Abstract: A composite for manufacturing a barrier layer, a barrier layer, a method for manufacturing the barrier layer, and a packaging material are provided. Based on the total mass of the composite as 100 parts by mass, the composite includes the following components by mass: Polyhydroxyalkanoate, 70 to 96 parts by mass; polylactic acid, 1 to 15 parts by mass; modified layered silicate, 1 to 5 parts by mass; polyalkylene carbonate, 1 to 20 parts by mass; and auxiliary agent, 1.3 to 12 parts by mass.

Abstract: A type of cat litter and its preparation method are provided. The content of this cat litter is calculated according to parts by mass and includes the following components: 100 parts of plant fiber waste, 1-7 parts of bacteriostat, 1-34 parts of deodorant, 1-27 parts of agent, 1-47 parts of binder, 1-94 parts of water-absorbing agent and 20-80 parts of water, wherein the bacteriostatic agent includes a mesoporous solid base.

Abstract: This application provides a paper pulp, a method for producing paper pulp, and a paper pulp product. The method for producing paper pulp includes: crushing bamboo shoot shells to obtain crushed materials; mixing the crushed materials with cooking, cooking the mixture to obtain slurry; washing the slurry to obtain waste liquid and washed slurry; purifying the washed slurry to obtain the paper pulp.

Abstract: The present invention discloses a non-invasive blood glucose measurement method, applied to noninvasive blood glucose measuring instruments including measuring hosts and fingertip measuring probes, comprising pre-storing a random forest algorithm and a neural network prediction algorithm in the measuring host; measuring energy metabolism parameters of a fingertip of an individual to be measured and transmitting the parameters to the measuring host by the fingertip measuring probe; calling the random forest algorithm to predict the blood glucose type of the energy metabolism parameters of the fingertip of the individual to be measured and calling the corresponding neural network prediction algorithm to calculate the blood glucose value of the fingertip of the individual to be measured by the measuring host. The present invention also provides a fingertip-measuring probe.

Abstract: The present invention discloses a non-invasive blood glucose measurement method, applied to noninvasive blood glucose measuring instruments including measuring hosts and fingertip measuring probes, comprising pre-storing a random forest algorithm and a neural network prediction algorithm in the measuring host; measuring energy metabolism parameters of a fingertip of an individual to be measured and transmitting the parameters to the measuring host by the fingertip measuring probe; calling the random forest algorithm to predict the blood glucose type of the energy metabolism parameters of the fingertip of the individual to be measured and calling the corresponding neural network prediction algorithm to calculate the blood glucose value of the fingertip of the individual to be measured by the measuring host. The present invention also provides a fingertip-measuring probe.