Abstract: Examples of video encoding methods and apparatus and video decoding methods and apparatus are described. An example method of processing video data includes determining, for a conversion between a video block of a video and a bitstream of the video, a gradient of a prediction vector at a sub-block level for the video block according to a rule, wherein the rule specifies to use a same gradient value is assigned for all samples within a sub-block of the video block; and performing the conversion based on the determining.

Abstract: The disclosure relates to nanoparticle drug conjugates (NDC) that comprise ultrasmall nanoparticles, folate receptor (FR) targeting ligands, and linker-drug conjugates, and methods of making and using them to treat cancer.

Abstract: A three-dimensional scene constructing method, apparatus and system, and a storage medium. The three-dimensional scene constructing method includes: acquiring point cloud data of a key object and a background object in a target scene, wherein the point cloud data of the key object comprises three-dimensional information and corresponding feature information, and the point cloud data of the background object at least comprises three-dimensional information; establishing a feature database of the target scene, wherein the feature database at least comprises a key object feature library for recording three-dimensional information and feature information of the key object; performing registration and fusion on the point cloud data of the key object and the point cloud data of the background object, so as to obtain a three-dimensional model of the target scene; and when updating the three-dimensional model, reconstructing the three-dimensional model in a regional manner according to the feature database.

Abstract: Examples of video encoding methods and apparatus and video decoding methods and apparatus are described. An example method of processing video data includes determining, for a conversion between a video block of a video and a bitstream of the video, a gradient of a prediction vector at a sub-block level for the video block according to a rule, wherein the rule specifies to use a same gradient value is assigned for all samples within a sub-block of the video block; and performing the conversion based on the determining.

Abstract: A method implemented by a video coding apparatus includes applying a neural network (NN) filter to an unfiltered sample of a video unit to generate a filtered sample. The NN filter is applied based on a syntax element of the video unit. The method also includes converting between a video media file and a bitstream based on the filtered sample that was generated.

Abstract: A method includes running, in an always-on display state of the mobile device, a first algorithm program to display a first clock interface in a first display area of a display of the mobile device, receiving a switching instruction when the mobile device is switched from a first clock style to a second clock style, wherein the second clock interface is different from the first clock interface, performing switching from the first algorithm program to a second algorithm program in response to the switching instruction, and running, in the always-on display state, the second algorithm program to display the second clock interface in a second display area of the display, wherein a size of the second display area is different from a size of the first display area, and wherein the second algorithm program is different from the first algorithm program.

Abstract: Provided are a wireless signal apparatus and an elevator service request system and method, which belong to the field of intelligent elevator control technologies. In the elevator service request system of the present invention, a corresponding wireless signal is broadcast by a wireless signal apparatus of an elevator system and the wireless signal is received by a personal mobile terminal. The personal mobile terminal is provided with an elevator service request application component running at an application layer of an operating system thereof. The wireless signal apparatus includes a location notification unit used for broadcasting corresponding location marker data. The elevator service request system includes a wake-up module running at a system layer of the operating system of the personal mobile terminal. The wake-up module is used for waking up the elevator service request application component in response to reception of the location marker data.

Abstract: The present disclosure provides an artificial intelligence-based (AI-based) medical image processing method performed by a computing device, and a non-transitory computer-readable storage medium. The AI-based medical image processing method includes: processing a medical image to generate an encoded intermediate image; processing the encoded intermediate image, to segment a first feature and generate a segmented intermediate image; processing the encoded intermediate image and the segmented intermediate image based on an attention mechanism, to generate a detected intermediate input image; and performing second feature detection on the detected intermediate input image, to determine whether an image region of the detected intermediate input image in which the first feature is located comprises a second feature.

Abstract: Described herein is a method of induced cell death via ferroptosis by nanoparticle ingestion. Moreover, the present disclosure describes the administration of high concentrations of ultrasmall nanoparticles at multiple times over the course of treatment in combination with a nutrient-depleted environment, thereby modulating cellular metabolic pathways to induce cell death by the mechanism ferroptosis. Ferroptosis involves iron, reactive oxygen species, and a synchronous mode of cell death execution.

Abstract: The present disclosure provides a high-plasticity rapidly-degradable Mg—Li—Gd—Ni alloy, including the following chemical elements by mass percentage: 1.0-10.0% of Gd, 0.2-2.0% of Ni, 5.5-10% of Li, and the rest of Mg and inevitable impurities. The impurities have a total content less than or equal to 0.3%. The present disclosure further provides a preparation method of the high-plasticity rapidly-degradable Mg—Li—Gd—Ni alloy. The high-plasticity rapidly-degradable Mg—Li—Gd—Ni alloy provided by the present disclosure constructs an ?-Mg+?-Li dual-phase matrix structure by introducing ?-Li with a body-centered cubic (BCC) structure with relatively more slip systems to improve plasticity of the alloy, then adds a certain amount of Gd element to weaken texture and promote non-basal plane slip, and further improves plasticity. In addition, by introducing the high-potential Ni-containing LPSO phase, a large potential difference with ?-Mg and ?-Li is formed to increase the degradation performance.

Abstract: A method of characterizing a serum or plasma portion of a specimen in a specimen container provides a fine-grained HILN index (hemolysis, icterus, lipemia, normal) of the serum or plasma portion of the specimen, wherein the H, I, and L classes may each have five to seven sub-classes. The HILN index may also have one un-centrifuged class. Pixel data of an input image of the specimen container may be processed by a deep semantic segmentation network having, in some embodiments, more than 100 layers. A small front-end container segmentation network may be used to determine a container type and boundary, which may additionally be input to the deep semantic segmentation network. A discriminative network may be used to train the deep semantic segmentation network to generate a homogeneously structured output. Quality check modules and testing apparatus configured to carry out the method are also described, as are other aspects.

Abstract: The disclosure relates to methods, devices, systems, and computer storage medium for performing medical image segmentation. The method includes: The method includes: obtaining, by a device, a first medical image and a second medical image with a labeled region; performing, by the device, feature extraction on the first medical image and the second medical image respectively, to obtain first feature information of the first medical image and second feature information of the second medical image; obtaining, by the device, optical flow motion information from the second medical image to the first medical image according to the first feature information and the second feature information; and segmenting, by the device, the first medical image according to the optical flow motion information and the labeled region, to obtain a segmentation result of the first medical image.

Abstract: An outer loop initial value adjustment method, a device, and a readable storage medium are disclosed. The method may include: acquiring feature information of a plurality of User Equipment (UEs) scheduled by a cell; performing raster division on the feature information of the plurality of UEs to obtain a plurality of rasters; determining an outer loop corresponding to each of the rasters, where an outer loop value of each raster is within a target Block Error Rate (BLER) range; determining a target raster corresponding to a target UE according to the feature information of the target UE, where the target UE is one of the plurality of UEs scheduled by the cell; and determining the outer loop value corresponding to the target raster as an initial outer loop value of the target UE.

Abstract: Embodiments of this disclosure include a method and an apparatus for segmenting a medical image. The method may include obtaining a slice pair comprising two slices and performing feature extraction on each slice in the slice pair, to obtain high-level feature information and low-level feature information of the each slice in the slice pair. The method may further include segmenting a target object in the each slice according to the low-level feature information and the high-level feature information of the slice, to obtain an initial segmentation result of the each slice and fusing the low-level feature information and the high-level feature information of the slices to obtain a fused feature information. The method may further include determining correlation information between the slices according to the fused feature information and generating a segmentation result of the slice pair based on the correlation information and the initial segmentation results of the slices.

Abstract: This application relates to a medical image segmentation method, a computer device, and a storage medium. The method includes: obtaining medical image data; obtaining a target object and weakly supervised annotation information of the target object in the medical image data; determining a pseudo segmentation mask for the target object in the medical image data according to the weakly supervised annotation information; and performing mapping on the medical image data by using a preset mapping model based on the pseudo segmentation mask, to obtain a target segmentation result for the target object. Because the medical image data is segmented based on the weakly supervised annotation information, there is no need to annotate information by using much labor during training of the preset mapping model, thereby saving labor costs. The preset mapping model is a model used for mapping the medical image data based on the pseudo segmentation mask.

Abstract: This application provides a gesture information processing method and apparatus, an electronic device, and a storage medium. The method includes: acquiring an electromyography signal sample generated by an electromyography signal collection target object in connection with performing multiple gestures; dividing the electromyography signal sample through a sliding window having a fixed window value and a fixed stride into different electromyography signals of the target object; and applying the different electromyography signals to a first neural network model to determine gesture information matching the multiple gestures performed by the target object.

Abstract: An image segmentation model training method includes acquiring a first image, a second image, and a labeled image of the first image; acquiring a first predicted image according to a first network model; acquiring a second predicted image according to a second network model; determining a reference image of the second image based on the second image and the labeled image of the first image; and updating a model parameter of the first network model based on the first predicted image, the labeled image, the second predicted image, and the reference image to obtain an image segmentation model.

Abstract: A method of characterizing a serum or plasma portion of a specimen in a specimen container includes capturing a plurality of images of the specimen container from multiple viewpoints, stacking the multiple viewpoint images along a channel dimension into a single stacked input, and processing the stacked input with a single deep convolutional neural network (SDNN). The SDNN includes a segmentation convolutional neural network that receives the stacked input and outputs multiple label maps simultaneously. The SDNN also includes a classification convolutional neural network that processes the multiple label maps and outputs an HILN determination (Hemolysis, Icterus, and/or Lipemia, or Normal) of the serum or plasma portion of the specimen. Quality check modules and testing apparatus configured to carry out the method are also described, as are other aspects.

Abstract: This application provides a gesture information processing method and apparatus, an electronic device, and a storage medium. The method includes: determining an electromyography signal collection target object in a gesture information usage environment; dividing the electromyography signal sample through a sliding window having a fixed window value and a fixed stride into different electromyography signals of the target object, and denoising the different electromyography signals of the target object; recognizing the denoised different electromyography signals, and determining probabilities of gesture information represented by the different electromyography signals; and weighting the probabilities of the gesture information represented by the different electromyography signals, so as to determine gesture information matching the target object.

Abstract: The disclosure relates to nanoparticle drug conjugates (NDC) that comprise ultrasmall nanoparticles, folate receptor (FR) targeting ligands, and linker-drug conjugates, and methods of making and using them to treat cancer.