Abstract: The present disclosure discloses an electric-machine housing structure, wherein the electric-machine housing structure includes an outer housing, an inner housing and a plurality of intermediate pieces provided between the outer housing and the inner housing; and the intermediate pieces are overall hollow arcuate structures or annular structures, upper surfaces and lower surfaces of the intermediate pieces are provided with a plurality of protrusions and/or grooves, the protrusions and/or grooves of the upper surfaces match with and are fixed to grooves and/or protrusions on an inner circumferential face of the outer housing, and the protrusions and/or grooves of the lower surfaces match with and are fixed to grooves and/or protrusions on an outer circumferential face of the inner housing.

Abstract: A computer-implemented system and method relate to natural language processing. The computer-implemented system and method include obtaining a query and selecting a candidate based on the query. The candidate includes a question and an answer to that question. The computer-implemented system and method are configured to classify the candidate into a class that indicates that the candidate is relevant to the query from among a group of classes that includes at least that class and another class. The another class indicates that the candidate has the answer to the query. A machine learning system is configured to handle the query after the candidate is classified in the class. The machine learning system is configured to generate a relevant response for the query upon receiving input data that includes at least the query and the question. The relevant response provides information associated with a keyword of the question that is not contained in the query.

Abstract: Systems and methods for weakly-supervised training a machine-learning model to perform named-entity recognition. All possible entity candidates and all possible rule candidates are automatically identified in an input data set of unlabeled text. An initial training of the machine-learning model is performed using labels assigned to entity candidates by a set of seeding rules as a first set of training data. The trained machine-learning model is then applied to the unlabeled text and a subset of rules from the rule candidates is identified that produces labels that most accurately match the labels assigned by the trained machine-learning model. The machine-learning model is then retrained using the labels assigned by the identified subset of rules as the second set of training data. This process is iteratively repeated to further refine and improve the performance of the machine-learning model for named-entity recognition.

Abstract: Systems and methods for training a machine-learning model for named-entity recognition. A rule graph is constructed including a plurality of nodes each corresponding to a different labeling rule of a set of labeling rules (including a set of seeding rules of known labeling accuracy and a plurality of candidate rules of unknown labeling accuracy). The nodes are coupled to other nodes based on which rules exhibit the highest sematic similarity. A labeling accuracy metric is estimated for each candidate rule by propagating a labeling confidence metric through the rule graph from the seeding rules to each candidate rule. A subset of labeling rules is then identified by ranking the rules by their labeling confidence metric. The identified subset of labeling rules is applied to unlabeled data to generate a set of weakly labeled named entities and the machine-learning model is trained based on the set of weakly labeled named entities.

Abstract: Methods and systems for performing semantic entity recognition. The method includes accessing a document stored in a memory and selecting from a general knowledge data repository, target domain information based on a specified target domain. The method also includes generating a plurality of weak annotators for the document based upon the selected target domain information and expert knowledge from a domain-specific expert knowledge data repository and applying the plurality of weak annotators to the document to generate a plurality of weak labels. The method further includes selecting at least one weak label from the plurality of weak labels as training data and training a semantic entity prediction model using the training data.

Abstract: This application discloses an information recommendation method and apparatus, a device, and a storage medium, and belongs to the field of information recommendation. The method includes starting an application program according to a start operation, a first account being logged in in the application program; obtaining a recommended information flow for the first account, recommended information in the recommended information flow including at least one piece of interactive recommended information, the interactive recommended information being information for which a second account generates an interactive message, the first account and the second account having a social relationship; and displaying an information presentation interface, the information presentation interface comprising the recommended information displayed in an information flow form.

Abstract: A system for ontology-aware sound classification. The system includes an electronic processor that is configured to create a first graph based on relationships between fine audio classification labels and create a second graph based on relationships between coarse audio classification labels. The electronic processor is also configured to receive an audio clip including one or more sounds, execute a first graph convolutional network with the first graph as input, and execute a second graph convolutional network with the second graph as input. Using the outputs of the first graph convolutional network and the second graph convolutional network, the electronic processor is configured to determine one or more coarse labels, one or more fine labels, or both to classify the one or more sounds in the audio clip.

Abstract: The present disclosure discloses an electric-machine shaft, wherein the electric-machine shaft is provided with a hollow structure in an axial direction at least one end, and the hollow structure is, at a position close to the end, provided with a coolant pumping mechanism having a spiral groove, so that the coolant is able to enter the hollow structure by an attractive force generated by rotation of the electric-machine shaft; the spiral groove is provided on an inner surface of an annular member, the annular member is fixedly mounted to the hollow structure, or the spiral groove is directly provided on an inner surface of the hollow structure; and the electric-machine shaft is provided with a plurality of groups of coolant channels in an axial direction, the coolant channels are in communication with the hollow structure, and when the electric-machine shaft is rotating, oil liquid inside the hollow structure is thrown out by the coolant channels, to cool components inside an electric-machine housing.

Abstract: The present invention is directed to amino and alkyl pyrazolopyrimidine compounds which may be useful as therapeutic agents for the treatment of disorders associated with phosphodiesterase 9 (PDE9). The present invention also relates to the use of such compounds for treating cardiovascular and cerebrovascular diseases, such as hypertension, chronic kidney disease and heart failure, and neurological and psychiatric disorders, such as schizophrenia, psychosis or Huntington's disease, and those associated with striatal hypofunction or basal ganglia dysfunction.

Abstract: The present disclosure discloses an electric-machine housing structure, wherein the electric-machine housing structure includes an outer housing, an inner housing and a plurality of intermediate pieces provided between the outer housing and the inner housing; and the intermediate pieces are overall hollow arcuate structures or annular structures, upper surfaces and lower surfaces of the intermediate pieces are provided with a plurality of protrusions and/or grooves, the protrusions and/or grooves of the upper surfaces match with and are fixed to grooves and/or protrusions on an inner circumferential face of the outer housing, and the protrusions and/or grooves of the lower surfaces match with and are fixed to grooves and/or protrusions on an outer circumferential face of the inner housing.

Abstract: A system for automatically labeling data using conceptual descriptions. In one example, the system includes an electronic processor configured to generate unlabeled training data examples from one or more natural language documents and, for each of a plurality of categories, determine one or more concepts associated with a conceptual description of the category and generate a weak annotator for each of the one or more concepts. The electronic processor is also configured to apply each weak annotator to each training data example and, when a training data example satisfies a weak annotator, output a category associated with the weak annotator. For each training data example, the electronic processor determines a probabilistic distribution of the plurality of categories. For each training data example, the electronic processor labels the training data example with a category having the highest value in the probabilistic distribution determined for the training data example.

Abstract: Methods and systems for performing semantic entity recognition. The method includes accessing a document stored in a memory and selecting from a general knowledge data repository, target domain information based on a specified target domain. The method also includes generating a plurality of weak annotators for the document based upon the selected target domain information and expert knowledge from a domain-specific expert knowledge data repository and applying the plurality of weak annotators to the document to generate a plurality of weak labels. The method further includes selecting at least one weak label from the plurality of weak labels as training data and training a semantic entity prediction model using the training data.

Abstract: This application discloses an information recommendation method and apparatus, a device, and a storage medium, and belongs to the field of information recommendation. The method includes starting an application program according to a start operation, a first account being logged in in the application program; obtaining a recommended information flow for the first account, recommended information in the recommended information flow including at least one piece of interactive recommended information, the interactive recommended information being information for which a second account generates an interactive message, the first account and the second account having a social relationship; and displaying an information presentation interface, the information presentation interface comprising the recommended information displayed in an information flow form.

Abstract: A system for ontology-aware sound classification. The system includes an electronic processor that is configured to create a first graph based on relationships between fine audio classification labels and create a second graph based on relationships between coarse audio classification labels. The electronic processor is also configured to receive an audio clip including one or more sounds, execute a first graph convolutional network with the first graph as input, and execute a second graph convolutional network with the second graph as input. Using the outputs of the first graph convolutional network and the second graph convolutional network, the electronic processor is configured to determine one or more coarse labels, one or more fine labels, or both to classify the one or more sounds in the audio clip.

Abstract: A method of detecting occupancy in an area includes obtaining, with a processor, an audio sample from an audio sensor and determining, with the processor, feature functional values of a set of selected feature functionals from the audio sample. The determining of the feature functional values includes extracting features in the set of selected feature functionals from the audio sample, and determining the feature functional values of the set of selected features from the extracted features. The method further includes determining, with the processor, occupancy in the area using a classifier based on the determined feature functional values.

Abstract: DIY (Do-It-Yourself) is challenging for many novices, requiring extensive knowledge such as the usage of particular tools and the properties of the required materials. Many DIYers use web searches to find relevant information and instructions, but web search is time-consuming and the results often do not fit the DIYers' specific needs. To address these problems, we present a Question Answering (QA) system that can assist DIYers through the whole cycle of a DIY project. Given a natural language question about a DIY project, the QA system described herein provides an answer along with the explanations that are tailored to the DIYers' specific needs.

Abstract: A biochemical analyzer delivery system, comprising a sample feeding track (42), an advancing track (43), a recovery track (44), at least one to-be-tested sub-track (45), at least one emergency sub-track (46) and at least one return sub-track (47); the sample feeding track (42), the advancing track (43) and the recovery track (44) are parallel to each other; the to-be-tested sub-track (45), the emergency sub-track (46) and the return sub-track (47) are disposed between and perpendicular to the sample feeding track (42) and the advancing track (43), an emergency sample may enter the emergency sub-track via the advancing track (43), and then enters the sample feeding track for sample suction. The track-based delivery system can be horizontally disposed in a biochemical analyzer, and can be butt-jointed with a vertical track in the biochemical analyzer, thereby greatly increasing the buffer amount of sample holders without increasing the length of the biochemical analyzer.

Abstract: The present invention relates to PCSK9 allosteric binding compounds of Formula I: (Formula (I)) and pharmaceutically acceptable salts thereof, wherein X1, X2, Y, R1, R2, RA, RB and n are as defined herein. The present invention also relates to compositions which comprise an allosteric binding compound of the invention or a pharmaceutically acceptable salt thereof and a pharmaceutically acceptable carrier. The invention further relates, inter alia, to methods for inducing PCSK9 protein degradation in a subject, and methods for treating atherosclerosis, hypercholesterolemia, coronary heart disease, metabolic syndrome, acute coronary syndrome, or related cardiovascular disease and cardiometabolic conditions, comprising administering to a subject an effective amount of a compound or a pharmaceutically acceptable salt of the invention. The invention also provides a means for the in vitro labeling, detection and/or quantification of PCSK9 in biological samples.

Abstract: A method and system for detecting and localizing a target audio event in an audio clip is disclosed. The method and system use utilizes a hierarchical approach in which a dilated convolutional neural network to detect the presence of the target audio event anywhere in an audio clip based on high level audio features. If the target audio event is detected somewhere in the audio clip, the method and system further utilizes a robust audio vector representation that encodes the inherent state of the audio as well as a learned relationship between state of the audio and the particular target audio event that was detected in the audio clip. A bi-directional long short term memory classifier is used to model long term dependencies and determine the boundaries in time of the target audio event within the audio clip based on the audio vector representations.

Abstract: The present invention relates to a compound represented by formula (I): and pharmaceutically acceptable salts thereof are disclosed as useful for treating or preventing diabetes, hyperlipidemia, obesity, NASH, inflammation related disorders, and related diseases and conditions. The compounds are useful as agonists of the G-protein coupled receptor GPR120. Pharmaceutical compositions and methods of treatment are also included.