Artificial Calculus
    3.
    发明公开
    Artificial Calculus 审中-公开

    公开(公告)号:US20240355227A1

    公开(公告)日:2024-10-24

    申请号:US18643653

    申请日:2024-04-23

    IPC分类号: G09B23/28

    CPC分类号: G09B23/283

    摘要: Example artificial dental calculus models are described. In one example, an in vitro artificial dental calculus includes a dental substrate and a mineralized biofilm comprising an extracellular support material and at least one bacterial species. In one example, a method for creating an in vitro dental calculus model includes applying saliva to a dental substrate in a production environment, applying a mixture of an extracellular support material and at least one bacterial species to the dental substrate, applying a solution comprising calcium and phosphate to the mixture on the dental substrate, and removing the dental substrate from the production environment after a period of time during which a mineralized biofilm comprising the extracellular support material and the at least one bacterial species forms on the dental substrate.

    ADJUSTING MUSICAL COMPOSITION DATA USING A COMPUTATIONAL MODEL OF RUBATO

    公开(公告)号:US20240331666A1

    公开(公告)日:2024-10-03

    申请号:US18621628

    申请日:2024-03-29

    IPC分类号: G10H1/00

    摘要: A musical composition is varied using a computational model of rubato. Rubato is modeled by changes to the symbolic onset and/or symbolic offset of each note, which allows for a greater flexibility in timing modifications, such as asymptotic tempo and localized retrogrades. A user selects notes to be modified (e.g., by plotting points to modify notes over a selected interval), and a curve fitting (e.g., a cubic spline interpolation) is used to determine modifications for other notes in the composition. These symbolic onset/offset modifications may also be translated into tempo modifications. The symbolic onset and/or offset modifications are applied to the composition to produce an adjusted musical composition, to which rubato has been applied. Rubato profiles can similarly be extracted from existing musical recordings and used to characterize the recordings, such as for training machine learning models and recommender systems.