Abstract: An artificial intelligence-based identification method for a wireless composite jamming signal forms a novel neural network structure ACSNet through the integration of an asymmetric convolutional block (ACB), aiming to address composite jamming signal identification in wireless communication systems. The model of the artificial intelligence-based identification method enhances the detection capability of neural networks for subtle signal feature variations based on artificial intelligence, thereby improving the identification accuracy for intricate jamming patterns. The artificial intelligence-based identification method can effectively address the challenge of jamming signal identification under a low jamming-to-noise ratio (JNR). Additionally, ACSNet demonstrates significant resilience to variations in power ratios (PRs) of composite jamming signals, highlighting its adaptability to real-world environments with imbalanced jamming signal power distributions.

Abstract: A porous carbon material has first pores, second pores, and third pores; where the first pores has a pore size of P1 nm and 0<P1?1; the second pores has a pore size of P2 nm and 1<P2?3; and the third pores has a pore size of P3 nm and 3<P3?10; where based on a sum of the pore volumes of the first pores, the second pores, and the third pores, a volume percentage of the first pores is V1%, a volume percentage of the second pores is V2%, and a volume percentage of the third pores is V3%; where 0.1?V1?10 and 50?V2?95.

Abstract: A self-referencing spectral constraint-based spectral reconstruction method and apparatus, a device, and a medium are provided. The method includes: acquiring a total transmission matrix through a calibration; acquiring each observed speckle generated after target light passes through each filtering interval of a spectral filter to enter a scattering medium, where all observed speckles form a total observed speckle; forming a self-referencing spectrum based on total intensities of each observed speckle; and constructing a spectral reconstruction model based on a neural network and a physical forward process of the total transmission matrix, constructing a composite loss function based on a speckle intensity estimation error and a self-referencing spectrum error, and optimizing the parameters of the neural network via the composite loss function until convergence, thereby yielding an optimized neural network for spectral reconstruction for a given total observed speckle.

Abstract: A porous carbon material having a sphericity of a, where 0.7?a?0.97; the porous carbon material includes potassium element; and based on a mass of the porous carbon material, a mass proportion of the potassium element is b ppm, where 1?b?2998.

Abstract: A self-referencing spectral constraint-based spectral reconstruction method and apparatus, a device, and a medium are provided. The method includes: acquiring a total transmission matrix through a calibration; acquiring each observed speckle generated after target light passes through each filtering interval of a spectral filter to enter a scattering medium, where all observed speckles form a total observed speckle; forming a self-referencing spectrum based on total intensities of each observed speckle; and constructing a spectral reconstruction model based on a neural network and a physical forward process of the total transmission matrix, constructing a composite loss function based on a speckle intensity estimation error and a self-referencing spectrum error, and optimizing the parameters of the neural network via the composite loss function until convergence, thereby yielding an optimized neural network for spectral reconstruction for a given total observed speckle.

Abstract: A processing method of heat transfer printing fabric based on UV-printed three-dimensional graphics is provided. The processing method includes the following steps: applying hot-melt adhesive onto a release layer, drying and preparing a hot-melt adhesive layer; performing UV inkjet printing on the hot-melt adhesive layer to form graphics, and laminating a protective layer onto the surface of the hot-melt adhesive layer to obtain a hot-melt adhesive layer with graphics; and removing the release layer from the hot-melt adhesive layer with graphics, spreading the hot-melt adhesive layer onto a fabric, pressing at a temperature of 140-160° C., removing the protective layer and obtaining printed fabric with three-dimensional graphics.

Abstract: An EVA composite hot-melt adhesive for UV-printed three-dimensional patterns, and a preparation method and an application thereof are provided. The EVA composite hot-melt adhesive includes thermoplastic polyurethane elastomer, ethylene-vinyl acetate copolymer, polyvinyl acetate, film-forming agent, viscosity modifier, and polypropylene; and a vinyl acetate content of the ethylene-vinyl acetate copolymer is ?28 wt %. The EVA composite hot-melt adhesive uses an ethylene-vinyl acetate copolymer with a higher VA content as base resin, combined with thermoplastic polyurethane elastomer to improve properties of ductility and tensile of the material, and to enhance the hydrophilicity of EVA, thereby strengthening color fastness to washing after heat pressing and film formation. The addition of polyvinyl acetate improves the adhesion and color fastness to washing of the material.

Abstract: The present invention provides a method for determining color difference defect compensation data, a compensation method, and an augmented reality device. The method for determining color difference defect compensation data, including: obtaining a generated image of an augmented reality device, and preprocessing the generated image to obtain a first image; using a preset filtering algorithm to detect a color difference defect in the first image; obtaining a position of the color difference defect region and color difference defect data; and generating corresponding color difference defect compensation data based on the color difference defect data.

Abstract: Disclosed is a preparation method of a plant biomass-based active tanning agent. Under a low-temperature reaction condition, cyanuric chloride and a plant biomass compound are used to synthesize an environment-friendly plant biomass-based active tanning agent through a nucleophilic substitution reaction. The active tanning agent obtained in the present disclosure appears as a white or light brown emulsion at room temperature, and has substantial active groups such as hydroxyl groups, carboxyl groups and ester groups introduced into its structure, thus endowing leathers with desirable hydrothermal stability and physical properties and having a desirable synergistic effect with metal tanning agents. Meanwhile, health and environment risks caused by hexavalent chromium and free formaldehyde in leathers are avoided.

Abstract: The present invention relates to compounds of formula (Ia), (Ia), wherein R1 to R3, Q1, Q2, A1 to A6 are as described herein, and their pharmaceutically acceptable salt thereof, and compositions including the compounds and methods of using the compounds.

Abstract: The present disclosure discloses a method, a device, and an electronic device for locating an anomaly root cause. The method for locating the anomaly root cause includes obtaining an anomaly indicator of a target system, obtaining a data item set based on the anomaly indicator, determining an anomaly data item based on data fluctuation information of each data item of the data item set, obtaining an anomaly field corresponding to the anomaly data item based on the anomaly data item, and locating an anomaly root cause of the target system based on the anomaly field.

Abstract: A protein detection method and a detection device as well as use are provided. The protein detection method includes: fixing a probe type graphic encoding chip coupled with a specific capture antibody in the detection device, and meanwhile respectively sealing SAPE and a detection antibody in the detection device; and when in detection, performing detection and analysis based on an enzyme linked immunosorbent assay (ELISA) principle through the probe-type graphic encoding chip after the detection antibody and the SAPE are respectively dissolved, so as to obtain protein quantitative analysis results.

Abstract: The present disclosure provides an energy storage container including a box body and one or more dehumidifiers, the box body includes a top cover and a bottom cover arranged relative to each other, and multiple battery clusters are arranged inside the box body, wherein a length and width of each dehumidifier are both greater than a thickness of the dehumidifier, and the dehumidifiers are arranged between a bottom of the multiple battery clusters and the bottom cover, and a thickness direction of the dehumidifiers is aligned with a height direction of the box body.

Abstract: The present application provides an energy storage container including a container body, battery clusters, and a fire-fighting system. The container body includes a top cover and a bottom cover oppositely disposed. The container body is provided with a battery compartment, and the top cover and the bottom cover surround a top portion and a bottom portion of the battery compartment, respectively. The battery clusters are disposed in the battery compartment. The fire-fighting system includes fire-fighting devices uniformly dispersedly arranged among the battery clusters and the top cover.

Abstract: This present invention provides dissolvable solid articles comprising multiple layers of flexible, dissolvable, porous sheets, in which a coating composition is present on at least one internal surface of at least one sheet in said solid articles. The present invention also provides a process for making such solid articles.

Abstract: The present disclosure discloses a method, a device, and an electronic device for locating an anomaly root cause. The method for locating the anomaly root cause includes obtaining an anomaly indicator of a target system, obtaining a data item set based on the anomaly indicator, determining an anomaly data item based on data fluctuation information of each data item of the data item set, obtaining an anomaly field corresponding to the anomaly data item based on the anomaly data item, and locating an anomaly root cause of the target system based on the anomaly field.

Abstract: Disclosed are a defect monitoring apparatus and detection method for a transformer oil conservator based on edge computing. The monitoring apparatus includes: a sensing terminal, an edge intelligent gateway, a monitoring terminal, an oil conservator defect monitoring cloud platform, and a client terminal. The edge intelligent gateway and the monitoring terminal are both disposed in a substation. The monitoring terminal is configured to access the edge intelligent gateway. The sensing terminal includes: an airflow sensor, an oil temperature sensor, an ambient temperature sensor, and a microwave oil level measurement assembly. The sensing terminal sends detection data information to the edge intelligent gateway, and the edge intelligent gateway stores and determines a category of the detection data information. The present disclosure can recognize capsule damage, partial blockage of a breathing circuit, leakage in the breathing circuit, moisture impurities in a breathing tube, and false oil level.