Abstract: Provided are a keyword extraction method applicable to a Word text, an electronic device, and a computer-readable storage medium. The method includes: acquiring a text and extracting a body of the text; extracting a set number of keywords in the body by a TFIDF algorithm and a set number of keywords in the body by a TextRank algorithm, respectively; acquiring a text name and a text title of the text and segmenting the text name and the text title into words of the text name and words of the text title; constructing text feature vectors of the text and inputting the text feature vectors into a trained keyword extraction model; and extracting a keyword set from the keywords extracted by the TextRank algorithm by using the keyword extraction model to achieve text keyword extraction.

Abstract: Provided is a secondary battery, including: an electrode assembly, a packing bag, an electrode lead and an insulation part; the electrode assembly is housed in the packing bag having a sealing part on edge, and the electrode lead is connected to the electrode assembly and passes through the sealing part. The sealing part includes a main body area, a first step area and a first transition area which are located on same side of the electrode lead along width direction, and the main body area, first transition area and first step area are successively arranged along direction approaching the electrode lead; the insulation part is wrapped around the electrode lead, and has a first portion which is located on a side of the electrode lead close to the main body area along width direction and covered by the first step area on both sides in thickness direction.

Abstract: A method for measuring a gradient field of a nuclear magnetic resonance (NMR) system based on a diffusion effect uses a non-uniform field magnet, an NMR spectrometer, a radio frequency (RF) power amplifier, an RF coil, and a standard quantitative phantom with known apparent diffusion coefficient (ADC) and time constant for decay of transverse magnetization after RF-pulse (T2). A plurality of sets of signals are acquired by an NMR sequence with different diffusion-sensitive gradient durations or different echo spacings and the magnitude of the gradient field is calculated by fitting based on the plurality of sets of signals. The method does not require an additional dedicated magnetic field detection device, has a short measurement time, is easy to use with the NMR system, and is convenient to complete gradient field measurement at the installation site, thereby improving the installation and service efficiency of the NMR system.

Abstract: The invention provides a bioactive substance composition, a serum-free medium comprising the composition and the uses thereof. The bioactive substance composition is used for serum-free medium and/or composition and the preparation thereof; The serum-free medium and/or composition can be used for primary culture and secondary culture of cells and/or tissues. The cells are selected from any one or more of tendon and/or ligament derived cells, chondrocytes, meniscus stem cells, mesenchymal stem cells, skeleton stem cells, and muscle stem cells. The tissue is the musculoskeletal system tissue. The bioactive substance composition and/or serum-free medium and/or the composition can be used to prepare drugs for tissue and/or organ injury treatment; The tissue or organ injury is selected from the tissue or organ injury of the musculoskeletal system.

Abstract: Provided are a text duplicate checking method, an electronic device and a computer-readable storage medium. The method includes storing a fingerprint set and a corresponding text ID in a byte data manner to obtain a fingerprint library; acquiring a target text and creating a target fingerprint; obtaining a comparison fingerprint set from map memories according to the target fingerprint, and calculating a similarity between the target fingerprint and each comparison fingerprint in the comparison fingerprint set separately; and based on a determination result that a number of 1 s in binary values of one similarity is less than or equal to a preset value, querying a text ID corresponding to the one similarity, to implement duplicate checking of the target text.

Abstract: A method for measuring a gradient field of a nuclear magnetic resonance (NMR) system based on a diffusion effect uses a non-uniform field magnet, an NMR spectrometer, a radio frequency (RF) power amplifier, an RF coil, and a standard quantitative phantom with known apparent diffusion coefficient (ADC) and time constant for decay of transverse magnetization after RF-pulse (T2). A plurality of sets of signals are acquired by an NMR sequence with different diffusion-sensitive gradient durations or different echo spacings and the magnitude of the gradient field is calculated by fitting based on the plurality of sets of signals. The method does not require an additional dedicated magnetic field detection device, has a short measurement time, is easy to use with the NMR system, and is convenient to complete gradient field measurement at the installation site, thereby improving the installation and service efficiency of the NMR system.

Abstract: This application provides a method and apparatus for sequence processing, relates to the field of artificial intelligence, and specifically relates to the field of sequence data processing. The method includes: receiving an input sequence (S410); performing self-attention calculation on a first element in the input sequence by using an element included in M windows, to obtain a representation of the first element, where each window includes one element or a plurality of consecutive elements in the input sequence, there is an interval of at least one element between different windows, at least one of the M windows does not include the first element, and M is an integer greater than or equal to 1 (S420); and obtaining, based on the representation of the first element, an output sequence corresponding to the input sequence (S430).

Abstract: A drain programmed read-only memory includes a diffusion region that spans a width of a bitcell and forms a drain of a first transistor and a second transistor. A bit line lead in a metal layer adjacent the diffusion region extends across the width of the bitcell. A first via extends from an upper half of the bit line lead and couples to a drain of the first transistor. Similarly, a second via extends from a lower half of the bit line and couples to a drain of the second transistor.

Abstract: Deep learning based systems, methods, and instrumentalities are described herein for registering images from a same imaging modality and different imaging modalities. Transformation parameters associated with the image registration task are determined using a neural ordinary differential equation (ODE) network that comprises multiple layers, each configured to determine a respective gradient update for the transformation parameters based on a current state of the transformation parameters received by the layer. The gradient updates determined by the multiple ODE layers are then integrated and applied to initial values of the transformation parameters to obtain final parameters for completing the image registration task. The operations of the ODE network may be facilitated by a feature extraction network pre-trained to determine content features shared by the input images.

Abstract: A fitting assembly includes a fitting comprising a housing and a connector assembly arranged within the housing. The connector assembly comprising a hollow interior and configured to be movable between an unactuated position and an actuated position. In the actuated position, the connector assembly is connectable to a pipe receivable within the hollow interior. An adapter coupled to the fitting includes a biasing mechanism configured to bias the connector assembly from the actuated position to the unactuated position.

Abstract: In an embodiment, a computer-implemented method comprises deploying a dual-active database on a first active database site and a second active database site. The first active database site comprises a first group of disks including a first sub-group of disks and a second sub-group of disks respectively corresponding to a third sub-group of disks and a fourth sub-group of disks included in a second group of disks in the second active database site. The method further comprises storing a first set of database logs on the first sub-group of disks while a second set of database logs is being written on the second sub-group of disks. Contents of the second set of database logs are consistent with contents of the first set of database logs and function as a duplication of the first set of database logs.

Abstract: A secondary battery includes a positive electrode, a negative electrode, and an electrolyte. The positive electrode includes a positive-electrode active substance layer, the positive-electrode active substance layer contains a pre-lithiation agent, and a molecular formula of the pre-lithiation agent is LixNiaCu1?a?bMbO2, where 1?x?2, 0<a<1, and 0?b <0.1, and M is selected from one or more of Zn, Sn, Mg, Fe, and Mn. The negative electrode includes a negative-electrode active substance layer including graphite and silicon-containing material. The electrolyte contains fluoroethylene carbonate (FEC). A weight percentage of the pre-lithiation agent in the positive-electrode active substance layer, a weight percentage of silicon content in the negative-electrode active substance layer, and a weight percentage of FEC in the electrolyte satisfy 0.2×WSi?WFEC?7.5%?0.6×WL.

Abstract: Metadata is replicated. For instance, in response to receiving a request for replicating metadata to a target node, information of an index structure associated with the metadata is obtained. The index structure may include terminal nodes for storing the metadata and index nodes for storing index information of the terminal nodes. Next, the metadata from the terminal nodes is extracted based on the information of the index structure. Further, a sequence is generated to be replicated of the metadata. The sequence to be replicated includes items of the metadata, and locations of the items in the sequence to be replicated are determined based on key information corresponding to the items. In addition, the items of the metadata, in the sequence to be replicated, are replicated to the target node. In this way, only the metadata in the index structure is replicated, thereby reducing the data amount of replication.

Abstract: Disclosed herein include systems, devices, and methods for identifying recombinant variants (e.g., gene conversion variants) of genes such as GBA gene and CYP21A2 gene, the copy numbers of recombinant variants, and gene variant status (e.g., carrier, compound heterozygous, or homozygous).

Abstract: Techniques, systems, and devices are described for providing a computational frame for estimating high-dimensional stochastic behaviors. In one exemplary aspect, a method for performing numerical estimation includes receiving a set of measurements of a stochastic behavior. The set of correlated measurements follows a non-standard probability distribution and is non-linearly correlated. Also, a non-linear relationship exists between a set of system variables that describes the stochastic behavior and a corresponding set of measurements. The method includes determining, based on the set of measurements, a numerical model of the stochastic behavior. The numerical model comprises a feature space comprising non-correlated features corresponding to the stochastic behavior. The non-correlated features have a dimensionality of M and the set of measurements has a dimensionality of N, M being smaller than N.

Abstract: For machine training and application of a trained complex-valued machine learning model, an activation function of the machine learning model, such as a neural network, includes a learnable parameter that is complex or defined in a complex domain with two dimensions, such as real and imaginary or magnitude and phase dimensions. The complex learnable parameter is trained for any of various applications, such as MR fingerprinting, other medical imaging, or non-medical uses.

Abstract: An approach is provided for evaluating a performance of a query. A risk of selecting a low performance access path for a query is determined. The risk is determined to exceed a risk threshold. Based on the risk exceeding the risk threshold and using a machine learning optimizer, first costs of access paths for the query are determined. Using a cost-based database optimizer, second costs of the access paths are determined. Using a strong classifier operating on the first costs and the second costs, a final access path for the query is selected from the access paths.

Abstract: Disclosed herein are systems, methods, and instrumentalities associated with reconstructing magnetic resonance (MR) images based on under-sampled MR data. The MR data include 2D or 3D information, and may encompass multiple contrasts and multiple coils. The MR images are reconstructed using deep learning (DL) methods, which may accelerate the scan and/or image generation process. Challenges imposed by the large quantity of the MR data and hardware limitations are overcome by separately reconstructing MR images based on respective subsets of contrasts, coils, and/or readout segments, and then combining the reconstructed MR images to obtain desired multi-contrast results.

Abstract: A method of forming graphene layers is disclosed. The method includes precleaning the substrate with a plasma formed from an argon- and hydrogen-containing gas, followed by forming a graphene layer by exposing the substrate to a microwave plasma to form a graphene layer on the substrate. The microwave plasma comprises hydrocarbon and hydrogen radicals. The substrate is then cooled. A capping layer may also be formed.

Abstract: Neural network based systems, methods, and instrumentalities may be used to remove motion artifacts from magnetic resonance (MR) images. Such a neural network based system may be trained to perform the motion artifact removal tasks without reference (e.g., without using paired motion-contaminated and motion-free MR images). Various training techniques are described herein including one that feeds the neural network with pairs of MR images with different levels of motion contamination and forces the neural network learn to correct the motion contamination by transforming a first image of a contaminated pair into a second image of the contaminated pair. Other neural network training techniques are also described with an aim to reduce the reliance on training data that is difficult to obtain.