Abstract: Disclosed a method for predicting permeability of a multi-mineral phase digital core based on deep learning. In the present disclosure, a three-dimensional digital core is constructed and a pore structure is randomly generated; after a plurality of multi-mineral digital core images is acquired by performing image segmentation on the three-dimensional digital core, permeability corresponding to each of the multi-mineral digital core images is acquired by simulation using multi-physics field simulation software and a multi-mineral digital core data set is constructed based on the plurality of multi-mineral digital core images and the permeability corresponding to each of the multi-mineral digital core images; an SE-ResNet18 convolutional neural network is constructed and trained with the multi-mineral digital core data set; and an image of a multi-mineral core to be predicted is input into the trained SE-ResNet18 convolutional neural network to determine the permeability of the multi-mineral core.

Abstract: A 5A5B6C tricyclic spironolactone derivative is provided with a formula XI: The present invention also relates to its preparation method and its applications in the areas of insecticide, nematicide, fungicide and anti-viral agent. The 5A5B6C tricyclic spironolactone derivatives in the present invention are high-performance, broad-spectrum, low-toxicity and low-ecological risk compounds with a wide range of applications in the areas of agriculture, horticulture, forestry and health.

Abstract: A 5A5B6C tricyclic spironolactone derivative is provided with a formula XI: The present invention also relates to its preparation method and its applications in the areas of insecticide, nematicide, fungicide and anti-viral agent. The 5A5B6C tricyclic spironolactone derivatives in the present invention are high-performance, broad-spectrum, low-toxicity and low-ecological risk compounds with a wide range of applications in the areas of agriculture, horticulture, forestry and health.

Abstract: The invention provides an analytical method to reduce the quantitative analysis systematic error of real-time fluorescence thermal cycler for polymerase chain reaction (PCR) and the application thereof. In the method, tn, the amplifying time by which fluorescence intensity (Rn) gets to a certain threshold, is set as the measuring index and initial template copy number (X0) is calculated according to the linear quantitative relation between tn and X0, shown as the formula 1: lnX0=?ln(1+E)(tn/tc)+lnK. Particularly, the method firstly needs to measure the values of tn of the standard samples whose X0 are known and protract the standard curve about lnX0˜tn; then to measure the values of tn of samples and calculate the initial copy number of samples in terms of the standard curve. In the process of measuring tn, real-time fluorescence thermal cycler collects fluorescent signals in the pattern of continuous scanning and measures real-time fluorescence intensity.