Abstract: There are provided systems and methods relating to checking and confirming merchandise purchased at shopping facilities. In one form, the system includes: a shopping cart containing merchandise items to be purchased; a sales transaction database; a point-of-sales system that creates transaction records identified by transaction identifiers; and a mobile device used by an employee that includes a sensor to scan a paper or digital receipt to obtain the transaction identifier and a camera to capture images of the items in the shopping cart. The system also includes a control circuit that receives the transaction identifier, accesses the database using the identifier to determine the purchased items; analyzes the images of the merchandise items in the shopping cart and creates a computer vision receipt listing detected items; compares the purchased items with the detected items; and takes an action if there is a discrepancy.

Abstract: The present invention relates to an amide derivative and use thereof in medicine, and specifically to an amide derivative shown as general formula (I) or a stereoisomer, solvate, metabolite, deuteride, prodrug, pharmaceutically acceptable salt or cocrystal thereof, a pharmaceutical composition containing the same, and use of the compound or the composition disclosed herein in preparing an NLRP3 inhibitor.

Abstract: The invention provides a bacterial cellulose-based biosensor, including bacterial cellulose (BC) and a cell presenting a cellulose-binding module CBM2a on the surface. The cell is attached to BC through CBM2a. The cell expresses CBM2a by using pETDuet-tac as a vector. The pETDuet-tac is obtained by replacing two T7 promoters on the vector pETDuet by tac promoters, that is, an upstream first tac promoter and a downstream second tac promoter. The pETDuet-tac includes a gene encoding a fluorescent protein downstream of the first tac promoter and a gene encoding CBM2a presented on the surface downstream of the second tac promoter. By the BC-based biosensor, efficient and specific immobilization of cells on the BC matrix is enabled, the biological activity of cells is maintained, the fluorescence signal output is enhanced, and sufficient pores are provided for the entry and exit of a detected substance, thereby significantly improving the detection sensitivity.

Abstract: Disclosed in the present disclosure are a method for training a multi-task model through multi-task reinforcement learning, an apparatus, an electronic device and a non-transitory computer readable storage medium. A method for training a multi-task model through multi-task reinforcement learning, including: acquiring observation signals observed for an environment by an agent; receiving T instructions each for instructing the agent to perform one of T tasks, T being a preset positive integer greater than 1; and generating K base policy models by performing training through multi-task reinforcement learning over a neural network based on the observation signals and the T instructions, wherein the K base policy models are combinable for generating respective task policy models for the T tasks to obtain the multi-task model for achieving the T tasks.