Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining whether to provide a digital component for presentation to a user based on the one or more predicted action values for a target action. The user is registered with both a first service platform and a second service platform. The predicted action values are generated in a way that does not combine or cross-use first user data that is specific to the first service platform and second user data that is specific to the second service platform.

Abstract: A processor-implemented method includes determining visual features, first hidden features, and second hidden features through a feature extraction network within a first artificial intelligence (AI) model, based on a scene image and a first command to move a target object, determining an action type associated with the target object through an action model selector within the first AI model, based on the first hidden features, selecting a target action model from a set of candidate action models within the first AI model, based on the action type, and determining an action sequence associated with the target object through the target action model, based on the second hidden features and the visual features.

Abstract: A display module includes a light-emitting layer, an encapsulation layer, a first light transmission layer, a pixel magnification layer, a second light transmission layer, and an anti-glare layer that are stacked in a light-emitting direction. The pixel magnification layer includes a first material having a first refractive index and a second material having a second refractive index. A difference between the first refractive index and the second refractive index is a first refractive index difference. A distance between a lower surface of the pixel magnification layer and an upper surface of the light-emitting layer is a first distance, and a product of the first distance and the first refractive index difference ranges from 15 ?m to 200 ?m.

Abstract: A system for medical imaging quality control and organ phenotype extraction is provided. A topological relationship tree of organ phenotypes is constructed according to association of anatomical structures between various organ phenotypic characteristics in a medical image, and a structural association graph of organ phenotypes in the medical image is determined; a semantic structure graph of medical entities in a text report is determined through a logical association relationship between the medical entities and a contextual relationship of clinical description statements in the text report; node-level alignment and fusion are performed on the structural association graph and the semantic structure graph of medical entities to obtain an organ-entity characteristic association map; medical imaging data is quality-controlled based on the characteristic association map, and a quality control warning is output if it is determined that the medical imaging data has an imaging quality anomaly.

Abstract: Provided are a video coding and decoding loop filtering method, a video decoding method, and an apparatus. The video coding and decoding loop filtering method includes: filtering a reconstructed picture of a current picture by using a first filter, so as to obtain a first reconstructed video unit; filtering the reconstructed picture by using a second filter, so as to obtain a second reconstructed video unit; determining a filter coefficient according to neighborhood information contained in a convolution template of the first reconstructed video unit and the second reconstructed video unit; and filtering, based on the convolution template and the filter coefficient, the first reconstructed video unit, the second reconstructed video unit, and the filter coefficient to obtain a third reconstructed video unit.

Abstract: In implementations of techniques and systems for digital hair generation using a parametric hair model, a processing device receives a shape parameter and a style parameter. The shape parameter represents the overall shape of a hair model, and the style parameter represents local strand details. Based on the shape parameter, a machine-learning model generates guide strands that sparsely represent the hair model. The machine-learning model also generates wisps based on the style parameter. The wisps indicate local strand details for the hair model. The processing device interpolates the wisps onto the guide strands to generate the digital hair model.

Abstract: The method provides for analyzing input and output connections of layers of a received neural network model configured for vertical federated learning. An undirected graph of nodes is generated in which a node having two or more child nodes includes an aggregation operation, based on the analysis of the model in which a model output corresponds to a node of the graph. A layer of the model is identified in which a sum of lower layer outputs are computed. The identified model layer is partitioned into a first part applied respectively to the multiple entities and a second part applied as an aggregator of the output of the first part. The aggregation operation is performed between pairs of lower layer outputs, and multiple forward and backward passes of the neural network model are performed that include secure aggregation and maintain model partitioning in forward and backward passes.

Abstract: The present invention relates to a use of edaravone in the treatment of autism spectrum disorder.

Abstract: A system and a computer-implemented method of training a global student model is disclosed. The global student model and a teacher model are stored on a server and each include a first layer. The method includes transmitting local student models based on the global student model, the local student models each including an embedding layer and a first layer. The method includes receiving an embedding layer output of one of the local student models. The method includes performing a forward pass on the first layer of the teacher model, with the embedding layer output as an input, to generate a teacher model first layer output. The method includes transmitting the teacher model first layer output. The method includes receiving first layer weights of the local student models. The method includes calculating first layer weights of the global student model using the received first layer weights of the local student models.

Abstract: A three-dimensional (3D) memory device includes a stack structure including a first stack structure and a second stack structure over the first stack structure, and a barrier layer disposed in a first channel hole in the first stack structure.

Abstract: An image acquisition method includes importing a three-dimensional model of an object into a three-dimensional virtual photographing scene having a virtual world coordinate system, determining model position information and model attitude information of the three-dimensional model in the virtual world coordinate system, determining, according to a layout pattern of a plurality of virtual cameras in the three-dimensional virtual photographing scene, camera position information and camera attitude information of each of the plurality of virtual cameras in the virtual world coordinate system, and acquiring, for each of the plurality of virtual cameras, an image of the object from a viewing angle of the virtual camera according to the model position information, the model attitude information, the camera position information, and the camera attitude information.

Abstract: A method of generating an autonomous driving trajectory includes generating a scene token and a first trajectory based on a collected image, obtaining a first query command including a first query for a logic of trajectory generation and a second query for safety of the trajectory, and generating a third trajectory based on the scene token, the first trajectory, and the first query command using a large language model (LLM). The third trajectory is obtained by processing a second trajectory based on second information obtained in response to the second query, the second trajectory is obtained based on first information obtained in response to the first query, and the first information and the second information are obtained based on the scene token, the first trajectory, and the first query command.

Abstract: The present application provides a hard carbon, a preparation method, a secondary battery, and an electrical apparatus. Based on the total mass of the hard carbon, the total mass ratio of water-soluble cations in the hard carbon does not exceed 500 ppm. The hard carbon can improve the viscosity of a negative electrode slurry and can improve the cycle performance of a battery.

Abstract: Disclosed is a panel of recombinant Escherichia coli strains for monitoring a plurality of analytes of interest in an aqueous sample, under aerobic physiological conditions, and a method for monitoring a plurality of analytes of interest employing the recombinant E. coli strains. The analytes of interest include ammonium, nitrate, nitrite, phosphate, manganese dication, an iron cation, and nickel dication, or a combination of any one of these analytes in real time, optionally, in a continuous series of aqueous samples, for example of environmental waters, agricultural aqueous run-off, or industrial aqueous inputs and/or outputs, aqueous biological samples, e.g., urine, serum, or cerebrospinal fluid. The disclosed panel of recombinant E. coli strains and the method can also be used to monitor these analytes in food samples that have been macerated and liquified.

Abstract: Three-dimensional (3D) semiconductor devices and fabricating methods are provided. In some implementations, a disclosed semiconductor device comprises: an array of vertical transistors each comprising a semiconductor body extending in a vertical direction; a plurality of word lines each extending along a first lateral direction and comprising a plurality of gate structures of a row of the array of vertical transistors arranged in the first lateral direction; and a plurality of bit lines each extending along a second lateral direction different from the first lateral direction and comprising silicide.

Abstract: Techniques for shape aware descriptive movement synthesis are described. In an example, a processing device is operable to receive a description of a body motion and a body, used as input to a trained machine learning system that generates motion data from the description. A shape parameter and a plurality of motion tokens are jointly predicted by the machine learning system based on the description. A plurality of discrete motion features is obtained from applying a finite scalar de-quantization to the motion tokens. Using the machine learning system, the processing device generates a plurality of shape conditioned motion features by integrating a shape feature projected from the shape parameter with the discrete motion features. The shape conditioned motion features are decoded by the machine learning system into the motion data, which models the motion with specific variations caused by the shape.

Abstract: Provided herein are processing apparatuses for producing high-quality films of sintered ceramics. The instant disclosure sets forth equipment and processes for making high quality, rapidly processed ceramic electrolyte films. These processes include high-throughput continuous sintering of oxides for use as electrolyte films. In certain processes, the film is not in contact with any surface as it sinters (i.e., during the sintering phase). Set forth herein are processes for making and using bilayers comprising a green body layer on a metal layer and bilayers comprising a sintered oxide layer on a metal layer. Set forth herein are processes for rapidly sintering thin bilayers comprising a green body layer on a metal layer in order to produce bilayers comprising a sintered oxide layer on a metal layer.

Abstract: A three-dimensional (3D) memory device includes a stack structure including a first stack structure and a second stack structure over the first stack structure, and a barrier layer disposed in a first channel hole in the first stack structure.

Abstract: Embodiments of the present disclosure provide a method and an apparatus for video processing, and a storage medium and an electronic apparatus. The method comprises: determining a neural network loop filtering enabled flag of a reconstructed video unit; setting, based on the neural network loop filtering enabled flag, an adaptive loop filtering enabled flag for the reconstructed video unit; and signaling at least one type of the following information: filter information related to neural network loop filter of the reconstructed video unit, and filter information related to adaptive loop filter of the reconstructed video unit.