Abstract: An automatic abnormal cell recognition method, the method including: 1) scanning a slide using a digital pathological scanner and obtaining a cytological slide image; 2) obtaining a set of centroid coordinates of all nuclei that is denoted as CentroidOfNucleus by automatically localizing nuclei of all cells in the cytological slide image using a feature fusion based localizing method; 3) obtaining a set of cell square region of interest (ROI) images that are denoted as ROI_images; 4) grouping all cell images in the ROI_images into different groups based on sampling without replacement, where each group contains ROW×COLUMN cell images with preset ROW and COLUMN parameters; obtaining a set of splice images; and 5) classifying all cell images in the splice image simultaneously by using the splice image as an input of a trained deep neural network; and recognizing cells classified as abnormal categories.

Abstract: Disclosed is a power sharing method, including: determining a transmit power of a UE on a first carrier and a transmit power of the UE on a second carrier; and receiving first uplink traffic transmitted by the UE on the first carrier according to the transmit power on the first carrier, and receiving second uplink traffic transmitted by the UE on the second carrier according to the transmit power on the second carrier. Further disclosed are a power sharing apparatus, a storage medium, and a processor.

Abstract: Disclosed are a resource allocation method for demodulation reference signals and a base station. The resource allocation method for demodulation reference signals executed by the base station includes: determining an allocation method for a resource required for transmitting a plurality of demodulation reference signals and a parameter for generating the plurality of demodulation reference signals, the plurality of demodulation reference signals respectively corresponding to a plurality of user equipments, the allocation method being capable of supporting transmission of the plurality of demodulation reference signals on the same time domain resource, and the parameter being capable of making the demodulation reference signals sent with the same time frequency resource distinguished from each other; and transmitting information indicating the allocation method and information indicating the parameter to the plurality of user equipments.

Abstract: Edge device task management by receiving an indicator corresponding to a first container running a task on a first edge device of a cluster of edge devices, wherein the indicator indicates an error status of the first container, and wherein task data of the task is stored in a first local storage of the first edge device, selecting a second edge device from the cluster of edge devices, wherein a second container on the second edge device is to run the task, instructing the first and second edge devices to transfer the task data from the first local storage of the first edge device to a second local storage of the second edge device, and in response to receiving a notification that indicates the task data has been transferred from the first local storage to the second local storage, sending the task to the second container.

Abstract: A method and an electronic apparatus for acquiring a floor map of a room layout are provided.

Abstract: The present invention provides a method for controlling a connection between an ONU and an OLT, wherein the method includes the steps of: (a) downloading an OMCI message from the OLT; (b) enabling an OMCI management program to process the OMCI message to try to generate a plurality of models; (c) if the plurality of models are not successfully generated by using the OMCI management program to process the OMCI message, modifying the OMCI management program to generate a modified OMCI management program when the ONU is not connected with the OLT; and (d) using the modified OMCI management program to process the OMCI message to try to generate the plurality of models.

Abstract: An okra polygalacturonic acid having a uric acid-lowering effect, a method for preparing the same, and use of the same are disclosed. The method includes: smashing an okra, lixiviating the okra in ethanol, and filtering to obtain a filtrate and a residue; removing the filtrate, and lixiviating the residue in heated water to obtain an extraction solution; adding the ethanol into the extraction solution to precipitate okra crude polysaccharides; purifying the okra crude polysaccharides over an anion exchange column by eluting with water or a NaCl solution, a Tris-HCl solution or a NaCl-containing Tris-HCl solution, or a phosphate solution or a NaCl-containing phosphate solution, and collecting a fraction eluted by the NaCl solution, the NaCl-containing Tris-HCl solution, or the NaCl-containing phosphate solution; and concentrating, dialyzing and drying the fraction to obtain the okra polygalacturonic acid.

Abstract: A terminal is disclosed including a receiving unit that receives a signal that is encoded by using transform precoding; and a controlling unit that assumes that size of transform precoding is determined based on a bandwidth of a downlink.

Abstract: The present invention belongs to the technical field of hard disk device, and specifically relates to a Hard Disk Device Based on Blockchain. The hard disk device comprises a storage unit and a protection unit; wherein a hard disk body stores information in the blockchain; the protection unit comprises a protective case, an airbag and an interface extension board; the airbag is laid flat on the inner bottom of the protective case; the interface extension board passes through a side wall of the protective case and is bolted to the protective case; a dust board in a first through hole of the interface extension board is located at the port on the interface extension board close to the hard disk body when the hard disk body is not placed in the protective case; the dust board is connected to the inside of the first through hole by a first spring.

Abstract: A diffractive image combiner is provided, to increase an exit pupil dimension, thereby improving user experience. The diffractive image combiner includes a first diffractive optical element DOE and a second diffractive optical element DOE. The first diffractive optical element DOE is parallel to the second diffractive optical element DOE. A grating vector of a first incidence point in the first diffractive optical element DOE is the same as a grating vector of a second incidence point in the second diffractive optical element DOE. The first incidence point is used to convert an incident light ray that meets a Bragg condition into a first diffracted light ray and a first transmitted light ray. The first transmitted light ray is incident to the second incidence point. The second incidence point is used to convert the first transmitted light ray into a second diffracted light ray.

Abstract: A method utilizes a framework for transaction categorization personalization. A transaction record is received. a baseline model is selected from a plurality of machine learning models. An account identifier, corresponding to the transaction record using the baseline model, is selected. The account identifier for the transaction record is presented.

Abstract: A method categorizes transaction records. A transaction record is received by a server application. The transaction record is encoded with a first machine learning model to obtain a transaction vector, wherein the transaction vector is in a same vector space as multiple account vectors. A second machine learning model executing in the server application, selects an account vector, from the multiple account vectors, corresponding to the transaction vector. An account identifier, corresponding to the account vector, is presented for the transaction record.

Abstract: A sizing composition for glass fiber direct roving for producing multiaxial fabrics is provided. The sizing composition includes, based on the total solids mass of the composition, 0.1 to 5.0% by solid mass of a first silane coupling agent, 2.5 to 11.0% by solid mass of a second silane coupling agent, 3.0 to 20.0% by solid mass of a first film former, 45.0 to 75.0% by solid mass of a second film former, 0 to 5.0% by solid mass of a plasticizer, 0.2 to 4.0% by solid mass of a first lubricant, 5.0 to 20.0% by solid mass of a second lubricant, and 0.01 to 3.0% by solid mass of a pH regulator. The first film former is a multifunctional epoxy emulsion, and the second film former is a low-molecular-weight liquid epoxy emulsion.

Abstract: Provided are a method and apparatus for sending and receiving feedback information, and a storage medium. The method includes: receiving service data sent by a user equipment (UE); and sending downlink feedback indication (DFI) information corresponding to the service data to the UE. Where the DFI information includes a HARQ ACK/non-acknowledgement NACK indication, and the HARQ ACK/NACK indication is configured for indicating a decoding result of a transport block (TB) and/or a code block group (CBG) in the service data decoded by a base station.

Abstract: Provided is a novel PDGFR kinase inhibitor, comprising a compound of formula (I) or a pharmaceutically acceptable salt, solvate, ester, acid, metabolite or prodrug thereof. Further provided are use and a method of the compound of formula (I) for preventing or treating conditions associated with PDGFR kinase activity, particularly use and a method for preventing or treating conditions associated with PDGFR? and/or PDGFR? kinase activity.

Abstract: Provided are a signal transmission method and device, a communication node and a storage medium. The method includes steps described below, a configuration manner of sequences is determined, where the configuration manner includes at least one of the number of the sequences, a length of the sequences, or a phase rotation angle of an element in one of the sequences; the sequences are generated according to the configuration manner; and the sequences are mapped to channel resources and the mapped sequences are transmitted.

Abstract: A method performs personalized transaction categorization. A transaction record is received, by a server application. In a first stage, sparse raw features are extracted from a transaction record of a transaction and converted into a transaction vector including dense features. In a second stage, the transaction vector is classified into a customized chart of accounts using the dense features to generate adapter model output. The method further includes selecting, an account identifier, corresponding to the transaction record and to an account of the customized chart of accounts, using the adapter model output, and presenting the account identifier for the transaction record.

Abstract: A terminal determines a target code rate by using a reference code rate, which is based on a modulation scheme and a modulation order, and an adjustment coefficient a that lowers the reference code rate. The terminal transmits/receives a signal encoded based on the target code rate.

Abstract: A method may include executing a baseline classifier on unreviewed transaction features of an unreviewed transaction record to obtain a baseline account identifier, and executing a comparison model on (i) an unreviewed transaction vector of the unreviewed transaction record and (ii) reviewed transaction vectors to obtain comparison scores. The reviewed transaction vectors may correspond to reviewed transaction records each having a user-approved account identifier. The method may further include selecting, using the comparison scores, a reviewed transaction record. The reviewed transaction record may correspond to a comparison score. The comparison score may correspond to a user-approved account identifier of the reviewed transaction record.

Abstract: Systems and methods for quantitative susceptibility mapping (“QSM”) using magnetic resonance imaging (“MRI”) are described. Localized magnetic field information is used when performing the inversion to compute quantitative susceptibility maps. The localized magnetic field information can include multi-resolution subvolumes obtained by segmenting, or dividing, a field shift map. In some instances, a trained machine learning algorithm, such as a trained neural network, can be implemented to convert the localized magnetic field information into quantitative susceptibility data. These local susceptibility maps can be combined to form a composite quantitative susceptibility map of the imaging volume.