Abstract: Provided is a transcranial magnetic stimulation coil. The transcranial magnetic stimulation coil includes n stereoscopic units. A plane where each of the n stereoscopic units is located intersects a plane where a to-be-stimulated target region is located. Each of the n stereoscopic units includes a start point and an end point, and an end point of an ith stereoscopic unit among the n stereoscopic units is connected to a start point of an (i+1)th stereoscopic unit among the n stereoscopic units. The transcranial magnetic stimulation coil is arranged in a spiral shape, and for any one of the n stereoscopic units on a side of the transcranial magnetic stimulation coil facing an edge of the to-be-stimulated target region, a minimum distance between a projection shape within the to-be-stimulated target region and the edge of the to-be-stimulated target region is less than a first preset distance.

Abstract: A method for constructing a sentiment classification model based on metaphor identification is disclosed, including: constructing a metaphor training corpus, and training a first pre-trained language model using the metaphor training corpus to obtain a metaphor recognition model; constructing and inputting a sentiment classification corpus into a second pre-trained language model and the metaphor recognition model to extract an explicit characteristic value and a metaphor information characteristic value of a text in the sentiment classification corpus; combining the explicit characteristic value and the metaphor information characteristic value to obtain a comprehensive characteristic value which is input to a feedforward neural network and a binary classification softmax layer to obtain a sentiment classification result; and performing optimization training based on the sentiment classification result using BP algorithm to obtain an optimal sentiment classification model.

Abstract: A method for constructing a sentiment classification model based on metaphor identification is disclosed, including: constructing a metaphor training corpus, and training a first pre-trained language model using the metaphor training corpus to obtain a metaphor recognition model; constructing and inputting a sentiment classification corpus into a second pre-trained language model and the metaphor recognition model to extract an explicit characteristic value and a metaphor information characteristic value of a text in the sentiment classification corpus; combining the explicit characteristic value and the metaphor information characteristic value to obtain a comprehensive characteristic value which is input to a feedforward neural network and a binary classification softmax layer to obtain a sentiment classification result; and performing optimization training based on the sentiment classification result using BP algorithm to obtain an optimal sentiment classification model.

Abstract: Disclosed herein are a cannabidiol (CBD)-containing bio-based polyurethane composite material and a preparation thereof. The composite material is prepared from a component A and a component B in a weight ratio of 100:(20-50), where the component A includes 40-60 parts by weight of a vegetable oil-based polyol, 35-50 parts by weight of polyether polyol I, 0-10 parts by weight of polyether polyol II, 0.5-5 parts by weight of CBD, 0-5 parts by weight of a natural pigment, 0.5-3 parts by weight of silicon oil, 0-5 parts by weight of a cross-linking agent, 0.2-1 part by weight of a catalyst and 0.8-4 parts by weight of water, and the component B includes 20-50 parts by weight of modified methylene diphenyl diisocyanate (MDI).

Abstract: Disclosed herein are a cannabidiol (CBD)-containing bio-based polyurethane composite material and a preparation thereof. The composite material is prepared from a component A and a component B in a weight ratio of 100:(20-50), where the component A includes 40-60 parts by weight of a vegetable oil-based polyol, 35-50 parts by weight of polyether polyol I, 0-10 parts by weight of polyether polyol II, 0.5-5 parts by weight of CBD, 0-5 parts by weight of a natural pigment, 0.5-3 parts by weight of silicon oil, 0-5 parts by weight of a cross-linking agent, 0.2-1 part by weight of a catalyst and 0.8-4 parts by weight of water, and the component B includes 20-50 parts by weight of modified methylene diphenyl diisocyanate (MDI).

Abstract: The invention discloses an antibacterial mildewproof polyurethane composite material containing natural plant and a preparing method thereof. The composite material comprises component A and component B with a ratio of component A and component B being 100:(20-50) by weight. The component A by weight comprises: 30-60 parts plant oil polyether polyols; 20-50 parts polyether polyols I; 5-20 parts polyether polyols II; 5-20 parts composite plant extract; 0-0.5 parts catalyst; 0.5-2 parts surfactant; 0-2 parts cross-linking agent; 1.5-3 parts foaming agents. The component B by weight comprising 20-50 parts modified MDI. The composite material made according to the preparation method of the invention shows a good stability and the polyurethane products made according to the preparation method is degradable. The antibacterial mildewproof natural plant adopted by the composite material in the invention enables the composite material to prevent the bacteria breeding effectively and provides environmental protection.

Abstract: The invention discloses an antibacterial mildewproof polyurethane composite material containing natural plant and a preparing method thereof. The composite material comprises component A and component B with a ratio of component A and component B being 100:(20-50) by weight. The component A by weight comprises: 30-60 parts plant oil polyether polyols; 20-50 parts polyether polyols I; 5-20 parts polyether polyols II; 5-20 parts composite plant extract; 0-0.5 parts catalyst; 0.5-2 parts surfactant; 0-2 parts cross-linking agent; 1.5-3 parts foaming agents. The component B by weight comprising 20-50 parts modified MDI. The composite material made according to the preparation method of the invention shows a good stability and the polyurethane products made according to the preparation method is degradable. The antibacterial mildewproof natural plant adopted by the composite material in the invention enables the composite material to prevent the bacteria breeding effectively and provides environmental protection.