Abstract: A method for preparing plant-based amyloid fibrils includes mixing a plant protein isolate with water, adjusting the pH to 1.5-2.5, and then performing solid-liquid separation. The resulting liquid material containing the plant protein isolate is subjected to a fibrillization treatment to obtain the plant-based amyloid fibrils. According to the growth kinetics curve, the fibrillization treatment sequentially includes a first incubation treatment, an ultrasonic treatment, and a second incubation treatment. The duration of the first incubation ranges from 0 h to the end of the exponential phase, and both the first and second incubation treatments are carried out under non-ultrasonic conditions. When the duration of the first incubation treatment is 0 h, the power density of the ultrasonic treatment is ?2.5 W/mL. The method enables simultaneous regulation of the fibril growth process and morphology, and reduces the proportion of rigid fibrils.

Abstract: Provided is an anisotropic hydrogel and its preparation method and use. In the preparation method of the anisotropic hydrogel, transglutaminase is added to introduce enzymatic chemical crosslinking, which, in combination with physical crosslinking, enables the hydrogel to be stretched to form anisotropy and stabilizes the resulting anisotropy. The surface of the anisotropic hydrogel exhibits an ordered and oriented structure. When applied to in vitro cell culture, it enables the cells to grow in a uniform direction. When the anisotropic hydrogel is used for preparing cultured meat, the resulting cultured meat presents a fibrous texture close to that of real meat. The preparation method of the anisotropic hydrogel is simple to operate. In the fibrous material dispersion, the fibrous material includes cellulose or protein isolate amyloid fibrils, and these raw materials are non-toxic and harmless, making them suitable for use in the food field.

Abstract: In one embodiment, when executing data compression or decompression for a data set, a particular compression category of the data set is determined, and a corresponding probability table specific to the particular compression category of the data set is accessed. Then, one of either arithmetic coding (e.g., an encoder device) or decoding (e.g., a decoder device) may be performed on the data set based on the specific probability table. Specifically, in one or more other embodiments, techniques may statistically generate probability tables specific to particular compression categories.

Abstract: In one embodiment, when executing data compression or decompression for a data set, a particular compression category of the data set is determined, and a corresponding probability table specific to the particular compression category of the data set is accessed. Then, one of either arithmetic coding (e.g., an encoder device) or decoding (e.g., a decoder device) may be performed on the data set based on the specific probability table. Specifically, in one or more other embodiments, techniques may statistically generate probability tables specific to particular compression categories.