Abstract: Motion contaminated magnetic resonance (MR) images for training an artificial neural network to remove motion artifacts from the MR images are difficult to obtain. Described herein are systems, methods, and instrumentalities for injecting motion artifacts into clean MR images and using the artificially contaminated images for machine learning and neural network training. The motion contaminated MR images may be created based on clean source MR images that are associated with multiple physiological cycles of a scanned object, and by deriving MR data segments for the multiple physiological cycles based on the source MR images. The MR data segments thus derived may be combined to obtain a simulated MR data set, from which one or more target MR images may be generated to exhibit a motion artifact. The motion artifact may be created by manipulating the source MR images and/or controlling the manner in which the MR data set or the target MR images are generated.

Abstract: Disclosed is an unmanned aerial vehicle (UAV)-aided over-the-air computing system based on full-duplex relay and a trajectory and power optimization method thereof. The UAV-aided over-the-air computing system adopts the UAV as a full-duplex relay for data fusing and forwarding. The method of the application aims at minimizing an average mean square error of over-the-air computing, and solves an optimization problem under constraints of sensor transmitting power, information transmission rate, UAV trajectory and denoising factor. For an overall joint optimization problem, each optimization variable is determined one by one by an alternative optimization method according to the high coupling of optimization variables.

Abstract: A non-invasive time domain reflection probe calibration method includes: using different volume ratio of ethanol and deionized water mixed solution to calculate a test target's medium weight coefficient and waveguide length of the non-invasive time domain reflection probes; using different concentrations of NaCl solutions to calibrate a waveguide geometric dimensioning of the non-invasive time domain reflection probes; preparing compacted soil samples with known different moisture contents and densities, and calibrating a correlation parameter of compacted soil samples' dielectric constant and conductivity with moisture content and density. The method not only determines the sensitivity of the test target medium of the non-invasive time domain reflection probes, but also obtains the waveguide length and geometric dimensioning of the probe, and realizes an accurate test of moisture content and density of the soil.

Abstract: An anatomy-aware contouring editing method includes receiving an image, wherein the image represents an anatomically recognizable structure; identifying a first image segment representing part of the anatomically recognizable structure; annotating the first image segment to generate a label of the part; drawing a contour along a boundary of the part; receiving a first input from a user device indicative of a region of contour failure, wherein the region of contour failure includes a portion of a contour that requires editing; editing the contour for generating an edited contour based on the first input and anatomical information; and updating another contour of another part of the anatomically recognizable structure based on the edited contour, wherein the another part is anatomically related to the part.

Abstract: A computer-implemented method for local arrangement of remote deployment is provided according to embodiments of the present disclosure. In this method, a starting request to connect with a remote virtualization entity proxy can be received. A network tunnel can be initiated between a local system and the remote virtualization entity proxy. Then, at least one component in the remote virtualization entity proxy can be arranged into a local virtualization entity in the local system via the network tunnel.

Abstract: Disclosed herein are systems, methods, and instrumentalities associated with reconstructing magnetic resonance (MR) images based on multi-slice, under-sampled MRI data (e.g., k-space data). The multi-slice MRI data may be acquired using a simultaneous multi-slice (SMS) technique and MRI information associated with multiple MRI slices may be entangled in the multi-slice MRI data. A neural network may be trained and used to disentangle the MRI information and reconstruct MRI images for the different slices. A data consistency component may be used to estimate k-space data based on estimates made by the neural network, from which respective MRI images associated with multiple MRI slices may be obtained by applying a Fourier transform to the k-space data.

Abstract: A 3D anatomical model of one or more blood vessels of a patient may be obtained using CT angiography, while a 2D image of the blood vessels may be obtained based on fluoroscopy. The 3D model may be registered with the 2D image based on a contrast injection site identified on the 3D model and/or in the 2D image. A fused image may then be created to depict the overlaid 3D model and 2D image, for example, on a monitor or through a virtual reality headset. The injection site may be determined automatically or based on a user input that may include a bounding box drawn around the injection site on the 3D model, a selection of an automatically segmented area in the 3D model, etc.

Abstract: Digital breast tomosynthesis (DBT) may provide richer information than full-field digital mammography (FFDM). DBT data such as DBT slices may be processed based on deep learning techniques such as using a neural network, and the DBT slices may be divided into groups and a pre-determined number of representative images may be derived based on the grouping. The neural network may be configured to process the representative images to predict the presence or non-presence of a breast disease such as breast cancer.

Abstract: An adaptive control method and system for an upper limb rehabilitation robot based on a game theory and surface Electromyography (sEMG) is disclosed. A movement trajectory that a robot is controlled to run within a training time is designed during subject operation. An sEMG-based Back Propagation Neural Network (BPNN) muscle force estimation model establishes a nonlinear dynamic relationship between an sEMG signal and end force by constructing a three-layer neural network. A human-computer interaction system is analyzed by the game theory principle, and a role of the robot is deduced. The control rate between the robot and a subject is updated by Nash equilibrium, and adaptive weight factors of the robot and the subject are determined. The robot adaptively adjusts the training mode thereof according to a movement intention of the subject during operation and a weight coefficient obtained by the game theory principle.

Abstract: The present invention relates to the field of pharmaceutical and chemical engineering, and specifically relates to a weakly acidic microenvironment-sensitive aptamer for tumors, a triptolide conjugate. The conjugate is formed by conjugation between the 14-position hydroxyl group of triptolide and the aptamer via an acetal ester linking bond, which is an acid-sensitive linking bond with a cleavage condition of (pH=3.5-6.5), which is much less pH-sensitive and is more likely to cleave under the tumor microenvironment. Based on the characteristics of the aptamer targeting the highly expressed proteins on the membrane surface of tumor cells, the conjugate delivered triptolide targeted to tumor cells and mediated endocytosis to reach the lysosome; based on the characteristics of the acidic environment of lysosomes, the acetal ester linking bond released intact triptolide in the lysosomal acidic environment, targeting and killing of tumor cells.

Abstract: Mammography data such as DBT and/or FFDM images may be processed using deep learning based techniques, but labeled training data that may facilitate the learning may be difficult to obtained. Described herein are systems, methods, and instrumentalities associated with automatically generating and/or augmenting labeled mammography training data, and training a deep learn model based on the auto-generated/augmented data for detecting a breast disease (e.g., breast cancer) in a mammography image.

Abstract: An energy Internet system, an energy routing conversion device, and an energy control method, relating to a field of energy information. An alternating-current (AC) side energy routing conversion device of the energy Internet system includes a plurality of first route ports, and a direct-current (DC) side energy routing conversion device includes a plurality of second route ports, where each second route port is connected to a corresponding first route port by means of a corresponding DC busbar. A plurality of energy devices are connected to a DC busbar by means of corresponding first AC/DC converters or first DC converters. The AC side energy routing conversion device and the DC side energy routing conversion device collect energy information of the energy devices and adjust energy of the energy devices on a basis of energy balance constraint conditions.

Abstract: Aspects are provided for dynamic resource sharing between V2V and I2V communications. A wireless device selects resources from a shared resource pool in frequency and time. The shared resource pool is shared for I2V communication and communication over a PC5 interface originating from a User Equipment (UE). The wireless device identifies a first priority level for communication from a set of priority levels for I2V communication and UE originated communication. The set of priority levels may comprise at least one priority level unique to the I2V communication.

Abstract: For detecting motion in MR imaging, a regression model, such as a convolutional neural network, is machine trained. To generalize to MR imagers, MR contrasts, or other differences in MR image generation, the regression model is trained adversarially. The discriminator for adversarial training discriminates between classes of the variation source (e.g., type of MR imager or type of contrast) based on values of features learned in the regression model for detecting motion. By adversarial training, the regression model learns features that are less susceptible or invariant to variation in image source.

Abstract: The composition includes a vinyl-substituted polysiloxane having at least two vinyl groups, a hydrosilylation catalyst, a hydrosilyl-substituted polysiloxane having at least two silicon-hydride groups, and a phosphorous-containing flame retardant encapsulated in a crosslinked, nitrogen-containing polymer. The composition may be a two-part composition including a first part and a second part. The first part includes a vinyl-substituted polysiloxane, a hydrosilylation catalyst, and a phosphorous-containing flame retardant encapsulated in a crosslinked, nitrogen-containing polymer. The second part includes a second vinyl-substituted polysiloxane and a hydrosilyl-substituted polysiloxane. A battery module including a plurality of battery cells and the composition at least partially encasing the plurality of battery cells is also disclosed.

Abstract: A method for preparing aluminum foam sandwich material by rotating friction extrusion and electromagnetic pulse hybrid process includes: step 1: preparing the filler; step 2: processing the filler to prepare a plurality of preforms; step 3: clamping and fixing the plurality of preforms to form a preform assembly; step 4: welding the panel on the surface of the preform assembly to form an non-foaming sandwich material; step 5: heating and foaming the non-foaming sandwich material through a foaming mold; step 6: insulating the foaming mold after completion of foaming; injecting cooling water into the foaming mold after completion of insulation to maintain pressure and shape, forming the aluminum foam sandwich material of the required shape. The aluminum foam sandwich material produced by this method has good interface bonding, no adverse interface reaction, high bending resistance, impact resistance, and excellent sound absorption and insulation properties.

Abstract: The present disclosure relates to a conveying roller for conveying a cell pole piece, the cell pole piece comprising a main body and pole tabs, the main body comprising a bearing area and a transition area, each of the pole tabs comprising a root portion connected to the transition area, a middle section and a top portion, and the conveying roller comprising: a central axis, a first end face and a second end face disposed opposite to each other along the central axis, a transmission portion and an avoidance position provided between the first end face and the second end face, wherein the transmission portion is rotatable around the central axis, the bearing area is contactable with the transmission portion, so that the transmission portion applies a transmission friction force to the cell pole piece, and the avoidance position is capable of avoiding the transition area and the pole tabs.

Abstract: The present disclosure relates to a control method of a virtual object, a control apparatus, a device and a medium. The method displays a target virtual scene in a target interactive interface, under the condition that there is a target virtual object in the plurality of virtual objects, displays a target control, the target virtual object being a virtual object controllable by the virtual subject in a non-contact manner; in response to receiving a trigger operation on the target control, causes the virtual subject to perform non-contact control on the target virtual object according to a control mode corresponding to the target control, wherein the target virtual scene includes a plurality of virtual objects and a virtual subject controlled by a user.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a network node may transmit, and a user equipment (UE) may receive, signaling that indicates at least a first random access channel (RACH) occasion (RO) partition and a second RO partition. The first RO partition may be associated with different uplink transmission capabilities than the second RO partition. The UE may select an RO in the first RO partition or the second RO partition based at least in part on a metric that relates to an uplink transmission capability of the UE. The UE may transmit, and the network node may receive, a preamble in the selected RO to initiate a RACH procedure. Numerous other aspects are described.

Abstract: Container data sharing is provided. A second container of a cluster of containers is started to process a service request in response to detecting a failure of a first container processing the service request. The service request and data generated by the first container that failed stored on a physical external memory device is accessed. The service request and the data generated by the first container that failed is loaded on the second container from the physical external memory device via a dedicated hardware link for high-speed container failure recovery.