Abstract: A method for growing bulk boron arsenide (BA) crystals, the method comprising utilizing a seeded chemical vapor transport (CVT) growth mechanism to produce single BAs crystals which are used for further CVT growth, wherein a sparsity of nucleation centers is controlled during the further CVT growth. Also disclosed are bulk BAs crystals produced via the method.

Abstract: Disclosed are a battery and an electronic device, including a housing, a sealing cover, and a battery cell. The housing has an accommodation cavity, and the battery cell is located in the accommodation cavity. The housing is provided with a liquid injection hole. An upper surface of a peripheral edge of the sealing cover is provided with a first step, and the first step divides the sealing cover into a first cover area and a second cover area. The thickness of the second cover area is less than or equal to a thickness of the housing at a seal-welding position with the second cover area. The battery provided in embodiments of the present disclosure has good seal-welding performance, to resolve problems of low battery yields, difficulty in mass production, and failure to achieve expected safety and stability due to poor seal-welding performance.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.

Abstract: Provided are a data processing system and method based on dynamic redundancy heterogeneous encoding, and a device. The method comprises: respectively performing error correction encoding on information to be processed and a processing rule, so as to form encoded information to be processed and an encoded processing rule; processing, by using the encoded processing rule, the encoded information to be processed, so as to obtain response data; and then performing error correction decoding on N pieces of response data, so as to obtain processing result information of the information to be processed.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing neural architecture search for machine learning models. In one aspect, a method comprises receiving training data for a machine learning, generating a plurality of candidate neural networks for performing the machine learning task, wherein each candidate neural network comprises a plurality of instances of a layer block composed of a plurality of layers, for each candidate neural network, selecting a respective type for each of the plurality of layers from a set of layer types that comprises, training the candidate neural network and evaluating performance scores for the trained candidate neural networks as applied to the machine learning task, and determining a final neural network for performing the machine learning task based at least on the performance scores for the candidate neural networks.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech synthesis. The methods, systems, and apparatus include actions of obtaining an audio representation of speech of a target speaker, obtaining input text for which speech is to be synthesized in a voice of the target speaker, generating a speaker vector by providing the audio representation to a speaker encoder engine that is trained to distinguish speakers from one another, generating an audio representation of the input text spoken in the voice of the target speaker by providing the input text and the speaker vector to a spectrogram generation engine that is trained using voices of reference speakers to generate audio representations, and providing the audio representation of the input text spoken in the voice of the target speaker for output.

Abstract: A power device includes a power tool, a mounting plate, a mounting table, a positioning assembly, and a locking assembly. The positioning assembly includes a positioning piece. A positioning space is formed between the positioning piece and the mounting table. An end of the mounting plate is enabled to be inserted into the positioning space so that the mounting plate is pre-positioned. The locking assembly includes a movable piece and a locking piece. The movable piece includes a support position where the mounting plate is supported and an unlocked position where support for the mounting plate is released. The locking piece fixes at least the mounting plate to the mounting table.

Abstract: A food processor and an electric motor for a food processor. The electric motor includes: a stator core having a ring-shaped stator yoke and a plurality of stator teeth provided at an inner peripheral face of the stator yoke, two adjacent stator teeth defining a stator slot there between, the plurality of the stator teeth defining a stator hole coaxial with the stator yoke, and an outer contour of a radial section of the stator yoke being substantially circular and having a maximum radial dimension D; and a rotor core rotatably provided in the stator hole and coaxial with the stator hole, the rotor core having a maximum radial dimension d, in which 0.4?d/D?0.55.

Abstract: A cross-coupling control method for moving beam of gantry machine tool is disclosed, which relates to the technical field of CNC machine tool control. The cross-coupling control method includes: Step 1: establishing a crossbeam dynamics model considering a ram on the crossbeam, and at the same time simplifying the model for an observer design; step 2: realizing a PID control parameter adjustment of motors at both ends in accordance with a method of parameter tuning of a unilateral servo control system; using a servo system with the same control parameters to jointly drive the crossbeam up and down, realizing the synchronous control and realizing PID control parameter tuning for both end motors. The disclosure not only reduces the synchronization error caused by the torsion of the crossbeam, but also solves the synchronization error caused by the asymmetric load on both sides, and improves the system robustness and stability.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-readable storage media, for speech recognition using attention-based sequence-to-sequence models. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A sequence of feature vectors indicative of the acoustic characteristics of the utterance is generated. The sequence of feature vectors is processed using a speech recognition model that has been trained using a loss function that uses a set of speech recognition hypothesis samples, the speech recognition model including an encoder, an attention module, and a decoder. The encoder and decoder each include one or more recurrent neural network layers. A sequence of output vectors representing distributions over a predetermined set of linguistic units is obtained. A transcription for the utterance is obtained based on the sequence of output vectors. Data indicating the transcription of the utterance is provided.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for machine translation using neural networks. In some implementations, a text in one language is translated into a second language using a neural network model. The model can include an encoder neural network comprising a plurality of bidirectional recurrent neural network layers. The encoding vectors are processed using a multi-headed attention module configured to generate multiple attention context vectors for each encoding vector. A decoder neural network generates a sequence of decoder output vectors using the attention context vectors. The decoder output vectors can represent distributions over various language elements of the second language, allowing a translation of the text into the second language to be determined based on the sequence of decoder output vectors.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.

Abstract: A regulating cementitious material for promoting hydration of Portland cement is provided. The regulating cementitious material may include ingredients by weight as follows: ye'elimite, 27˜68 parts; anhydrite, 29˜68 parts; lithium nitrite, 2˜5 parts; ethylene glycol monoisopropanolamine, 0.14˜0.29 parts; triethanolamine acetate, 0.04˜0.09 parts; and polyglycerol, 0.04˜0.09 parts. An early strength of Portland cement can be improved through a cooperative hydration between minerals and an enhanced solubilization of a complexing agent.

Abstract: Described herein are methods and systems associated with viewing condition adaption of multimedia content. A method for receiving multimedia content with a device from a network may include determining a viewing parameter, transmitting a request for the multimedia content to the network, whereby the request may be based on the viewing parameter, and receiving the multimedia content from the network, whereby the multimedia content may be processed at a rate according to the viewing parameter. The viewing parameter may include at least one of: a user viewing parameter, a device viewing parameter, or a content viewing parameter. The method may further include receiving a multimedia presentation description (MPD) file from the network. The MPD file may include information relating to the rate of the multimedia content and information relating to the rate may include a descriptor relating to the viewing parameter, whereby the descriptor may be required or optional.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech synthesis. The methods, systems, and apparatus include actions of obtaining an audio representation of speech of a target speaker, obtaining input text for which speech is to be synthesized in a voice of the target speaker, generating a speaker vector by providing the audio representation to a speaker encoder engine that is trained to distinguish speakers from one another, generating an audio representation of the input text spoken in the voice of the target speaker by providing the input text and the speaker vector to a spectrogram generation engine that is trained using voices of reference speakers to generate audio representations, and providing the audio representation of the input text spoken in the voice of the target speaker for output.

Abstract: A table cutting device includes: a workbench on which a workpiece is capable of being placed; a cutting assembly capable of performing a cutting operation on the workpiece; a drive assembly including a motor and driving the cutting assembly to move; and a power supply connection assembly for connecting a battery pack. The battery pack supplies an energy source to the table cutting device. The table cutting device further includes a display assembly capable of displaying an electric quantity of the battery pack. When the battery pack is mounted to the table cutting device, the distance between the display assembly and the battery pack is greater than or equal to 5 mm. The table cutting device has the additional display assembly so that an operator can observe electric quantity information of the battery pack when operating the table cutting device, thereby greatly improving operation convenience.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for machine translation using neural networks. In some implementations, a text in one language is translated into a second language using a neural network model. The model can include an encoder neural network comprising a plurality of bidirectional recurrent neural network layers. The encoding vectors are processed using a multi-headed attention module configured to generate multiple attention context vectors for each encoding vector. A decoder neural network generates a sequence of decoder output vectors using the attention context vectors. The decoder output vectors can represent distributions over various language elements of the second language, allowing a translation of the text into the second language to be determined based on the sequence of decoder output vectors.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing data generated by a sensing system that rotationally senses an environment. In one aspect, a method comprises partitioning a predetermined period of time into a plurality of sub-periods, wherein the predetermined period of time is a period of time for which data generated by the sensing system constitutes a complete rotational sensing of the environment; for each sub-period: receiving current data generated by the sensing system during the sub-period and characterizing a respective partial scene of the environment; processing the current data using an object detection neural network to generate a current object detection output that is specific to the respective partial scene of the environment.