Abstract: The application discloses an animal nail polisher. The animal nail polisher includes a housing, a motor is mounted inside the housing, and a battery mounted inside the housing is arranged below the motor; an output end of the motor is connected with a rotating shaft, and an end portion of the rotating shaft is provided with a polishing head for nail polishing; a limiting sleeve is sheathed outside the polishing head, and the limiting sleeve is fixed to a top portion of the housing by a clamping mode; and a top portion of the limiting sleeve is provided with a first gap, and one side of the limiting sleeve is provided with a second gap. The nail polisher of the application is small in size, convenient to use, and may be used for different nails.

Abstract: A method for determining interaction information, a method for training interaction information prediction model, a device, and a medium are provided. The method includes obtaining basic information of a first target object, basic information of a second target object, and a target interaction information prediction model, the target interaction information prediction model being obtained through training by using a global-level loss function and a key local-level loss function, the key local-level loss function being determined based on attention information corresponding to one or more key sub-sample objects in one or more sample objects meeting a reference condition; and invoking the target interaction information prediction model to process the basic information of the first target object and the basic information of the second target object, and obtaining target interaction information between the first target object and the second target object.

Abstract: This disclosure provides a drug screening method and apparatus, an electronic device, and a computer-readable storage medium. The method includes: determining a structural feature of a protein molecule and a structural feature of a target molecule; obtaining a concatenated node feature corresponding to the protein molecule and the target molecule based on a node information passing sub-network in a drug screening model, the structural feature of the protein molecule, and the structural feature of the target molecule, the node information passing sub-network being a graph neural network; and predicting a first predicted activity value after the protein molecule and the target molecule are bound according to the concatenated node feature.