Abstract: The present disclosure provides a method for preparing a catalyst for pyrolysis of waste plastics to produce oil, comprising: washing and modifying coal gangue powder with acid, and then placing in an alkaline solution, etching under magnetic stirring for 20-30 minutes, and washing with water until neutral; placing the catalyst washed until neutral in a metal solution, loading the metal by impregnation, and then filtering and washing; then placing the catalyst in the molding machine and adding adhesive and water, to compress into a suitable shape, drying, and finally calcinating to activate to obtain a product. The present disclosure not only solves the problem of waste plastic pollution, but also obtains fuel oil with high valuable products while reducing the cost of waste plastic treatment, and also improves the yield of fuel oil.

Abstract: A display substrate, including: a base substrate; and a metal conductive layer, located at a side of the base substrate, and including a core conductive layer and a functional conductive layer laminated along a direction away from the base substrate; a material of the core conductive layer includes a conductive metal material; a material of the functional conductive layer includes a first diffusion barrier metal material and a first adhesion force enhancing metal material, wherein the first diffusion barrier metal material is configured to block diffusion of the conductive metal material, and the first adhesion force enhancing metal material is configured to enhance an adhesion force between the functional conductive layer and a photoresist used in a patterning process of the functional conductive layer; a surface energy of any of first adhesion force enhancing metal materials is less than or equal to 325 mJ/m2.

Abstract: Disclosed is a method for qualitative and quantitative determination of key substances in mixture based on terahertz spectrum. Terahertz spectrum of a reference mixture is trained through an SVR algorithm, and predicting parameters of key substances in the mixture to be determined after a model is generated. According to the method, an initial pure spectrum corresponding to each composition in the mixture does not need to be separately determined, no limitation on the number of samples contained in the mixture, and no limitation on frequency range to be determined, and the proportion requirement of the mixture in the early test stage is not limited, and the SVR model does not need to be re-trained after a database is formed in the later stage, and the result can be obtained immediately after the spectrum of item to be determined is introduced into the algorithm model.

Abstract: A method for quantitative detection of blood lipid in blood based on terahertz spectroscopy, including: matching the terahertz spectral absorption coefficient curves of blood samples obtained in step 3 with parameters of component concentration and component type of the blood lipid detected by hospital instruments, and establishing a terahertz blood lipid parameter database by combining the time-domain signal data of samples of the triglyceride and cholesterol; determining parameters of a support vector regression (SVR) model; performing a training with the training set as input to the SVR model to obtain a support vector and a corresponding weight; and testing the test set of an unknown blood sample using the trained support vector and the corresponding weight.

Abstract: A method for quantitative detection of blood lipid in blood based on terahertz spectroscopy, including: matching the terahertz spectral absorption coefficient curves of blood samples obtained in step 3 with parameters of component concentration and component type of the blood lipid detected by hospital instruments, and establishing a terahertz blood lipid parameter database by combining the time-domain signal data of samples of the triglyceride and cholesterol; determining parameters of a support vector regression (SVR) model; performing a training with the training set as input to the SVR model to obtain a support vector and a corresponding weight; and testing the test set of an unknown blood sample using the trained support vector and the corresponding weight.

Abstract: Disclosed is a method for qualitative and quantitative determination of key substances in mixture based on terahertz spectrum. Terahertz spectrum of a reference mixture is trained through an SVR algorithm, and predicting parameters of key substances in the mixture to be determined after a model is generated. According to the method, an initial pure spectrum corresponding to each composition in the mixture does not need to be separately determined, no limitation on the number of samples contained in the mixture, and no limitation on frequency range to be determined, and the proportion requirement of the mixture in the early test stage is not limited, and the SVR model does not need to be re-trained after a database is formed in the later stage, and the result can be obtained immediately after the spectrum of item to be determined is introduced into the algorithm model.