Abstract: A Lyophyllum decastes polysaccharide, a preparation method and an application thereof are provided in the present disclosure, relating to the technical field of biomedicine. The preparation method includes the following steps: (1) adding an aqueous solution containing EDTA-2Na into a fruiting body of Lyophyllum decastes, performing ultrasonic treatment, and then performing water extraction treatment to obtain an extractive solution; (2) concentrating the extractive solution, adding anhydrous ethanol for precipitation, followed by centrifuging to obtain precipitates, then obtaining a crude Lyophyllum decastes polysaccharide; and (3) conducting removal of proteins and dialysis of the crude Lyophyllum decastes polysaccharide to obtain the Lyophyllum decastes polysaccharide.

Abstract: A Lyophyllum decastes polysaccharide, a preparation method and an application thereof are provided in the present disclosure, relating to the technical field of biomedicine. The preparation method includes the following steps: (1) adding an aqueous solution containing EDTA-2Na into a fruiting body of Lyophyllum decastes, performing ultrasonic treatment, and then performing water extraction treatment to obtain an extractive solution; (2) concentrating the extractive solution, adding anhydrous ethanol for precipitation, followed by centrifuging to obtain precipitates, then obtaining a crude Lyophyllum decastes polysaccharide; and (3) conducting removal of proteins and dialysis of the crude Lyophyllum decastes polysaccharide to obtain the Lyophyllum decastes polysaccharide.

Abstract: A method for parallel processing of retinal images includes: optimizing an objective function with a chaotic supply-demand algorithm to enhance a real retinal image; synthesizing a virtual retinal image by a hybrid image generation method; establishing a parallel multi-layer decomposed interval type-2 intuitionistic fuzzy convolutional neural network model based on the virtual retinal image and the enhanced real retinal image; and integrating outputs from a plurality of parallel multi-layer decomposed interval type-2 intuitionistic fuzzy convolutional neural network models as a final classification result.

Abstract: A method for parallel processing of retinal images includes: optimizing an objective function with a chaotic supply-demand algorithm to enhance a real retinal image; synthesizing a virtual retinal image by a hybrid image generation method; establishing a parallel multi-layer decomposed interval type-2 intuitionistic fuzzy convolutional neural network model based on the virtual retinal image and the enhanced real retinal image; and integrating outputs from a plurality of parallel multi-layer decomposed interval type-2 intuitionistic fuzzy convolutional neural network models as a final classification result.