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.

Abstract: A manufacturing method for mass production for a tissue or cell microarray, which is characterized in comprising: using a molding device to mold tissue particles, cultivated cells or collected exfoliated cells (such as exfoliated cells from pleural effusion and ascites), forming the tissue particles from blended fresh tissue, tissue fixed by formalin or another solvent (such as alcohol and so on) or a tissue block embedded in paraffin (blended by a tissue blender), implanting the molded tissue or cells cores in a receptor wax or adhering the molded tissue or cells cores onto a metal plate, and then slicing to obtain a tissue or cell microarray.

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: A random write method includes: using a wear-leveling module to scan the number of free blocks and the number of bad blocks in a target super logic unit; using a lookup management module to iteratively update, according to the number of current remaining solid-state disk data frames, the number of historically weighted solid-state disk data frames in a long short-term memory network manner; using dynamic write arbitration to determine an adjustment stage based on the number of historically weighted solid-state disk data frames, and determining the expected number of read and write operations per second based on the adjustment stage; and re-updating the number of historically weighted solid-state disk data frames, and adjusting the actual number of read and write operations per second based on the re-updated number of historically weighted solid-state disk data frames and the expected number of read and write operations per second.

Abstract: A method and a system for calculating tumor neoantigen burden (TNB) are provided. The method includes: step S1: processing a normal sample and a tumor sample, sequencing a specific region and detecting somatic mutations in the sample; step S2: annotating and filtering the somatic mutations, and translating to obtain mutant peptide sequences of a patient; step S3: filtering the mutant peptide sequences to obtain neopeptide sequences based on a proteome of the normal sample; step S4, performing a human leukocyte antigen (HLA) typing analysis based on alignment data of the normal sample to obtain HLA genotypes of the sample; step S5, predicting binding affinities between the neopeptide sequences and the HLA genotypes to obtain specific neoantigens of the sample, and performing a weighted scoring on each of the specific neoantigens and calculating the TNB of the sample.

Abstract: A method and a platform for detecting an immunogenicity of a tumor neoantigen are provided. Specifically, the detection method includes the following steps: culturing human peripheral blood monocytes ex vivo for 13 days, adding an antigenic peptide fragment of human influenza virus and stimulating and activating cytokines, antigenic peptides, and immunoadjuvants during the 13 days, and finally conducting enzyme-linked immunospot (ELISPOT) chromogenic reaction and instrument-based scanning, counting, and analysis to detect the immunogenicity of tumor neoantigen. An application of the detection method and platform in biomedicine is provided. Compared with the prior art, the detection method and platform have advantages and characteristics of a short detection period, high convenience, low consumption of experimental cells, and low detection cost. Therefore, the detection method and platform can be used for ex vivo high-throughput assay for the immunogenicity of the tumor neoantigen.

Abstract: A method for generating a plot based on a state graph is provided. The method includes: displaying an editing interface, the editing interface including candidate state nodes; determining at least two target state nodes in response to receiving a configure operation on the candidate state nodes; receiving a timing relationship establish operation for at least two target state nodes; and displaying a state graph including the at least two target state nodes in the editing interface based on the timing relationship establish operation, the state graph being configured to generate the plot in a virtual scenario by a specified engine.

Abstract: The present disclosure discloses a method for vector reading-writing, a vector-register system, a device and a medium. When a vector-writing instruction is obtained, by using a vector-register controller, a to-be-written-vector address space is converted into a to-be-written-vector-register-file bit address, and, for a nonstandard vector, by using a nonstandard-vector converting unit, after the nonstandard vector is converted into a to-be-written nonstandard vector, and, subsequently, writing is performed, to realize the saving of vector data of any format. When a vector-reading instruction is obtained, by using the vector-register controller, according to the to-be-read width and the to-be-read length, after the to-be-read-vector address space is converted into a to-be-read-vector-register-file bit address, and, subsequently, reading is performed, to realize the reading of vector data of any format.

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 discloses a method for vector reading-writing, a vector-register system, a device and a medium. When a vector-writing instruction is obtained, by using a vector-register controller, a to-be-written-vector address space is converted into a to-be-written-vector-register-file bit address, and, for a nonstandard vector, by using a nonstandard-vector converting unit, after the nonstandard vector is converted into a to-be-written nonstandard vector, and, subsequently, writing is performed, to realize the saving of vector data of any format. When a vector-reading instruction is obtained, by using the vector-register controller, according to the to-be-read width and the to-be-read length, after the to-be-read-vector address space is converted into a to-be-read-vector-register-file bit address, and, subsequently, reading is performed, to realize the reading of vector data of any format.