Abstract: Disclosed herein are salt and solvate forms of (4S,7aR,9aR,10R,11E,14S,15R)-6?-chloro-10-methoxy-14,15-dimethyl-10-{[(9aR)-octahydro-2H-pyrido[1,2-a]pyrazin-2-yl]methyl}-3?,4?,7a,8,9,9a,10,13,14,15-decahydro-2?H,3H,5H-spiro[1,19-etheno-16,16-cyclobuta[i][1,4]oxazepino[3,4-f][1,2,7]thiadlazacyclohexadecine-4,1 naphthalene]-16,16,18 (7H,17H)-trione (AMG 397): (AMG 397), such as crystalline salt and solvate forms thereof. Also disclosed are methods of making the salt and solvate forms, and methods of treating diseases and disorders with the salt and solvate forms.

Abstract: Disclosed herein are crystalline forms of (4S,7aR,9aR,10R,11E,14S,15R)-6?-chloro-10-methoxy-14,15-dimethyl-10-{[(9aR)-octahydro-2H-pyrido[1,2-a]pyrazin-2-yl]methyl}-3?,4?,7a,8,9,9a,10,13,14,15-decahydro-2?H,3H,5H-spiro[1,19-etheno-1616-cyclobuta[i] [1,4]oxazepino[3,4-f][1,2,7]thiadiazacyclohexadecine-4,1?-naphthalene]-16,16,18(7H,17H)-trione (AMG 397): (AMG 397), hydrates, and solvates thereof. Also disclosed are methods of making the crystalline forms, and methods of treating diseases and disorders with the crystalline forms.

Abstract: A method and apparatus for generating a virtual character, an electronic device and a computer readable storage medium are provided. The method includes: performing mesh simplification on an initial model of a virtual character to obtain a mesh-simplified model; obtaining a first target model by performing white model mapping rendering on an area of each material type on the mesh-simplified model, and obtaining a second target model by performing hyper-realistic rendering on the area of each material type on the mesh-simplified model; and establishing a bidirectional mapping between the first target model and the second target model, and obtaining a target virtual character through iterative updating of the bidirectional mapping.

Abstract: A method for training a three-dimensional face reconstruction model includes inputting an acquired sample face image into a three-dimensional face reconstruction model to obtain a coordinate transformation parameter and a face parameter of the sample face image; determining the three-dimensional stylized face image of the sample face image according to the face parameter of the sample face image and the acquired stylized face map of the sample face image; transforming the three-dimensional stylized face image of the sample face image into a camera coordinate system based on the coordinate transformation parameter, and rendering the transformed three-dimensional stylized face image to obtain a rendered map; and training the three-dimensional face reconstruction model according to the rendered map and the stylized face map of the sample face image.

Abstract: Provided are a text processing method, a device and a storage medium, relating to a field of computer technology, and especially to a field of artificial intelligence, such as natural language processing and deep learning. The specific implementation scheme includes: performing text processing on first text, by using a text processing acceleration operator; and processing, in parallel and faster, content after the text processing, by using the text processing acceleration operator. Text processing and parallel acceleration are carried out by the text processing acceleration operator, which can improve the speed of text processing.

Abstract: Embodiments of the present disclosure provide a method and apparatus for performing a structured extraction on a text, a device and a storage medium. The method may include: performing a text detection on an entity text image to obtain a position and content of a text line of the entity text image; extracting multivariate information of the text line based on the position and the content of the text line; performing a feature fusion on the multivariate information of the text line to obtain a multimodal fusion feature of the text line; performing category and relationship reasoning based on the multimodal fusion feature of the text line to obtain a category and a relationship probability matrix of the text line; and constructing structured information of the entity text image based on the category and the relationship probability matrix of the text line.

Abstract: A fault detection method and apparatus for a three-phase power supply circuit of a frequency converter, and an air conditioner. The fault detection method for the three-phase power supply circuit of the frequency converter includes: when a fault occurs in the three-phase power supply circuit, increasing a current or power of a load of the three-phase power supply circuit; quickly determining a fault type of the three-phase power supply circuit according to a frequency of a ripple voltage of a bus voltage. In this way, the fault type of the three-phase power supply circuit can be quickly determined simply based on the main loop of the three-phase power supply circuit.

Abstract: A large model optimization training method in the artificial intelligence fields, such as large models, deep learning, natural language processing, may include: taking, as candidate queries, queries collected from a predetermined data source and capable of serving as input to a large model in response to determining that an optimization triggering condition is met; screening out target queries from the candidate queries, the target queries being queries which cannot be correctly processed by the large model; and constructing respectively corresponding training samples according to the target queries, the training samples being used for carrying out optimization training on the large model.

Abstract: Disclosed herein is a salt, a crystalline anhydrous form, a hydrate, a solvate, or a co-crystal of a free base compound 2-(6-azaspiro[2.5]octan-6-yl)-N-[2-(4,4-difluoropiperidin-1-yl)-6-methylpyrimidin-4-yl]-4-[(2-hydroxyethanesulfonyl)amino]benzamide (Compound A); method of preparation, pharmaceutical compositions, and method of treating a disease mediated by a motor protein kinesin family member 18A (KIF18A) inhibition, wherein said disease is a neoplastic disease, including a cancer or a tumor.

Abstract: The present disclosure provides a control method and a control apparatus for a communication device, a communication system, and a storage medium. The control method for a communication device includes periodically outputting, a first level signal and a second level signal to the communication bus, and the second communication device establishes a data connection with the first communication device based on that the level signal on the communication bus is the first level signal, and the second communication device establishes a power supply connection with the first communication device based on that the level signal on the communication bus is the second level signal. Since the data connection and the power supply connection do not appear at the same time, the communication bus using the above-mentioned control method does not need to set an inductance compared to the traditional Home Bus.

Abstract: The present application provides a heating control method and an apparatus for an electric control box and an air conditioner, which relate to the technical field of air conditioning devices and are used to solve the technical problem that components in the electric control box are more likely to be damaged when a heating component is heated. The heating control method for the electric control box includes: acquiring a detected temperature of a temperature sensor in the electric control box; controlling a heating component in the electric control box to heat the electric control box according to the detected temperature; and sequentially driving circulating fans in the electric control box to conduct internal circulation heating of the electric control box according to a heating time of the heating component.

Abstract: A method and apparatus is provided for generating and applying a deep learning model based on a deep learning framework, and relates to the field of computers. A specific implementation solution includes that a basic operating environment is established on a target device, where the basic operating environment is used for providing environment preparation for an overall generation process of a deep learning model; a basic function of the deep learning model is generated in the basic operating environment according to at least one of a service requirement and a hardware requirement, to obtain a first processing result; an extended function of the deep learning model is generated in the basic operating environment based on the first processing result, to obtain a second processing result; and a preset test script is used to perform function test on the second processing result, to output a test result.

Abstract: Aspects of the invention include computer systems, computer-implemented methods, and computer program products configured to integrate documentation knowledge with log mining data. A non-limiting example computer-implemented method includes determining a message-message relationship based on log message documentation and building a first subgraph based on the message-message relationship. The method further includes receiving a first message log entry having a message identifier and message field data. A second message log entry is correlated with the first message log entry based on at least one of the message identifier and the message field data. A second subgraph is built that includes the first message log entry and the second message log entry. The method includes building a graph that includes the first subgraph and the second subgraph.

Abstract: An apparatus and a method for executing a customized production line using an artificial intelligence development platform, a computing device and a computer readable storage medium are provided. The apparatus includes: a production line executor configured to generate a native form of the artificial intelligence development platform based on a file set, the native form to be sent to a client accessing the artificial intelligence development platform so as to present a native interactive page of the artificial intelligence development platform; and a standardized platform interface configured to provide an interaction channel between the production line executor and the artificial intelligence development platform. The production line executor is further configured to generate an intermediate result by executing processing logic defined in the file set and to process the intermediate result by interacting with the artificial intelligence development platform via the standardized platform interface.

Abstract: A forecasting modeling computing system includes a processors and a memory including a set of computer-executable instructions that, when executed by the processor, cause the forecasting modeling computing system to receive design parameters, determine a predicted median particle size, identify a predictive quadratic model, and display a response surface visualization. A computer-implemented method includes receiving design parameters, determining a predicted median particle size, identifying a predictive quadratic model; and display a response surface visualization.

Abstract: A data generation method based on a deep learning model and a training method is provided. The data generation method includes: determining an initial input of the deep learning model based on input data; obtaining a first output of the model, where in response to the model determining that generating a reply based on the initial input requires calling a first functional component different from the deep learning model, the first output includes a first token for calling the first functional component and a first intermediate inquiry determined based on the initial input and recognizable by the first functional component; obtaining a first intermediate result determined by the first functional component based on the first intermediate inquiry; determining a second input for the model based on the initial input and the first intermediate result; and obtaining a second output of the model for generating a reply to the initial input.

Abstract: Embodiments of the invention are directed to annotating a log based on processing log documentation. Aspects include obtaining the data set and obtaining a set of templates, wherein one or more template of the set of templates includes a variable labeled as the data type. Aspects also include annotating the data set based on the set of templates, wherein the annotating includes labeling each value of the variable in the data set with the data type. Aspects further include creating an updated data set by replacing each value of the variable in the data set that is labeled with the data type with a new data value.

Abstract: Systems and methods are disclosed herein for detecting impurities of harvested plants in a receptacle of a harvester. In an embodiment, a harvester controller receives, from a camera facing the contents of the receptacle, an image of the contents. The harvester controller applies the image as input to a machine learning model. The harvester controller receives, as output from the machine learning model, an identification of an impurity of the harvested plants. The harvester controller transmits a control signal based on the impurity.

Abstract: A method for training a three-dimensional face reconstruction model includes inputting an acquired sample face image into a three-dimensional face reconstruction model to obtain a coordinate transformation parameter and a face parameter of the sample face image; determining the three-dimensional stylized face image of the sample face image according to the face parameter of the sample face image and the acquired stylized face map of the sample face image; transforming the three-dimensional stylized face image of the sample face image into a camera coordinate system based on the coordinate transformation parameter, and rendering the transformed three-dimensional stylized face image to obtain a rendered map; and training the three-dimensional face reconstruction model according to the rendered map and the stylized face map of the sample face image.

Abstract: An image rendering method includes the steps below. A model of an environmental object is rendered to obtain an image of the environmental object in a target perspective. An image of a target object in the target perspective and a model of the target object are determined according to a neural radiance field of the target object. The image of the target object is fused and rendered into the image of the environmental object according to the model of the target object.