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: Certain aspects of the present disclosure provide techniques for vectorization of transactions including: receiving electronic transaction information of one or more transactions of a user; for each transaction of the one or more transactions: segmenting the electronic transaction information of the transaction into one or more transaction words; generating a second transaction description related to the transaction; and identifying a category of the transaction; generating, based on the corresponding identified categories of the one or more transactions, a set of transaction history data of the user; providing the set of transaction history data of the user as an input to a machine learned model trained to output a set of word embedding vectors; determining, based on an output of the machine learned model comprising a set of word embedding vectors, a set of similar merchants; and providing the set of similar merchants for display to the user.

Abstract: An automatic classification method of whole slide images (WSIs) for cervical tissue pathology based on confidence coefficient selection. The automatic classification method includes steps: S1: dividing the WSIs for the cervical tissue pathology into small pieces having set size, gathering the small pieces of each WSI into a packet, and removing blank pieces in the packets; S2: building a deep CNN model; S3: training the deep CNN for designated rounds; S4: performing sequential arrangement and connection to obtain feature vectors of WSIs by using the trained deep CNN as the feature extractor; S5: training a support vector machine classifier; and S6: processing the WSIs for the cervical tissue pathology, to be classified, through step S1 and step S4 to obtain the feature vectors of the images, and inputting the feature vectors into the trained support vector machine classifier to realize classification.

Abstract: Predictive modeling within a special purpose hardware platform to determine scenarios that are most likely to increase conversion potential for each trial user and retention potential for each active subscriber of a service, collectively referred to as a propensity score. The predictive models are integrated with a contextual marketing system that uses a loss risk assessment to learn user behavior and optimize content messaging designed to improve actual conversion or retention behavior for the user.

Abstract: Dynamic state-space modeling within a special purpose hardware platform to determine non-conversion risks for each trial user and churn risks for each active subscriber having exhibited a sequence of behaviors. The state-space model may be operable to determine a loss risk for each of a provider's active trial users and/or subscribers.

Abstract: A chip structure includes a chip substrate and a plurality of bumps. The plurality of bumps are disposed on a surface of the chip substrate and function as an interface for electrical connection between the chip substrate and an external connecting portion. The plurality of bumps are spaced apart from each other, and each of the plurality of bumps includes a rhombic configuration.

Abstract: The present invention provides a tapered side-polished fiber-optic biosensor (FOBS) and a method for preparing a tapered side-polished fiber (SPF). The biosensor includes a broadband light source, a first single-mode fiber, a tapered SPF, a second single-mode fiber, and a spectrometer. The broadband light source is connected to the tapered SPF through the first single-mode fiber, and the tapered SPF is connected to the spectrometer through the second single-mode fiber. The broadband light source is configured to emit a light wave. The spectrometer is configured to display a spectrum corresponding to a light wave passing through the first single-mode fiber, the tapered SPF, and the second single-mode fiber successively. In the present invention, a fiber side-polishing technology is combined with a fiber tapering technology to construct a tapered SPF, and a spectrum changes by changing a refractive index around a side-polished tapered region, thereby measuring the refractive index.

Abstract: An automatic classification method of whole slide images (WSIs) for cervical tissue pathology based on confidence coefficient selection. The automatic classification method includes steps: S1: dividing the WSIs for the cervical tissue pathology into small pieces having set size, gathering the small pieces of each WSI into a packet, and removing blank pieces in the packets; S2: building a deep CNN model; S3: training the deep CNN for designated rounds; S4: performing sequential arrangement and connection to obtain feature vectors of WSIs by using the trained deep CNN as the feature extractor; S5: training a support vector machine classifier; and S6: processing the WSIs for the cervical tissue pathology, to be classified, through step S1 and step S4 to obtain the feature vectors of the images, and inputting the feature vectors into the trained support vector machine classifier to realize classification.

Abstract: A 3D information detection device includes a DLP projector (100), a camera (200), a controller (300) and an image processing module (400). The DLP projector (100) is configured for projecting encoded structured light to an object, the camera (200) is configured for acquiring an image of the object to which the structured light has been projected, the image processing module (400) is connected to the camera (200) and is configured for processing the image to obtain 3D information about the object, the controller (300) is connected to both the DLP projector (100) and the camera (200) and controls the operations thereof. The above device can solve the problem that 3D information about an object cannot be directly obtained at present.

Abstract: An optical network device with abnormal light emission detection includes an optical transceiver circuit and a control circuit. The optical transceiver circuit receives a transmission signal. The control circuit enables the optical transceiver circuit according to the transmission signal, so that the optical transceiver circuit outputs an optical signal. The optical transceiver circuit outputs a status signal according to whether or not the optical transceiver circuit outputs the optical signal. The status signal triggers an interrupt system of the control circuit. The interrupt system is provided with a counter to count a light emission duration of the optical transceiver circuit. When the light emission duration is greater than a preset value, the control circuit stops the optical transceiver circuit from outputting the optical signal.

Abstract: An optical network device with abnormal light emission detection includes an optical transceiver circuit and a control circuit. The optical transceiver circuit receives a transmission signal. The control circuit enables the optical transceiver circuit according to the transmission signal, so that the optical transceiver circuit outputs an optical signal. The optical transceiver circuit outputs a status signal according to whether or not the optical transceiver circuit outputs the optical signal. The status signal triggers an interrupt system of the control circuit. The interrupt system is provided with a counter to count a light emission duration of the optical transceiver circuit. When the light emission duration is greater than a preset value, the control circuit stops the optical transceiver circuit from outputting the optical signal.

Abstract: Provided is an information transmission processing method and device, a node, storage medium and processor. The information transmission processing method comprises: a first predefined pattern of a first network node is determined, where the first predefined pattern comprises a link direction of a system resource of the first network node and a priority of the link direction; and information transmission according to the first predefined pattern is processed.

Abstract: The present invention provides a tapered side-polished fiber-optic biosensor (FOBS) and a method for preparing a tapered side-polished fiber (SPF). The biosensor includes a broadband light source, a first single-mode fiber, a tapered SPF, a second single-mode fiber, and a spectrometer. The broadband light source is connected to the tapered SPF through the first single-mode fiber, and the tapered SPF is connected to the spectrometer through the second single-mode fiber. The broadband light source is configured to emit a light wave. The spectrometer is configured to display a spectrum corresponding to a light wave passing through the first single-mode fiber, the tapered SPF, and the second single-mode fiber successively. In the present invention, a fiber side-polishing technology is combined with a fiber tapering technology to construct a tapered SPF, and a spectrum changes by changing a refractive index around a side-polished tapered region, thereby measuring the refractive index.

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: An accompanying service method for a robot includes obtaining a map model of a set area; planning an accompanying user path from a current position of the robot to a destination position based on the map model of the set area; monitoring an accompanied user in real time in a process of accompanying the user to travel on the planned accompanying user path; and based on the accompanied user being lost, searching for the accompanied user using a search model.

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: The invention discloses a multi-human tracking system and method with single Kinect for supporting mobile virtual reality applications. The system can complete the real-time tracking of users occluded in different degrees with a single Kinect capture device to ensure smooth and immersive experience of players. The method utilizes the principle that the user's shadow is not occluded when the user is occluded under certain lighting conditions, and converts the calculation of the motion of the occluded user into a problem of solving the movement of the user's shadow, and can accurately detect the position of each user, rather than just predicting the user's position, thereby actually realizing tracking.

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: The present invention relates to the field of functional materials for medical use, and particularly to a biomimetic bone composite material, a preparation method and uses thereof. The biomimetic bone composite material provided by the invention is prepared from the raw material containing the following components: gelatin and/or collagen, hydroxyapatite and a silicon source. The present invention also provides a preparation method of the composite material and uses thereof in preparing bone repair materials. The highly biomimetic composite material with fibrous network structure prepared by the present invention can simulate the microenvironment similar to natural bone for cells, meet the biological requirements of bone tissue engineering, and is expected to become an ideal bioactive scaffold for bone repair.

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.