Scheme of negative acoustic radiation force based on a multiple-layered spherical structure

Acoustic radiation force(ARF), as an important particle manipulation method, has been extensively studied in recent years. With the introduction of the concept of “acoustic tweezers”, negative acoustic radiation has become a research hotspot. In this paper, a scheme of realizing negative ARF based on the multiple-layered spherical structure design is proposed. The specific structure and design idea are presented. Detailed theoretical calculation analysis is carried out.Numerical simulations have been performed to verify the correctness of this prediction. The conjecture that the suppression of backscattering can achieve negative ARF is verified concretely, which greatly expands the application prospect and design ideas of the ARF. This work has laid a theoretical foundation for realizing precise control of the structure.

Detection of healthy and pathological heartbeat dynamics in ECG signals using multivariate recurrence networks with multiple scale factors

The electrocardiogram(ECG)is one of the physiological signals applied in medical clinics to determine health status.The physiological complexity of the cardiac system is related to age,disease,etc.For the investigation of the effects of age and cardiovascular disease on the cardiac system,we then construct multivariate recurrence networks with multiple scale factors from multivariate time series.We propose a new concept of cross-clustering coefficient entropy to construct a weighted network,and calculate the average weighted path length and the graph energy of the weighted network to quantitatively probe the topological properties.The obtained results suggest that these two network measures show distinct changes between different subjects.This is because,with aging or cardiovascular disease,a reduction in the conductivity or structural changes in the myocardium of the heart contributes to a reduction in the complexity of the cardiac system.Consequently,the complexity of the cardiac system is reduced.After that,the support vector machine(SVM)classifier is adopted to evaluate the performance of the proposed approach.Accuracy of 94.1%and 95.58%between healthy and myocardial infarction is achieved on two datasets.Therefore,this method can be adopted for the development of a noninvasive and low-cost clinical prognostic system to identify heart-related diseases and detect hidden state changes in the cardiac system.

Acoustic radiation force on a multilayered sphere in a Gaussian standing field

We develop a model for calculating the radiation force on spherically symmetric multilayered particles based on the acoustic scattering approach.An expression is derived for the radiation force on a multilayered sphere centered on the axis of a Gaussian standing wave propagating in an ideal fluid,The effects of the sound absorption of the materials and sound wave on acoustic radiation force of a multilayered sphere immersed in water are analyzed,with particular emphasis on the shell thickness of every layer,and the width of the Gaussian beam.The results reveal that the existence of particle trapping behavior depends on the choice of the non-dimensional frequency ka,as well as the shell thickness of each layer.This study provides a theoretical basis for the development of acoustical tweezers in a Gaussian standing wave,which may benefit the improvement and development of acoustic control technology,such as trapping,sorting,and assembling a cell,and drug delivery applications.

Location of micro-cracks in plates using time reversed nonlinear Lamb waves

A promising tool to detect micro-cracks in plate-like structures is used for generating higher harmonic Lamb waves.In this paper,a method combining nonlinear S0 mode Lamb waves with time reversal to locate micro-cracks is presented and verified by numerical simulations.Two different models,the contact acoustic nonlinearity(CAN)model and the Preisach-Mayergoyz(PM)model,are used to simulate a localized damage in a thin plate.Pulse inversion method is employed to extract the second and fourth harmonics from the received signal.Time reversal is performed to compensate the dispersion of S0 mode Lamb waves.Consequently,the higher harmonics generated from the damaged area can be refocused on their source.By investigating the spatial distribution of harmonic wave packets,the location of micro-cracks will be revealed.The numerical simulations indicate that this method gives accurate locations of the damaged area in a plate.Furthermore,the PM model is proved to be a suitable model to simulate the micro-cracks in plates for generation of higher harmonics.

基于水平可视图多元联合模体熵的多维EEG情感脑电信号识别

目前,许多基于深度学习和神经网络的算法被应用于脑电(electroencephalogram, EEG)信号情感识别.然而,现有研究大多采用提取单维脑电信号特征的方法.随着多传感技术的更新,更具全面性和系统性的多维信号特征提取需求出现.本文尝试将复杂网络研究应用到多维情感脑电识别中,提出一种基于水平可视图多元联合模体熵的情感识别算法,该方法可以有效避免人工选取特征对实验结果的影响,保持原始序列的非线性动力学特征.首先利用水平可视图算法将多维情感脑电信号分别转换为多路可视图网络,提取模体熵特征识别情感脑电研究中的关键频带和关键通道.在此基础上,将水平可视图网络两两联合,提取多元水平联合模体熵向量,作为输入参数对情感脑电信号进行识别.由于情感脑电序列长度会对识别效果产生影响,我们将脑电信号切割成大小不一的窗口,对比不同窗口大小对分类准确率的影响.实验结果表明,当切割窗口大小为10 s时,多元水平联合模体熵对情感脑电信号的识别效果最佳,对积极脑电/消极脑电、积极脑电/中性脑电、消极脑电/中性脑电的分类准确率分别达到95.07%, 97.73%, 90.26%,优于其他二维连接参数.同时,三分类的准确率为93.67%,本文算法无论在识别复杂度和准确率上,与已有算法相比均有较大提高.

基于分形的心电信号复杂度及其非线性动力学机制

体表心电图(electrocardiogram, ECG)信号是典型的非平稳谐和变频信号,属于非线性信号.传统的线性分析方法并不能很好地揭示ECG信号非线性本质.本研究采用多重分形理论,研究了大量样本同步十二导联心电图信号的奇异谱面积,经方差分析(analysis of variance, ANOVA)检验,该参数对所研究人群各导联均统计可分.结果显示,健康年轻人(healthy young, HY)十二导联ECG信号奇异谱面积的算术均值最大、离散度最小,而心梗(myocardial infraction, MI)患者十二导联ECG信号奇异谱面积算术均值最小、离散度最大,其他人群如心肌缺血(ischemia)患者、健康老年人(healthy old, HO)这两个值均处于中等大小水平.表明随着病变程度加深,心脏组织类分形结构受损或者发生结构改变,导致心电系统非线性动力学复杂程度降低,同时增加了心电信号传播的不规则性和各向异性.另外研究发现, ECG信号奇异谱面积在一定程度上反映了人体自主神经控制的强弱.随着年龄增长,奇异谱面积的十二导联均值逐渐减小,提示自主神经的自律控制功能逐渐减弱;ECG信号非线性复杂性下降,由多重分形趋向单重分形,意味着个体适应能力的降低.