Abstract: An apparatus and method for preparing high-purity spherical magnesium and/or high-purity magnesium powder are provided. The apparatus includes a vertical furnace body, a heating zone, and a condensing zone, where a periphery of the condensing zone is provided with a first thermal insulation device and a second thermal insulation device sequentially from bottom to top, and each of the first thermal insulation device and the second thermal insulation device is removably arranged; the periphery of the condensing zone is further provided with a liquid cooling device; a gas inlet and a gas outlet are formed in the condensing zone; and an inner wall of the condensing zone is provided with an arrangement structure configured to arrange a collection device. A heating temperature of a material and condensation conditions in the condensing zone are controlled to make an evaporated magnesium vapor condensed on the collection device in the condensing zone.

Abstract: A flexible substrate has at least one bendable region. The flexible substrate includes a flexible base, a first electrode layer disposed on the base, a first insulating layer disposed on a side of the first electrode layer away from the base, and a second electrode layer disposed on a side of the first insulating layer away from the base. The first electrode layer includes at least one first detection electrode, and the second electrode layer includes at least one second detection electrode. An orthogonal projection of a first detection electrode on the base overlaps at least partially with an orthogonal projection of a second detection electrode on the base. A region where orthogonal projections of the first detection electrode and the second detection electrode on the base are located overlaps with a bendable region.

Abstract: A method for improving estimation of leaf area index in an early growth stage of wheat based on red-edge bands of Sentinel-2 satellite images includes the following steps: acquiring field background spectrum and wheat canopy spectrum information by means of Sentinel-2; respectively acquiring a “straw-soil” spectrum and a “wheat-straw-soil” spectrum, and calculating slopes of red-edge areas of the “straw-soil” spectrum and the “wheat-straw-soil” spectrum; calculating a tangent function SATF corrected by a background adjustment coefficient ?; constructing a wheat LAI estimation model based on a spectral variable SATFNIR-RE2; performing preliminary screening on the LAI estimation model using cross validation; and then testing the screened model with independent data.

Abstract: A display panel, a display apparatus, and a manufacturing method are disclosed. The display panel includes a base substrate having a first through hole; a conductive structure located on the base substrate and at least partially covering the first through hole; and a display structure including a first display structure, a control line, and a second display structure that are arranged in layers on a side of the base substrate where the conductive structure is located, wherein the first display structure has a second through hole, and the control line is electrically connected to the conductive structure by passing through the second through hole.

Abstract: The present disclosure relates to a composite logic gate circuit, including: a simple logic gate circuit including a first logic gate circuit and an inverter circuit, a first PMOS transistor, and a first NMOS transistor. The first logic gate circuit is configured to receive a first input signal and a second input signal, and to output a first output signal. The inverter circuit includes a second PMOS transistor and a second NMOS transistor. A source of the second PMOS transistor is coupled to a power input terminal, a drain is coupled to a drain of the second NMOS transistor, and a gate is configured to receive the first output signal. A source of the second NMOS transistor is coupled to a ground terminal, and a gate is configured to receive the first output signal. A source of the first PMOS transistor is coupled to the drain of the second PMOS transistor, a drain is coupled to a drain of the first NMOS transistor, and a gate is configured to receive a third input signal.

Abstract: Mechanisms are provided for scheduling a workload in a cloud computing system. A cloud affinity factor (CAF) computer model is trained, via a machine learning process based on a training dataset comprising static characteristics of a workload binary for a workload, and dynamic characteristics corresponding to historical performance data for the workload, such that the trained CAF computer model predicts a performance classification for a given workload binary. The trained CAF computer model processes a new workload to generate a performance classification for the new workload. Cloud affinity factor(s) are generated based on the performance classification for the new workload. Node affinity and dispatch rule(s) are applied to the cloud affinity factor(s) to select one or more nodes of the cloud computing system to which to dispatch the workload. The workload is then scheduled on the selected one or more nodes.

Abstract: Disclosed in the present disclosure is a display module and a display apparatus, wherein the orthographic projection region of the sealant on the display panel is located within the orthographic projection region of the second ink layer on the display panel, and the distance between the edge of the sealant and the edge of the second ink layer is greater than or equal to 0.1 mm, so as to prevent the small molecular oily organic substance precipitated from the sealant from diffusing to the surface of the first ink layer and improve the quality problems such as ungluing, dehiscing of the display module.

Abstract: A method, apparatus or system for processing point cloud information can involve a learned deep entropy model over octrees for lossless compression/decompression of 3D point cloud data, wherein self-supervised compression/decompression involves an adaptive entropy coder operating on a tree-structured conditional entropy model and utilizing information from the local neighborhood as well as the global topology from the tree structure.

Abstract: A backlight module and a display panel are provided. The display panel includes a main body and a backlight module. The backlight module includes a light source and a light guide plate. By accommodating a light-emitting chip of the light source into a groove of the light guide plate, misalignment of the light source and the light guide plate is prevented so that a relative positional relationship between the light source and the light guide plate is always consistent, thereby improving the consistency and stability of the light effect of a lamp port of the backlight module.

Abstract: A display device and an electronic device are provided. The display device has an array substrate, a touch function layer, a backlight module, and a first polarizer. By coating and/or embedding conductive particles on the first adhesive layer, a conductive film layer that is electrically connected to a backlight metal frame can be formed between a backlight film and the touch function layer. A capacitance formed by the backlight metal frame and the touch function layer can be reduced or eliminated, so as to reduce or avoid mechanical vibration of the film.

Abstract: A method for adaptively abstracting a point cloud includes initializing a set of primitives associated with a query shape and a set of query parameters. For each primitive a local point set is accessed using the set of query parameters and the query shape associated with the primitive. For each local point set, using a first neural network, a descriptor vector comprising a sub-vector for a primitive update and a sub-vector for a local descriptor is determined. The set of primitives is updated based on the descriptor vector for each local point set.

Abstract: A method includes generating, using a neural network, a point-level feature vector for each point of a point cloud and a set-level feature vector for the point cloud. A representative position is generated based on the point-level feature vectors and on the set-level feature vector. The representative position and the set-level feature vector is output as a set descriptor.

Abstract: A display device is provided, which includes a display panel including a first surface and a second surface of the display panel disposed opposite to each other; a backlight module including a first surface and a second surface of the backlight module disposed opposite to each other, wherein the first surface of the backlight module is attached to the second surface of the display panel; a circuit board including an end attached to the first surface of the display panel and another end bent to the second surface of the backlight module; and an adhesive layer including a first surface and a second surface disposed opposite to each other, wherein the first surface of the adhesive layer is bonded to a side of the backlight module close to the circuit board, and the second surface of the adhesive layer is bonded to the circuit board.

Abstract: Method, apparatus and system implemented by a neural network-based decoder (NNBD) are disclosed. In one method, the NNBD may obtain or receive a codeword, as a descriptor of an input data representation. A first neural network module may determine, based on at least the codeword and an initial graph, a preliminary reconstruction of the input data representation. The NNBD may determine, based on at least the preliminary reconstruction and the codeword, a modified graph. The first neural network module may determine, based on at least the codeword and the modified graph, a refined reconstruction of the input data representation. The modified graph may indicate topology information associated with the input data representation.

Abstract: A backlight module and a display panel are provided. The display panel includes a display panel main body and a backlight module. The backlight module includes a light guide, a first reflector, and a light source. By arranging the light source in a receiving cavity of the light guide, a width of a lamp socket of the backlight module is reduced, and a light effect of the lamp socket of the backlight module is improved.

Abstract: Systems and methods are described for refining first point cloud data using at least second point cloud data and one or more sets of quantizer shifts. An example point cloud decoding method includes obtaining data representing at least a first point cloud and a second point cloud; obtaining information identifying at least a first set of quantizer shifts associated with the first point cloud; and obtaining refined point cloud data based on at least the first point cloud, the first set of quantizer shifts, and the second point cloud. The obtaining of the refined point cloud data may include performing a subtraction based on at least the first set of quantizer shifts. Corresponding encoding systems and methods are also described.

Abstract: A method of encoding or decoding a video comprising a current picture, a first reference picture, and a weight tensor associated with a trained neural network (NN) model are provided. The method includes generating any number of kernel tensors, input channels and output channels associated with the weight tensor, each kernel tensor being associated with any of: a layer type, an input signal type, and a tree partition type, and each kernel tensor including weight coefficients, generating, for each of the any number of kernel tensors, tree partitions for any of a coding tree unit (CTU), a coding unit (CU), a prediction unit (PU), and a transform unit (TU) according to respective tree partition types associated with each of the any number of kernel tensors, and generating a compressed representation of the trained NN model by compressing and coding the any number of kernel tensors.

Abstract: A display device is provided, which includes a display panel including a first surface and a second surface of the display panel disposed opposite to each other; a backlight module including a first surface and a second surface of the backlight module disposed opposite to each other, wherein the first surface of the backlight module is attached to the second surface of the display panel; a circuit board including an end attached to the first surface of the display panel and another end bent to the second surface of the backlight module; and an adhesive layer including a first surface and a second surface disposed opposite to each other, wherein the first surface of the adhesive layer is bonded to a side of the backlight module close to the circuit board, and the second surface of the adhesive layer is bonded to the circuit board.

Abstract: Systems, methods, and instrumentalities are disclosed for clustering-based quantization for neural network (NN) compression. A distribution of weights in weight tensors in NN layers may be analyzed to identify cluster outliers. Cluster inliers may be coded from cluster outliers, for example, using scalar and/or vector quantization. Weight-rearrangement may rearrange weights for higher dimensional weight tensors into lower dimensional matrices. For example, weight rearrangement may flatten a convolutional kernel into a vector. Correlation between kernels may be preserved, for example, by treating a filter or kernels across a channel as a point. A tensor may be split into multiple subspaces, for example, along an input and/or an output channel. Predictive coding may be performed for a current block of weights or weight matrix based on a reshaped or previously coded block or matrix. Arrangement, inlier, outlier, and/or prediction information may be signaled to a decoder for reconstruction of a compressed NN.