Abstract: This application discloses a method for automatically activating an NFC application and a terminal, and relates to the terminal field. When a terminal has a plurality of SEs, an NFC application accessed by a transaction instruction is automatically activated. The terminal may include an NFC controller and at least two SEs, and each of the at least two SEs carries at least one NFC application. A specific solution is as follows: The NFC controller receives a transaction instruction, determines a target SE from the at least two SEs according to the transaction instruction, and sends the transaction instruction to the target SE; the target SE receives the transaction instruction, and determines, according to the transaction instruction, a target NFC application from an NFC application carried in the target SE; and the target SE runs the target NFC application, and executes the transaction instruction.

Abstract: An image generation system implements a multi-branch GAN to generate images that each express visually similar content in a different modality. A generator portion of the multi-branch GAN includes multiple branches that are each tasked with generating one of the different modalities. A discriminator portion of the multi-branch GAN includes multiple fidelity discriminators, one for each of the generator branches, and a consistency discriminator, which constrains the outputs generated by the different generator branches to appear visually similar to one another. During training, outputs from each of the fidelity discriminators and the consistency discriminator are used to compute a non-saturating GAN loss. The non-saturating GAN loss is used to refine parameters of the multi-branch GAN during training until model convergence. The trained multi-branch GAN generates multiple images from a single input, where each of the multiple images depicts visually similar content expressed in a different modality.

Abstract: Synthetic ?v?6 integrin ligands of Formula I having serum stability and affinity for integrin ?v?6, which is a receptor expressed in a variety of cell types, are described. The described ligands are useful for delivering cargo molecules, such as RNAi agents or other oligonucleotide-based compounds, to cells that express integrin ?v?6, and thereby facilitating the uptake of the cargo molecules into these cells. Compositions that include ?v?6 integrin ligands and methods of use are also described.

Abstract: A memory device comprises a memory array and a memory controller operatively coupled to the memory array. The memory controller includes a processor configured to initiate read operations to the memory array; compare the number of rad operations to a predetermined threshold number of read operations; initiate scanning memory pages of a block of memory cells for errors in response to reaching the threshold number of read operations for the block; and iteratively change the threshold number to a new threshold number, perform the new threshold number of read operations on the block of memory cells, and error scan memory pages associated with the last read operation of the new threshold number of rad operations.

Abstract: Implementations include receiving a first intermediate document representation of a first document, the first intermediate document representation including OCR data of document text and positions of document text in the first document, receiving a set of intermediate template representations for a set of templates, the set of intermediate template representations including, for each template in the set of templates, OCR data representative of template text and positions of template text in a respective template, determining a first sub-set of templates using text-based detection based on the first intermediate document representation and the set of intermediate template representations, determining a second sub-set of templates using position-based detection based on the first intermediate document representations and intermediate template representations associated with one or more templates in the first sub-set of templates, and transmitting instructions to execute template-based data extraction for the fi

Abstract: A method, a device and electronic device for clarification question generation are provided in one or more embodiments of this disclosure. The method includes: extracting entity information from a fuzzy context input by a user; inputting the fuzzy context into a template generating module of a pre-built CQG neural network model so as to obtain a clarification question template; inputting the entity information into an entity rendering module of the CQG neural network model so as to obtain at least one entity phrase; and generating a clarification question for a fuzzy question based on the clarification question template and the at least one entity phrase for presenting to the user.

Abstract: Implementations include receiving a first intermediate document representation of a first document, the first intermediate document representation including OCR data of document text and positions of document text in the first document, receiving a set of intermediate template representations for a set of templates, the set of intermediate template representations including, for each template in the set of templates, OCR data representative of template text and positions of template text in a respective template, determining a first sub-set of templates using text-based detection based on the first intermediate document representation and the set of intermediate template representations, determining a second sub-set of templates using position-based detection based on the first intermediate document representations and intermediate template representations associated with one or more templates in the first sub-set of templates, and transmitting instructions to execute template-based data extraction for the fi

Abstract: A method, a device and electronic device for clarification question generation are provided in one or more embodiments of this disclosure. The method includes: extracting entity information from a fuzzy context input by a user; inputting the fuzzy context into a template generating module of a pre-built CQG neural network model so as to obtain a clarification question template; inputting the entity information into an entity rendering module of the CQG neural network model so as to obtain at least one entity phrase; and generating a clarification question for a fuzzy question based on the clarification question template and the at least one entity phrase for presenting to the user. The CQG neural network model is constructed by adding a layered Transformer mechanism and a pointer generator mechanism into a coarse-to-fine CTF neural network model, so as to solve problems of insufficient processing of Out-of-Vocabulary and lacking of fuzzy semantic representation.