Abstract: Provided are an imaging method and system for residual stress of a basin insulator and a method for preparing a test block. The imaging method includes cutting and preparing a standard industrial sample of a basin insulator and testing the acoustoelastic coefficient of the standard industrial sample; then obtaining the residual stress data of the basin insulator and obtaining the spatial point sound velocity distribution of the basin insulator; finally, obtaining a stress distribution cloud map of the basin insulator by calculation of the attribute value and the coordinate data of a to-be-measured location, and performing reliability verification based on the residual stress data.

Abstract: A comic image generating method, a computer device and a storage medium, wherein the method includes: acquiring target objects of a plurality of categories in a comic storyboard, wherein the plurality of categories at least include a character category, a scene category and a prop category; determining, for the target object of each category, a target image matching the target object according to an object level of the target object, wherein the object level is determined according to a degree of importance of the target object, and target images corresponding to the target objects with different object levels are determined through different image determination modes; and combining the target images matching the target objects according to image layer levels corresponding to the plurality of categories, to obtain a comic image corresponding to the comic storyboard.

Abstract: A method of generating a comic image, a computer device and a storage medium are provided. The method includes: acquiring a target novel to be used to generate a comic; determining keyword information corresponding to comic storyboards that correspond to the target novel in a plurality of comic image generation dimensions according to a content of the target novel; with respect to any comic storyboard of the comic storyboards, determining target model input information corresponding to the comic storyboard according to a mapping relationship library between dimension keywords and model input information, and the keyword information of the comic storyboards in the comic image generation dimensions, wherein the dimension keywords include a keyword that has been determined in any comic image generation dimension; and using an artificial intelligence model to generate a comic image corresponding to the comic storyboard according to the target model input information.

Abstract: The present disclosure provides a comic image generation method and apparatus, a computer device, and a storage medium, and the method includes: acquiring pose text information corresponding to a comic storyboard, the pose text information being used for describing target action poses of at least one target object; determining a pose assistance image corresponding to the comic storyboard according to the pose text information, reference action poses of a reference object in the pose assistance image matching the target action poses; and generating comic images corresponding to the comic storyboard using an artificial intelligence model according to the pose text information and the pose assistance image, target objects in the comic images having the target action poses.

Abstract: A zero calibration method includes: adding, based on a first forward kinematics model of a robotic arm of a robot, zero deviations of each joint to form a second forward kinematics model, and simultaneously solving the second forward kinematics model and the first forward kinematics model to obtain an end deviation function; sending target end pose instructions to the robotic arm in a current zero point situation, and acquiring a spatial deviation of an actual position of an end; inputting position information of each joint angle and the spatial deviation, after each stop of motion of the end, into the end deviation function, and performing phase shifting to obtain an objective optimization function; and solving the objective optimization function to obtain a zero deviation value.

Abstract: An optical communication method and system with high spectral efficiency and low power consumption based on joint channel coding modulation relates to the technical field of high-speed fiber communication. The method includes a data acquisition step, a symbol multiplexing joint channel coding modulation step, a signal optical communication step, a channel equalization step, and a symbol demultiplexing step. The optical communication method and system improves the problems of relative independence of forward error correction channel coding (FEC) and high order modulation function modules, long code length dependence of FEC, limited spectral efficiency promotion under the limitation of fiber nonlinear effect, and high FEC decoding latency and power consumption in optical communication system. It is beneficial to improving the spectral efficiency and capacity of a coherent optical communication system and optimizing the system latency and power consumption.

Abstract: Provided are an imaging method and system for residual stress of a basin insulator and a method for preparing a test block. The imaging method includes cutting and preparing a standard industrial sample of a basin insulator and testing the acoustoelastic coefficient of the standard industrial sample; then obtaining the residual stress data of the basin insulator and obtaining the spatial point sound velocity distribution of the basin insulator; finally, obtaining a stress distribution cloud map of the basin insulator by calculation of the attribute value and the coordinate data of a to-be-measured location, and performing reliability verification based on the residual stress data.

Abstract: Provided are antibodies that specifically bind to Programmed Death-1 (PD1, Pdcd-1, or CD279) and inhibit PD1-mediated cellular signaling and activities in immune cells, antibodies binding to a set of amino acid residues required for its ligand binding, and uses of these antibodies to treat or diagnose cancer, infectious diseases or other pathological disorders modulated by PD1-mediated functions.

Abstract: A method and an apparatus for generating information based on a FIFO memory, a device and a medium. In the method, a write credit score and a read credit score of a current FIFO memory are determined by a total capacity of the FIFO memory, and a read address, a write address, a read data enable signal value and a write data enable signal value of the current FIFO memory; and the write credit score represents the number of data sets that can be written into the FIFO memory normally; and the read credit score represents the number of data sets that can be read from the FIFO memory normally; and after sending the write credit score and the read credit score to a preceding-stage device, the preceding-stage device read and write data according to the write credit score and the read credit score.

Abstract: A method for adjusting random write performance, an electronic device, and a storage medium are provided. The method includes: obtaining a remaining space of a target module of a hard drive, and performing balancing processing on a storage unit of the remaining space; calculating a quantity of data frames of each storage block in the storage unit based on a balancing processing result to obtain a first data set; performing convergence processing on the first data set to obtain a second data set; and calculating Input/Output Operations Per Second (IOPS) of the hard drive based on the second data set, and performing write arbitration adjustment on the IOPS of the hard drive.

Abstract: This disclosure discloses a method and system for predicting disease quantification parameters for an anatomical structure. The method includes extracting a centerline structure based on a medical image. The method further includes predicting the disease quantification parameter for each sampling point on the extracted centerline structure by using a GNN, with each node corresponds to a sampling point on the extracted centerline structure and each edge corresponds to a spatial constraint relationship between the sampling points. For each node, a local feature is extracted based on the image patch for the corresponding sampling point by using a local feature encoder, and a global feature is extracted by using a global feature encoder based on a set of image patches for a set of sampling points, which include the corresponding sampling point and have a spatial constraint relationship defined by the centerline structure.

Abstract: The present disclosure relates to a method and a system for generating anatomical labels of an anatomical structure. The method includes receiving an anatomical structure with an extracted centerline, or a medical image containing the anatomical structure with the extracted centerline; and predicting the anatomical labels of the anatomical structure based on the centerline of the anatomical structure, by utilizing a trained deep learning network. The deep learning network includes a branched network, a Graph Neural Network, a Recurrent Neural Network and a Probability Graph Model, which are connected sequentially in series. The branched network includes at least two branch networks in parallel. The method in the disclosure can automatically generate the anatomical labels of the whole anatomical structure in medical image end to end and provide high prediction accuracy and reliability.

Abstract: The present disclosure relates to a training method and a training system for training a learning network for medical image analysis. The training method includes: acquiring an original training data set for a learning network with a predetermined structure; performing, by a processor, a pre-training on the learning network using the original training data set to obtain a pre-trained learning network; evaluating, by the processor, the pre-trained learning network to determine whether the pre-trained learning network has an evaluation defect; when the pre-trained learning network has the evaluation defect, performing, by the processor, a data augmentation on the original training data set for the existing evaluation defect; and performing, by the processor, a refined training on the pre-trained learning network using a data augmented training data set.

Abstract: Embodiments of the disclosure provide systems and methods for analyzing a medical image containing a vessel structure using a sequential model. An exemplary system includes a communication interface configured to receive the medical image and the sequential model. The sequential model includes a vessel extraction sub-model and a lesion analysis sub-model. The vessel extraction sub-model and the lesion analysis sub-model are independently or jointly trained. The exemplary system also includes at least one processor configured to apply the vessel extraction sub-model on the received medical image to extract location information of the vessel structure. The at least one processor also applies the lesion analysis sub-model on the received medical image and the location information extracted by the vessel extraction sub-model to obtain a lesion analysis result of the vessel structure. The at least one processor further outputs the lesion analysis result of the vessel structure.

Abstract: Embodiments of the disclosure provide methods and systems for multi-modality joint analysis of a plurality of vascular images. The exemplary system may include a communication interface configured to receive the plurality of vascular images acquired using a plurality of imaging modalities. The system may further include at least one processor, configured to extract a plurality of vessel models for a vessel of interest from the plurality of vascular images. The plurality of vessel models are associated with the plurality of imaging modalities, respectively. The at least one processor is also configured to fuse the plurality of vessel models associated with the plurality of imaging modalities to generate a fused model for the vessel of interest. The at least one processor is further configured to provide a diagnostic analysis result based on the fused model of the vessel of interest.

Abstract: An array substrate and a display panel are provided. Pixel units of the array substrate include a thin film transistor region, pixel electrode regions, thin film transistors disposed in the thin film transistor region, and pixel electrodes disposed in the pixel electrode regions. The pixel electrode is electrically connected to the thin film transistor. Meanwhile, a shielding member is further disposed in the thin film transistor region, and an interval between the shielding member and the pixel electrode in an extending direction of data lines is a first threshold value.

Abstract: The present disclosure provides a pixel unit, wherein a first sub-pixel electrode trunk, a second sub-pixel electrode trunk, and a sub-pixel frame electrode divide a sub-pixel area into a first partition, a second partition, a third partition, and a fourth partition; the fourth partition is provided with a fourth sub-pixel electrode branch, the fourth partition is located in a lower right area of the sub-pixel area, and an included angle between the fourth sub-pixel electrode branch and a left side of a lower frame electrode of the sub-pixel frame electrode is an obtuse angle.

Abstract: A recessed ceiling lamp and an inductor plug thereof belong to the technical field of lamps. The inductor plug includes a left end plate, an intermediate plate, and a right end plate. The intermediate plate is clamped between the left end plate and the right end plate, and integrally formed with the left end plate and the right end plate as an upside-down boat-shaped structure. An accommodating opening is formed in the intermediate plate. The left end plate is configured to be connected to a profile. The right end plate is configured to be docked with an end of a diffusing cover. An inductor to be mounted is connected to the intermediate plate through the accommodating opening.

Abstract: Embodiments of the disclosure provide methods and systems for joint abnormality detection and physiological condition estimation from a medical image. The exemplary method may include receiving, by at least one processor, the medical image acquired by an image acquisition device. The medical image includes an anatomical structure. The method may further include applying, by the at least one processor, a joint learning model to determine an abnormality condition and a physiological parameter of the anatomical structure jointly based on the medical image. The joint learning model satisfies a predetermined constraint relationship between the abnormality condition and the physiological parameter.

Abstract: The present disclosure provides a method, a device, and a non-transitory computer-readable storage medium for detecting a medical condition of an organ. The method includes obtaining 2D image sequences of the organ in a plurality of different directions and applying a plurality of classification branches to the 2D image sequences. Each classification branch receives a 2D image sequence of one direction and provides a classification result with respect to that direction. Each classification branch includes a convolutional neural network configured to extract first image features from the corresponding 2D image sequence and a recurrent neural network configured to extract second image features from the first image features. The method further includes fusing the classification results provided by the plurality of classification branches for detecting the medical condition.