Abstract: The present invention relates to the field of data identification, and in particular to two-dimensional code technology. Provided in the present invention is a two-dimensional code-based file acquisition method, comprising: step 1, parsing a two-dimensional code to acquire two-dimensional code encoded data, wherein the encoded data comprises a first unique value, encrypted data, and signature data; step 2, verifying the signature data; step 3, decrypting the encrypted data to acquire a file address and an. nth data segment In; step 4, acquiring an. encrypted file according to the nth data segment In and the file address; step 5, verifying the encrypted file according to the first unique value to acquire a decrypted file. The present invention solves the technical problems of easy tampering and poor security when data is stored and acquired on the basis of a two-dimensional code, and implements secure and reliable information protection.

Abstract: The present disclosure provides a method for separating a neural crest derived cell from peripheral blood. In the present disclosure, a mononuclear cell is separated from the peripheral blood and then directly cultured, thereby maximizing use of a neural crest stem cell with a differentiation potential to avoid loss of the neural crest stem cell. In the method of the present disclosure, a sample to be separated is derived from the peripheral blood. The method shows less trauma and low cost. Most importantly, compared to extracting the neural crest derived cell from tissues, the neural crest derived cell extracted from the peripheral blood can be used clinically as a type of biomarker.

Abstract: An intelligent question answering method includes: determining, based on received question information, a target object and a target attribute corresponding to the question information; obtaining an answer knowledge path and an external knowledge path of the target object other than the answer knowledge path from a pre-established knowledge graph based on the target object and the target attribute, the answer knowledge path including target context information for describing the target attribute, and the external knowledge path including external context information for describing another attribute; inputting the answer knowledge path and the external knowledge path into a trained neural network model to obtain a reply text, a training corpus of the neural network model during training including at least comment information of the target object; and outputting the reply text.