Abstract: An information management method, a device, a system and a medium. The information management method applied to a first terminal, including: sending an information acquisition request to a server, so that the server responds to the information acquisition request and sends visitor information to the first terminal; receiving the visitor information sent by the server; generating card information according to the visitor information; and sending the card information to an electronic card, so that the electronic card displays the card information.

Abstract: The present invention belongs to the technical field of mechanical fault data recognition, and discloses a cross-domain mechanical fault diagnosis method based on multi-channel feature fusion of an improved CBAM and use thereof, wherein the method comprises: conducting preliminary feature extraction in a grey-scale graph formed by original signals with convolutional neural network, obtaining high-level features, and compressing the high-level features with a full-connection layer module; conducting deep-level multi-sensor feature extraction with an improved convolutional block attention module (CBAM); conducting fusion for multi-sensor features extracted with an improved convolutional block attention module and obtaining multi-sensor fusion features; and inputting the multi-sensor fusion features into a tag assignor for fault diagnosis results.

Abstract: A display may have a pixel array such as a liquid crystal pixel array. The pixel array may be illuminated by a backlight unit that includes an array of light-emitting diodes (LEDs). The backlight unit may determine the type of content in the image data. The backlight unit may decide to prioritize either mitigating halo or mitigating clipping based on the type of content. The determination of the type of content in the image data may be used to determine the brightness values for the LEDs in the LED array. If the content is determined to be a first type of content, at least one given LED in the LED array may have a different brightness value than if the content is determined to be a second, different type of content. Classifying content in the image data may be useful in optimizing visible artifacts such as visible halo and clipping.

Abstract: Motion contaminated magnetic resonance (MR) images for training an artificial neural network to remove motion artifacts from the MR images are difficult to obtain. Described herein are systems, methods, and instrumentalities for injecting motion artifacts into clean MR images and using the artificially contaminated images for machine learning and neural network training. The motion contaminated MR images may be created based on clean source MR images that are associated with multiple physiological cycles of a scanned object, and by deriving MR data segments for the multiple physiological cycles based on the source MR images. The MR data segments thus derived may be combined to obtain a simulated MR data set, from which one or more target MR images may be generated to exhibit a motion artifact. The motion artifact may be created by manipulating the source MR images and/or controlling the manner in which the MR data set or the target MR images are generated.

Abstract: A transaction processing method includes: determining a first moment from a query time period of a target transaction, the first moment being a moment at which a most recent dumping of historical-state data is completed, and the historical-state data meeting a data query condition of the target transaction; obtaining a full analysis result of the historical-state data by processing the historical-state data based on analysis semantic of the target transaction; obtaining an incremental analysis result based on a specific change that occurs on current-state data corresponding to the historical-state data, the specific change occurring between the first moment and an end moment of the query time period, and the incremental analysis result being obtained by processing, based on the analysis semantic, data obtained by the specific change; and obtaining a final analysis result of the target transaction based on the full analysis result and the incremental analysis result.

Abstract: Provided is a conformation-specific antigen binding domain (ABD) specific for the Hedgehog receptor Patched1, which may be provided in the form of a nanobody. This nanobody potently activates the Hedgehog pathway in vitro and in vivo by stabilizing an alternative conformation of a Patched1 “switch helix”. This ABD or nanobody is water soluble, i.e. does not require lipid modifications for its activity, facilitating mechanistic studies of Hedgehog pathway activation and therapeutic use.

Abstract: Neural network based systems, methods, and instrumentalities may be used to remove motion artifacts from magnetic resonance (MR) images. Such a neural network based system may be trained to perform the motion artifact removal tasks without reference (e.g., without using paired motion-contaminated and motion-free MR images). Various training techniques are described herein including one that feeds the neural network with pairs of MR images with different levels of motion contamination and forces the neural network learn to correct the motion contamination by transforming a first image of a contaminated pair into a second image of the contaminated pair. Other neural network training techniques are also described with an aim to reduce the reliance on training data that is difficult to obtain.

Abstract: Motion contaminated magnetic resonance (MR) images for training an artificial neural network to remove motion artifacts from the MR images are difficult to obtain. Described herein are systems, methods, and instrumentalities for injecting motion artifacts into clean MR images and using the artificially contaminated images for machine learning and neural network training. The motion contaminated MR images may be created based on clean source MR images that are associated with multiple physiological cycles of a scanned object, and by deriving MR data segments for the multiple physiological cycles based on the source MR images. The MR data segments thus derived may be combined to obtain a simulated MR data set, from which one or more target MR images may be generated to exhibit a motion artifact. The motion artifact may be created by manipulating the source MR images and/or controlling the manner in which the MR data set or the target MR images are generated.

Abstract: The present invention discloses a wearable waste removal and cleansing apparatus, comprising a wearable part, a receptacle part detachably connected to the wearable part, and a control assembly connected to the receptacle part for automatic flushing. The wearable part includes a sliding sleeve and wearable pants connected to the sliding sleeve. An engaging mechanism is disposed between the sliding sleeve and the receptacle part. The wearable waste removal and cleansing apparatus of the present invention is simple in structure, convenient to operate, and sanitary and intelligent, and therefore is suitable for popularization and application.

Abstract: The present invention provides a novel groove cutter with chip breaker, comprising: a cutter body; a cutter head arranged at the end part of the cutter body, a cutting edge being arranged at a bordering position of the cutter head; and a chip breaker arranged on the cutter head, wherein the chip breaker comprises a breaker bottom and a breaker wall, the breaker bottom being connected to the cutting edge, the breaker wall being arranged on one side of the breaker bottom away from the cutting edge, the breaker bottom being non-coplanar with the breaker wall, an intersecting line of the breaker bottom and the breaker wall comprising multiple connecting sections, and one curved transition section being arranged between two adjacent connecting sections. By means of the technical solutions provided in the present application, the problem that breaking chips in a groove machining process is difficult in the prior art can be solved.

Abstract: A system for pumping lubricant in a gas transportation pipeline includes a pipeline robot and a control terminal system. The pipeline robot includes a lubricant position detection, module, a lubricant pumping module, an electro-hydraulic control system, a data acquisition and processing system, and a lubricant sucking port. The location at which the lubricant deposits can be detected online, and the lubricant staving in the gas transportation pipeline can be removed in real time. The system is highly automatic and efficient. Resistance against the natural as transportation is reduced effectively, the efficiency of transporting the natural gas is improved, and safety of transporting the natural gas is ensured.