Abstract: A grating regulating device is applied to a 3D displaying device. The 3D displaying device includes a display panel, the display panel includes a first polarizing unit, the grating regulating device is provided on one side of the display panel away from the first polarizing unit, and the grating regulating device includes: a first substrate and a second substrate, wherein the first substrate and the second substrate face each other; a second polarizing unit provided on one side of the second substrate away from the first substrate; and a third polarizing unit provided on one side of the first substrate away from the second substrate; and an absorption axis of the first polarizing unit and an absorption axis of the second polarizing unit are perpendicular, and the absorption axis of the second polarizing unit and an absorption axis of the third polarizing unit are perpendicular.

Abstract: Disclosed are a tea type differentiation method and system, belonging to the technical field of detection. The method comprises: building a differentiation function by using ionic strengths of 20 compounds as evaluation indexes to discriminate tea types. According to the disclosure, the tea types are discriminated by using relative abundance of 20 compounds in tea, problems in sensory differentiation can be solved, the tea is classified more objectively and scientifically, and the reliability and accuracy of differentiation results are improved. By using three algorithms, the feasibility and accuracy of using 20 discovered compounds for tea type differentiation in a combined manner are validated.

Abstract: The present disclosure relates to an information obtaining method and apparatus, a device, and a medium. The method includes setting a label table corresponding to each sample sentence in a sample set, wherein row characters and column characters in the label table are set identically in accordance with an order of characters of the corresponding sample sentence; and marking cells composed of the row characters and the column characters in the label table with corresponding information category labels; taking each sample sentence in the sample set as input information to a model to be trained and the label table corresponding to each sample sentence as output information of the model to be trained, and performing model training according to a preset target function; and generating an information extraction model based on parameters of the trained model to extract target sentence information by the information extraction model.

Abstract: Provided are metal oxide ceramic materials and intermediate materials thereof (e.g., nanozirconia gels, nanozirconia green bodies, pre-sintered ceramic bodies, zirconia dental ceramic materials, and dental articles). The nanozirconia gels are formable gels. Also provided are methods of making and using the metal oxide materials and intermediate materials. The nanozirconia gels can be made using, for example, osmotic processing. The nanozirconia gels can be used to make nanozirconia green bodies, pre-sintered ceramic bodies, zirconia dental ceramic materials, and dental article. The nanozirconia green bodies, pre-sintered ceramic bodies, zirconia dental ceramic materials, and dental articles have desirable properties (e.g., optical properties and mechanical properties).

Abstract: Methods, systems, and devices for multi-track music generation are described. In some examples, a method includes receiving a text prompt describing desired musical attributes and generating, using a diffusion model, multiple audio tracks based on the text prompt, wherein each audio track corresponds to a different musical component. The method can further include assigning individual timestep vectors respectively to each of multiple audio tracks and generating, using a diffusion model, one or more enhanced audio tracks based on the individual timestep vectors and corresponding audio track. Finally, the method can include combining the generated audio tracks to produce a multi-track musical composition.

Abstract: The present disclosure discloses a preparation device for magnesium oxide fiber and preparation method thereof. The preparation device for the magnesium oxide fiber includes a fiber releasing device, an electrochemical reaction device, a heating device, and a fiber receiving device. The fiber releasing device is used for releasing magnesium metal fiber. The electrochemical reaction device is used for oxidizing the magnesium metal fiber released by the fiber releasing device into magnesium hydroxide fiber, comprising a solution storage part, a negative electrode, and a positive electrode. Neutral electrolyte is stored in the solution storage part to soak the magnesium metal fiber released by the fiber releasing device. The heating device is used for heating the magnesium hydroxide fiber prepared by the electrochemical reaction device, to obtain magnesium oxide fiber. The fiber receiving device is used for receiving the magnesium oxide fiber obtained after being heated.

Abstract: Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this through deriving backpropagation signals through a competitive process involving a pair of networks. The representations that can be learned by GANs may be used in a variety of applications, including image synthesis, semantic image editing, style transfer, image super-resolution and classification. The aim of this review paper is to provide an overview of GANs for the signal processing community, drawing on familiar analogies and concepts where possible. In addition to identifying different methods for training and constructing GANs, we also point to remaining challenges in their theory and application. Index Terms—neural networks, unsupervised learning, semi-supervised learning.

Abstract: Systems and methods for generating and displaying clothing recommendations via a network are disclosed herein. In an embodiment, a system for generating and displaying a clothing recommendation via a network includes a mirror unit configured to enable the first user to view himself or herself on at least one side, a memory configured to store a wardrobe database, a communications network configured to communicate between the mirror unit and a second user; and a processor programmed to: (i) cause the one or more image of the first user captured by the image capturing device to be transmitted from the mirror unit to the second user via the communications network; (ii) receive feedback from the second user regarding the one or more image; and (iii) update the wardrobe database.

Abstract: A display device is provided, and the display device includes a display panel and a light adjusting portion. The light adjusting portion is stacked with the display panel, the light adjusting portion includes a first substrate, a refractive index variable material layer, an electrode structure, and a second substrate stacked with each other, and the refractive index variable material layer and the electrode structure are between the first substrate and the second substrate. The light adjusting portion further includes a plurality of signal lines, and the electrode structure and the plurality of signal lines are on the first substrate; the electrode structure includes a first electrode structure and a second electrode structure, the first electrode structure includes a plurality of first electrodes insulated from each other, the first substrate includes a plurality of regions, and first electrodes in different regions are configured to be electrically connected to different signal lines.

Abstract: A method and apparatus for reconstructing a three-dimensional (3D) scene from a two-dimensional (2D) input image of the scene using a fully-differentiable transformer-based encoder-decode. A 2D input image encoded into a set of image features using a pre-trained vision transformer model, wherein the vision transformer model is pre-trained with multi-view RGB image supervision and point cloud supervision. The set of image features is projected onto a 3D triplane representation using a transformer decoder to obtain output triplane tokens. A triplane representation is created from the tokens and queried. 3D point features of color and density for volumetric rendering re predicted using a multi-layer perceptron. The geometry of the generated 3D asset is represented with a surface mesh including vertices and triangular faces. A texture map by is created with a multichannel image in UV space. Multiple views of the 3D scene are simultaneously generated based on the surface mesh.

Abstract: Provided are metal oxide ceramic materials and intermediate materials thereof (e.g., nanozirconia gels, nanozirconia green bodies, pre-sintered ceramic bodies, zirconia dental ceramic materials, and dental articles). The nanozirconia gels are formable gels. Also provided are methods of making and using the metal oxide materials and intermediate materials. The nanozirconia gels can be made using, for example, osmotic processing. The nanozirconia gels can be used to make nanozirconia green bodies, pre-sintered ceramic bodies, zirconia dental ceramic materials, and dental article. The nanozirconia green bodies, pre-sintered ceramic bodies, zirconia dental ceramic materials, and dental articles have desirable properties (e.g., optical properties and mechanical properties).

Abstract: The method involves configuring a pretrained text to music AI model that includes a neural network implementing a diffusion model. The process includes receiving audio sample data corresponding to a specific audio concept, generating a concept identifier token based on the audio sample data, adapting a loss function of the diffusion model based on the concept identifier token, selecting pivotal parameters in weight matrices in a self-attention layer of the neural network of the AI model based on the audio sample data, and further training the pivotal parameters of the AI model, to optimize the Al model for the specific audio concept.

Abstract: The present disclosure provides a method for configuring a learning model for music generation and the corresponding learning model. The method includes training a masked autoencoder with training data comprising a combination of a reconstruction loss over time and frequency domains and a patch-based adversarial objective operating at different resolutions. An omnidirectional latent diffusion model is trained based on music data represented in a latent space to obtain a pretrained diffusion model. The pretrained diffusion model is fine-tuned based on text-guided music generation, bidirectional music in-painting, and unidirectional music continuation. The method enables high-fidelity music generation conditioned on text or music representations while maintaining computational efficiency.

Abstract: Systems and methods for generating clothing recommendations are disclosed herein. In an embodiment, a system for generating a clothing recommendation includes a mirror, a display device, an image capturing device, a memory and a processor. The mirror has a first side including a reflective surface. The display device displays a clothing recommendation to the user. The image capturing device records an image of the user. The memory stores a wardrobe database including clothing data related to a plurality of items of clothing. The processor is programmed to: (i) access the clothing data; (ii) generate a clothing recommendation; (iii) cause the image capturing device to record an image of the user; and (iv) cause the display device to display the clothing recommendation to the user by combining the image with the at least one suggested item of clothing.

Abstract: The present disclosure provides a method for configuring a learning model for music generation and the corresponding learning model. The method includes training a masked autoencoder with training data comprising a combination of a reconstruction loss over time and frequency domains and a patch-based adversarial objective operating at different resolutions. An omnidirectional latent diffusion model is trained based on music data represented in a latent space to obtain a pretrained diffusion model. The pretrained diffusion model is fine-tuned based on text-guided music generation, bidirectional music in-painting, and unidirectional music continuation. The method enables high-fidelity music generation conditioned on text or music representations while maintaining computational efficiency.

Abstract: A furniture unit in the form of a multi-function table including a base having front end, a rear end, and a primary cavity. A first storage unit is located within the primary cavity to define a first storage area having a first opening at the front end of the base that is closed by a first closure member. A second storage unit is located within the primary cavity to define a second storage area having a second opening at the front end of the base that is closed by a second closure member. The primary cavity may have a rear portion located between the first and second storage units and the rear end of the base. A compressor may be located within the rear portion of the primary cavity and may be operably coupled to the first storage area to cool the first storage area.

Abstract: Disclosed are a dimmable panel (001) and a display device. The dimmable panel includes a first substrate (101) and a second substrate (102) that are arranged opposite each other; a first electrode (103) and a second electrode (104) that are insulated from each other and located between the first substrate (101) and the second substrate (102), where the first electrode (103) and the second electrode (104) are located in a dimmable area (AA), at least one of the first electrode (103) and the second electrode (104) includes a plurality of strip-shaped electrodes, extension trends of all the strip-shaped electrodes are approximately the same, and orthographic projections of the strip-shaped electrodes on the first substrate (101) do not overlap each other; and a liquid crystal layer (105) located between the first substrate (101) and the second substrate (102), where the liquid crystal layer (105) is located in the dimmable area (AA).

Abstract: The present disclosure provides a method for configuring a learning model for music generation and the corresponding learning model. The method includes training a masked autoencoder with training data comprising a combination of a reconstruction loss over time and frequency domains and a patch-based adversarial objective operating at different resolutions. An omnidirectional latent diffusion model is trained based on music data represented in a latent space to obtain a pretrained diffusion model. The pretrained diffusion model is fine-tuned based on text-guided music generation, bidirectional music in-painting, and unidirectional music continuation. The method enables high-fidelity music generation conditioned on text or music representations while maintaining computational efficiency.

Abstract: A display device is provided, and the display device includes a display panel and a light adjusting portion. The light adjusting portion is stacked with the display panel, the light adjusting portion includes a first substrate, a refractive index variable material layer, an electrode structure, and a second substrate stacked with each other, and the refractive index variable material layer and the electrode structure are between the first substrate and the second substrate. The light adjusting portion further includes a plurality of signal lines, and the electrode structure and the plurality of signal lines are on the first substrate; the electrode structure includes a first electrode structure and a second electrode structure, the first electrode structure includes a plurality of first electrodes insulated from each other, the first substrate includes a plurality of regions, and first electrodes in different regions are configured to be electrically connected to different signal lines.