level of STAT3 is increased in rat OA models.TMF reverses the STAT3-mediated expression of MMP-13 and type v collagen.Activation of STAT3 or inhibition of Sirt1 function attenuates the inhibitory effect of TMF on ECM degradation.Conclusion:TMF can inhibit ECM degradation mediated by the STAT3 signal pathway by activating Sirt1 expression in OA cell and animal models.展开更多
Objectives:High-grade serous ovarian cancer(HGSOC),the most common subtype of epithelial ovarian cancer(EOC),exhibits a mesenchymal phenotype characterized by fibrotic stroma and poor prognosis.Human epididymis protei...Objectives:High-grade serous ovarian cancer(HGSOC),the most common subtype of epithelial ovarian cancer(EOC),exhibits a mesenchymal phenotype characterized by fibrotic stroma and poor prognosis.Human epididymis protein 4(HE4),a key diagnostic biomarker for ovarian cancer,is involved in fibrotic processes in several non-malignant diseases.Given the clinical significance of stromal fibrosis in HGSOC and the potential link between HE4 and fibrosis,this study aimed to investigate the role of HE4 in the formation of stromal fibrosis in HGSOC.Methods:A total of 126 patients with gynecological conditions were included and divided into normal,benign,and EOC groups.Tissue stiffness was quantitatively measured and analyzed for its correlation with clinicopathological features.We further investigated the correlation between tumor stiffness and the expression levels of HE4 and fibroblast activation markers(α-smooth muscle actin(α-SMA)and fibroblast activation protein(FAP))in tumor tissues from 22 HGSOC patients.In vitro,primary fibroblasts were treated with recombinant HE4(rHE4)or conditioned media from HE4-knockdown ovarian cancer cells to assess fibroblasts activation and matrix contractility(Collagen gel contraction assays).In vivo,a subcutaneous xenograft model using HE4-knockdown cells was established to evaluate the effects of HE4 suppression on tumor growth and extensive extracellular matrix(ECM)remodeling.Results:Ovarian cancer tissues showed significantly increased stiffness compared to benign/normal groups,showing positive correlation with serum HE4 levels.High-stiffness HGSOC tumors exhibited upregulated expression of HE4,α-SMA,FAP,and collagen I.rHE4 stimulated fibroblast activation and enhanced matrix contractility,whereas HE4 knockdown in cancer cells abrogated these pro-fibrotic effects.In vivo,HE4-silenced xenografts displayed restricted tumor growth accompanied by reduced stromal expression ofα-SMA,FAP,and collagen I.Conclusion:Our findings suggest that HE4 may facilitate ECM remodeling in HGSOC through promoting fibroblast activation and increasing collagen deposition.展开更多
The Gabor and S transforms are frequently used in time-frequency decomposition methods. Constrained by the uncertainty principle, both transforms produce low-resolution time-frequency decomposition results in the time...The Gabor and S transforms are frequently used in time-frequency decomposition methods. Constrained by the uncertainty principle, both transforms produce low-resolution time-frequency decomposition results in the time and frequency domains. To improve the resolution of the time-frequency decomposition results, we use the instantaneous frequency distribution function（IFDF） to express the seismic signal. When the instantaneous frequencies of the nonstationary signal satisfy the requirements of the uncertainty principle, the support of IFDF is just the support of the amplitude ridges in the signal obtained using the short-time Fourier transform. Based on this feature, we propose a new iteration algorithm to achieve the sparse time-frequency decomposition of the signal. The iteration algorithm uses the support of the amplitude ridges of the residual signal obtained with the short-time Fourier transform to update the time-frequency components of the signal. The summation of the updated time-frequency components in each iteration is the result of the sparse timefrequency decomposition. Numerical examples show that the proposed method improves the resolution of the time-frequency decomposition results and the accuracy of the analysis of the nonstationary signal. We also use the proposed method to attenuate the ground roll of field seismic data with good results.展开更多
Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional...Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive （TVAR） model based on the process neural network （PNN） and the empirical mode decomposition （EMD） is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions （IMFs）. Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.展开更多
Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyze...Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyzed. Experimental results show that for a spectrum of some density, the joint time-frequency gain-modification based speech enhancement algorithm achieves significant improvement in intelligibility. Additionally, the spectrum region where the estimated spectrum is smaller than the clean spectrum, is the most important region contributing to intelligibility improvement for the enhanced whisper. The spectrum region where the estimated spectrum is larger than twice the size of the clean spectrum is detrimental to speech intelligibility perception within the whisper context.展开更多
The ground roll and body wave usually show significant differences in arrival time, frequency content, and polarization characteristics, and conventional polarization filters that operate in either the time or frequen...The ground roll and body wave usually show significant differences in arrival time, frequency content, and polarization characteristics, and conventional polarization filters that operate in either the time or frequency domain cannot consider all these elements. Therefore, we have developed a time-frequency dependent polarization filter based on the S transform to attenuate the ground roll in seismic records. Our approach adopts the complex coefficients of the S transform of the multi-component seismic data to estimate the local polarization attributes and utilizes the estimated attributes to construct the filter function. In this study, we select the S transform to design this polarization filter because its scalable window length can ensure the same number of cycles of a Fourier sinusoid, thereby rendering more precise estimation of local polarization attributes. The results of applying our approach in synthetic and real data examples demonstrate that the proposed polarization filter can effectively attenuate the ground roll and successfully preserve the body wave.展开更多
In this paper, it is described that the time-frequency resolution of geophysical signals is affected by the time window function attenuation coefficient and sampling interval and how such effects are eliminated effect...In this paper, it is described that the time-frequency resolution of geophysical signals is affected by the time window function attenuation coefficient and sampling interval and how such effects are eliminated effectively. Improving the signal resolution is the key to signal time-frequency analysis processing and has wide use in geophysical data processing and extraction of attribute parameters. In this paper, authors research the effects of the attenuation coefficient choice of the Gabor transform window function and sampling interval on signal resolution. Unsuitable parameters not only decrease the signal resolution on the frequency spectrum but also miss the signals. It is essential to first give the optimum window and range of parameters through time-frequency analysis simulation using the Gabor transform. In the paper, the suggestions about the range and choice of the optimum sampling interval and processing methods of general seismic signals are given.展开更多
基金supported by the Innovative Human Resource Development for Local Intel-lectualization program through the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.IITP-2026-2020-0-01741)the research fund of Hanyang University(HY-2025-1110).
文摘Arrhythmias are a frequently occurring phenomenon in clinical practice,but how to accurately dis-tinguish subtle rhythm abnormalities remains an ongoing difficulty faced by the entire research community when conducting ECG-based studies.From a review of existing studies,two main factors appear to contribute to this problem:the uneven distribution of arrhythmia classes and the limited expressiveness of features learned by current models.To overcome these limitations,this study proposes a dual-path multimodal framework,termed DM-EHC(Dual-Path Multimodal ECG Heartbeat Classifier),for ECG-based heartbeat classification.The proposed framework links 1D ECG temporal features with 2D time–frequency features.By setting up the dual paths described above,the model can process more dimensions of feature information.The MIT-BIH arrhythmia database was selected as the baseline dataset for the experiments.Experimental results show that the proposed method outperforms single modalities and performs better for certain specific types of arrhythmias.The model achieved mean precision,recall,and F1 score of 95.14%,92.26%,and 93.65%,respectively.These results indicate that the framework is robust and has potential value in automated arrhythmia classification.
基金We would like to thank the associate editor and the reviewers for their constructive comments.This work was supported in part by the National Natural Science Foundation of China under Grant 62203234in part by the State Key Laboratory of Robotics of China under Grant 2023-Z03+1 种基金in part by the Natural Science Foundation of Liaoning Province under Grant 2023-BS-025in part by the Research Program of Liaoning Liaohe Laboratory under Grant LLL23ZZ-02-02.
文摘High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.
基金supported by Natural Science Foundation of China(No.62371231)Natural Science Foundation on Frontier Leading Technology Basic Research Project of Jiangsu under Grant BK20222001Jiangsu Provincial Key Research and Development Program(No.BE2023027).
文摘With the increasingly complex and changeable electromagnetic environment,wireless communication systems are facing jamming and abnormal signal injection,which significantly affects the normal operation of a communication system.In particular,the abnormal signals may emulate the normal signals,which makes it very challenging for abnormal signal recognition.In this paper,we propose a new abnormal signal recognition scheme,which combines time-frequency analysis with deep learning to effectively identify synthetic abnormal communication signals.Firstly,we emulate synthetic abnormal communication signals including seven jamming patterns.Then,we model an abnormal communication signals recognition system based on the communication protocol between the transmitter and the receiver.To improve the performance,we convert the original signal into the time-frequency spectrogram to develop an image classification algorithm.Simulation results demonstrate that the proposed method can effectively recognize the abnormal signals under various parameter configurations,even under low signal-to-noise ratio(SNR)and low jamming-to-signal ratio(JSR)conditions.
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.
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.
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.
基金supported by the Shenzhen Hong Kong Joint Funding Project,No.SGDX20230116093645007(to LY)the Shenzhen Science and Technology Innovation Committee International Cooperation Project,No.GJHZ20200731095608025(to LY)+7 种基金Shenzhen Development and Reform Commission’s Intelligent Diagnosis,Treatment and Prevention of Adolescent Spinal Health Public Service Platform,No.S2002Q84500835(to LY)Shenzhen Medical Research Fund,No.B2303005(to LY)Team-based Medical Science Research Program,No.2024YZZ02(to LY)Zhejiang Provincial Natural Science Foundation of China,No.LWQ20H170001(to RL)Basic Research Project of Shenzhen Science and Technology from Shenzhen Science and Technology Innovation Commission,No.JCYJ20210324103010029(to BY)Shenzhen Second People’s Hospital Clinical Research Fund of Guangdong Province High-level Hospital Construction Project,Nos.2023yjlcyj029(to BY),2023yjlcyj021(to LL)Guangdong Basic and Applied Basic Research Foundation,No.2022A1515110679(to LL)China Postdoctoral Science Foundation,No.2022M722203(to GL).
文摘Peripheral nerve injury causes severe neuroinflammation and has become a global medical challenge.Previous research has demonstrated that porcine decellularized nerve matrix hydrogel exhibits excellent biological properties and tissue specificity,highlighting its potential as a biomedical material for the repair of severe peripheral nerve injury;however,its role in modulating neuroinflammation post-peripheral nerve injury remains unknown.Here,we aimed to characterize the anti-inflammatory properties of porcine decellularized nerve matrix hydrogel and their underlying molecular mechanisms.Using peripheral nerve injury model rats treated with porcine decellularized nerve matrix hydrogel,we evaluated structural and functional recovery,macrophage phenotype alteration,specific cytokine expression,and changes in related signaling molecules in vivo.Similar parameters were evaluated in vitro using monocyte/macrophage cell lines stimulated with lipopolysaccharide and cultured on porcine decellularized nerve matrix hydrogel-coated plates in complete medium.These comprehensive analyses revealed that porcine decellularized nerve matrix hydrogel attenuated the activation of excessive inflammation at the early stage of peripheral nerve injury and increased the proportion of the M2 subtype in monocytes/macrophages.Additionally,porcine decellularized nerve matrix hydrogel negatively regulated the Toll-like receptor 4/myeloid differentiation factor 88/nuclear factor-κB axis both in vivo and in vitro.Our findings suggest that the efficacious anti-inflammatory properties of porcine decellularized nerve matrix hydrogel induce M2 macrophage polarization via suppression of the Toll-like receptor 4/myeloid differentiation factor 88/nuclear factor-κB pathway,providing new insights into the therapeutic mechanism of porcine decellularized nerve matrix hydrogel in peripheral nerve injury.
基金financial support from the National Natural Science Foundation of China(52473248,52203123,52125301,22279070 and U21A20170)the State Key Laboratory of Polymer Materials Engineering(Grant No:sklpme 2023-1-05 and sklpme 2024-2-04)+3 种基金the Ministry of Science and Technology of China(No.2019YFA0705703)the Sichuan Science and Technology Program(2023NSFSC0991 and 2025ZNSFSC1411)the Fundamental Research Funds for the Central Universitiespartially sponsored by the Double First-Class Construction Funds of Sichuan University.
文摘The development of shape-customizable and bulk flexible electrochemical devices through processing technologies as versatile as those used for plastics promises to revolutionize the future of battery technology.However,this pursuit has been fundamentally hindered by the absence of transformative battery materials capable of delivering the necessary electrochemical functions,robust interface adhesion,and,crucially,the suitable rheological properties required for on-demand shaping.In this work,we introduce a concept of a multifunctional plasticine electrode matrix(PEM)featuring nano-interpenetrating networks(nano-IPN)to address this challenge.Utilizing the nonflammable liquid-electrolyte hydration combined with conductive nanomaterials,we have realized a PEM in the form of a multifunctional nanocomposite that integrates ion and electron conduction,component binding,non-flammability,and plasticine-like moldability.With this PEM,we have successfully fabricated a variety of bulk-flexible electrodes with high mass loading of active material(AM)(>70 wt%)using industry-friendly extrusion and compression molding techniques.Moreover,these high AM-loading composite electrodes achieve an unparalleled bulk conformability and flexibility,remaining structurally intact even under severe mechanical stress.Ultimately,we have successfully produced shape-patternable and flexible batteries via extrusion molding.This study underscores the potential of the PEM to revolutionize battery microstructures,interfaces,manufacturing processes,and performance characteristics.
基金Project Supported by Jiangxi Provincial Natural Science Foundation(20212ACB206002)。
文摘Objective:Osteoarthritis(OA)is a degenerative joint disease characterized by extracellular matrix(ECM)degradation,chondrocyte apoptosis,and chronic inflammation.Cartilage destruction and ECM degeneration contribute to joint function loss and disability.Signal transducer and activator of transcription 3(STAT3)up-regulates the expression of MMP-13,which degrades collagen Ⅱ.Our previous study found that 5,7,3',4'-tetramethoxyflavone(TMF)exhibited protective effects on OA chondrocytes.This study aims to investigate the protective role of TMF in inhibiting ECM degradation by mediating the Sirt1/STAT3 signaling pathway.Methods:Rat OA models were established by the injection of monosodium iodoacetate(MIA).Hematoxylin&eosin(HE)staining and immunohistochemistry(IHC)analysis were performed.IL-1β stimulated C28/I2 cells were used as OA-like chondrocyte cell model.Western blotting assays were used to determine the protein expression.Results:The expression of MMP-13 was upregulated while type Ⅱ collagen expression is downregulated,and the phosphorylation level of STAT3 is increased in rat OA models.TMF reverses the STAT3-mediated expression of MMP-13 and type v collagen.Activation of STAT3 or inhibition of Sirt1 function attenuates the inhibitory effect of TMF on ECM degradation.Conclusion:TMF can inhibit ECM degradation mediated by the STAT3 signal pathway by activating Sirt1 expression in OA cell and animal models.
文摘Objectives:High-grade serous ovarian cancer(HGSOC),the most common subtype of epithelial ovarian cancer(EOC),exhibits a mesenchymal phenotype characterized by fibrotic stroma and poor prognosis.Human epididymis protein 4(HE4),a key diagnostic biomarker for ovarian cancer,is involved in fibrotic processes in several non-malignant diseases.Given the clinical significance of stromal fibrosis in HGSOC and the potential link between HE4 and fibrosis,this study aimed to investigate the role of HE4 in the formation of stromal fibrosis in HGSOC.Methods:A total of 126 patients with gynecological conditions were included and divided into normal,benign,and EOC groups.Tissue stiffness was quantitatively measured and analyzed for its correlation with clinicopathological features.We further investigated the correlation between tumor stiffness and the expression levels of HE4 and fibroblast activation markers(α-smooth muscle actin(α-SMA)and fibroblast activation protein(FAP))in tumor tissues from 22 HGSOC patients.In vitro,primary fibroblasts were treated with recombinant HE4(rHE4)or conditioned media from HE4-knockdown ovarian cancer cells to assess fibroblasts activation and matrix contractility(Collagen gel contraction assays).In vivo,a subcutaneous xenograft model using HE4-knockdown cells was established to evaluate the effects of HE4 suppression on tumor growth and extensive extracellular matrix(ECM)remodeling.Results:Ovarian cancer tissues showed significantly increased stiffness compared to benign/normal groups,showing positive correlation with serum HE4 levels.High-stiffness HGSOC tumors exhibited upregulated expression of HE4,α-SMA,FAP,and collagen I.rHE4 stimulated fibroblast activation and enhanced matrix contractility,whereas HE4 knockdown in cancer cells abrogated these pro-fibrotic effects.In vivo,HE4-silenced xenografts displayed restricted tumor growth accompanied by reduced stromal expression ofα-SMA,FAP,and collagen I.Conclusion:Our findings suggest that HE4 may facilitate ECM remodeling in HGSOC through promoting fibroblast activation and increasing collagen deposition.
基金funded by the National Basic Research Program of China(973 Program)(No.2011 CB201002)the National Natural Science Foundation of China(No.41374117)the great and special projects(2011ZX05005–005-008HZ and 2011ZX05006-002)
文摘The Gabor and S transforms are frequently used in time-frequency decomposition methods. Constrained by the uncertainty principle, both transforms produce low-resolution time-frequency decomposition results in the time and frequency domains. To improve the resolution of the time-frequency decomposition results, we use the instantaneous frequency distribution function（IFDF） to express the seismic signal. When the instantaneous frequencies of the nonstationary signal satisfy the requirements of the uncertainty principle, the support of IFDF is just the support of the amplitude ridges in the signal obtained using the short-time Fourier transform. Based on this feature, we propose a new iteration algorithm to achieve the sparse time-frequency decomposition of the signal. The iteration algorithm uses the support of the amplitude ridges of the residual signal obtained with the short-time Fourier transform to update the time-frequency components of the signal. The summation of the updated time-frequency components in each iteration is the result of the sparse timefrequency decomposition. Numerical examples show that the proposed method improves the resolution of the time-frequency decomposition results and the accuracy of the analysis of the nonstationary signal. We also use the proposed method to attenuate the ground roll of field seismic data with good results.
基金Aeronautical Science Foundation of China (20071551016)
文摘Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive （TVAR） model based on the process neural network （PNN） and the empirical mode decomposition （EMD） is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions （IMFs）. Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.
基金The National Natural Science Foundation of China(No.61301295,61273266,61301219,61201326,61003131)the Natural Science Foundation of Anhui Province(No.1308085QF100,1408085MF113)+2 种基金the Natural Science Foundation of Jiangsu Province(No.BK20130241)the Natural Science Foundation of Higher Education Institutions of Jiangsu Province(No.12KJB510021)the Doctoral Fund of Anhui University
文摘Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyzed. Experimental results show that for a spectrum of some density, the joint time-frequency gain-modification based speech enhancement algorithm achieves significant improvement in intelligibility. Additionally, the spectrum region where the estimated spectrum is smaller than the clean spectrum, is the most important region contributing to intelligibility improvement for the enhanced whisper. The spectrum region where the estimated spectrum is larger than twice the size of the clean spectrum is detrimental to speech intelligibility perception within the whisper context.
基金supported by the National Science and Technology Major Project of China(Grant No.2011ZX05014 and 2011ZX05008-005)
文摘The ground roll and body wave usually show significant differences in arrival time, frequency content, and polarization characteristics, and conventional polarization filters that operate in either the time or frequency domain cannot consider all these elements. Therefore, we have developed a time-frequency dependent polarization filter based on the S transform to attenuate the ground roll in seismic records. Our approach adopts the complex coefficients of the S transform of the multi-component seismic data to estimate the local polarization attributes and utilizes the estimated attributes to construct the filter function. In this study, we select the S transform to design this polarization filter because its scalable window length can ensure the same number of cycles of a Fourier sinusoid, thereby rendering more precise estimation of local polarization attributes. The results of applying our approach in synthetic and real data examples demonstrate that the proposed polarization filter can effectively attenuate the ground roll and successfully preserve the body wave.
基金This work was funded by National Natural Science Foundation of China-（No. 40474044）.
文摘In this paper, it is described that the time-frequency resolution of geophysical signals is affected by the time window function attenuation coefficient and sampling interval and how such effects are eliminated effectively. Improving the signal resolution is the key to signal time-frequency analysis processing and has wide use in geophysical data processing and extraction of attribute parameters. In this paper, authors research the effects of the attenuation coefficient choice of the Gabor transform window function and sampling interval on signal resolution. Unsuitable parameters not only decrease the signal resolution on the frequency spectrum but also miss the signals. It is essential to first give the optimum window and range of parameters through time-frequency analysis simulation using the Gabor transform. In the paper, the suggestions about the range and choice of the optimum sampling interval and processing methods of general seismic signals are given.
