Abstract: In a sensing session establishment process, an access point sends a first frame to a first station, where the first frame includes first information, the first information indicates a first role of the first station in a sensing session, the first role of the first station in the sensing session is a transmitter and/or a receiver, and the first station is a station participating in the sensing session in a second station associated with the access point; and the access point receives a second frame from the first station, where the second frame includes confirm information for the first frame.

Abstract: Aggregated log index-based log record identification is provided by maintaining log files of a database system on a plurality log storage devices, the log files including log records of changes to database objects, indexing the log files to obtain a collection of log indexes, where the indexing includes, for each log storage device, indexing log records stored on the log storage device to obtain a respective log index, then based on a request, identifying log storage devices that store log records for servicing the request, the log storage devices storing log indexes, of the collection of log indexes, that index an aggregate set of log records on the log storage devices, obtaining the log indexes from the log storage devices, and aggregating the log indexes to provide an aggregated log index that provides an index of the aggregate set of log records on the log storage devices.

Abstract: The present disclosure provides methods for identifying cells in an image. An apparatus for identifying cells in an image is also provided by the present disclosure. Further provided herein is a non-transitory computer-readable storage medium for performing the methods disclosed herein. Methods of diagnosing a disease or disorder and of treating a disease or disorder in a subject using the methods disclosed are also provided herein.

Abstract: Certain aspects of the present disclosure provide techniques for reporting an indication of a PHR when the UE's assigned of UL resources is insufficient to transmit both UL data and a PHR. Additionally, aspects described herein introduce a negative PHR used to indicate the UE requires additional UL resources.

Abstract: A method and system for predicting an insulated gate bipolar transistor (IGBT) lifetime based on compound failure mode coupling are provided. First, a simultaneous failure probability model of a bonding wire and a solder layer is calculated. Next, expectancy of the simultaneous failure probability model is calculated and recorded as a lifetime under a coupling effect. A coupling function relation is established. A lifetime of the solder layer and a lifetime of the bonding wire are predicted. An IGBT lifetime prediction model not taking the coupling effect into account is established. An IGBT lifetime prediction model taking the coupling effect into account is established. In the disclosure, the lifetime of the IGBT module under the coupling effect of the solder layer and the bonding wire may be accurately predicted.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive information indicating a condition for a conditional handover, and an indication to communicate on a source cell after transmitting a message on a target cell, associated with the conditional handover, and before receiving an additional message on the target cell. The UE may transmit the message on the target cell responsive to the condition for the conditional handover being satisfied. Numerous other aspects are described.

Abstract: An assembled subway station and a construction method thereof are provided. The assembled subway station includes a plurality of components combined in a ring shape, comprising a bottom plate component, two bottom corner components, two side wall components, a middle plate component, two top corner components, and a top plate component. Connection surfaces of each component are each provided with a concave-convex structure being matched with another concave-convex structure on a relevant connection surface of an adjacent component. Butt joint positions of two adjacent components are filled with sealing structures. The embedded grooves of two adjacent components are oppositely arranged, and connecting members for exerting opposite fastening forces on the two adjacent components are installed in the oppositely arranged embedded grooves.

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.