Abstract: An electrode assembly, a battery cell, a battery, and an electrical apparatus are disclosed. The electrode assembly includes a first electrode plate, the electrode plate includes a current collector and active material layers arranged on the current collector, the active material layer is provided with a plurality of material removal regions at intervals in an extension direction (L) of the first electrode plate, and the material removal region extends in a width direction (Y) of the first electrode plate; the active material layer is provided with a marking portion, a width of the marking portion in the extension direction (L) of the first electrode plate is greater than or equal to a width of the material removal region, and the marking portion spans across the material removal region.

Abstract: A communication method includes: a terminal device sends, to a network side device, information indicating that a first user identity of the terminal device and a second user identity of the terminal device are associated with the terminal device; and the terminal device receives, by using the first user identity, paging information corresponding to the second user identity of the terminal device. In the method, the terminal device receives a paging-related message or paging-related information in a cell corresponding to a single user identity, to monitor paging information of a plurality of user identities of the terminal device, so that the plurality of user identities of the terminal device can be effectively paged.

Abstract: Some embodiments of this application provide an electrode assembly, a battery cell, a battery, and an electrical device. The electrode assembly includes at least one first electrode plate, where the first electrode plate is bent and includes: a current collector; and an active material layer, disposed on the current collector. The active material layer includes a material-removed region in at least a part of bends of the first electrode plate. The material-removed region extends along a width direction of the first electrode plate. A depth of the material-removed region does not exceed a thickness of the active material layer at which the material-removed region is located.

Abstract: A method of counting photons using a plurality of single photon avalanche diodes (SPADs), including initiating a detection phase, enabling each single photon avalanche diode (SPAD) of the plurality of SPADs for a period of time within the detection phase, accumulating a SPAD event from each SPAD of the plurality of SPADs, wherein each SPAD event corresponds to a detection of a single photon, determining a counter code at an end of the detection phase, where the counter code corresponds to accumulated SPAD events, and enabling one or more SPADs of the plurality of SPADs within an exposure phase based on the counter code, where the counter code is greater than an expected number of the SPAD events during the exposure phase, and where the expected number of SPAD events during the exposure phase is based on the counter code that is determined at the end of the detection phase.

Abstract: Methods of making such compounds, powders, and cathode active materials are described. The powders are formed of particles with specific properties: a particle size distribution with a D50 ranging from 10 ?m to 20 ?m, a D10 less than 8 ?m, and a D99 of the particles ranges from 25 ?m to 35 ?m. The final compound is represented by the Formula Li?(Co1-x-y-zMnxMezAly)O?, wherein 0.95<?<1.05, x?1.00, 0<y?0.04, 0<z?0.050, and ??2.

Abstract: A method for predicting traffic flow or a travel time, includes: obtaining navigation route data; obtaining, according to the navigation route data, navigation flow of a road within a prediction time period; obtaining real-time traffic flow, a real-time travel time, past traffic flow, and a past travel time of the road; and training a neural network with the real-time travel time, the past travel time, the real-time traffic flow, the past traffic flow, and the navigation flow of the road to obtain predicted traffic flow or a predicted travel time of the road within the prediction time period.

Abstract: This application provides a method, includes: receiving a second message from a second network node, wherein the second message comprises identification information of a terminal device, and wherein the identification information of the terminal device is in association with context information of the terminal device that is stored at a first network node; retrieving based on the identification information of the terminal device, the context information of the terminal device stored at the first network node; and, replacing the original cell radio network temporary identifier with a new cell radio network temporary identifier allocated by the first network node for the context information of the terminal device.

Abstract: The disclosed technology involves autonomously identifying goals and sub-goals from a user utterance and generating responses to the user based on the goals and sub-goals.

Abstract: Compounds, particles, and cathode active materials that can be used in lithium ion batteries are described herein. Methods of making such compounds, powders, and cathode active materials are described. The particles have a particle size distribution with a D50 ranging from 10 ?m to 20 ?m.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive configuration information that specifies one or more parameters associated with generating, by the UE, a time domain covariance matrix specific to the UE. The UE may receive a channel state information (CSI) reference signal (CSI-RS). The UE may transmit, based at least in part on the CSI-RS and the one or more parameters, a CSI report, the CSI report including data representing the time domain covariance matrix. Numerous other aspects are described.

Abstract: A method for predicting traffic flow or a travel time, includes: obtaining navigation route data; obtaining, according to the navigation route data, navigation flow of a road within a prediction time period; obtaining real-time traffic flow, a real-time travel time, past traffic flow, and a past travel time of the road; and training a neural network with the real-time travel time, the past travel time, the real-time traffic flow, the past traffic flow, and the navigation flow of the road to obtain predicted traffic flow or a predicted travel time of the road within the prediction time period.

Abstract: The embodiments of the present application provide a method and apparatus for modulation recognition of signals based on cyclic residual network, the method comprises: obtaining a signal matrix of a to-be-recognized signal, and extracting real part information and imaginary part information of the signal matrix; generating, according to extracted real part information and imaginary part information, a real-and-imaginary-part feature matrix of the to-be-recognized signal; converting, according to a preset matrix conversion method, the real-and-imaginary-part feature matrix into an amplitude-and-phase feature matrix; and inputting the amplitude-and-phase feature matrix into a pre-trained cyclic residual network to obtain a modulation mode corresponding to the to-be-recognized signal.

Abstract: The present disclosure provides a time calibration method, an electronic device, and a storage medium, and relates to the technical field of automatic driving. The method can include: determining a first observation error between first reference time point and first system time point; determining a second observation error between second reference time point and second system time point; determining a unit drift per second of the system to be calibrated based on the first system time point, the second system time point, the first observation error, and the second observation error; and calibrating the time of the system to be calibrated based on the unit drift per second.

Abstract: A device and a method for recognizing person activity in a sequence of frames (100) comprising: obtaining a set of consecutives 3D poses (103), obtaining a feature map (102), obtaining a vector of spatiotemporal features, obtaining a matrix of spatial attention weights, obtaining a matrix of temporal attention weights (110), modulating (106) the feature map using the matrix of spatial attention weights to obtain a spatially modulated feature map, modulating (111) the feature map using the vector of temporal attention weights to obtain a temporally modulated feature map, performing a convolution (114) of the spatially modulated feature map and of the temporally modulated feature map to obtain a convoluted feature map, performing a classification (115) using the convoluted feature map so as to determine the activity of the person in the video.

Abstract: The embodiments of the present application provide a method and apparatus for modulation recognition of signals based on cyclic residual network, the method comprises: obtaining a signal matrix of a to-be-recognized signal, and extracting real part information and imaginary part information of the signal matrix; generating, according to extracted real part information and imaginary part information, a real-and-imaginary-part feature matrix of the to-be-recognized signal; converting, according to a preset matrix conversion method, the real-and-imaginary-part feature matrix into an amplitude-and-phase feature matrix; and inputting the amplitude-and-phase feature matrix into a pre-trained cyclic residual network to obtain a modulation mode corresponding to the to-be-recognized signal.

Abstract: A method for predicting traffic flow or a travel time, includes: obtaining navigation route data; obtaining, according to the navigation route data, navigation flow of a road within a prediction time period; obtaining real-time traffic flow, a real-time travel time, past traffic flow, and a past travel time of the road; and training a neural network with the real-time travel time, the past travel time, the real-time traffic flow, the past traffic flow, and the navigation flow of the road to obtain predicted traffic flow or a predicted travel time of the road within the prediction time period.