Further study on particle size, stability, and complexation of silver nanoparticles under the composite effect of bovine serum protein and humic acid.

Silver nanoparticles (AgNPs) are widely used due to their unique antibacterial properties and excellent photoelectric properties. Wastewater treatment plants form a pool of AgNPs due to the social cycle of wastewater. During biological treatment processes, the particle size and stability of AgNPs change. We studied the particle size changes and stability of silver nanoparticles in the presence of bovine serum albumin (BSA) and humic acid (HA). The experimental results indicated that silver nanoparticles can complex with the functional groups in BSA. For AgNP-BSA composites, as the BSA concentration increases, the size of the silver nanoparticles first decreases and then increases. AgNPs can combine with the amide, amino, and carboxyl groups in HA. As the concentration of HA increases, the particle size and large particle size distribution of AgNPs increase. This increasing trend is more obvious when the HA concentration is lower than 20 mg L-1. When HA and BSA exist at the same time, HA will occupy the adsorption sites of BSA on the surface of AgNPs, and the AgNP-HA complex will dominate the system. This study aims to provide key operational control strategies for the process operation of wastewater treatment plants containing AgNPs and theoretical support for promoting water environment improvement and economic development such as tourism.

Multiview intelligent networking based on the genetic evolution algorithm for precise 3D measurements.

The use of multi-visual network 3D measurements is increasing; however, finding ways to apply low-cost industrial cameras to achieve intelligent networking and efficient measurement is a key problem that has not been fully solved. In this paper, the multivision stereo vision 3D measurement principle and multivision networking process constraints are analyzed in depth, and an intelligent networking method based on the genetic evolution algorithm (GEA) is proposed. The genetic operation is improved, and the fitness function is dynamically calibrated. Based on the visual sphere model, the best observation distance is assigned as the radius of the visual sphere, and the required constraints are fused to establish an intelligent networking design of the centering multivision. A simulation and experiment show that the proposed algorithm is widely feasible, and its measurement accuracy meets the requirements of the industrial field. Our multiview intelligent networking algorithms and methods provide solid theoretical and technical support for low-cost and efficient on-site 3D measurements of industrial structures.

Case report: Diagnosis and treatment of a chinchilla's old radius and ulna fracture.

The cortex of the limb bones of chinchillas is very thin and brittle, so it is prone to fractures of the limb bones, among which fractures of the tibia, radius and ulna are the most frequent types. When a chinchilla has a closed fracture, it can be immobilized with a splint, cast, or bandage. If the broken end of the fracture pierces the skin, it is best to choose internal fixation or external fixation brackets for treatment. In this report, a 0.661 kg, 2-year-old male uncastrated chinchilla was presented to the Veterinary Teaching Hospital of Huazhong Agricultural University due to an old fracture of the right forearm. With the consent of the owner, we decided to use a 25-gauge needle as an IM pin to fix the fracture. Ten days after surgery, the wound had healed well, and the limb could support body weight, but the palm did not show a grasping position. Twenty four days after the operation, the affected limb had not regained the ability to grasp. The X-ray showed a slight rotation of the IM pin and good callus growth in the ulna, but not in the radius. One month after the operation, it was found that the function of the affected limb of the chinchilla was normal and the grasping ability was restored through follow-up consultation and the return visit.

Variable Density Filling Algorithm Based on Delaunay Triangulation.

The quality of the filling algorithm in additive manufacturing directly affects the strength of the part. The commonly used 3D printing filling algorithm at this stage is the classic filling algorithm. The density of each part in the filling region is the same, and there is a cavity structure in the transverse direction, which makes the strength of the part in the transverse direction lower. Therefore, this paper proposed a new filling algorithm-variable density filling algorithm based on Delaunay triangulation. First, we performed concave-polygon-convex decomposition on the filling area to form printing sub-regions; then, the filling density value was set according to the required intensity of each region, and we used the Poisson disk sampling algorithm to generate the filling point set. Finally, Delaunay triangulation was performed on the generated point set to generate filled traces. The comparison with the two commonly used classical filling algorithms proves that the algorithm can improve the strength of the part to a certain extent, and the printing time and the consumption of consumables will not increase significantly.

Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error.

The characteristics of fused deposition 3D printing lead to the inevitable step effect of surface contour in the process of forming and manufacturing, which affects molding accuracy. Traditional layering algorithms cannot take into account both printing time and molding accuracy. In this paper, an adaptive layering algorithm based on the optimal volume error is proposed. The angle between the normal vector and the layering direction is used for data optimization. The layer thickness is determined by calculating the volume error, and based on the principle of the optimal volume error, the unequal thickness adaptive layering of each printing layer of the model is realized. The experimental results show that the self-adaptive layering algorithm based on the optimal volume error has a better layering effect, greatly improves the forming efficiency and surface forming accuracy, and has a good adaptability to models with complex surfaces.

Research on encoding multi-gray-scale phase hologram and wavefront reconstruction.

Application of computer-generated holography for wavefront generation is beneficial for optical interferometry and 3D image display. However, there is a noticeable encoding error in computer-generated holograms, which is encoded by using the object's wavefront function in a computer. The encoding error will be transmitted and amplified during fabrication of a hologram, which can cause a reconstructed error in the generated wavefront. A correction method of encoding errors based on the least-squares fitting is proposed. A validating experiment is completed by using a liquid crystal spatial light modulator to reconstruct a group of paraboloid wavefronts. The results show that encoding errors increase the reconstructed error of a wavefront less than optical system errors, and the root-mean-square value drops 0.022λ after the correction of the encoding error, but it falls 0.092λ after the correction of optical system errors. The total error has been reduced by 0.114λ. This research is helpful for prediction of encoding errors and improvement of wavefront reconstruction accuracy.