Abstract: Embodiments of the present disclosure provide a method and an apparatus for protecting data in an electronic device, an electronic device, and a program product. The method includes: receiving first data from a first application by a security service, where the security service blocks the first application from accessing a second application to protect data. The method further includes: receiving second data from the second application by the security service. In addition, the method further includes: determining third data for the electronic device by the security service based on the first data and the second data.

Abstract: The present application discloses a method, system, and computer system for classifying stream data at an edge device. The method includes obtaining a stream of a file at the edge device, aligning a predetermined amount of data in chunks associated with the stream of the file, processing a plurality of aligned chunks associated with the stream of the file using a machine learning model, and classifying, at the edge device, the file based at least in part on a classification of the plurality of aligned chunks.

Abstract: The detection of malicious documents using knowledge distillation assisted learning is disclosed. A document is received for maliciousness determination. A likelihood that the received document represents a threat is determined. The determination is made, at least in part, using a raw bytes model that was trained, at least in part, using image model prediction probabilities. A verdict for the document is provided as output based at least in part on the determined likelihood.

Abstract: A retrieval method for an open-vocabulary 3D target, a device and a storage medium are provided. The method includes: inputting text description information of a target object and an image sequence of a real scene into an open-vocabulary 3D target retrieval model. The retrieval model includes an LLM, an open-vocabulary 2D detection and segmentation model, an object filtering module and a 3D projection module. The LLM is used to enhance the text description information to obtain names of a plurality of candidate objects of the target object. The open-vocabulary 2D detection and segmentation model is used to detect and segment according to the names of the candidate objects, to obtain 2D segmentation masks of the plurality of candidate objects. The object filtering module is used to determine the target object from the candidate objects according to the text description information and a 2D segmentation mask of each candidate object.

Abstract: A method and an apparatus for positioning an interactive component of an open-vocabulary 3D target, a device, and a storage medium. The method includes: acquiring text description information of a target task and an image sequence of a real scene; and inputting the text description information and the image sequence into an interactive component positioning model to obtain a positioning result of an interactive component of a target object to be operated by the target task, wherein the interactive component positioning model includes a large language model (LLM), an open-vocabulary 2D detection and segmentation model, a filtering module, and a 3D projection module.

Abstract: The detection of malicious documents using knowledge distillation assisted learning is disclosed. A document is received for maliciousness determination. A likelihood that the received document represents a threat is determined. The determination is made, at least in part, using a raw bytes model that was trained, at least in part, using image model prediction probabilities. A verdict for the document is provided as output based at least in part on the determined likelihood.

Abstract: Techniques for using deep learning to identify malicious image files are disclosed. A plurality of sections of a first image are received. The received sections are used to determine a likelihood that the first image is malicious. The determination is made, at least in part, using a model trained using a set of sections extracted from a set of sample images. A verdict is provided for the first image.

Abstract: Methods for identifying a modulator of angiogenesis and methods for modulating angiogenesis in a mammalian subject are described herein. In some embodiments, the methods include obtaining data sets from a model for angiogenesis and generating a causal relationship network model based on the obtained data. In some embodiments, the methods include identifying, from the causal relationship network model, a causal relationship unique in angiogenesis, where a gene, lipid, protein, metabolite, transcript, or SNP associated with the unique causal relationship is identified as a modulator of angiogenesis.

Abstract: The detection of phishing Portable Document Format (PDF) files using an image-based deep learning approach is disclosed. A PDF document is received. A likelihood that the received PDF document represents a threat is determined, at least in part, by using an image based model that was previously trained, at least in part, using a plurality of images that were generated using one or more tools that collectively convert a set of given PDF document files to the respective plurality of images. A verdict for the PDF document is provided as output based at least in part on the determined likelihood.

Abstract: The present application discloses a method, system, and computer system for classifying stream data at an edge device. The method includes obtaining a stream of a file at the edge device, aligning a predetermined amount of data in chunks associated with the stream of the file, processing a plurality of aligned chunks associated with the stream of the file using a machine learning model, and classifying, at the edge device, the file based at least in part on a classification of the plurality of aligned chunks.

Abstract: This application is applicable to the field of communications technologies, and provides an embedded subscriber identity module (eSIM) card identification method and a terminal device method. The method includes: after completing an initialization process, driving an eSIM card to be powered on; querying whether an activated profile exists in the eSIM card; and when a query result is that no activated profile exists in the eSIM card, powering off the eSIM card. When the eSIM card is not activated or no activated profile exists in the eSIM card, it indicates that a user does not need to use a related function or service of the eSIM card. In this case, the eSIM card is powered off. When the eSIM card is not activated, it means that no profile exists in the eSIM card.

Abstract: Disclosed are antigen binding constructs targeting HER2 and uses thereof. Specifically provided is an antibody comprising a monovalent antigen-binding fragment that specifically binds to the HER2 ECD4 antigen on HER2-expressing cells, with the heavy chain variable region containing a mutation at position 30 and the light chain variable region containing a mutation at position 53, both according to Kabat numbering, a nucleic acid that encodes the same, a vector that comprises said nucleic acid, a cell that comprises an isolated nucleic acid of said vector, and a pharmaceutical composition that comprises the foregoing. Further provided are uses thereof in aspects such as treating subjects who suffer from HER2-expressing tumors, killing HER2-expressing tumor cells, or inhibiting the growth of HER2-expressing tumor cells.

Abstract: The detection of phishing Portable Document Format (PDF) files using an image-based deep learning approach is disclosed. A PDF document that includes a Universal Resource Locator is received. A likelihood that the received PDF document represents a phishing threat is determined, at least in part, by using an image based model. A verdict for the PDF document is provided as output based at least in part on the determined likelihood.

Abstract: Malware signature generation through combination rule mining is disclosed. A set of properties associated, collectively, with a plurality of data samples is received. A first data sample has a first set of properties and a second data sample has a second set of properties. A combination signature comprising at least a first property included in the first set of properties and a second property included in the second set of properties is generated.

Abstract: This invention discloses a method for comprehensively apportioning the source contribution to fine particular matter (PM2.5) based on the receptor model and the chemical transport model, which comprises the receptor model calculation steps, chemical transport model calculation steps and comprehensive source apportionment steps; the said comprehensive source apportionment step comprises the following sub-steps: according to the principle of inverse proportionality between uncertainty and weight coefficient, the first (receptor model) uncertainty and the second (chemical transport model) uncertainty are normalized to obtain their respective weight coefficients; the comprehensive source apportionment results are calculated based on the apportionment results of the receptor model and the chemical transport model, and their respective weight coefficient.

Abstract: Techniques for using deep learning to identify malicious image files are disclosed. A plurality of sections of a first image are received. The received sections are used to determine a likelihood that the first image is malicious. The determination is made, at least in part, using a model trained using a set of sections extracted from a set of sample images. A verdict is provided for the first image.

Abstract: A cluster management method includes starting an operating system of a network device and feeding back a startup result of an operating system. The cluster management system sends the startup indication to the computing device to control to start the computing device and the operating system of the network device included in the computing device, and the computing device feeds back the startup result.

Abstract: The present application discloses a method, system, and computer system for classifying stream data at an edge device. The method includes obtaining a stream of a file at the edge device, aligning a predetermined amount of data in chunks associated with the stream of the file, processing a plurality of aligned chunks associated with the stream of the file using a machine learning model, and classifying, at the edge device, the file based at least in part on a classification of the plurality of aligned chunks.

Abstract: A method for quantifying mRNA capping efficiency includes combining a sample, an enzyme mixture, and an isotopic standard solution in a buffer solution to create an incubation mixture, the enzyme mixture including a non-specific, single-stranded nuclease and an acid phosphatase and the isotopic standard including isotopically labeled m7G and isotopically labeled 2?-O-methylated nucleoside; incubating the mixture; and analyzing the mixture using liquid chromatography-mass spectrometry to determine at least one of a capping efficiency and a 2-O-methyltransferase efficiency.

Abstract: A multi-specific antibody targeting BCMA. Specifically provided are a multi-specific antibody, a nucleic acid encoding same, a vector including the nucleic acid, a cell including the vector, and a pharmaceutical composition including same. Further provided is the use thereof for treating a subject having a disease related to BCMA expression.