Abstract: Disclosed are a decellularized matrix material, a preparation method therefor and use thereof. The preparation method includes: subjecting small intestinal submucosa to pre-treatment, and subjecting the small intestinal submucosa after the pre-treatment to swelling treatment, freeze-thaw treatment, oxidase immersion treatment, and surfactant treatment in sequence, so as to obtain the decellularized matrix material. In the present application, the combination of physical swelling, physical freezing and thawing, and chemical elution guarantees a high decellularization efficiency; moreover, by adding the oxidase at an appropriate time during the decellularization treatment process, the oxidase thoroughly permeates into the decellularized matrix, and thereby plays a buffering role in the tissue when the surfactant is applied, ensuring the intactness of the collagen structure in the extracellular matrix.

Abstract: A computer-based airplane flight path planning method based on the pigeon-inspired optimization (PIO) algorithm includes steps of establishing an uncertainty prediction model, determining the path to be optimized, and obtaining an optimal path using the PIO algorithm for a flight controller onboard to execute. The PIO algorithm treats a pigeon flock as a scale-free network, applies map and compass operators to the scale-free network, and performs landmark operations to obtain the optimal path. The device that performs the path planning includes an access module for obtaining the regional environment information and a flight controller onboard the airplane. The flight controller includes a building module for setting up the trajectory prediction model including uncertainties; a determining module to determine the trajectories which need optimization; an optimization module, which uses the PIO algorithm to optimize the flight path; and a computer memory module.

Abstract: A computer-based airplane flight path planning method based on the pigeon-inspired optimization (PIO) algorithm includes steps of establishing an uncertainty prediction model, determining the path to be optimized, and obtaining an optimal path using the PIO algorithm for a flight controller onboard to execute. The PIO algorithm treats a pigeon flock as a scale-free network, applies map and compass operators to the scale-free network, and performs landmark operations to obtain the optimal path. The device that performs the path planning includes an access module for obtaining the regional environment information and a flight controller onboard the airplane. The flight controller includes a building module for setting up the trajectory prediction model including uncertainties; a determining module to determine the trajectories which need optimization; an optimization module, which uses the PIO algorithm to optimize the flight path; and a computer memory module.