Using computer vision technology to obtain and analyze biomechanical information is an important research direction in recent years. However, the linear model in the computer vision system cannot accurately describe the geometric relationship of the camera imaging, so it is difficult to realize human posture recognition in high-precision mechanics information. Therefore, how to improve the recognition accuracy is very important. In this paper, we apply nonlinear differential equations to stereo computer vision (SCV) information systems. And based on the median theorem, a nonlinear posture recognition and error compensation algorithm based on BP neural network is proposed to reduce the recognition error. The test set uses the Leeds Motion Pose (LSP) dataset to verify the performance of the algorithm. Experimental results show that the compensated median filter of BP neural network can eliminate glitches in attitude data. Superimposing the output attitude error compensation value with the attitude estimation value can greatly reduce the root-mean-square error of the attitude angle. The result of gesture recognition is closer to reality. Compared with traditional algorithms, the cyclomatic complexity of the proposed BP neural network algorithm has a much lower growth rate in high-order calculations, which indicates that the proposed BP neural network algorithm is more concise and scalable.

In this paper, the structure optimization scheme of multi-layer absorber on the surface of human tissue is designed. The absorber uses graphite, foam and other materials to build a resistance loss layer. Solve the electromagnetic parameters of graphite through its characteristics, use the equivalent transmission line theory to calculate the reflection coefficient. Establish the objective function of the reflection coefficient, and use genetic algorithm to optimize the design of the absorbing device. The experimental results show that compared with the Jaumann type three-layer absorber, the reflection coefficient of the multi-layer absorber optimized by genetic algorithm in this paper has decreased by nearly 13 dB. From the analysis of error and sensitivity, it can be concluded that when the material thickness error is within the range of ±0.005 mm, the microwave absorption performance error of the multilayer absorber is about 5%. Within this error range, the performance of the multilayer absorber can be guaranteed. The sensitivity analysis results of the materials in each layer of the absorber indicate that the concentration and thickness of the graphite layer have the greatest impact on the performance of the absorber.

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Mechanical stimulation is capable of affecting cell apoptosis. Several studies have shown that the Bcl-2 gene family, including the Bcl-2 gene and Bax gene, plays an important role in apoptosis, as proteins produced by the Bcl-2 gene can inhibit apoptosis while proteins produced by the Bax gene can promote cell apoptosis. Understanding how mechanical stimulation alters the expression of apoptosis-related genes in cardiomyocytes can contribute to the development of ways to inhibit cardiomyocyte necrosis. Intermediate myocytes showed a clear transmural repolarization. The cytoskeleton changed slowly in the cytoplasm of cardiomyocytes. The high-frequency mechanical signal stimulation under caspase inhibitors had the lowest apoptotic rate of cardiomyocytes, and a comparison showed that the rate of necrosis of cardiomyocytes was lower in the high-frequency group than in the inhibitor group at different times. The expression of the Bcl-2 gene increased significantly after the stimulation of the high-frequency mechanical signal. Overall, the results suggest that high-frequency stimulation can effectively inhibit cardiomyocyte apoptosis. KeywordsBcl-2 gene • Cardiomyocyte • Apoptosis • Stimulation • Loading model Abbreviations ER Endoplasmic reticulum GFP Green fluorescent protein PBS Phosphate buffer saline Rt-qPCR Real-time fluorescence quantitative polymerase chain * Yuejin Zhang

Aiming at the problem of poor construction accuracy of the cellular three-dimensional (3D) mechanical microenvironment, this article studies the cellular 3D mechanical microenvironment based on machine vision. The gelatin methacrylate microgel column was prepared by NIH/3T3 mouse fibroblast and precursor solution of gelatin methacrylate microgel. The gelatin methacrylate microgel array with magnetic end was adopted. The external magnetic field was used to load microgel array and build 3D mechanics microenvironment model. The deformed pictures of hydrogel under magnetic field were obtained by fluorescence microscope. The scanning electron microscope was used to characterize the pore structure of gelatin methacrylate hydrogel. The pictures obtained by machine vision method were used to calculate the deformed parameters of sample. The machine vision method adopted the discrete cosine transform for autofocus, and then used the image analysis and processing technology to identify and estimate the cell motion parameters. After getting the cell motion parameters, Comsol multiphysics (COMSOL) multiphysics multifield coupling finite element analysis software was adopted. The correlative numerical simulation method and gel deformed simulation method were used to obtain the mechanical changes of cells in the 3D mechanical microenvironment. Experimental results show that the modulus of gelatin methacrylate microgel is changed significantly during the tensile loading. The tensile strain and the cell spreading area are nonlinearly related. The increase in stiffness of the hydrogel substrate helps to promote cell proliferation to a certain extent.