公开(公告)号：US20250125003A1

公开(公告)日：2025-04-17

申请号：US18608945

申请日：2024-03-19

Applicant: ZHEJIANG LAB

Inventor： Zenghui XU ,  Jin TANG ,  Yu ZHANG ,  Gaoxiang CHEN ,  Ting YU ,  Jin ZHAO ,  Ji ZHANG

IPC: G16B15/00

Abstract: A graph calculation method of RNA similarity analysis, an apparatus, a device, and a medium are provided. The method includes: converting sequence data of a looked-up RNA into a looked-up RNA structure graph; obtain a first similarity between the looked-up RNA structure graph and a target RNA structure graph; obtaining a second similarity based on the number of base constituent structures in the looked-up RNA structure graph and the number of base constituent structures in the target RNA structure graph; reconstructing the looked-up RNA structure graph based on the base constituent structures in the looked-up RNA structure graph to generate a looked-up RNA higher-order graph; and analyzing similarity between the looked-up RNA higher-order graph and a target RNA higher-order graph to obtain a third similarity; and obtaining a final similarity between the looked-up RNA and the target RNA based on the first similarity, the second similarity, and the third similarity.

公开(公告)号：US20250132057A1

公开(公告)日：2025-04-24

申请号：US18600800

申请日：2024-03-11

Applicant: ZHEJIANG LAB

Inventor： Zenghui XU ,  Ji ZHANG ,  Yu ZHANG ,  Ting YU ,  Jin ZHAO ,  Linlin HOU ,  Zhan ZHANG

IPC: G16H50/80

Abstract: An infectious disease infection prediction method, an apparatus, and a storage medium based on macro-micrograph fusion are provided. The method includes: acquiring macrographs of a plurality of first regions and micrographs of second regions within a set period; inputting the macroscopic graphs and the microscopic graphs into two graph convolutional neural networks to obtain two hidden layer vectors respectively, and fusing the two hidden layer vectors to obtain fusion hidden layer information of the first regions; performing a time sequence calculation of the fusion hidden layer information to obtain time sequence hidden layer information of the first regions; inputting the time series hidden layer information into two prediction networks to obtain two prediction results, respectively, and performing fusion calculation of the two prediction results to obtain a final prediction result of infectious diseases in the first regions.

公开(公告)号：US20250102792A1

公开(公告)日：2025-03-27

申请号：US18973068

申请日：2024-12-08

Applicant: ZHEJIANG LAB

Inventor： Yiming LIANG ,  Haoyuan DU ,  Keren XIE ,  Yanyan ZHANG ,  Chen QIAN ,  Yunhe BAI ,  Ji ZHANG ,  Jiakai ZHU

IPC: G02B27/00 ,  B08B1/16 ,  H04N23/50

Abstract: A thermally-driven full-ocean-depth lens wiping device and a method. The device includes a wiper hingedly mounted on a housing, a shape memory alloy wire mounted on the housing and configured to connect and drive the wiper to perform a wiping motion, and a fixing component configured to position and arrange the shape memory alloy wire, and further includes the housing mounted on a full-ocean-depth lens and a waterproof connector electrically connected to the shape memory alloy wire; in the method, the shape memory alloy wire is electrically heated to be extended and contracted, thereby pulling the wiper to rotate, and wiping of the lens is completed.

公开(公告)号：US20240273118A1

公开(公告)日：2024-08-15

申请号：US18472202

申请日：2023-09-21

Applicant: ZHEJIANG LAB

Inventor： Ting JIANG ,  Yu ZHANG ,  Ting YU ,  Ji ZHANG ,  Linlin HOU ,  Jin ZHAO

IPC: G06F16/28

CPC classification number: G06F16/285

Abstract: A data classification method and apparatus, a device and a storage medium. A structural feature of the respective node in graph data may be determined according to a neighbor node of the respective node in the graph data through a deviation between the decoded feature obtained by decoding the embedded coding feature of the respective node in the graph data and the initial feature of the respective node, and then the embedded coding feature corresponding to the respective node is adjusted according to the decoded feature of the respective node and the structural feature of the respective node in the graph data to obtain the adjusted feature corresponding to the respective node, so that accuracy of an obtained feature of the respective node is improved, and thus accuracy of data classification may be improved.