Abstract: An optimal rescue orbital elements online decision-making method based on RBFNN for launch vehicles under thrust drop fault includes establishing the flight dynamic equations of launch vehicles in the second-stage ascending phase in the geocentric inertial coordinate system, to construct a series of optimization problems of maximum semi-major axis of circular orbit under the thrust drop fault. The method further includes using the adaptive pseudo-spectrum method to solve the optimization problems of maximum semi-major, and using the maximum and minimum method to normalize the sample data to [?1, 1], using the orthogonal least square method to select the data center of the radial basis function neural network (RBFNN), where the Gaussian function is selected as the radial basis function, and the RBFNN is trained offline to establish a nonlinear mapping relationship from the fault states to the optimal rescue orbital elements.

Abstract: A real-time imaging system for a three-dimensional ultrasonic seismic model, which is used for three-dimensional real-time imaging of a seismic model in an indoor water tank experiment, comprising: an ultrasonic sensor network, comprising at least one emitting probe and at least one receiving probe spaced apart from each other to form a network, which is arranged above a seismic model; and a hardware subsystem, comprising a main control unit, an acquisition unit, an emitting unit, an industrial computer and a display, wherein the acquisition unit, the emitting unit and the industrial computer are electrically connected to the main control unit, the emitting probe is electrically connected to the emitting unit, the receiving probe is electrically connected to the acquisition unit, the display is electrically connected to the industrial computer, and a software subsystem is configured in the industrial computer.

Abstract: A hologram projection system for a vehicle includes a controller, a housing including a plurality of through-holes formed in an upper surface of the housing, a casing used to store water, a sprayer mounted in the housing, fluidly connected to the casing, including a plurality of nozzles protruding through the through-holes in the upper surface of the housing, electrically connected to the controller, configured to spray water in the casing as water mist by performing a spray operation under a control of the controller, and configured to spray the water mist, and a hologram projection device provided in the housing, electrically connected to the controller, and including a light-emitting device mounted on the upper surface of the housing, in which the hologram projection device is configured to generate different beams under control of the controller and to form different patterns by projecting the different beams to the water mist.

Abstract: A rotary multifunctional speaker and a vehicle includes: a mounting plate; a speaker assembly including a first hemispherical housing and a speaker mounted in the first hemispherical housing; a mood light assembly including a second hemispherical housing and a light source mounted in the second hemispherical housing; and a driving assembly provided on the mounting plate, electrically connected to an in-vehicle computer, and controlled by the in-vehicle computer, in which the speaker is electrically connected to the in-vehicle computer, the light source is electrically connected to the in-vehicle computer, the first and second hemispherical housings form a spherical housing and are mounted on the mounting plate, and the driving assembly coupled to the spherical housing rotates the spherical housing relative to the mounting plate according to control performed by the in-vehicle computer to make one of the mood light assembly and the speaker assembly face the interior of the vehicle.

Abstract: The present invention discloses a method, equipment, and readable storage medium for tracking and evaluating the life cycle EUR of horizontal wells, and relates to the field of oil and gas development technology. The present invention divides the life cycle stages of fractured horizontal wells in unconventional oil and gas reservoirs, provides corresponding EUR evaluation steps for different life cycle stages based on the production performance characteristics of fractured horizontal wells in unconventional oil and gas reservoirs in the drilling and fracturing stage, extraction and testing stage, rapid production decline stage, and low pressure and small volume production stage, and establishes the EUR tracking and evaluation process of fractured horizontal wells in unconventional oil and gas reservoirs throughout their life cycle from drilling to abandonment.

Abstract: Disclosed herein are hydrogel precursor solutions, hydrogels, and methods of preparation and uses of the same. The hydrogels may be gelled at room temperature, in the absence of added light or heat, to yield ultra-strong hydrogel fibers suitable for load-bearing applications, or as adhesives or coatings. The hydrogels may include a polymerized polymer containing acrylic acid, additional acrylic acid, an organic acid such as citric acid, and an oxidizing agent such as a persulfate salt. Silver-lignin nanoparticle suspensions may be used to initiate a free radical oxidative decarboxylation reaction in the disclosed compositions. Hydrogels may be prepared from such compositions through incubation leading to gelling. The gelled hydrogels may be stretched or spun into hydrogel fibers having desirable mechanical properties, such as strength, stretchability, and adhesion.

Abstract: A map matching method and apparatus, an electronic device and a storage medium are provided. The method includes: acquiring initial positioning information of a vehicle and vehicle sensor data; determining a plurality of pieces of candidate positioning information on the basis of the initial positioning information; determining a plurality of observation semantic features on the basis of the vehicle sensor data; acquiring local map information on the basis of the initial positioning information of the vehicle, the local map information including a plurality of map semantic features; for each piece of candidate positioning information: converting the plurality of map semantic features into a coordinate system of the vehicle sensor; and matching the plurality of observation semantic features with the plurality of candidate map semantic features; and determining optimal candidate positioning information of the vehicle and a matching pair corresponding to the optimal candidate positioning information.

Abstract: A method for coupling hydraulic fracture network extension and production performance of a horizontal well in an unconventional oil and gas reservoir includes: establishing a complex hydraulic fracture network model of a fractured horizontal well in an unconventional oil and gas reservoir based on a fracture extension theory; constructing three-dimensional three-phase mathematical models of seepage for the fractured horizontal well based on an embedded discrete fracture model; and constructing a fully implicit numerical calculation model by a finite difference method through three-dimensional orthogonal grids, and solving iteratively, thereby accurately predicting a production performance characteristic of the fractured horizontal well in the unconventional oil and gas reservoir.

Abstract: A method for scalable multi-task learning with convex clustering includes: extracting features from a dataset of a plurality of tasks; generating a graph from the extracted features, nodes of the graph representing linear learning models, each of the linear learning models being for one of the tasks; constraining the graph using convex clustering to generate a convex cluster constrained graph; and obtaining a global solution by minimizing a graph variable loss function, the minimizing the graph variable loss function comprising: introducing auxiliary variables for each connection between nodes in the convex cluster constrained graph; iteratively performing the following operations until convergence: updating the linear learning models by solving a sparse linear system; and updating the auxiliary variables by solving an equation having the auxiliary variables each be proportional to a vector norm for their respective nodes.

Abstract: A method of continual learning in an artificial intelligence system through bi-level optimization includes providing a stored data sample of a current task and providing a neural network subdivided into two parts including a parameter part and a hyper-parameter part. The method further includes performing bi-level optimization by separately training the two parts of the neural network. The neural network has been trained, prior to the bi-level optimization, on data samples of previous tasks.

Abstract: A method for online learning from a data stream with an ensemble of meta-trees includes: observing a data instance from the data stream; for each of the meta-trees, replicating the data instance to generate a number of replicated data instances; for each of the meta-trees, updating meta-tree components using the number or replicated data instances; and inducing each of the meta-trees based on the data instance and the updated meta-tree components. Inducing each of the meta-trees includes employing inequality concentration bound to determine whether a split criterion is satisfied.

Abstract: The present disclosure provides heterodimeric antibodies that bind to two different target antigens at the same time. In one embodiment, the heterodimeric antibodies are bispecific antibodies. In one embodiment, the heterodimeric antibodies comprise three polypeptides including: a first polypeptide comprising an scFv-Fc fusion polypeptide; a second polypeptide comprising an immunoglobulin heavy chain; and a third polypeptide comprising an immunoglobulin light chain. In one embodiment, the first polypeptide includes one or more point mutations that confer increased thermal-stability to the first polypeptide.

Abstract: The present disclosure provides several embodiments of multi-specific antigen binding protein complexes. In some embodiments, the multi-specific antigen binding protein complex is composed of either two or three polypeptide chains that assemble with each other to form het-erodimeric complexes comprising two different Fab regions each capable of binding two different epitopes and comprising an Fc region which is capable of exhibiting Fc effector function, thus having a relatively simple structure compared to certain other multi-specific antibodies. In one embodiment, the multi-specific antigen binding protein complex is activatable as one of the polypeptide chains that compose the protein complex carries a cleavable linker.

Abstract: An optimal rescue orbital elements online decision-making method based on RBFNN for launch vehicles under thrust drop fault includes establishing the flight dynamic equations of launch vehicles in the second-stage ascending phase in the geocentric inertial coordinate system, to construct a series of optimization problems of maximum semi-major axis of circular orbit under the thrust drop fault. The method further includes using the adaptive pseudo-spectrum method to solve the optimization problems of maximum semi-major, and using the maximum and minimum method to normalize the sample data to [?1, 1], using the orthogonal least square method to select the data center of the radial basis function neural network (RBFNN), where the Gaussian function is selected as the radial basis function, and the RBFNN is trained offline to establish a nonlinear mapping relationship from the fault states to the optimal rescue orbital elements.

Abstract: A variation testing system environment for performing variation testing of web pages and applications is disclosed. Users requesting a view from a content provider are not randomly assigned to one of a plurality of variations of the view. Rather, a function is applied to each user's identifier in order to determine which variation of the view is provided to a client device of the user.

Abstract: A method of continual learning in an artificial intelligence system through bi-level optimization includes providing a stored data sample of a current task and providing a neural network subdivided into two parts including a parameter part and a hyper-parameter part. The method further includes performing bi-level optimization by separately training the two parts of the neural network. The neural network has been trained, prior to the bi-level optimization, on data samples of previous tasks.

Abstract: A method for processing an input data matrix so as to provide co-clustering assignments of rows and columns of the input data matrix includes generating, from the input data matrix, a graph of rows in the data matrix and a graph of columns in the data matrix, determining an objective function for generating a compact representation of the input data matrix, and generating the compact representation of the input data matrix by performing alternating optimization of the objective function until a test compact representation that causes the objective function to converge is generated. The method additionally includes generating a new graph of rows and a new graph of columns from the compact representation of the input data matrix, and returning a connected component of the new graph of rows and a connected component of the new graph of columns as the co-clustering assignments of the rows and columns.

Abstract: A method for online learning from a data stream with an ensemble of meta-trees includes: observing a data instance from the data stream; for each of the meta-trees, replicating the data instance to generate a number of replicated data instances; for each of the meta-trees, updating meta-tree components using the number or replicated data instances; and inducing each of the meta-trees based on the data instance and the updated meta-tree components. Inducing each of the meta-trees includes employing inequality concentration bound to determine whether a split criterion is satisfied.

Abstract: A computer-implemented method can include providing a data set arranged into multiple nodes and assigning a random variable and a hyper-parameter to at least one pair of the multiple nodes. The hyper-parameter can define a current probability distribution of the random variable. The method can further include: causing the random variable to occupy a discrete state based on the current probability distribution; sampling a graph structure for the data set based on the discrete state; adjusting a weight of a prediction model based on the sampled graph structure; estimating a gradient of the hyper-parameter based on the sampled graph structure and the adjusted weight; adjusting the hyper-parameter based on the estimated gradient; resampling a graph structure for the data set based on the adjusted hyper-parameter; and assigning a final graph structure to the data set based on the resampled graph structure.