Solid medium for
    1.
    发明授权

    公开(公告)号:US12043825B2

    公开(公告)日:2024-07-23

    申请号:US17813977

    申请日:2022-07-21

    CPC classification number: C12N1/14 C12N2500/10 C12N2500/76

    Abstract: The present disclosure relates to the technical field of culture materials for fungi and provides a solid medium for Coriolus versicolor, and a preparation method and use. Bran is used as a main component in the solid medium, and has advantages in economy and environmental protection, and provides high Coriolus versicolor growth rate and strong contamination resistance. The solid medium avoids the tendency to contamination of current media during an experimental process, and reduces culture cost. The solid medium provides higher biomass and stronger contamination resistance than a potato dextrose agar (PDA) medium.

    Cold-storage instantaneous heat pump water heater

    公开(公告)号:US11927366B2

    公开(公告)日:2024-03-12

    申请号:US16807718

    申请日:2020-03-03

    Inventor: Rongji Xu Yinshi Li

    CPC classification number: F24H4/04 E03B7/045 E03B7/07

    Abstract: The present invention provides a cold-storage instantaneous heat pump water heater (HPWH). The HPWH includes a cold-water tank, a main evaporator, a compressor, and a hot water heat exchanger. In the present invention, heat of a working medium in the cold-water tank is absorbed by the main evaporator, and bathing water is rapidly heated by the hot water heat exchanger (condenser of the heat pump), thereby realizing instant heating with small input electrical power. Cold-water tank replaces the hot water tank of conventional HPWH avoiding energy loss during hot water storage. The working medium in the cold-water tank absorbs heat from the environment, to further improve energy utilization. In addition, there are three energy recovery evaporators to recover the waste heat of bathing.

    THREE-DIMENSIONAL ROTATING INTELLIGENT STORAGE COMPARTMENT

    公开(公告)号:US20210032890A1

    公开(公告)日:2021-02-04

    申请号:US16493298

    申请日:2018-12-13

    Abstract: A three-dimensional rotating intelligent storage compartment is provided in the present invention, which includes a tower body, a center of the tower body being provided with a central garage for storing bicycles, the central garage including a central pillar. A plurality of layers of placement plates are arranged around the central pillar, and each layer of the placement plates is equally divided into a plurality of independent storage spaces by a longitudinal partitioning plate. A longitudinal edge on one side of the longitudinal partitioning plate is fixed to the central pillar; each storage space is provided with a clamping mechanism for clamping bicycle. An inner wall of the tower body is longitudinally provided with a plurality of loop tracks, each loop track is provided with a plurality of ferry parking spaces, which are movable within the loop track, is capable of clamping bicycle in a standing position and capable of pushing bicycle to the placement plate. The present invention can operate conveniently, and can save footprint area of bicycles.

    FULL-AUTOMATIC CLASSIFICATION METHOD FOR THREE-DIMENSIONAL POINT CLOUD AND DEEP NEURAL NETWORK MODEL

    公开(公告)号:US20230076092A1

    公开(公告)日:2023-03-09

    申请号:US17748185

    申请日:2022-05-19

    Abstract: A full-automatic classification method for a three-dimensional point cloud, including: acquiring a three-dimensional point cloud dataset; performing down-sampling on a three-dimensional point cloud represented by the three-dimensional point cloud dataset, selecting some points in the three-dimensional point cloud as sampling points, constructing a point cloud area group based on each sampling point, extracting a global feature of each point cloud area group, and replacing the point cloud area group where the sampling point is located with the sampling point; performing up-sampling on the three-dimensional point cloud, and performing splicing fusion on the global features of the point cloud area group where each point in the three-dimensional point cloud is located; performing category discrimination on each point in the three-dimensional point cloud; performing statistics on the number of points contained in each category, and selecting the category with the largest number of points as the category of the three-dimensional point cloud.

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