Abstract: A circuit breaker, comprising a housing, an operation assembly, an arc extinguishing device, and a transmission mechanism. The housing has, in a first direction, a bottom and a top opposite to each other, an accommodation portion recessed from the top to the bottom, and an accommodation cavity semi-surrounding the accommodation portion; a rotating wheel and a movable contact connected to the rotating wheel are provided in the accommodation cavity close to the top and adjacent to the accommodation portion in a second direction, wherein the first direction intersects the second direction; the operation assembly is rotatably and detachably connected to the top of the housing; the arc extinguishing device comprises an arc extinguishing chamber located in the accommodation cavity and close to the bottom of the housing. The circuit breaker can avoid interference between the transmission mechanism and other components while increasing the size of the arc extinguishing chamber.

Abstract: A display device is disclosed. The display device includes an array substrate and at least two driving units. The array substrate includes a peripheral region and a display region, the array substrate further includes a peripheral grounding line and a test line, wherein the peripheral grounding line is located in the peripheral region, and the test line is located in the peripheral region. The at least two driving units are located on at least one side of the array substrate, the driving unit includes at least two grounding pins, a grounding pin of at least one of the driving units is connected to the peripheral grounding line, and each of at least one grounding pin of one of two adjacent driving units is electrically connected to a corresponding grounding pin of the other adjacent driving unit.

Abstract: The systems and methods described herein are directed to a Co-Augmentation framework that may learn new rules and labels simultaneously from unlabeled data with a small set of seed rules and a few manually labeled training data. The augmented rules and labels are further used to train supervised neural network models. Specifically, the systems and methods described herein include two major components: a rule augmenter, and a label augmenter. The rule augmenter is directed to learning new rules, which can be used to obtain weak labels from unlabeled data. The label augmenter is directed to learning new labels from unlabeled data. The Co-Augmentation framework is an iterative learning process which generates and refines a high precision set. At each iteration, both the rule augmenter and label augmenter will contribute new and more accurate labels to the high precision set, which is in turn used to train both the rule augmenter and label augmenter.

Abstract: Disclosed are a display apparatus and a method for controlling screen projections from multiple devices to a same screen. The display apparatus includes: a display and at least one processor configured to execute instructions to cause the display apparatus to: establish a connection with a first projection device; receive projection contents; control the display to show a top-level application of a user interface displayed, in a case that the projection content is vertical media resource; determine whether the top-level application supports split screen display; when the top-level application supports split screen display, the top-level application is displayed in a first window and the projection contents are displayed in a second window; when the top-level application does not support split screen display, the top level application after proportional reduction is displayed in either of the two windows, and the projection content are displayed in the other window of the two windows.

Abstract: Disclosed are systems and methods for a computerized framework that provides a document structure parsing system for requirement engineering documents, where the logical structure of the text is not available, and is to be rebuilt based on the raw textual content. The framework approaches the build of the logical structure according to two phases. The first phase involves creating a list of list of text snippets from the raw text, where sequence labeling is adopted to re-segment and merge initially segmented text snippets. The second phase involves the framework executing computerized techniques including embedding adaptation approach, a hierarchy structure rebuilt algorithm, and a requirement text selection strategy to rebuild the hierarchy structure.

Abstract: Some embodiments of the present application disclose a display apparatus and a voice control method for the display apparatus. The display apparatus comprises a display, a detector and a controller. The display is configured to present a user interface, and the detector is configured to acquire user voice information; and the controller is configured to cause the display apparatus to perform: acquiring voice information inputted from a user; in response to the voice information, extracting at least one keyword from the voice information; traversing action items in a configuration library; in response to determining that no action item in the configuration library matches the at least one keyword, obtaining text information of the user interface on the display to in order to determine an control instruction according to the text information.

Abstract: A generative automatic text summarization system and method is disclosed that may adopt a search and reranking strategy to improve the performance of a summarization task. The system and method may employ a transformer neural model to assist with the summarization task. The transformer neural model may be trained to learn human abstracts and may then be operable to generate abstractive summaries. With multiple summary hypothesis generated, a best-first search algorithm and reranking algorithm may be employed to select the best candidate summary as part of the output summary.

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: Provided are a display apparatus and display method for the display apparatus with a rotatable display. A controller thereof is configured to, during a power-off state or standby state of the display apparatus, in response to an instruction for starting the display apparatus, detect a current rotation state of the rotatable display; in response to the rotatable display being in the horizontal state, control the display to present an animation for the starting of the display apparatus corresponding to the horizontal state; and in response to the rotatable display being in the portrait state, control the display to present an animation for the starting of the display apparatus corresponding to the portrait state.

Abstract: A generative automatic text summarization system and method is disclosed that may adopt a search and reranking strategy to improve the performance of a summarization task. The system and method may employ a transformer neural model to assist with the summarization task. The transformer neural model may be trained to learn human abstracts and may then be operable to generate abstractive summaries. With multiple summary hypothesis generated, a best-first search algorithm and reranking algorithm may be employed to select the best candidate summary as part of the output summary.

Abstract: A method of determining an operational difficulty of a process described in a document including text includes generating text data corresponding to the text of the document, and generating a word vector output by processing the text data through a plurality of word vectors, the plurality of word vectors based on a domain-specific text collection and a general-language text collection. The method further includes generating a statistical information output by processing the text data through a plurality of statistical information vectors, the plurality of statistical information vectors based on the domain-specific text collection and the general-language text collection, and generating a gated recurring unit (GRU) output by processing (i) the word vector output, (ii) the statistical information output, (iii) word-level data based on the text data, (iv) sentence-level data based on the text data, and (v) paragraph-level data based on the text data through at least one GRU.

Abstract: To present one or more content to users of an online system, the online system identifies a content evaluation pipeline including an order of a plurality of stages having one or more computer models for evaluating a likelihood of user interaction with a content item. The content evaluation pipeline selects a decreasing number of content items, from each stage of the order, according to the order of the stages in the order. The online system identifies a set of candidate modifications to one or more operational parameters of the content evaluation pipeline. For each candidate modification, the online system determines a compute time value and a content selection value. For a given amount of compute time, the online system optimizes the one or more operational parameters based on the determined content time value and the determined content selection value to increase the content selection value of the content evaluation pipeline.

Abstract: Disclosed is a skin care composition comprising starch, benzotriazole derivative sunscreen, whitening pigment and a cosmetically acceptable carrier, wherein the starch is present in amount of less than 2.2% by weight of the composition, and the benzotriazole derivative sunscreen is present in amount of less than 0.22% by weight of the composition.

Abstract: A method of determining an operational difficulty of a process described in a document including text includes generating text data corresponding to the text of the document, and generating a word vector output by processing the text data through a plurality of word vectors, the plurality of word vectors based on a domain-specific text collection and a general-language text collection. The method further includes generating a statistical information output by processing the text data through a plurality of statistical information vectors, the plurality of statistical information vectors based on the domain-specific text collection and the general-language text collection, and generating a gated recurring unit (GRU) output by processing (i) the word vector output, (ii) the statistical information output, (iii) word-level data based on the text data, (iv) sentence-level data based on the text data, and (v) paragraph-level data based on the text data through at least one GRU.

Abstract: Disclosed is a skin care composition comprising starch, benzotriazole derivative sunscreen, whitening pigment and a cosmetically acceptable carrier, wherein the starch is present in amount of less than 2.2% by weight of the composition, and the benzotriazole derivative sunscreen is present in amount of less than 0.22% by weight of the composition.

Abstract: To present one or more content to users of an online system, the online system identifies a content evaluation pipeline including an order of a plurality of stages having one or more computer models for evaluating a likelihood of user interaction with a content item. The content evaluation pipeline selects a decreasing number of content items, from each stage of the order, according to the order of the stages in the order. The online system identifies a set of candidate modifications to one or more operational parameters of the content evaluation pipeline. For each candidate modification, the online system determines a compute time value and a content selection value. For a given amount of compute time, the online system optimizes the one or more operational parameters based on the determined content time value and the determined content selection value to increase the content selection value of the content evaluation pipeline.

Abstract: Hydrophobic paramagnetic nanoparticles can be injected with the enhanced oil recovery injection water by incorporating them inside of surfactant micelles to serve as an oil tracer. A variety of paramagnetic nanoparticles that show different susceptibility and magnetization responses to applied magnetic oscillation can be injected at different injectors, so that the origin of the oil from the different enhanced oil recovery patterns could be quantitatively identified. The concentrations of the nanoparticles in the produced crude oil and brine can be easily and instantly measured individually, employing the magnetic susceptibility meter without contacting the fluids directly.

Abstract: Exemplary embodiments include an apparatus and method for performing angle-resolved imaging of scattering samples such as tissue, including the use of a pathlength multiplexing element.