Glutaraldehyde (GA) was conventionally used to crosslink bovine pericardium to prepare bioprosthetic heart valves (BHVs), which usually fail within 10 years because of valve deterioration and calcification. To overcome the high cytotoxicity and severe calcification of GA-crosslinked BHVs, a quaternary ammonium salt of epoxy chitosan (epoxy group-modified 3-chlorine-2-hydroxypropyl trimethyl chitosan, abbreviated as “eHTCC”) was developed to modify the acellular bovine pericardium to substitute GA and improve its anti-calcification and biocompatible properties. Mechanical test, enzymatic stability test, blood compatibility assay, and cytocompatibility assay were used to investigate its mechanical property and biocompatibility. The anti-calcification effect of the eHTCC-modified bovine pericardium (eHTCC-BP) was assessed by in vitro assay and rat subcutaneous implantation assay. The results showed that eHTCC-BP could improve the mechanical properties and anti-enzymolysis ability of BP, as well as retain the original three-dimensional structure, compared with the uncrosslinked-BP group. Moreover, the in vivo calcification level of the eHTCC-BP group was much lower than that of the GA-BP group, which was 5.1% (2 weeks), 2.3% (4 weeks), and 0.8% (8 weeks) of the GA-BP group. In summary, this study demonstrated that eHTCC could be a potential crosslinking agent for the extracellular matrix for its favorable crosslinking effects, anti-enzymolysis, anti-calcification, and biocompatibility.

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In patients with traumatic orbital defects, accurate digital evaluations of the three-dimensional position of the globe and changes in the orbital volume aid in surgical planning with a personalized model and promote early surgery with minimal trauma. When the orbital volume was restored and the position of the globe was maintained or corrected, the precise reconstruction of the anatomic shape of the orbit was concurrently completed. Personalized orbital reconstruction can improve the efficacy of plastic surgery in patients with orbital deformities.

In the information processing procedure of stereo vision, the uniqueness constraint has been used as one of the constraints to solve the "correspondence problem". While the uniqueness constraint is valid in most cases, whether it is still valid in some particular stimulus configuration (such as Panum's limiting case) has been a problem of widespread debate for a long time. To investigate the problem, we adopted the Panum's limiting case as its basic stimulus configuration, and delved into the phenomenon of binocular fusion from two distinct aspects: visual direction and orientation disparity. The results show that in Panum's limiting case binocular fusion does not comply with the rules governing regular binocular fusion as far as visual direction and orientation disparity are concerned. This indicates that double fusion does not happen in Panum's limiting case and that the uniqueness constraint is still valid.

In order to solve the problem of how to quickly and accurately obtain crop images during crop growth monitoring, this paper proposes a deep compressed sensing image reconstruction method based on a multi-feature residual network. In this method, the initial reconstructed image obtained by linear mapping is input to a multi-feature residual reconstruction network, and multi-scale convolution is used to autonomously learn different features of the crop image to realize deep reconstruction of the image, and complete the inverse solution of compressed sensing. Compared with traditional image reconstruction methods, the deep learning-based method relaxes the assumptions about the sparsity of the original crop image and converts multiple iterations into deep neural network calculations to obtain higher accuracy. The experimental results show that the compressed sensing image reconstruction method based on the multi-feature residual network proposed in this paper can improve the quality of crop image reconstruction.

According to the characteristics of human gait and the requirements of power assistance, locomotive mechanisms and electrohydraulic servo driving are designed on a lower limb exoskeleton robot, in which the miniaturization and lightweight of driving system are realized. The kinematics of the robot is analyzed and verified via the typical movements of the exoskeleton. In this article, the simulation on the power of joints during level walking was analyzed in ADAMS 2016, which is a multibody simulation and motion analysis software. Motion ranges and driving strokes are then optimized. A proportional integral derivative (PID) control method with error estimation and pressure compensation is proposed to satisfy the requirements of joints power assistance and comply with the motion of human lower limb. The proposed method is implemented into the exoskeleton for assisted walking and is verified by experimental results. Finally, experiments show that the tracking accuracy and power-assisted performance of exoskeleton robot joints are improved.

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