Abstract: This application provides techniques of improving video recommendation. The techniques comprise temporarily pre-adding a first video to a recommendation video sequence; capturing a sub-sequence including the first video; modifying an initial recommendation score of the first video based on a position sequence number of the first video in the sub-sequence and a position sequence number of another video in the sub-sequence to obtain a modified recommendation score of the first video, the another video sharing a target attribute with the first video; and adding a video with a highest modified recommendation score to the recommendation video sequence.

Abstract: A microfluidic ion detection chip having a bubble brightening structure includes a substrate, an upper plate, two glass cover plates, and a foam board. The substrate is provided with a fluid mixing region, a lower optical detection through hole, and a lower gas flow channel. The upper plate is adhesively connected to the substrate and is provided with a sample outlet, an upper optical detection through hole, an upper gas flow channel, and two sample inlets, the upper gas flow channel and the lower gas flow channel are combined to form a gas flow channel. The two glass cover plates are respectively disposed at the lower optical detection through hole and the upper optical detection through hole. The foam board is provided with a foaming structure capable of generating bubbles and a surfactant coated on the foam board, the foam board is disposed at the gas flow channel.

Abstract: Techniques provided comprises obtaining a content set to be screened, wherein the content set comprises a plurality of to-be-screened contents, wherein each to-be-screened content is associated with identification information, at least one tag indicative of at least one category, and a score; computing a distribution quota value of each category indicated by a corresponding tag and associated with the plurality of to-be-screened contents based on the at least one category and a weight value corresponding to the at least one category; computing a target distribution quota value of the tag of each category based on the distribution quota value of each category and a preset tag distribution quota adjustment function; and sequentially selecting target contents from the content set based on the target distribution quota value of each category and the weight value corresponding to the at least one category associated with each to-be-screened content.

Abstract: m This application provides techniques of improving video recommendation. The techniques comprise temporarily pre-adding a first video to a recommendation video sequence; capturing a sub-sequence including the first video; modifying an initial recommendation score of the first video based on a position sequence number of the first video in the sub-sequence and a position sequence number of another video in the sub-sequence to obtain a modified recommendation score of the first video, the another video sharing a target attribute with the first video; and adding a video with a highest modified recommendation score to the recommendation video sequence.

Abstract: An retinal vessel image enhancement method comprises: constructing a blood vascular dictionary; applying Frangi-based filtering to retinal vessel images, deciding blood vessels in a second image sub-block belong to wide or thin vessels by directional filtering, and setting residual error weight and residual error threshold of a vascular region; calculating inner products between the second image sub-block and each first image sub-block, selecting a first image sub-block with maximum inner product, and calculating its corresponding sparse coefficient; calculating residual error image, and calculating the residual error of the vascular region according to the residual error weight of the vascular region, when the residual error is greater than the residual error threshold, the residual error image is set as a second image sub-block, repeating and calculating residual error; reconstructing the second image sub-block according to the sparse coefficient, then restructuring each reconstructed second image sub-block

Abstract: An retinal vessel image enhancement method comprises: constructing a blood vascular dictionary; applying Frangi-based filtering to retinal vessel images, deciding blood vessels in a second image sub-block belong to wide or thin vessels by directional filtering, and setting residual error weight and residual error threshold of a vascular region; calculating inner products between the second image sub-block and each first image sub-block, selecting a first image sub-block with maximum inner product, and calculating its corresponding sparse coefficient; calculating residual error image, and calculating the residual error of the vascular region according to the residual error weight of the vascular region, when the residual error is greater than the residual error threshold, the residual error image is set as a second image sub-block, repeating and calculating residual error; reconstructing the second image sub-block according to the sparse coefficient, then restructuring each reconstructed second image sub-block