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Computational modeling and investigation have become increasingly useful in assessing the hemodynamic and structural factors that contribute to aneurysm rupture, particularly when conventional clinical tools are inadequate. To this end, we conduct a study of a realistic internal carotid artery (ICA) under various working conditions using computational fluid dynamics. We analyze nine specific real ICA geometries in terms of coiling porosity and blood hematocrit, using a response surface model to evaluate 25 runs across selected geometrical parameters and treatment factors. The computational domain is created using computed tomography data from an actual patient, and we apply proposed boundary conditions to solve three-dimensional transient Navier–Stokes equations. By analyzing these cases, we try to understand how the sac section area, mean radius of the parent vessel, hematocrit, and coiling porosity interact and affect the risk of ICA rupture. We conduct an extensive study of the effects of sac section area and mean radius of the parent vessel on blood hemodynamics, examining several factors and comparing them at the peak systolic time instant, including wall shear stress (WSS), oscillatory shear index (OSI), pressure distributions, and velocity. Our results show that a 12% increase in the mean radius of the parent vessel reduced the maximum OSI value by approximately 50%, while a 120% increase in the sac section area decreases WSS on the aneurysm wall by up to 300%. These findings demonstrate the potential of computational modeling to provide valuable insight into the complex factors that influence aneurysm rupture, especially in cases where traditional clinical tools may be insufficient. [ABSTRACT FROM AUTHOR]

Pathological examination is the gold standard for breast cancer diagnosis. The recognition of histopathological images of breast cancer has attracted a lot of attention in the field of medical image processing. In this paper, on the base of the Bioimaging 2015 dataset, a two-stage nuclei segmentation strategy, that is, a method of watershed segmentation based on histopathological images after stain separation, is proposed to make the dataset recognized to be the carcinoma and non-carcinoma recognition. Firstly, stain separation is performed on breast cancer histopathological images. Then the marker-based watershed segmentation method is used for images obtained from stain separation to achieve the nuclei segmentation target. Next, the completed local binary pattern is used to extract texture features from the nuclei regions (images after nuclei segmentation), and color features were extracted by using the color auto-correlation method on the stain-separated images. Finally, the two kinds of features were fused and the support vector machine was used for carcinoma and non-carcinoma recognition. The experimental results show that the two-stage nuclei segmentation strategy proposed in this paper has significant advantages in the recognition of carcinoma and non-carcinoma on breast cancer histopathological images, and the recognition accuracy arrives at 91.67%. The proposed method is also applied to the ICIAR 2018 dataset to realize the automatic recognition of carcinoma and non-carcinoma, and the recognition accuracy arrives at 92.50%. [ABSTRACT FROM AUTHOR]

Grasshopper optimization algorithm (GOA) proposed in 2017 mimics the behavior of grasshopper swarms in nature for solving optimization problems. In the basic GOA, the influence of the gravity force on the updated position of every grasshopper is not considered, which possibly causes GOA to have the slower convergence speed. Based on this, the improved GOA (IGOA) is obtained by the two updated ways of the position of every grasshopper in this paper. One is that the gravity force is introduced into the updated position of every grasshopper in the basic GOA. And the other is that the velocity is introduced into the updated position of every grasshopper and the new position are obtained from the sum of the current position and the velocity. Then every grasshopper adopts its suitable way of the updated position on the basis of the probability. Finally, IGOA is firstly performed on the 23 classical benchmark functions and then is combined with BP neural network to establish the predicted model IGOA-BPNN by optimizing the parameters of BP neural network for predicting the closing prices of the Shanghai Stock Exchange Index and the air quality index (AQI) of Taiyuan, Shanxi Province. The experimental results show that IGOA is superior to the compared algorithms in term of the average values and the predicted model IGOA-BPNN has the minimal predicted errors. Therefore, the proposed IGOA is an effective and efficient algorithm for optimization. [ABSTRACT FROM AUTHOR]

Due to the complex underwater environment and the selective absorption and scattering effect of water on light waves, underwater images often suffer from issues such as low contrast, color distortion, and blurred details. This paper presents a stable and effective algorithm for enhancing underwater images to address these challenges. Firstly, an improved color correction algorithm based on the gray world and minimum information loss is employed to remove the blue-green bias present in the images. Secondly, a contrast enhancement algorithm is based on the guided filter and wavelet decomposition to make the texture details of the image clearer. Then, the normalized weight map of the image is obtained to carry out multi-scale fusion. Finally, the fused image is applied to perform the multi-scale decomposition. The experimental results show that the algorithm proposed in this paper can correct the image color deviation, improve the image contrast and enhance the image details. [ABSTRACT FROM AUTHOR]

Abstract Endometrial carcinoma is a life-threatening disease that causes serious damage to the women's health. This paper discusses classifications of 87 endometrial samples with gene expressions that are cancerous or cancer-free. Every sample has 5 indicators. For every indicator, the corresponding genes of the missing data are deleted and the signal noise ratios (SNRs) are calculated to filter the irrelevant genes. Then the obtained new samples use the principle component analysis to decrease the dimensions. Finally 10 random samples are selected to be the testing samples for classification. Thus the classification accuracy rate is given for every indicator. Based on cancer related to 5 indicators, the combination of the 5 indicators is used to classify to make new 87 endometrial samples as cancerous or cancer-free. We repeatedly process these new samples by deleting the missing data, filtering the irrelevant genes with SNRs, and decreasing the dimensions with PCA, an obtain the new data. The proposed method is that the particle swarm algorithm (PSO) and the grey wolf optimizer (GWO) is combined to optimize the parameters of Elman recurrent neural network (ERNN), written as PSOGWO-ERNN. The results show that PSOGWO-ERNN is superior to the single ERNN, ERNN optimized by PSO or GWO (PSO-ERNN or GWO-ERNN), and the classification accuracy rate of PSOGWO-ERNN reaches 88.8506%. The results also show that the neural networks optimized by some swarm intelligence algorithms are more useful for classification. [ABSTRACT FROM AUTHOR]

The stock market is affected by many factors, such as political events, general economic conditions, and traders’ expectations. Predicting the direction of stock markets movement has been one of the most widely investigated and challenging problems for investors and researchers as well. Many researchers focus on stock market analysis using advanced knowledge of mathematics, computer sciences, economics and many other disciplines. In this paper, we present an improved sine cosine algorithm (ISCA), which introduces an additional parameter into the sine cosine algorithm (SCA), to optimize the weights and basis of back propagation neural networks (BPNN). Thus, ISCA and BPNN are combined to create a new network, ISCA-BPNN, for predicting the directions of the opening stock prices for the S&P 500 and Dow Jones Industrial Average Indices, respectively. In addition, Google Trends data are taken into consideration for improving stock prediction. We analyze two types of prediction: Type I is the prediction without Google Trends and Type II is the prediction with Google Trends. The predictability of stock price direction is verified by using the hybrid ISCA-BPNN model. The experimental results indicate that ISCA–BPNN outperforms BPNN, GWO-BPNN, PSO-BPNN, WOA-BPNN and SCA-BPNN in terms of predicting the direction of the opening price for both types and significantly for Type II. The hit ratios for ISCA-BPNN with Google Trends reach 86.81% for the S&P 500 Index, and 88.98% for the Dow Jones Industrial Average Index. Our results show that Google Trends can help in predicting the direction of the stock market index. [ABSTRACT FROM AUTHOR]

A phononic crystal with an ultra‐wide band gap is proposed, whose unit cell consists of a cross‐like concave hole in the center and four square convex holes at the corners. The dispersion relations, modal kinetic energy ratio, and eigenmodes at edges of the band gaps are investigated by using the finite element method. The influence of the geometrical parameters of the convex and concave holes on the band gaps is further analyzed. After optimization, an ultra‐wide band gap with gap‐to‐midgap ratio of 156.0% is achieved, with the filling fraction keeping a relative small value. Numerical results illustrate that the combination of convex and concave holes is a practicable direction for structural optimization of phononic crystals exhibiting ultra‐wide band gaps. [ABSTRACT FROM AUTHOR]

A two-dimensional cross-like phoxonic crystal (PxC) model is proposed, which exhibits simultaneously large complete photonic crystal (PtC) and phononic crystal (PnC) bandgaps. The most salient trait of the structure is the wide range of geometrical parameters compatible with large complete bandgaps. After geometrical optimization, photonic and phononic bandgaps with gap-to-midgap ratios of 11.5% and 90.7% are obtained, respectively. These values are close to the best topology-optimized reported values but are obtained with simple shapes compatible with nanoscale fabrication technology. These characteristics make the convex–concave topology a promising candidate for PxC devices. A cavity is then introduced by filling up one cross-like hole in the 7 × 7 super-cell. PtC and PnC bands with defects appear in the respective large complete bandgaps, confining phonons and photons in the same cavity. Acousto-optic (AO) coupling between photonic and phononic defect modes is further investigated by the finite element method, taking both photoelastic and moving interface mechanisms into consideration. The symmetries of both photonic and phononic modes play a dominant role in the coupling strength. Results show that the strongest linear coupling between a photonic transverse magnetic mode and phononic breathing mode is obtained due to the in-phase superposition in the x and y directions. A quadratic nonlinear coupling is observed when photonic modes are coupled with the phononic stretching mode due to the inverse superposition of x and y directions. Finally, the optomechanical coupling rates relative to zero-point motion are estimated. [ABSTRACT FROM AUTHOR]

An effective two-level self-organizing map (SOM) neural network for direction of arrival (DOA) of sound signals estimation is proposed. The approach is based on the distance difference of arrival (DDOA) and a uniform linear sensor array in a 2D plane; it performs a nonlinear mapping between the DDOA vectors and angles of arrival (AOA). We found that the topological order of DDOA vectors and AOAs of same signals is uniform; thus, the topological order preserving of SOM network makes it valid to estimate AOA through DDOA. From the results of simulations and lake experiments, it is shown that the network has the advantage of accuracy and robustness, can be trained in advance, and is easy to implement. [ABSTRACT FROM AUTHOR]

The architecture and parameter initialization of wavelet neural network are discussed and a novel initialization method is proposed. The new approach can be regarded as a dynamic clustering procedure which will derive the neuron number as well as the initial value of translation and dilation parameters according to the input patterns and the activating wavelets functions. Three simulation examples are given to examine the performance of our method as well as Zhang's heuristic initialization approach. The results show that the new approach not only can decide the WNN structure automatically, but also provides superior initial parameter values that make the optimization process more stable and quickly. [ABSTRACT FROM AUTHOR]

This paper proposes an improved dynamic particle swarm optimization algorithm, which uses a new and effective exponential decreasing inertia weight (EDIW) strategy. Based on the improved EDIW-PSO algorithm together with AdaBoost algorithm, we adjust the parameters (centers, widths, shape parameters and connection weights) of GRBF and present a novel hybrid EDIW-PSO-AdaBoost-GRBF model. Two application examples are given on the proposed model. The results obtained show that the proposed model is effective and feasible for prediction problems. [ABSTRACT FROM AUTHOR]

The size-dependent band structure of an Si phononic crystal (PnC) slab with an air hole is studied by utilizing the non-classic wave equations of the nonlocal strain gradient theory (NSGT). The three-dimensional (3D) non-classic wave equations for the anisotropic material are derived according to the differential form of the NSGT. Based on the the general form of partial differential equation modules in COMSOL, a method is proposed to solve the non-classic wave equations. The bands of the in-plane modes and mixed modes are identified. The in-plane size effect and thickness effect on the band structure of the PnC slab are compared. It is found that the thickness effect only acts on the mixed modes. The relative width of the band gap is widened by the thickness effect. The effects of the geometric parameters on the thickness effect of the mixed modes are further studied, and a defect is introduced to the PnC supercell to reveal the influence of the size effects with stiffness-softening and stiffness-hardening on the defect modes. This study paves the way for studying and designing PnC slabs at nano-scale. [ABSTRACT FROM AUTHOR]

We propose a new structure consisting of a piezoelectric spring?mass system as a low-frequency piezoelectric energy harvester. A theoretical model is developed for the system from the theory of piezoelectricity. An analysis is performed to demonstrate the low-frequency nature of the system. Other basic characteristics of the energy harvester, including the output power, voltage, and efficiency, are also calculated and examined. [ABSTRACT FROM AUTHOR]

The outbreak of Corona Virus Disease 2019 (COVID-19) in Wuhan has significantly impacted the economy and society globally. Countries are in a strict state of prevention and control of this pandemic. In this study, the development trend analysis of the cumulative confirmed cases, cumulative deaths, and cumulative cured cases was conducted based on data from Wuhan, Hubei Province, China from January 23, 2020 to April 6, 2020 using an Elman neural network, long short-term memory (LSTM), and support vector machine (SVM). A SVM with fuzzy granulation was used to predict the growth range of confirmed new cases, new deaths, and new cured cases. The experimental results showed that the Elman neural network and SVM used in this study can predict the development trend of cumulative confirmed cases, deaths, and cured cases, whereas LSTM is more suitable for the prediction of the cumulative confirmed cases. The SVM with fuzzy granulation can successfully predict the growth range of confirmed new cases and new cured cases, although the average predicted values are slightly large. Currently, the United States is the epicenter of the COVID-19 pandemic. We also used data modeling from the United States to further verify the validity of the proposed models. [ABSTRACT FROM AUTHOR]

The definitions of the third-order elastic, piezoelectric, and dielectric constants and the properties of the associated tensors are discussed. Based on the energy conservation and coordinate transformation, the relations among the third-order constants are obtained. Furthermore, the relations among the third-order elastic, piezoelectric, and dielectric constants of the seven crystal systems and isotropic materials are listed in detail. These third-order constants relations play an important role in solving nonlinear problems of elastic and piezoelectric materials. It is further found that all third-order piezoelectric constants are 0 for 15 kinds of point groups, while all third-order dielectric constants are 0 for 16 kinds of point groups as well as isotropic material. The reason is that some of the point groups are centrally symmetric, and the other point groups are high symmetry. These results provide the foundation to measure these constants, to choose material, and to research nonlinear problems. Moreover, these results are helpful not only for the study of nonlinear elastic and piezoelectric problems, but also for the research on flexoelectric effects and size effects. [ABSTRACT FROM AUTHOR]

A high-precision equipment is very sensitive to vibration, even micro vibration. How to isolate the low-frequency broadband multidirectional vibration remains a challenge. As the main component of piezoelectric smart vibration isolation model, the piezoelectric stack consists of a piezoelectric actuator, a piezoelectric sensor, and a rubber layer. The numerical results obtained by the finite element method agree well with theoretical solutions. The vibration attenuates rapidly under displacement and velocity feedback control with negative gains. As the control gain decreases, the vibration isolation band is extended to lower frequency. A piezoelectric smart multidirectional vibration isolation platform model is further proposed by inclined installation of two piezoelectric stacks. A spring-like structure is designed to exert a preload pressure on these piezoelectric stacks. After optimization on the control gain, the platform can isolate vibration from 0 to 3000 Hz in multiple directions. [ABSTRACT FROM AUTHOR]

A novel breast ultrasound tomography system based on a circular array of capacitive micromechanical ultrasound transducers (CMUT) has broad application prospects. However, the images produced by this system are not suitable as input for the training phase of the super-resolution (SR) reconstruction algorithm. To solve the problem, this paper proposes an improved medical image super-resolution (MeSR) method based on the sparse domain. First, we use the simultaneous algebraic reconstruction technique (SART) with high imaging accuracy to reconstruct the image into a training image in a sparse domain model. Secondly, we denoise and enhance the contrast of the SART images to obtain improved detail images before training the dictionary. Then, we use the original detail image as the guide image to further process the improved detail image. Therefore, a high-precision dictionary was obtained during the testing phase and applied to filtered back projection SR reconstruction. We compared the proposed algorithm with previously reported algorithms in the Shepp Logan model and the model based on the CMUT background. The results showed significant improvements in peak signal-to-noise ratio, entropy, and average gradient compared to previously reported algorithms. The experimental results demonstrated that the proposed MeSR method can use noisy reconstructed images as input for the training phase of the SR algorithm and produce excellent visual effects. [ABSTRACT FROM AUTHOR]

The significance of flu prediction is that the appropriate preventive and control measures can be taken by relevant departments after assessing predicted data; thus, morbidity and mortality can be reduced. In this paper, three flu prediction models, based on twitter and US Centers for Disease Control’s (CDC’s) Influenza-Like Illness (ILI) data, are proposed (models 1-3) to verify the factors that affect the spread of the flu. In this work, an Improved Particle Swarm Optimization algorithm to optimize the parameters of Support Vector Regression (IPSO-SVR) was proposed. The IPSO-SVR was trained by the independent and dependent variables of the three models (models 1-3) as input and output. The trained IPSO-SVR method was used to predict the regional unweighted percentage ILI (%ILI) events in the US. The prediction results of each model are analyzed and compared. The results show that the IPSO-SVR method (model 3) demonstrates excellent performance in real-time prediction of ILIs, and further highlights the benefits of using real-time twitter data, thus providing an effective means for the prevention and control of flu. [ABSTRACT FROM AUTHOR]

We study a few transient effects of AT-cut quartz thickness-shear resonators, including resonator turning on and turning off as well as voltage amplitude and frequency fluctuations. Mindlin?s two-dimensional plate equations are used and solved analytically. Both a sudden change and a gradual change of the driving voltage are studied. It is found that for a resonator with a frequency of 1.649430868 MHz and material quality factor of Q = 105, the characteristic time scale of the transient effects is of the order of 0.1 s. [ABSTRACT FROM PUBLISHER]

An enhanced plane wave expansion (PWE) method is proposed to solve piezoelectric phononic crystal (PPC) connected with resonant shunting circuits (PPC-C), which is named as PWE-PPC-C. The resonant shunting circuits can not only bring about the locally resonant (LR) band gap for the PPC-C but also conveniently tune frequency and bandwidth of band gaps through adjusting circuit parameters. However, thus far, more than one-dimensional PPC-C has been studied just by Finite Element method. Compared with other methods, the PWE has great advantages in solving more than one-dimensional PC as well as various lattice types. Nevertheless, the conventional PWE cannot accurately solve coupling between the structure and resonant shunting circuits of the PPC-C since only taking one-way coupling from displacements to electrical parameters into consideration. A two-dimensional PPC-C model of orthorhombic lattice is established to demonstrate the whole solving process of PWE-PPC-C. The PWE-PPC-C method is validated by Transfer Matrix method as well as Finite Element method. The dependence of band gaps on circuit parameters has been investigated in detail by PWE-PPC-C. Its advantage in solving various lattice types is further illustrated by calculating the PPC-C of triangular and hexagonal lattices, respectively. [ABSTRACT FROM AUTHOR]

• Liquid-solid synergistic (LSS) mechanism is proposed for sound absorption. • 3 mm coating efficiently absorbs sound from 1 to 1000 Hz. • Optimal channel widths are obtained corresponding to viscosities of viscous liquid. • Three conditions for implementing LSS mechanism are given. The liquid-solid synergistic (LSS) mechanism is put forward for sound absorption. An ultra-thin LSS anechoic coating model is established to achieve significant low-frequency and broadband sound absorption. Based on the LSS mechanism, the coating converts longitudinal acoustic waves into shear wave of viscous liquids and bending wave of viscoelastic solids. The wavelengths of shear wave in viscous liquids and bending wave in viscoelastic solids are both very short, but not equal to each other. Through liquid-solid synergistic coupling, low-frequency broadband water acoustic waves are attenuated and absorbed by the ultra-thin LSS coating. The LSS mechanism is analyzed in detail and further compared with that of Helmholtz resonator. Three conditions for implementing LSS mechanism are given. The effects of structural parameters, and material parameters of the solid and the liquid on the sound absorption capacity are investigated. The anechoic coating owns the sound absorption coefficient greater than 0.5 in the band of 1 to 1000 Hz, with a thickness of only 3 mm, which is far less than 1‰ of the incident wavelength at 100 Hz. The innovative mechanism provides a solution to the challenge of achieving thin thickness and low-frequency broad band sound absorption of underwater anechoic coatings. [Display omitted] [ABSTRACT FROM AUTHOR]

• Considering the hardening and softening effects simultaneously, a novel size-dependent FEM model is established to reveal the size effect of nano-scale 2D phononic crystals. • The propagations of in-plane wave and out-of-plane wave in nano-scale phononic crystals are investigated respectively. • The influences of the two nonlocal parameters on the first band gap are discussed. • The dependences of the size effect upon structural parameters are investigated. It is found that thickness of minimum connector is the key factor to the size effect, while filling ratio and surface length have little influence on the size effect. Phononic crystal (PnC) has attracted strong attention due to its tremendous capabilities to manipulate acoustic and elastodynamic waves. For high frequency (gigahertz) PnC, the size effect becomes significant when the dimension of the structure approaches nano-scale. In the present paper, the size-dependent band structure of a two dimensional (2D) PnC is studied by utilizing differential governing equation of nonlocal strain gradient theory (NSGT). The general equation of motion and boundary conditions are first derived by a variational formulation based on Hamilton's principle. Based on general form partial differential equation module in COMSOL® Multiphysics, a method is further proposed to solve the non-classic wave equations, which are derived from strain-, and stress-driven nonlocal models, and NSGT. The square lattice PnCs with circle, cross, and octangle air holes are investigated. Numerical results show size effect becomes significant when the lattice constant approaches nano-scale. The smaller size results in the stronger size effect. The influence of two nonlocal parameters on the first band gap is investigated simultaneously. The band gap always tends to narrower because of the size effect. Finally, it is found that the strength of size effect is mainly related to the thickness of minimum connector, but not to the filling ratio and surface length. This study paves the way for the studying and designing PnC in nano-scale or at ultra-high frequency. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: Asymmetrical oscillation of a micro-bubble confined inside a deformable pseudoelastic vessel with comparable initial radius with the bubble is studied in detail. Unlike the symmetric oscillation in an unconstrained environment, the oscillating bubble under the constraint of a pseudoelastic vessel gradually becomes as an ellipsoid from a sphere (this is called asymmetrical effect), and leads to substantially larger stresses within the vessel wall. Influence of inertial effect, circumferential stiffness and pre-existing blood pressure on bubble’s asymmetrical oscillation are taken into account in the paper. Computational results show that a vessel wall with larger circumferential stiffness corresponds to larger stress amplitude with higher frequency within the wall, where the stress amplitude and the pertinent frequency are the two most dominating parameters in determining the failure event under cyclic loading, as well known in the community of materials science. Similar results have been obtained for the case of decreasing in thickness of vessel walls, and for the case of increasing pre-existing pressure in the liquid filling the vessel. These conclusions support the notion that the asymmetric effect is one of the primary mechanisms for the clinical injuries of those with thinner vessel walls, such as capillary and small blood vessels, and for the higher risk of elder and hypertension patients in the shock-wave lithotripsy and other medical procedures involving shock waves, such as ultrasound-assisted encapsulated drug delivery. [Copyright &y& Elsevier]

• Pipe clamp equations are given to calculate equivalent support stiffness and torsional stiffness from structural and material parameters. • Nonlinear dynamic response of a liquid-conveying pipe within a cross-flow field is investigated. • Differential Quadrature Method is provided in detail to solve nonlinear partial differential equations with the boundary conditions of different constraint stiffness. • Influence of material and structure parameters on lock-in region is clarified to guide layout and design of pipe clamps. Nonlinear dynamic response of a viscoelastic fluid-conveying pipe excited by uniform external cross flow is investigated, which is installed by pipe clamps. A pipe clamp theoretical model is proposed for the actual pipe clamp instead of the commonly used simply supported or clamped boundary conditions. Based on the model, equivalent support stiffness and torsional stiffness are obtained from structure and material parameters of the pipe clamp. The vortex-induced lift force and the mean drag force are described by van der Pol oscillator model. The nonlinear equations of motion with the boundary conditions of different constraint stiffness are discretized by Differential Quadrature Method (DQM) and then solved by Runge-Kutta algorithm. The results are verified by Galerkin method for the pinned-pinned pipe, and by ANSYS for the pipe with two arbitrary constraint stiffnesses. The dependence of critical external fluid velocity upon constraint stiffness and pipe length is investigated. Moreover, the effects of support stiffness, torsional stiffness, internal fluid velocity, and viscoelastic coefficient on the amplitude response of the pipe are studied in detail. The influence of constraint stiffness on characteristics of lock-in region is elucidated. Consequently, pipe clamp spacing, material and structure parameters of the rubber mat can be designed to ensure the requirement of economy and safety, which are helpful to guide the layout and design of pipe clamps. [ABSTRACT FROM AUTHOR]

We propose a new type of phononic crystal (PnC) composed of a periodic alternation of circular cavity sandwich plates. In the low-frequency regime, the crystal can modulate the propagation of flexural waves. Governing equations are deduced basing on the classical theory of coupled extensional and flexural vibrations of plates. The dispersion relation of the infinite PnC is calculated by combining the transfer matrix method with Bloch theory. The dynamic response of the PnC with finite unit cells is further studied with finite element analysis. An experiment is carried out to demonstrate the performance of the PnC in vibration isolation. Numerical results and experimental results both illustrate that the proposed PnC can generate several wide low-frequency Bragg band gaps providing strong attenuation. The dependence of band gaps upon geometric and material parameters is also analyzed in detail in view of vibration isolation applications. [ABSTRACT FROM AUTHOR]

A folding beam-type piezoelectric phononic crystal model is proposed to isolate vibration. Two piezoelectric bimorphs are joined by two masses as a folding structure to comprise each unit cell of the piezoelectric phononic crystal. Each bimorph is connected independently by a resistive-inductive resonant shunting circuit. The folding structure extends the propagation path of elastic waves, while its structure size remains quite small. Propagation of coupled extension-flexural elastic waves is studied by the classical laminated beam theory and transfer matrix method. The theoretical model is further verified with the finite element method (FEM). The effects of geometrical and circuit parameters on the band gaps are analyzed. With only 4 unit cells, the folding beam-type piezoelectric phononic crystal generates two Bragg band gaps of 369Hz to 1 687Hz and 2 127Hz to 4 000Hz. In addition, between these two Bragg band gaps, a locally resonant band gap is induced by resonant shunting circuits. Appropriate circuit parameters are used to join these two Bragg band gaps by the locally resonant band gap. Thus, a low-frequency and broad band gap of 369Hz to 4 000Hz is obtained. [ABSTRACT FROM AUTHOR]

This work presents an investigation on vibration transmission in a circular thin plate consisting of metal rings and piezoelectric rings arrayed periodically. Each piezoelectric ring is linked to an independent resistive–inductive (RL) resonant shunting circuit. For a periodic rectangular piezoelectric plate, equal inductances are commonly used in resonant shunting circuits. However, for the circular one, the locally resonant (LR) band gap (BG) cannot be formed by shunting circuits with equal inductances, because different periodic cell has a different capacitance. Instead of equivalent inductance circuits, the equal frequency shunting circuits are employed to tune the resonance frequency of each circuit into the same, thus an integrating LR BG is obtained. A transfer matrix method is used to calculate transmission factor in the low frequency range. The theoretical model is verified by finite element method (FEM). The impact of geometric and circuit parameters on the properties of the LR BG and vibration attenuation band (VAB) has also been analyzed. [ABSTRACT FROM AUTHOR]

As a preliminary attempt for the study on nonlinear vibrations of a finite crystal plate, the thickness-shear mode of an infinite and isotropic plate is investigated. By including nonlinear constitutive relations and strain components, we have established nonlinear equations of thickness-shear vibrations. Through further assuming the mode shape of linear vibrations, we utilized the standard Galerkin approximation to obtain a nonlinear ordinary differential equation depending only on time. We solved this nonlinear equation and obtained its amplitude-frequency relation by the homotopy analysis method (HAM). The accuracy of the present results is shown by comparison between our results and the perturbation method. Numerical results show that the homotopy analysis solutions can be adjusted to improve the accuracy. These equations and results are useful in verifying the available methods and improving our further solution strategy for the coupled nonlinear vibrations of finite piezoelectric plates. [ABSTRACT FROM AUTHOR]

Background: COVID-19 has become a major global threat. The present study aimed to develop a nomogram model to predict the survival of COVID-19 patients based on their clinical and laboratory data at admission.Methods: COVID-19 patients who were admitted at Hankou Hospital and Huoshenshan Hospital in Wuhan, China from January 12, 2020 to March 20, 2020, whose outcome during the hospitalization was known, were retrospectively reviewed. The categorical variables were compared using Pearson's χ2-test or Fisher's exact test, and continuous variables were analyzed using Student's t-test or Mann Whitney U-test, as appropriate. Then, variables with a P-value of ≤0.1 were included in the log-binomial model, and merely these independent risk factors were used to establish the nomogram model. The discrimination of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), and internally verified using the Bootstrap method.Results: A total of 262 patients (134 surviving and 128 non-surviving patients) were included in the analysis. Seven variables, which included age (relative risk [RR]: 0.905, 95% confidence interval [CI]: 0.868-0.944; P < 0.001), chronic heart disease (CHD, RR: 0.045, 95% CI: 0.0097-0.205; P < 0.001, the percentage of lymphocytes (Lym%, RR: 1.125, 95% CI: 1.041-1.216; P = 0.0029), platelets (RR: 1.008, 95% CI: 1.003-1.012; P = 0.001), C-reaction protein (RR: 0.982, 95% CI: 0.973-0.991; P < 0.001), lactate dehydrogenase (LDH, RR: 0.993, 95% CI: 0.990-0.997; P < 0.001) and D-dimer (RR: 0.734, 95% CI: 0.617-0.879; P < 0.001), were identified as the independent risk factors. The nomogram model based on these factors exhibited a good discrimination, with an AUC of 0.948 (95% CI: 0.923-0.973).Conclusions: A nomogram based on age, CHD, Lym%, platelets, C-reaction protein, LDH and D-dimer was established to accurately predict the prognosis of COVID-19 patients. This can be used as an alerting tool for clinicians to take early intervention measures, when necessary. [ABSTRACT FROM AUTHOR]

Underwater acoustic technology is an important means of detecting the ocean. Due to the complex influence of the marine environment, there is a lot of noise and baseline drift in the signals collected by hydrophones. In order to solve this problem, this paper proposes a denoising and baseline drift removal algorithm for MEMS vector hydrophone based on whale-optimized variational mode decomposition (VMD) and correlation coefficient (CC). Firstly, the power spectrum entropy (PSE), which reflects the variation characteristics of the signal frequency is selected as the fitness function of the whale-optimization algorithm to find the parameters (K,α) of the VMD. It is easier to find the global optimal solution of the parameters by combining the whale-optimization algorithm. Then, using the VMD algorithm after obtaining the parameters, the original signal is decomposed to obtain the intrinsic mode functions (IMFs), and calculating the correlation coefficients (CCs) between the IMFs and the original signal. Finally, the CC threshold is used to remove the noise IMFs, and the rest of the useful IMFs are reconstructed to complete the denoising and baseline drift removal process of the original signals. In the simulation experiments, the algorithm proposed in this paper shows better performance by comparing conventional digital signal-processing methods and the related algorithms proposed recently. Applied in the experiments of a MEMS hydrophone, the effectiveness of the proposed algorithm is also verified. This algorithm can provide new ideas for signal denoising and baseline drift removal. [ABSTRACT FROM AUTHOR]

A power harvester with adjustable frequency, which consists of a hinged?hinged piezoelectric bimorph and a concentrated mass, is studied by the precise electric field method (PEFM), taking into account a distribution of the electric field over the thickness. Usually, using the equivalent electric field method (EEFM), the electric field is approximated as a constant value in the piezoelectric layer. Charge on the upper electrode (UEC) of the bimorph is often assumed as output charge. However, different output charge can be obtained by integrating on electric displacement over the electrode with different thickness coordinates. Therefore, an average charge (AC) on thickness is often assumed as the output value. This method is denoted EEFM AC. The flexural vibration of the bimorph is calculated by the three methods and their results are compared. Numerical results illustrate that EEFM UEC overestimates resonant frequency, output power, and efficiency. EEFM AC can accurately calculate the output power and efficiency, but underestimates resonant frequency. The performance of the harvester, which depends on concentrated mass weight, position, and circuit load, is analyzed using PEFM. The resonant frequency can be modulated 924 Hz by moving the concentrated mass along the bimorph. This feature suggests that the natural frequency of the harvester can be adjusted conveniently to adapt to frequency fluctuation of the ambient vibration. [ABSTRACT FROM AUTHOR]

The effects of first-order strain gradient in micro piezoelectric-bimorph (PB) power harvesters are investigated by including the first-order gradient terms in the energy density functions. For a PB, the gradient effects can be focused on the analysis of the strain gradient effect in the thickness direction through choosing the strains and the electric displacements as the independent constitutive variables. It is shown theoretically that the first-order gradient effects have raised the natural frequency of the PB and effectively enhanced the output power density of the harvester. [ABSTRACT FROM PUBLISHER]