Abstract: The present disclosure provides method and apparatus for automatically generating motions of an avatar. A message in a session between a user and an electronic conversational agent may be obtained, the avatar being a visual representation of the electronic conversational agent. At least one facial animation and/or body animation may be determined based on at least one part of the message. At least one motion of the avatar may be generated based at least on the facial animation and/or the body animation.

Abstract: The disclosure relates an Al—Mg series aluminum alloy sheet, a preparation method and use thereof. The preparation method includes: step S1, melting and casting the alloy raw materials in sequence to obtain an aluminum alloy ingot; step S2, subjecting the aluminum alloy ingot to a two-stage homogenization treatment so as to obtain a homogenized aluminum alloy ingot; and step S3, subjecting the homogenized aluminum alloy ingot to hot rolling, primary cold rolling, intermediate annealing, final cold rolling, and finished product annealing in sequence to obtain the aluminum alloy sheet.

Abstract: A channel information obtaining method and a communication apparatus are provided. The method includes: a network device sends reference signals to a terminal device by using a plurality of antenna unit groups, where at least two antenna unit groups of the plurality of antenna unit groups belong to one antenna port; and the network device receives first information from the terminal device, where the first information indicates channel information corresponding to the plurality of antenna unit groups, so as to improve accuracy of obtained channel information.

Abstract: A device for on-site detection of soil organic matter, including a pre-processing module, a centrifugal system, a microfluidic chip, and a photoelectric detection module. The pre-processing module is configured to process a soil sample into a soil solution. The centrifugal system is configured to generate a centrifugal force. The microfluidic chip is configured to allow mixing of the soil solution and an extraction solvent for extraction under the centrifugal force to obtain an extract. The photoelectric detection module is configured to detect the extract to determine organic matter content in the soil solution. An on-site detection method and a microfluidic chip are also provided. The microfluidic chip includes a channel layer, a cover layer arranged above the channel layer, and a base plate layer arranged below the channel layer.

Abstract: A multi-port valve includes a valve housing and a valve core. The valve housing comprises a cylindrical main body defining an inner cavity to rotatably accommodate the valve core and a plurality of ports in fluid communication with the inner cavity. The valve core defines a plurality of flow channels, each extending through a sidewall of the valve core to form two opposite open ends. The valve housing is provided with a guider passage, and the plurality of flow channels include a first flow channel, a second flow channel and a third flow channel. The multi-port valve is operable to be switched between a plurality of work modes in response to the valve core rotating to different positions relative to the valve housing. The first flow channel is connected in series with the second flow channel via the guide passage in response to a first work mode of the plurality of work modes.

Abstract: A device for detecting soil nutrients on site, including an extracting grid, an on-site real-time detection assembly and a transfer assembly for transferring a soil extract from the extracting grid to the on-site real-time detection assembly. A soil nutrient detection method using the device and a microfluidic chip are also provided. The microfluidic chip includes a cover plate and a base plate. The base plate includes a soil extract feeding groove, a quantitative feeding groove, a reagent storage groove, and a serpentine groove.

Abstract: Embodiments of the present disclosure provide a method and a device for music play. The method comprises receiving a first operation instruction in a target application for playing music; in response to the first operation instruction, presenting a first interface of the target application, the first interface including an operation control for enhancing a play effect of the music through at least one processing, the processing being used for representing music content in a way more than sound; receiving a second operation instruction for the operation control; processing the music based on the second operation instruction during a process of playing the music.

Abstract: Disclosed are a display substrate, a liquid crystal display panel (100) and a display device. The display substrate (9) includes: a base substrate (1), a plurality of sub-pixels arranged in an array on the base substrate, a plurality of data lines (D) extending in a first direction (X), a plurality of gate lines (G) extending in a second direction (Y), and a common electrode (2) arranged in a minimum area enclosed by the data lines and the gate lines; wherein the minimum area includes two sub-pixels, the common electrode includes a main electrode (21) with strip-shaped which is arranged at the junction of the two sub-pixels and a plurality of branch electrodes (22) with strip-shaped which are symmetrically distributed on two sides of the main electrode, and the extending directions of a part of the plurality of branch electrodes arranged on a same side of the main electrode are identical.

Abstract: The present disclosure provides a method and system for optimizing first-diffraction-order reconstruction of holograms, a device and a medium, and relates to the field of image processing. The method includes: acquiring a target image; determining a target image light field according to the target image; calculating a target diffraction field for the target image light field by performing backward propagation by a set distance; constructing a U-Net network model; and inputting the target diffraction field into a trained U-Net network model to acquire an optimized hologram. The trained U-Net network model is obtained by constructing a U-Net network model and training and optimizing the U-Net network model, thereby continuously improving the quality of the zero-diffraction-order reconstructed image of the initial hologram and finally achieving the effect of optimizing the first-diffraction-order reconstructed image of the hologram.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may establish one or more wireless connections for different subscriptions with a base station. The UE may receive an indication of a temporary mobile subscription identifier (TMSI) from the base station during a registration procedure. The UE may calculate a paging occasion (PO) based on the TMSI and may determine the PO fails to satisfy a threshold timing value. The UE may transmit one or more registration request to trigger additional registration procedures in which base station may transmit a new TMSI. The UE may calculate an updated PO based on the new TMSI. The UE may periodically receive one or more paging messages from the base station in a set of POs based on calculating the updated PO.

Abstract: A computer readable storage medium is provided. When contents of the computer readable storage medium are executed by a processor, multi-photon imaging may be performed on a histopathological section containing tumor environment information, and pathological partitioning of a tumor microenvironment may be further performed through image processing. A value of each collagen feature parameters, such as a morphological feature parameter, an energy feature parameter and a texture feature parameter, may be extracted from a tumor tissue region, an invasive margin (IM) region and a normal tissue (N) region. An inter-region difference and a variation may be calculated according to feature parameters of regions. A collagen feature scoring model may be established. A collagen feature score may be calculated with the collagen feature parameters input to the model.

Abstract: A virtual scene playback method is disclosed, which comprises: receiving a scene playback instruction and determining playback parameters according to the scene playback instruction, wherein the playback parameters include playback space and playback time; querying virtual space information and user model information corresponding to the playback parameters; and generating virtual scene playback content according to the virtual space information and the user model information. The present disclosure can save all the information in the virtual scene and play back the virtual scene corresponding to specific space and time. A virtual scene playback apparatus, an electronic device and a storage medium are also disclosed, which also have the above beneficial effects.

Abstract: Novel methods and systems for adapting a voice cloning synthesizer for a new speaker using real speech data are disclosed. Utterances from one or more target speakers are parameterized and are used to initialize an embedding vector for use with a voice synthesizer, by means of clustering the utterance data and determining the centroid of the data, using a speaker identification neural network, and/or by finding the closest stored embedded vector to the utterance data.

Abstract: A power transformer fault diagnosis method based on a stacked time series network, includes: collecting gas-in-oil data of a transformer in each substation; performing z-score normalization on the collected data to obtain a normalized matrix; dividing the normalized matrix into a training set and a test set in proportion; constructing a stacked time series network based on Xgboost and a bidirectional gated neural network, and inputting the training set and the test set to perform network training; and normalizing real-time collected data to obtain trainable data to predict a fault and update network parameters. The gas-in-oil data is predicted by using Xgboost and a gated neural network, obtains prediction data of a power transformer from two time series networks by using a meta learner, and obtains a fault diagnosis result of the transformer by using a Softmax layer. The neural network has accurate fault diagnosis performance and stable robustness.

Abstract: Described is a method of training a deep-learning-based system for sound source separation. The system comprises a separation stage for frame-wise extraction of representations of sound sources from a representation of an audio signal, and a clustering stage for generating, for each frame, a vector indicative of an assignment permutation of extracted frames of representations of sound sources to respective sound sources. The representation of the audio signal is a waveform-based representation. The separation stage is trained using frame-level permutation invariant training. Further, the clustering stage is trained to generate embedding vectors for the frames of the audio signal that allow to determine estimates of respective assignment permutations between extracted sound signals and labels of sound sources that had been used for the frames. Also described is a method of using the deep-learning-based system for sound source separation.

Abstract: A DC/DC converter fault diagnosis method based on an improved sparrow search algorithm, includes: establishing an simulation module of the converter, selecting a leakage inductance current of a transformer as a diagnosis signal, and collecting diagnosis signal samples under OC faults of different power switching devices of the converter as a sample set; improving a global search ability of a sparrow search algorithm by using a Levy flight strategy; dividing the sample set into a training set and a test set, preliminarily establishing an architecture of a deep belief network, and initializing network parameters; optimizing a quantity of hidden-layer units of the deep belief network by using an improved sparrow search algorithm, to obtain a best quantity of hidden-layer units of the deep belief network; and training an optimized deep belief network obtained based on the improved sparrow search algorithm, and obtaining a fault diagnosis result based on a trained network.

Abstract: A DC/DC converter fault diagnosis method based on an improved sparrow search algorithm, includes: establishing an simulation module of the converter, selecting a leakage inductance current of a transformer as a diagnosis signal, and collecting diagnosis signal samples under OC faults of different power switching devices of the converter as a sample set; improving a global search ability of a sparrow search algorithm by using a Levy flight strategy; dividing the sample set into a training set and a test set, preliminarily establishing an architecture of a deep belief network, and initializing network parameters; optimizing a quantity of hidden-layer units of the deep belief network by using an improved sparrow search algorithm, to obtain a best quantity of hidden-layer units of the deep belief network; and training an optimized deep belief network obtained based on the improved sparrow search algorithm, and obtaining a fault diagnosis result based on a trained network.

Abstract: A method for diagnosing transformer fault based on a deep coupled dense convolutional neural network, includes: obtaining datasets of dissolved gas in oil of a transformer in normal and fault states; expanding the datasets by using an adaptive synthetic oversampling method; performing, in a form of a two-dimensional matrix, feature reconstruction on characteristic gas dissolved in the oil; building a transformer fault diagnosis model based on a deep coupled dense convolutional neural network; and dividing an expanded dataset into a training set and a test set, and taking the two-dimensional matrix as an input of the deep coupled dense convolutional neural network and a set label as an output to train the network to obtain a fault diagnosis model. The present disclosure can resolve a problem that a fault diagnosis accuracy rate of the transformer is low due to insufficient and unbalanced fault samples in the dissolved gas in the oil.

Abstract: The present invention relates to a magnetic navigation-guided tear-away sheath for cardiac conduction bundle pacing, including a sheath body and a joint fixedly connected to a rear end of the sheath body. The sheath body includes a front flexible section and a rear fixed section, and the front flexible section is freely bendable. An outer surface near a head end of the front flexible section is provided with a plurality of pairs of half-ring magnets, two half-ring magnets in each pair of half-ring magnets are symmetrically disposed and form a ring, and a gap is kept between the two half-ring magnets. The head end of the front flexible section is provided with three electrodes uniformly disposed in a circumferential direction, and the three electrodes can be freely combined two by two, to form three electrode pairs used to record and position an intracardiac potential.

Abstract: A system for suppressing noise and enhancing speech and a related method are disclosed. The system trains a neural network model that takes banded energies corresponding to an original noisy waveform and produces a speech value indicating the amount of speech present in each band at each frame. The neural model comprises a feature extraction block that implements some lookahead. The feature extraction block is followed by an encoder with steady down-sampling along the frequency domain forming a contracting path. The encoder is followed by a corresponding decoder with steady up-sampling along the frequency domain forming an expanding path. The decoder receives scaled output feature maps from the encoder at a corresponding level. The decoder is followed by a classification block that generates a speech value indicating an amount of speech present for each frequency band of the plurality of frequency bands at each frame of the plurality of frames.