Abstract: Provided are an intelligent feeding method and system for fish in a recirculating aquaculture system based on repeated games. The method includes: constructing repeated games, determining Nash equilibrium strategies based on the repeated games, determining a payoff relationship between different strategies in a research phase, and quantifying a hunger level and determining a feeding amount based on the payoff relationship as well as an intrinsic connection between hunger levels and energy intake and expenditure in fish group feeding behavior. This application uses a simple and effective repeated game method to determine the feeding amount that promotes cooperative swimming feeding behavior in the fish group, effectively reducing feed waste caused by the existing method of determining the feeding amount based on total fish biomass and farming experience. This application ensures sufficient energy supply for fish growth while promoting cooperative swimming feeding behavior among individual fish in the group.

Abstract: Provided in the present disclosure is a compound of formula (I), or an N-oxide, solvate, pharmaceutically acceptable salt or stereoisomer thereof, which is an extrahepatic targeted cationic lipid compound with high efficiency and low toxicity. Further provided are a composition containing the aforementioned compound, and the use thereof in the delivery of a therapeutic or prophylactic agent.

Abstract: A compound of Formula (I) or an N-oxide, a solvate, a pharmaceutically acceptable salt or a stereoisomer thereof is an ionizable cationic lipid compound.

Abstract: Provided in the present disclosure is a compound of formula (I), or an N-oxide, solvate, pharmaceutically acceptable salt or stereoisomer thereof, which is an extrahepatic targeted cationic lipid compound with high efficiency and low toxicity. Further provided are a composition containing the aforementioned compound, and the use thereof in the delivery of a therapeutic or prophylactic agent.

Abstract: Embodiments of this application provide a method for making recommendations to a user and an apparatus, a computing device, and a storage medium. The method includes obtaining user attribute information, reading attribute information, reading history information, and candidate items; performing intra-group information fusion on the reading attribute information according to preset groupings to obtain reading feature information; obtaining a reading history weight according to the reading history information; obtaining history feature information according to the reading history weight and the reading history information; obtaining user feature information according to the user attribute information, the reading feature information, and the history feature information; and selecting a recommendation item from the candidate items according to the user feature information.

Abstract: This application provides an article recommendation method and apparatus, a computer device, and a storage medium.

Abstract: A video recommendation method is provided, including: inputting a video to a first feature extraction network, performing feature extraction on at least one consecutive video frame in the video, and outputting a video feature of the video; inputting user data of a user to a second feature extraction network, performing feature extraction on the discrete user data, and outputting a user feature of the user; performing feature fusion based on the video feature and the user feature, and obtaining a recommendation probability of recommending the video to the user; and determining, according to the recommendation probability, whether to recommend the video to the user.

Abstract: Embodiments of this application provide a method for making recommendations to a user and an apparatus, a computing device, and a storage medium. The method includes obtaining user attribute information, reading attribute information, reading history information, and candidate items; performing intra-group information fusion on the reading attribute information according to preset groupings to obtain reading feature information; obtaining a reading history weight according to the reading history information; obtaining history feature information according to the reading history weight and the reading history information; obtaining user feature information according to the user attribute information, the reading feature information, and the history feature information; and selecting a recommendation item from the candidate items according to the user feature information.

Abstract: A video recommendation method is provided, including: inputting a video to a first feature extraction network, performing feature extraction on at least one consecutive video frame in the video, and outputting a video feature of the video; inputting user data of a user to a second feature extraction network, performing feature extraction on the discrete user data, and outputting a user feature of the user; performing feature fusion based on the video feature and the user feature, and obtaining a recommendation probability of recommending the video to the user; and determining, according to the recommendation probability, whether to recommend the video to the user.

Abstract: This application provides an article recommendation method and apparatus, a computer device, and a storage medium.