Abstract: An information recommendation method, an apparatus, a device, and a medium based on embedding table compression are provided. The method includes: determining, based on a preset compression ratio, to-be-compressed features and non-compressed features in a to-be-compressed embedding table of a recommendation model, generating a similarity index matrix based on a similarity between the to-be-compressed features and the uncompressed features; generating an index dictionary based on the similarity index matrix; substituting a first feature mapping dictionary based on the index dictionary to generate a second feature mapping dictionary, wherein the first feature mapping dictionary is generated based on a data set; and acquiring to-be-recommended data, replacing features in the to-be-recommended data according to the second feature mapping dictionary, inputting replaced features into the recommendation model, and outputting a prediction result.

Abstract: Embodiments disclosed herein include a liquid metal interposer. In an embodiment, the liquid metal interposer comprises a substrate with a first opening in the substrate and a second opening in the substrate. In an embodiment, a channel is between the first opening and the second opening. In an embodiment, the channel fluidically couples the first opening to the second opening.

Abstract: An LED lighting device includes a seat, an optical assembly and a light source. The seat has a baseplate and a sidewall. A chamber is formed between the baseplate and the sidewall. The optical assembly completely covers a light-emitting side of the LED lighting device. The light source is disposed in the chamber of the seat and includes multiple LED arrays. Each LED array includes an LED chip. The optical assembly includes an optical unit. The optical unit includes multiple first optical members and multiple second optical members corresponding to the first optical members. The LED arrays correspond to the first optical members. Each first optical member possesses an effect of light diffusion resulting from its own material property. Each second optical member includes one or more sets of optical walls. Each set of optical walls surrounds one of the first optical members.

Abstract: Multichannel optical assemblies for optical IO (input output) systems are provided. The optical assemblies comprise an optical isolator. In some examples the optical assemblies also comprise an array of GRIN lenses. In other examples, the optical assemblies also comprise micromirrors.

Abstract: A LED lighting device, comprising: a base which has a bottom plate and a side wall, a cavity being formed between the bottom plate and the side wall; an optical component which covers one side of the base in a light-emitting direction of the LED lighting device; and a light source which is provided in the cavity of the base and comprises a circuit board and several LED arrays, the LED arrays comprising LED lamp beads fixed on the circuit board. The optical component comprises an optical unit, and the optical unit comprises a plurality of first optical components and a plurality of second optical components which correspond to the first optical components.

Abstract: The present application relates to a test structure and a test method for implementing an on-site dry-wet cycle of a large-grain-size rock-soil body. The solution includes: a test site evenly paved with a test material; a test tank arranged in the test site, where two ends of each test tank in a width direction are separated from soil bodies of other test sites by steel plates, and each test tank is provided with a plurality of water permeable holes. The present application can implement an on-site dry-wet cycle test of a large-grain-size rock-soil body, and is suitable for engineering practice.

Abstract: The disclosure provides display substrate and display panel, and belongs to field of display technology. The display substrate includes base substrate; and gate lines, data lines and sub-pixels on base substrate. Sub-pixels form first pixel groups arranged side by side along first direction and second pixel groups arranged side by side along second direction; first region is between any two adjacent first pixel groups, and second region is between any two adjacent second pixel groups; common electrode line is in at least a portion of the first regions, and common electrode line and data line are in different first regions; and common electrode line includes common electrode line segments and protrusions each coupled between two common electrode line segments, a width of protrusion in any direction is larger than that of common electrode line segment in first direction; and protrusion is in the second region.

Abstract: An LED lighting device includes a seat having a baseplate, a sidewall, and an end wall. The first end of the sidewall is connected to a periphery of the baseplate and forms a chamber with the baseplate. The second end of the sidewall is connected to the end wall and forms a receiving space with the end wall. A light source containing a plurality of LED arrays is disposed in the chamber. An electric power source is disposed in the receiving space, and an optical assembly is disposed on the light source. The optical assembly includes a plurality of first optical members and a plurality of second optical members. Each of the first optical members covers one of the LED arrays. Each of the second optical members includes a set of optical walls surrounding one of the first optical members.

Abstract: A semiconductor chip package is described. The semiconductor chip package has a substrate. The substrate has side I/Os on the additional surface area of the substrate. The side I/Os are coupled to I/Os of a semiconductor chip within the semiconductor chip package. A cooling assembly has also been described. The cooling assembly has a passageway to guide a cable to connect to a semiconductor chip's side I/Os that are located between a base of a cooling mass and an electronic circuit board that is between a bolster plate and a back plate and that is coupled to second I/Os of the semiconductor chip through a socket that the semiconductor chip's package is plugged into.

Abstract: Techniques and mechanisms for optically coupling a photonic integrated circuit (PIC) chip to an optical fiber via a planar optical waveguide structure. In an embodiment, a PIC chip comprises integrated circuitry, photonic waveguides, and integrated edge-oriented couplers (IECs) which are coupled to the integrated circuitry via the photonic waveguides. The PIC chip forms respective divergent lens surfaces of the IECs, which are each at a respective terminus of a corresponding one of the photonic waveguides. A planar optical waveguide structure, which is adjacent to the IECs, comprises a core which is optically coupled between the PIC chip and an array of optical fibers. In another embodiment, an edge of the PIC forms a stepped structure, wherein an upper portion of the stepped structure comprises the plurality of coplanar IECs, and a lower portion of the stepped structure extends past the plurality of coplanar IECs.

Abstract: The display panel includes an active area and a border-frame area located at a periphery of the active area, the active area includes a plurality of sub-pixels and a plurality of data lines connected to the sub-pixels, and the border-frame area includes a testing area and a bonding area; the testing area includes a plurality of testing units that are arranged periodically in a first direction, each of the testing units includes one or more switching transistors, a first electrode of each of the switching transistors is connected to a testing-signal lead wire, and a second electrode is connected to one of the data lines; the bonding area includes a plurality of bonding units that are arranged periodically in the first direction, each of the bonding units includes one or more bonding pads, and each of the bonding pads is connected to one of the data lines.

Abstract: An uninterruptible power supply, a control method and a power supply system for normally starting the uninterruptible power supply and securing switch devices are provided. The uninterruptible power supply includes a first rectification circuit, a charge-discharge circuit, a bus capacitor, a first switch circuit and a second rectification circuit. The first rectification circuit is connected to the charge-discharge circuit, and is configured to rectify a voltage outputted by the alternating current power supply. The charge-discharge circuit is connected to the bus capacitor, and is configured to charge the bus capacitor after boosting the voltage outputted by the first rectification circuit, until the voltage across the bus capacitor reaches a first voltage. The first switch circuit is connected to the second rectification circuit, and is configured to connect the alternating current power supply to the second rectification circuit.

Abstract: This application provides a shooting method. By implementing the method, a terminal device such as a mobile phone or a tablet computer can determine a shot protagonist based on a user operation when starting shooting or in a shooting process. In the shooting process, the terminal device may display, in a preview window, an image stream collected by a camera, and the terminal device may further generate a small window that specially displays the protagonist. After recording ends, a user may obtain two videos: an original video generated based on the image stream in the preview window, and a close-up video generated based on a protagonist image stream in the small window. In this way, the user can choose to use the original video and/or the close-up video to meet personalized requirements in different scenarios at different moments of the user.

Abstract: A system for classifying working memory task magnetoencephalography based on machine learning, including: the magnetoencephalography data acquisition module configured to acquire magnetoencephalography data of a subject in different working memory task states; the magnetoencephalography data preprocessing module configured to control the quality of magnetoencephalography data in different working memory tasks and separate noises and artifacts; the magnetoencephalography source reconstruction module configured for sensor signal analysis and source reconstruction analysis for the data processed by the magnetoencephalography data preprocessing module; and the machine learning classification module is configured to classify the working memory tasks to which the subjects belong by taking power time series as features.

Abstract: A system for precisely locating abnormal areas of brain fiber bundles. The system extracts fiber connections of the whole brain from diffusion magnetic resonance data, and fiber bundle pathways extracts through self-defined fiber bundle pathways or based on brain fiber bundle templates. A selected fiber bundle pathway is projected on a fiber connection result of the whole brain and finely segmented. The imaging indexes such as fractional anisotropy, mean diffusivity, intra-neurite volume fraction and orientation dispersion index are calculated from diffusion magnetic resonance data, so as to obtain the imaging index of each node of each fiber bundle pathway. These imaging indexes are configured to classify the disease group and the healthy group by a machine learning method, and which nodes on which fiber bundle pathways have abnormal changes with different diseases can be precisely located.

Abstract: A system for predicting disease with graph convolutional neural network based on multimodal magnetic resonance imaging, which extracts the radiomics information of multiple brain regions across modals as the features of nodes from multimodal magnetic resonance data, and extracts the connectomics information between brain regions to form an adjacency matrix. T1-weighted structural images extract cortical information through cortical reconstruction, and resting-state magnetic resonance data are used to calculate amplitude of low frequency fluctuations, regional homogeneity and functional connectivity. Through multimodal data preprocessing, image index extraction and structured data integration, multimodal unstructured magnetic resonance image data are integrated into unified graph-structured data, and the disease is predicted by a graph convolutional neural network method.

Abstract: A method and a system for simulating magnetic resonance echo-planar imaging artifacts. Firstly, for K-space artifacts, K-space data are restored through normal magnetic resonance images, and the K-space data are modified pertinently, and then images with artifacts are reconstructed; for susceptibility artifacts, a susceptibility model is constructed through normal magnetic resonance images, and the magnetic field distribution is reconstructed, and then the images with distortion artifacts are reconstructed. According to the present disclosure, a large number of artifact data sets with different artifact types and artifact degrees can be quickly created through a small number of normal images, thus laying a foundation for the research of identifying artifacts, eliminating or weakening artifacts.

Abstract: A cognitive training material generation method, a cognitive training method, a device, and a medium are provided. The cognitive training material generation method includes: acquiring a first feature and a second feature, the first feature including a multimedia material and semantic information corresponding to the multimedia material, the second feature including a magnetic resonance representation; fitting the first feature and the second feature, obtaining a semantic map according to a fitting result and a preset brain map, and acquiring target semantic information corresponding to a target point according to the semantic map; taking the first feature as input of a deep learning model and the second feature as a constraint of the deep learning model, training the deep learning model, and determining a weight parameter of the deep learning model; generating a cognitive training material according to the target semantic information and the weight parameter of the deep learning model.

Abstract: Embodiments described herein may be related to apparatuses, processes, and techniques related to disaggregating co-packaged SOC and photonic integrated circuits on an multichip package. The photonic integrated circuits may also be silicon photonics engines. In embodiments, multiple SOCs and photonic integrated circuits may be electrically coupled, respectively, into modules, with multiple modules then incorporated into an MCP using a stacked die structure. Other embodiments may be described and/or claimed.

Abstract: The embodiments of the present disclosure provide a display substrate, a display panel, and a display device. The display substrate includes: a first base substrate, wherein a plurality of sub-pixel regions arranged in an array are provided on the first base substrate; and a reflective layer provided on one side of the first base substrate, wherein a surface of the reflective layer away from the first base substrate is formed to include a plurality of first bumps and a plurality of second bumps, and the first bump has a size greater than that of the second bump.