Abstract: A USB protocol-based IP infringement identification method for USB devices, including the following steps: S1, connecting an infringement identification device at a peer side of the USB host to be tested; S2, the USB host to be tested entering compliance mode; S3, the infringement identification device sending an X.LFPS file to the USB host to be tested; S4, upon the USB host to be tested receiving the X.LFPS file, the USB host to be tested sending IP copyright information to the infringement identification device; S5, determining whether the USB host to be tested infringes the IP. The infringement identification of the USB device to be tested is performed by using the compliance mode specified in the USB protocol, which is more stable, reliable and can also save costs.

Abstract: Provided are biaryl amides and coumarin-based compounds with modified sugar groups for treatment of diseases associated with heat shock protein pathway. The compounds having the following formulas, wherein variables are as defined herein. Formulae (I), (II), (III), (IV), and (V), Pharmaceutical compositions of the compounds are also provided. These biaryl amides and coumarin-based derivatives with modified sugar groups are useful for treatment and prevention of diseases and disorders, including neurological disorders, such as neurodegenerative diseases and nerve damaging disorders, for example, diabetic peripheral neuropathy.

Abstract: Disclosed herein are novel antioxidant inflammation modulators, including those of the formula: wherein the variables are defined herein. Also provided are pharmaceutical compositions, kits and articles of manufacture comprising such compounds. Methods and intermediates useful for making the compounds, and methods of using the compounds and compositions thereof are also provided.

Abstract: A cab roof structure, a cab and a rail train are described. The cab roof structure comprises: at least one roof connecting beam disposed on a roof carline; and at least two aluminum honeycomb panels, one roof connecting beam is disposed between every two aluminum honeycomb panels, and each aluminum honeycomb panel is fixedly connected to a left or right side of the roof connecting beam. The cab roof structure has the advantages of high structural strength, light weight, less welding and good manufacturability.

Abstract: A computing device trains a fair machine learning model. A predicted target variable is defined using a trained prediction model. The prediction model is trained with weighted observation vectors. The predicted target variable is updated using the prediction model trained with weighted observation vectors. A true conditional moments matrix and a false conditional moments matrix are computed. The training and updating with weighted observation vectors are repeated until a number of iterations is performed. When a computed conditional moments matrix indicates to adjust a bound value, the bound value is updated based on an upper bound value or a lower bound value, and the repeated training and updating with weighted observation vectors is repeated with the bound value replaced with the updated bound value until the conditional moments matrix indicates no further adjustment of the bound value is needed. A fair prediction model is trained with the updated bound value.

Abstract: This application relates to the field of artificial intelligence, and provides a model training method. The method includes: obtaining a to-be-trained first neural network model, where the first neural network model includes a first operator, and the first operator is used to perform a product operation on input data and a target weight matrix; replacing the first operator in the first neural network model with a second operator, to obtain a second neural network model, where the second operator is used to perform a product operation on input data and a plurality of sub-weight matrices, and the plurality of sub-weight matrices are obtained by performing matrix factorization on the target weight matrix; and performing model training on the second neural network model to obtain a target neural network model.

Abstract: A question answering method includes obtaining target question information; determining a candidate question and answer pair based on the target question information; calculating a confidence of answer information in the candidate question and answer pair, where the confidence is used to indicate a probability that question information in the candidate question and answer pair belongs to an answer database or an adversarial database; determining whether the confidence is less than a first preset threshold; and when the confidence is less than the first preset threshold, outputting information indicating incapable of answering.

Abstract: Disclosed herein are C4 modified oleanolic acid derivatives of the formula: as well as analogs thereof, wherein the variables are defined herein. In addition, disclosed herein are pharmaceutical compositions of these derivatives or analogs, methods for their manufacture, and methods for their use, including for the prevention and treatment of diseases or disorders associated with overproduction of IL-17.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may obtain a band priority list identifying a set of bands in a prioritized order. The UE may perform a system scan of one or more bands of a frequency list that are associated with at least a threshold energy level in the prioritized order of the one or more bands in the band priority list. Numerous other aspects are described.

Abstract: A data processing method includes: obtaining to-be-processed data and a target neural network model, where the target neural network model includes a first transformer layer, the first transformer layer includes a first residual branch and a second residual branch, the first residual branch includes a first attention head, and the second residual branch includes a target feed-forward network (FFN) layer; and performing target task related processing on the to-be-processed data based on the target neural network model, to obtain a data processing result, where the target neural network model is for performing a target operation on an output of the first attention head and a first weight value to obtain an output of the first residual branch, and/or the target neural network model is for performing a target operation on an output of the target FFN and a second weight value to obtain an output of the second residual branch.

Abstract: A computing device trains a fair machine learning model. A predicted target variable is defined using a trained prediction model. The prediction model is trained with weighted observation vectors. The predicted target variable is updated using the prediction model trained with weighted observation vectors. A true conditional moments matrix and a false conditional moments matrix are computed. The training and updating with weighted observation vectors are repeated until a number of iterations is performed. When a computed conditional moments matrix indicates to adjust a bound value, the bound value is updated based on an upper bound value or a lower bound value, and the repeated training and updating with weighted observation vectors is repeated with the bound value replaced with the updated bound value until the conditional moments matrix indicates no further adjustment of the bound value is needed. A fair prediction model is trained with the updated bound value.

Abstract: A model training method applied to the field of artificial intelligence is disclosed. The method includes: sending a first submodel to a first device, where the first submodel is obtained by compressing a to-be-trained model; receiving a first gradient sent by the first device, where the first gradient is obtained when the first device trains the first submodel; and performing model training on the to-be-trained model based on at least the first gradient, to obtain an updated to-be-trained model. In the method, a server compresses the to-be-trained model and delivers the to-be-trained model to a terminal device, so that the terminal device does not need to train a large model with a same scale as that of the server.

Abstract: An oxygen reduction device in an ion source region of inductively coupled plasma is provided. The oxygen reduction device includes a torch and an inflation sleeve. An upper end of the inflation sleeve is sealed and sleeved outside the torch, and a lower end of the inflation sleeve and the torch are arranged at an interval to form an inflation gap. An inflation hole communicating with the inflation gap is formed in an outer side wall of the inflation sleeve. An outer side face of the lower end of the inflation sleeve is protruded outwards to form an annular gas guiding protrusion. The annular gas guiding protrusion is configured for being arranged opposite to a sampling cone base arranged below the torch, and a gas outlet gap is formed between the annular gas guiding protrusion and the sampling cone base.

Abstract: A method and neural network system for human-computer interaction, and user equipment are disclosed. According to the method for human-computer interaction, a natural language question and a knowledge base are vectorized, and an intermediate result vector that is based on the knowledge base and that represents a similarity between a natural language question and a knowledge base answer is obtained by means of vector calculation, and then a fact-based correct natural language answer is obtained by means of calculation according to the question vector and the intermediate result vector. By means of this method, a dialog and knowledge base-based question-answering are combined by means of vector calculation, so that natural language interaction can be performed with a user, and a fact-based correct natural language answer can be given according to the knowledge base.

Abstract: In some aspects, the present disclosure provides compounds of the formula: (I) and (II), wherein the variables are defined herein. Also provided are pharmaceutical compositions thereof. In some aspects, the compounds and compositions provided herein may be used as antioxidant inflammation modulators. In some aspects, the present disclosure provides methods wherein the compounds and composition described herein are used for the treatment of diseases and disorders associated with inflammation and cancer.

Abstract: Embodiments of the present invention relate to solvents for pesticides and pesticide formulations. In one aspect, a solvent for pesticides comprises (a) an ether ester of Formula 1: wherein R1 and R2 are each independently one of an alkyl group having 1 to 4 carbon atoms or an aryl group, wherein R3 is hydrogen, methyl, or ethyl, and wherein n is 1 to 6; and (b) a polar amide of Formula 2: R4—C(O)—NR5R6??(Formula 2) wherein R4 is an alkyl group having 1 to 4 carbon atoms, and wherein R5 and R6 are each independently an alkyl group having 1 to 3 carbon atoms.

Abstract: A method for multi-task-based predicting massive-user loads based on a multi-channel convolutional neural network, and belongs to the technical field of electric power systems. The method includes clustering all residential users into a plurality of clusters with different daily average electricity consumption modes by adopting an agglomerative hierarchical clustering method. Corresponding input data sets are constructed for various clusters by adopting a multi-channel-based multi-source input fusion method. Then, a multi-task-based load prediction model based on a convolutional neural network is established for each of the clusters. Load prediction values for different users in the corresponding cluster are output in parallel by each model to eventually obtain load prediction results of all of the residential users.

Abstract: A paraphrase sentence generation method and apparatus relating to the research field of natural language processing include generating m second sentences based on a first sentence and a paraphrase generation model, determining a matching degree between each of the m second sentences and the first sentence based on a paraphrase matching model, and determining n second sentences from the m second sentences based on matching degrees among the m second sentences and the first sentence, where the paraphrase generation model is obtained through reinforcement learning-based training based on a reward of the paraphrase matching model.

Abstract: Disclosed herein are C4 modified oleanolic acid derivatives of the formula: Formula (X) or Formula (XII), as well as analogs thereof, wherein the variables are defined herein. In addition, disclosed herein are pharmaceutical compositions of these derivatives or analogs, methods for their manufacture, and methods for their use, including for the prevention and treatment of diseases or disorders associated with overproduction of IL-17.

Abstract: A semiconductor device and fabrication method thereof are provided. The fabrication method include: providing a to-be-etched material layer; forming a plurality of discrete sacrificial layers on the to-be-etched material layer; forming first initial spacers on sidewalls of each of the discrete sacrificial layers. Each first initial spacer includes a first bottom region and a first top region on the first bottom region; removing the discrete sacrificial layers. The method further includes: removing the first top region of each first initial spacer to form a first spacer from each first bottom region; forming second spacers on sidewalls of each of the first spacers. Each second spacer includes a second bottom region and a second top region on the second bottom region; removing the first spacers; The method further includes: removing the second top regions by etching; and etching the to-be-etched material layer by using the second spacers as a mask.