Abstract: The present disclosure belongs to the technical fields of nanoscience and fluorescence sensing, and specifically relates to a preparation method of a paper-based sensor for detecting an ammonia gas, and a use of the paper-based sensor. In the present disclosure, Zn(PA)(BPE) is first prepared, and a porous structure on a surface of the Zn(PA)(BPE) is used to adsorb an ammonia gas to improve a reaction sensitivity of the ammonia gas; then a Zn(PA)@CNQD ratiometric fluorescent substance is prepared from Zn(PA)(BPE) and CNQD through embedding, and finally dissolved in ultrapure water (UPW) to obtain a solution; and the solution is added dropwise on a filter paper, and the filter paper is purged with nitrogen, such that the solution is loaded on the filter paper to obtain a ratiometric fluorescent paper-based sensor.

Abstract: An inversion method of river course depth based on a mathematical model and remote sensing of water depth-water surface area includes the following steps: constructing the first mathematical model; calculating the relation function between the water flowing cross-section area, the triangle area at two sides and the water depth as well as the flow path, and substituting the relation functions into the first mathematical model to obtain the second mathematical model; transforming the second mathematical model into the mathematical model of water level-water surface area; solving the unknowns in the mathematical model, and substituting the unknowns into the second mathematical model to obtain the third mathematical model; and substituting the water surface area extracted by the remote sensing into the third mathematical model to obtain the water depth of the river course.

Abstract: Embodiments of the present application provide a prediction method, device and system for rock mass instability stages, and belong to the technical field of rock mass instability prediction. The method includes the steps: acquiring acoustic emission signals of rock mass; extracting feature parameters from the acquired acoustic emission signals; and predicting instability stages of the rock mass in accordance with the feature parameters and a preset back propagation (BP) neural network model, wherein the preset BP neural network model is obtained by training a BP neural network and a genetic algorithm by virtue of the feature parameters of the acoustic emission signals at different rock mass instability stages. According to the technical solution in the present application, the problem in the training process of the BP neural network model that model parameter optimization may be easily trapped in a locally optimal solution is effectively solved.

Abstract: Embodiments of the present application provide a prediction method, device and system for rock mass instability stages, and belong to the technical field of rock mass instability prediction. The method includes the steps: acquiring acoustic emission signals of rock mass; extracting feature parameters from the acquired acoustic emission signals; and predicting instability stages of the rock mass in accordance with the feature parameters and a preset back propagation (BP) neural network model, wherein the preset BP neural network model is obtained by training a BP neural network and a genetic algorithm by virtue of the feature parameters of the acoustic emission signals at different rock mass instability stages. According to the technical solution in the present application, the problem in the training process of the BP neural network model that model parameter optimization may be easily trapped in a locally optimal solution is effectively solved.

Abstract: This invention relates to a cream containing interferon encapsulated with liposome, which comprises IFN liposome and cream substrate. The advantage of the cream of the present invention is high efficiency of encapsulation, stable production technique, good homogeneity of products, stable efficacy and low rate of leakage. In order to improve the capability of encapsulation of liposome and the activity and efficacy of IFN, IFN liposome and substrate are utilized to prepare a form of cream which cures those skin disease infected by virus, such as herpes zoster, herpetic stomatitis, verruca, condyloma acuminata, mollusoum contagiosum, herpes genitalis, verrca planae, verruca vulgaris, genital ulcer, oral ulcer and pruritus.