Abstract: A method for acquiring magnetic resonance (MR) data from a subject with a magnetic resonance imaging (MRI) system includes generating a first pre-saturation RF pulse having a first flip angle for each of at least one slice in the subject, generating a series of first gradient echo sequences following each first pre-saturation RF pulse, and calculating a B0 value for each of the at least one slice. A second pre-saturation RF pulse having a second flip angle is generated for each of the at least one slice in the subject, followed by a series of second gradient echo sequences, and a B1 is calculated for each of the at least one slice based on the first gradient echo sequences and the second gradient echo sequences.

Abstract: An azaquinolinone compound having a structure of the following formula (I) as an enzyme inhibitor for the poly(ADP-ribose)polymerase (PARP) family, and a pharmaceutically acceptable salt, a stereoisomer, a tautomer or an N-oxide drug thereof, a preparation method therefor and the use thereof.

Abstract: A method performed by a processing system in a cellular core network includes receiving, from a session management function of the cellular core network, a query for a policy rule associated with a subscriber who has requested a packet data unit session, querying a charging function of the cellular core network for a charging counter associated with the subscriber, receiving, from the charging function, the charging counter, wherein the charging counter contains a value identifying a service package to which the subscriber is subscribed, determining a rating group associated with the service package, and sending, to the session management function, a set of application identifiers associated with the rating group, wherein each application identifier of the set of application identifiers identifies one software application that is included in the service package.

Abstract: An underwear includes an underwear main body. The underwear main body includes a front piece and a rear piece. The front piece is connected to the rear piece. The front piece is provided with a first cup body and a second cup body. The underwear main body further includes an elastic supporting piece. The front piece includes an inner piece and an outer piece. The inner piece is connected to the outer piece. The elastic supporting piece is disposed between the inner piece and the outer piece. The elastic supporting piece is connected to the inner piece or the outer piece, and a transverse tensile force of the elastic supporting piece is great than a longitudinal tensile force of the elastic supporting piece.

Abstract: A video classification system and method and a neural network training system are provided. The video classification system captures multiple sampled images, encodes first and second images of all sampled images into feature matrices of the sampled images using a convolutional neural network module, and obtains the classification of the videos based on a recurrent neural network module and the feature matrices. The neural network training system captures multiple first sampled images and uses first training samples of all the first sampled images to train the convolutional neural network module and a classification module to obtain multiple parameter values of the convolutional neural network module. The neural network training system trains the recurrent neural network module based on the parameter values and multiple second sampled images.

Abstract: An underwear includes an underwear main body, a first supporting part, and a second supporting part. The underwear main body includes a front piece and a rear piece. The front piece is connected to the rear piece. The front piece is equipped with a first cup body and a second cup body. The first supporting part is connected between the first cup body and one side of the rear piece. The first supporting part is configured for squeezing and retracting an accessory breast towards the first cup body. The second supporting part is connected between the second cup body and an opposite side of the rear piece. The second supporting part is configured for squeezing and retracting another accessory breast towards the second cup body. Therefore, when a user is wearing the underwear, the accessory breasts on both sides of the user's chest can be retracted.

Abstract: To generate data for populating/updating accounting databases based on digitized accounting source documents, access to an entity database comprising identifiers of entities associated with an accounting database and to a digital template library comprising processing templates for processing digitized accounting source documents is provided. Each entity in the entity database is associated with one processing template.

Abstract: To generate data for populating/updating accounting databases based on digitized accounting source documents, access to an entity database comprising identifiers of entities associated with an accounting database and to a digital template library comprising processing templates for processing digitized accounting source documents is provided. Each entity in the entity database is associated with one processing template.

Abstract: Various methods and systems are provided for correcting transmit attenuation of an amplifier of a transmit radio frequency (RF) coil for use in a magnetic resonance imaging (MRI) system.

Abstract: A video classification system and method and a neural network training system are provided. The video classification system captures multiple sampled images, encodes first and second images of all sampled images into feature matrices of the sampled images using a convolutional neural network module, and obtains the classification of the videos based on a recurrent neural network module and the feature matrices. The neural network training system captures multiple first sampled images and uses first training samples of all the first sampled images to train the convolutional neural network module and a classification module to obtain multiple parameter values of the convolutional neural network module. The neural network training system trains the recurrent neural network module based on the parameter values and multiple second sampled images.

Abstract: Various methods and systems are provided for correcting transmit attenuation of an amplifier of a transmit radio frequency (RF) coil for use in a magnetic resonance imaging (MRI) system.

Abstract: Various methods and systems are provided for correcting transmit attenuation of an amplifier of a transmit radio frequency (RF) coil for use in a magnetic resonance imaging (MRI) system. In one example, a method includes setting a reference value of transmit attenuation for an amplifier of a transmit radio frequency (RF) coil, acquiring a two-dimensional B1 field map with the transmit attenuation set at the reference value, determining a mean flip angle from the B1 field map, determining a transmit attenuation correction value based on a prescribed flip angle and the mean flip angle, correcting the reference value of transmit attenuation with the transmit attenuation correction value to obtain a final value of transmit attenuation, and performing an MRI scan with the transmit attenuation set at the value.

Abstract: The present application provides an intelligent cloud traffic control system, which has a traffic data recalling and transmission architecture arranged hierarchically from bottom to top, and which includes: terminal devices, first-level cloud devices, second-level cloud devices, . . . ith-level cloud devices; wherein the ith-level cloud devices include a first cloud device, . . . a jth cloud device; the ith-level cloud devices further include: a first cache cloud, . . . a kth cache cloud arranged corresponding to the jth cloud device; wherein the jth cloud device stores a jth cloud device traffic data set, and the kth cache cloud stores a kth characteristic traffic data set; and data in the kth characteristic traffic data set has a higher priority of being recalled than data in the jth cloud device traffic data set.

Abstract: The present application provides an intelligent cloud traffic control system, which has a traffic data recalling and transmission architecture arranged hierarchically from bottom to top, and which includes: terminal devices, first-level cloud devices, second-level cloud devices, . . . ith-level cloud devices; wherein the ith-level cloud devices include a first cloud device, . . . a jth cloud device; the ith-level cloud devices further include: a first cache cloud, . . . a kth cache cloud arranged corresponding to the jth cloud device; wherein the jth cloud device stores a jth cloud device traffic data set, and the kth cache cloud stores a kth characteristic traffic data set; and data in the kth characteristic traffic data set has a higher priority of being recalled than data in the jth cloud device traffic data set.

Abstract: The present disclosure relates to an intelligent traffic cloud control system; by making full use of technologies such as cloud computing, edge computing, big data, and artificial intelligence, the present disclosure proposes a technical architecture of a cloud-edge-end cooperative road traffic cloud control platform, which can overcome the defects of the technical architecture of existing road traffic operation management and monitoring systems. The highway cloud control platform designed and developed based on this technical architecture can improve the operational efficiency of the road network under the premise of ensuring safety, so that highway users can obtain more timely, effective, and personalized driving and traveling assistance information; moreover, practical applications such as vehicle-road cooperative autonomous driving and other functions are supported.

Abstract: Methods and systems are provided for predicting B1+ field maps from magnetic resonance calibration images using deep neural networks. In an exemplary embodiment a method for magnetic resonance imaging comprises, acquiring a magnetic resonance (MR) calibration image of an anatomical region, mapping the MR calibration image to a transmit field map (B1+ field map) with a trained deep neural network, acquiring a diagnostic MR image of the anatomical region, and correcting inhomogeneities of a transmit field in the diagnostic MR image with the B1+ field map. Further, methods and systems are provided for collecting and processing training data, as well as utilizing the training data to train a deep learning network to predict B1+ field maps from MR calibration images.

Abstract: Methods and systems are provided for predicting B1+ field maps from magnetic resonance calibration images using deep neural networks. In an exemplary embodiment a method for magnetic resonance imaging comprises, acquiring a magnetic resonance (MR) calibration image of an anatomical region, mapping the MR calibration image to a transmit field map (B1+ field map) with a trained deep neural network, acquiring a diagnostic MR image of the anatomical region, and correcting inhomogeneities of a transmit field in the diagnostic MR image with the B1+ field map. Further, methods and systems are provided for collecting and processing training data, as well as utilizing the training data to train a deep learning network to predict B1+ field maps from MR calibration images.

Abstract: Various methods and systems are provided for selecting radio frequency (RF) coil array for magnetic resonance imaging (MRI). In one embodiment, the method comprises grouping the plurality of coil elements into receiving elements groups (REGs) according to REGs information, generating channel sensitivity maps for the plurality of coil elements, generating REG sensitivity maps based on the REGs information and the channel sensitivity maps, selecting one or more REGs based on the REG sensitivity maps and a region of interest (ROI), and scanning the ROI with the coil elements of the one or more selected REGs being activated and the coil elements not in any selected REGs being deactivated. In this way, coil arrays may be automatically selected for improved image quality of the MRI.

Abstract: Various methods and systems are provided for selecting coil elements of a plurality of coil elements of a radio frequency (RF) coil array for use in a magnetic resonance imaging (MRI) system. In one example, a method includes grouping the plurality of coil elements into receive elements groups (REGs) according to REGs information, generating channel sensitivity maps for the plurality of coil elements, generating REG sensitivity maps based on the REGs information and the channel sensitivity maps, labeling each REG as either selectable or not selectable based on the REG sensitivity maps, selecting one or more REGs from the selectable REGs based on the REG sensitivity maps and a region of interest (ROI), and scanning the ROI with the coil elements in the one or more selected REGs being activated and the coil elements not in any selected the other REGs being deactivated.