4results about How to "Reduce screening" patented technology

The invention belongs to the technical field of experimental animal models, biomedical research and immunology, and discloses a photocoagulation thymus ischemia animal model, a method and application of the photocoagulation thymus ischemia animal model in rapid simulation of thymus degeneration and immune senescence, and the model shows at least one or more characteristics 1-7 days after induction: thymus atrophy, thymus weight or thymus index is significantly reduced; the cortical-medullary structure of thymus is disordered or disappears; the expression distribution of the Keratin 5 / Keratin 8 is abnormal; thymic cell apoptosis is increased, and lipid deposition is enhanced; the proportion of CD4 + CD8 + double positive T cells is reduced, and the proportion of DN2 / DN3 stage T cells is increased; the initial T cell output is reduced; and the immune function is reduced. The pathological mechanism is clear; the modeling period is short, and the immune senescence phenotype can be stably obtained within several days; the injury focus is controllable, and systemic stress or hormone interference is avoided; the model has high repeatability and is suitable for mechanism research and drug screening.

The present application relates to a kind of boron stainless steel sheet for thermal neutron absorption preparation method, comprising the following process steps: (1) induction melting; (2) atomization and deposition; (3) forging; (4) hot rolling; (5) profile processing.The present application is through innovative process route, reasonable melting, plate processing deformation and heat treatment process, significantly improve the microstructure of material, refine hard and brittle boride particles, and then improve the hot workability of material and the mechanical properties of finished plate, meet the higher requirements of boron stainless steel sheet for thermal neutron absorption.According to the process manufactured by the present application, the performance of the plate is similar to powder metallurgy boron stainless steel, also has excellent comprehensive performance, and the process flow is shorter, and the manufacturing cost is also lower.

The present application relates to the field of artificial intelligence and finance, and provides a user behavior prediction method, device, equipment and storage medium. The method screens a target label from a plurality of feature labels obtained, obtains training information and user behavior results of a plurality of training users on the target label, inputs the training information and training text into a plurality of behavior prediction models, obtains the prediction behavior results of the plurality of training users by each behavior prediction model, generates model indicators according to the user behavior results and the prediction behavior results, and screens a target model. In response to a user behavior prediction request, the target model is used to predict and process user information and test text of a test user, and the target behavior result can be accurately obtained. In addition, the present application also relates to blockchain technology, and the target behavior result can be stored in the blockchain.

The application discloses a kind of high-precision prediction method of friction coefficient based on ceramic coating, it is related to ceramic coating friction coefficient prediction technical field, comprising the following steps: step one: obtaining the experimental data and literature auxiliary data of APS spraying ceramic coating;Step two: complete field alignment, training / test set division, missing value processing and training set enhancement;Step three: construct five-level physical feature chain, convert original variable into descriptor with tribological physical meaning;Step four: descriptor input machine learning model for training and prediction;Step five: robustness verification and explainability analysis are carried out, the method constructs five-level physical feature chain, and further maps original material parameter and working condition parameter into physical descriptor related to contact stiffness, pore weakening, bearing capacity and lubrication response, so that model input no longer stays in surface experimental variable, but can more fully characterize tribological mechanism.