Abstract: The present application is applicable to the technical field of muscle oxygen saturation detection, and provides a muscle oxygen saturation detection method, and a muscle oxygen saturation recovery method and system. The muscle oxygen saturation detection method is applied to a muscle oxygen saturation detection device. The present application combines pulse electrical stimulation for relieving the muscle fatigue and improving the muscle activity function with muscle oxygen saturation detection, and automatically triggers the turning-on and turning-off of electrical stimulation with the muscle oxygen saturation detection data of a wearer to form a closed-loop muscle function detection and stimulation system with feedback.

Abstract: An image feature visualization method and apparatus, and an electronic device during model training, inputs the real training data with positive samples into a mapping generator to obtain fictitious training data with negative samples. The mapping generator includes a mapping module configured to learn a key feature map that distinguishes the real training data with positive samples/negative samples, and the fictitious training data with negative samples is generated based on the real training data with positive samples and the key feature map. The training data with negative samples is input into a discriminator to obtain a discrimination result. An optimizer optimizes the mapping generator and the discriminator until training is completed. During model application, a target image that is to be processed is input into the mapping generator, and the mapper in the mapping generator extracts features of the target image.

Abstract: A method for preparing a flexible electrode is provided. The method comprises sequentially forming a flexible base layer and an intermediate conductive layer on a carrier plate; treating an elastomeric template having an electrode pattern with an acid, followed by transferring and printing the electrode pattern onto the intermediate conductive layer to form an electrode inducing layer; forming a titanium dioxide-polydopamine composite layer in a gap of the electrode inducing layer; forming a platinum electrode layer on the titanium dioxide-polydopamine composite layer; removing the carrier plate. The invention solves the problems of slow formation of a polydopamine film and slow formation of a platinum electrode layer. A flexible electrode is further provided.

Abstract: The present disclosure discloses a method for predicting the battery performance based on a combination of material parameters of a battery pulping process, including obtaining a target prediction model; and obtaining a combination of material parameters to be predicted corresponding to the battery pulping process, and inputting the combination of the material parameters to be predicted into the target prediction model to obtain a target battery performance level corresponding to the combination of the material parameters to be predicted. The method of the present disclosure adopts a mathematical model method instead of manual testing, can quickly predict battery performance levels corresponding to different combinations of material parameters, and solves the problem that in the prior art, it is necessary to conduct separate tests for different input ratios of various materials to determine the impact of different material ratios on the battery performance.

Abstract: A multi-row ultrasonic imaging apparatus and an ultrasonic imaging instrument are disclosed. The multi-row ultrasonic imaging apparatus includes a housing, and a first ultrasonic transducer, a second ultrasonic transducer, and an adjustment mechanism that are installed in the housing. Ultrasonic waves emitted by the first ultrasonic transducer and the second ultrasonic transducer can intersect to form a confocal point. At least one of the first ultrasonic transducer and the second ultrasonic transducer is connected to the adjustment mechanism to move relative to the housing under the action of the adjustment mechanism, so as to adjust the position of the confocal point.

Abstract: Provided is the use of two-dimensional nanomaterials in the inhibition of a coronavirus, and specifically disclosed is the use of the two-dimensional nanomaterials in the preparation of a medicament for treating or preventing diseases caused by a coronavirus or of a material for adhering to or inhibiting the coronavirus. The two-dimensional nanomaterial is selected from the group consisting of copper indium thiophosphate (CIPS) nanosheet, graphene oxide nanosheet, molybdenum disulfide nanosheet, black phosphorus nanosheet and mixtures thereof. The coronavirus is selected from one of HCoV-229E, HCoV-OC43, HCoV-NL63, HCoV-HKU1, SARS-CoV, SARS-CoV2 or MERS-CoV. The diseases caused by the coronavirus are diseases caused by coronavirus infection. The material has the advantages of being simple to prepare, having a high biological safety and an excellent effect.

Abstract: A magnetic resonance imaging method includes: obtaining three-dimensional under-sampling data of a target object based on a first three-dimensional magnetic resonance imaging sequence; obtaining a three-dimensional point spread function based on the three-dimensional under-sampling data or a two-dimensional mapping data of the target object; obtaining a sensitivity map of the target object based on the data collected by three-dimensional low-resolution complete sampling; performing imaging reconstruction to the three-dimensional under-sampling data based on the three-dimensional point spread function and the sensitivity map to obtain a reconstructed magnetic resonance image. The first three-dimensional magnetic resonance imaging sequence has a first sinusoidal gradient field on a phase direction and a second sinusoidal gradient field on a layer selection direction. 0-order moments of the first and the second three-dimensional magnetic resonance imaging sequences are 0.

Abstract: An apriori guidance network for multitask medical image synthesis is provided. The apriori guidance network includes a generator and a discriminator, wherein the generator includes an apriori guidance module configured to convert an input feature map into a target modal image pointing to a target domain according to an apriori feature, and the apriori feature is a deep feature of the target modal image. The generator is configured to generate a corresponding target domain image by taking the apriori feature of the target modal image and source modal image data as an input. The discriminator is configured to discriminate an authenticity of the target domain image outputted by the generator.

Abstract: Disclosed are a process parasitism-based branch prediction method and device for serverless computing, an electronic device, and a readable storage medium. The method includes: receiving a calling request of a user for a target function; when capacity expansion is required, scheduling a container executing the target function to a new server that has not executed the target function in a preset period of time, wherein a parasitic process is pre-added to a base image of the container; triggering the parasitic process when the container is initialized on the new server, the parasitic process being used for initiating a system call, and triggering a system kernel to select a target template function according to the type of the target function and copying the target template function N times; using execution data of the copied N target template functions as training data to train a branch predictor on the new server.

Abstract: The invention relates to a method for constructing an obligate anaerobic Salmonella strain, the obligate anaerobic Salmonella strain constructed by using said method, and the use thereof in tumor therapy.

Abstract: A low-dose PET image restoration method and system, a device, and a medium are provided. The method includes: S1, performing blocking processing on a training image comprising a low-dose PET image, an MR image, and a standard-dose PET image to obtain a first patch, and performing first preprocessing on the first patch to obtain a second patch; S2, obtaining, according to the second patch, a first joint dictionary by means of sparse coding and dictionary updating; and S3, restoring the low-dose PET image to a restored image of the standard-dose PET image according to the first joint dictionary.

Abstract: The present application provides an image-driven brain atlas construction method and apparatus, a device and a storage medium, and involves in the field of medical imaging technologies. The method includes: acquiring a node feature matrix, where the node feature matrix includes time sequences of multiple nodes of a brain; performing hypergraph data structure transformation on the node feature matrix to acquire a first hypergraph incidence matrix; inputting the first hypergraph incidence matrix and the node feature matrix into a trained hypergraph transition matrix generator for processing to output and acquire a first hypergraph transition matrix, where the first hypergraph transition matrix characterizes a constructed multi-modal brain atlas. The technical solution provided by the present application can construct the multi-modal brain atlas, and this multi-modal brain connection structure can express more feature information.

Abstract: A method for training a dialog generation model includes: acquiring a dialog data set, and encoding a post in the dialog data set by using an encoder in the dialog generation model to obtain an encoded representation of the post; fusing, by using a decoder in the dialog generation model, the encoded representation of the post and knowledge information corresponding to the post that is obtained from a knowledge base question answering model through transfer learning to obtain a predicted response corresponding to the post; determining a value of a loss function of the dialog generation model based on the predicted response and the annotated response that correspond to the post; and updating a model parameter of the dialog generation model based on the value of the loss function. A method, an apparatus, a device, and a computer storage medium for generating a dialog are also provided.

Abstract: Provided are a method and device for magnetic resonance parameter imaging, medical equipment, and a storage medium. The method comprises: performing acceleration sampling with respect to an image to be reconstructed of an observation target in a preset parameter direction to acquire K-space data corresponding to the image to be reconstructed, calculating, on the basis of the K-space data and of a parameter relaxation model, a parameter value and a compensation coefficient of the image to be reconstructed, generating, on the basis of the compensation coefficient, a compensation image corresponding to the image to be reconstructed, calculating, on the basis of the compensation image, respectively a low-rank part and a sparse part of the image to be reconstructed so as to update the compensation image.

Abstract: A method, an apparatus, a device, and a storage medium for extracting a cardiovascular vessel from a CTA image, the method including the steps of: performing erosion operation and dilation operation on image data successively via a preset structural element to obtain a structure mask; performing a slice-by-slice transformation on the plane of section images of the structural mask to acquire the first ascending aortic structure in the structural mask, and acquiring an aortic center position and an aortic radius in the last slice of the plane of section image of the said structural mask; establishing a binarized sphere structure according to the aortic center position and the aortic radius, and synthesizing a second ascending aorta structure by combining the first ascending aorta structure with the structure mask and the binarized sphere structure.

Abstract: The present application is applicable to the field of medical imaging technologies, and provides an image-driven brain atlas construction method and apparatus, a device and a storage medium. The method includes: acquiring multi-modal data of a brain to be predicted, where the multi-modal data is acquired according to image data collected when the brain is under at least three different modalities; inputting the multi-modal data into a preset fusion network for processing to output and acquire feature parameters of the brain; where the processing of the multi-modal data by the fusion network includes: extracting a non-Euclidean spacial feature and an Euclidean spacial feature of the multi-modal data, and performing hypergraph fusion on the non-Euclidean spacial feature and the Euclidean spacial feature to acquire the feature parameters, where the feature parameters are used to characterize a brain connection matrix and/or a disease category of the brain.

Abstract: A method and a device for a three-dimensional reconstruction of brain structure, and terminal equipment. The method includes steps of: obtaining a 2D image of a brain, inputting the 2D image of the brain into a 3D brain point-cloud reconstruction model that has been trained to be processed, and outputting a 3D point-cloud of the brain. The 3D brain point-cloud reconstruction model includes a ResNet encoder and a graphic convolutional neural network. The ResNet encoder is configured to extract a coding feature vector of the 2D image of the brain, and the graphic convolutional neural network is configured to construct the 3D point-cloud of the brain according to the coding feature vector.

Abstract: A method and an apparatus for generating time series data based on multi-condition constraints, and a medium are provided. The method include the following: a data repair request from a client is received, the data repair request including to-be-repaired data and condition information; normalization processing is performed on the to-be-repaired data to obtain normalized data, and tensor processing is performed on the condition information to obtain a feature label; a trained data repair model is called to perform repair processing on the normalized data according to the feature label to obtain first repaired data, the data repair model being obtained by training according to sample data, a first sample condition, real sample data and a second sample condition, and the sample data being noise data; and the first repaired data is sent to the client.

Abstract: The present invention discloses a real-time ultrasonic stimulation electric signal recording chip and a preparation method thereof, where the preparation method includes the following steps: S1 manufacturing an interdigital electrode on a piezoelectric substrate to obtain a surface acoustic wave chip, and manufacturing a recording electrode and an electrode lead; S2, manufacturing an insulation protection layer on the chip obtained in the S1, and processing the insulation protection layer to form the recording electrode, so as to obtain a chip combining the interdigital electrode and the recording electrode; S3, preparing a PDMS cavity; and S4, bonding the PDMS cavity prepared in the S3 and the chip obtained in the S2. In the present invention, combining the interdigital electrode generating a surface acoustic wave ultrasound with a multi-channel recording electrode, such that real-time recording of a multi-channel electric signal under ultrasonic stimulation is achieved.

Abstract: The present application provides an ultrasonic wake-up system. The system includes an ultrasonic imaging device, an ultrasound stimulation device, and an ultrasound stimulation effect evaluation device, and acquires an ultrasonic image of a target object through the ultrasonic imaging device, transmits an ultrasound to the target object based on the ultrasonic image through the ultrasound stimulation device, and adjusts the transmitted ultrasound required through the ultrasound stimulation effect evaluation device. Therefore, peripheral nerves are accurately stimulated, an uplink reticular wake-up system is activated, so as to wake up patients with disorders of consciousness.