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: Disclosed herein are glass compositions that present several advantages over glasses and other materials currently used for redistribution layers for RF, interposers, and similar applications. The glasses disclosed herein are low cost, flat glasses that have high throughput for the laser damage and etching process used to create through glass vias (TGV). TGV generated using the silicate glasses and processes described herein have large waist diameters (Dw), which is a desirable feature with respect to producing glass articles such as interposers.

Abstract: A method for cutting or extracting video clips from a video, including the audio content relevant to points of particular interest, and combining the same for instruction or training on particular points; a computing device applying the method extracts text information from the spoken audio content of a video to be cut and obtains multiple paragraph segmentation positions as candidates for inclusion in a desired and finished presentation by analyzing the information from text representing the spoken audio content, the analysis being carried out by a semantic segmentation model. Candidate items of text are obtained by isolating pieces of text according to the paragraph segmentation positions. Time stamps of the candidate text segments are acquired, and candidate video clips are obtained by cutting the video according to the acquired time stamps.

Abstract: The present disclosure provides a method for processing defect information of a product, which includes the following steps of: acquiring defect information on a current film layer and defect information on historical film layers; determining whether defect information exists at a target location of the historical film layer if defect information exists at a target location of the current film layer; if defect information exists for a corresponding location to the target location in at least one of the historical film layers, deleting the defect information detected at the target location in the current film layer; and if no defect information exists for the target location in any of the historical film layers, retaining the defect information detected at the target location in the current film layer.

Abstract: Information output methods and apparatuses, computer equipment and readable storage media which relate to the field of computer technology are provided. The information output method includes: detecting whether a search connection is established between a delivery terminal and a beacon device deployed by a target physical object by using a pre-cached joint beacon atlas bound to the target physical object, where the joint beacon atlas records a set of communication identifiers covered by a physical object; if the search connection is established between the delivery terminal and the beacon device deployed by the target physical object, outputting a corresponding time point when the search connection is in a stable state as information of a delivery resource arriving at the target physical object.

Abstract: A quantum layout optimization method includes: determining target Hamiltonian parameters of a quantum device; determining an initial quantum layout of the quantum device and initial geometric parameters of the initial quantum layout; determining a target gradient of Hamiltonian parameters of the quantum device to geometric parameters of the initial quantum layout; and adjusting the initial geometric parameters based on the target gradient to have the Hamiltonian parameters of the quantum device be the target Hamiltonian parameters to obtain a target quantum layout.

Abstract: Provided is engineered microorganisms expressing acetoacetyl-CoA reductase variants and a method for improving the yield of PHA. Compared with the wild-type acetoacetyl-CoA reductase represented by SEQ ID NO. 31, the variant has one or more of the following mutations: (1) mutation of valine at position 141 to isoleucine or leucine; (2) mutation of methionine at position 12 to threonine, serine, alanine, leucine, lysine or isoleucine; (3) mutation of isoleucine at position 194 to valine, leucine or methionine; (4) mutation of glutamic acid at position 42 to lysine, glutamine, leucine, aspartic acid, proline, threonine, asparagine, or histidine; and (5) mutation of phenylalanine at position 55 to valine, alanine or isoleucine. The variants and their coding genes can promote the synthesis and accumulation of PHA by the strain and increase the yield of PHA.

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.

Abstract: Aspects of the invention include computer systems, computer-implemented methods, and computer program products configured to perform message correlation extraction for mainframe operation. A non-limiting example computer-implemented method includes receiving a first message log entry having a message identifier and message field data. The first message log entry is pre-processed to determine the message identifier and to tokenize the message field data. A second message log entry is identified based on at least one of the message identifier and the tokenized message field data. The method further includes determining that the second message log entry is correlated with the first message log entry and providing an output comprising the message correlation between the first message log entry and the second message log entry.

Abstract: A method for marking a virtual article in a virtual environment includes: displaying a pickup list of a first virtual object, where the pickup list is used to display at least one virtual article to be picked up by the first virtual object in the virtual environment, and list items in the pickup list are arranged in a first direction; receiving a first sliding operation performed on the pickup list; and sliding the list item of the target virtual article in the pickup list along a second direction in response to the first sliding operation, and displaying the target virtual article in a marked state, where the marked state is used to share position information of the target virtual article to a second virtual object.

Abstract: Provided herein are solid dispersions comprising AMG 397, methods of preparing the solid dispersion, and pharmaceutical formulations comprising AMG 397.

Abstract: Embodiments of the present invention relate to methods, systems, and computer program products for event management. In a method, a plurality of notes that are comprised in a plurality of event records are obtained in a computer system. A plurality of paragraphs that are comprised in the plurality of notes are classified into a plurality of content types based on a content analysis of the plurality of paragraphs. The plurality of notes are classified into a plurality of semantic types based on the plurality of content types and a syntactic parsing to the plurality of notes. A knowledge item is generated for managing an event in the computer system based on a group of notes in the plurality of notes that are classified into the plurality of semantic types. With these embodiments, knowledge items for managing events may be obtained in an easier and more effective way.

Abstract: Provided are a joint perception model training method, a joint perception method, a device, and a storage medium. The joint perception model training method includes: acquiring sample images and perception tags of the sample images; acquiring a preset joint perception model, where the joint perception model includes a feature extraction network and a joint perception network; performing feature extraction on the sample images through the feature extraction network to obtain target sample features; performing joint perception through the joint perception network according to the target sample features to obtain perception prediction results; and training the preset joint perception model according to the perception prediction results and the perception tags, where the joint perception includes executing at least two perception tasks.

Abstract: A display method and apparatus for a virtual prop, an electronic device and a non-transitory computer-readable storage medium. The method includes: displaying a virtual prop list in a virtual scene, the virtual prop list having an interactive option for at least one virtual prop, displaying based on a slide operation on the interactive option for a target virtual prop in the virtual prop list meeting a first target condition, a first target region, and marking the target virtual prop based on an operation end point of the slide operation being within the first target region.

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.