Abstract: This disclosure describes methods and systems for exchanging AI computing information for load prediction model between network elements of a wireless communication network. The methods include: sending, by a first network element of a wireless communication network, a first message for load prediction to a second network element of the wireless communication network, wherein the first message comprises at least one of an input to a machine learning model for load prediction of the first network element or model configuration information of the machine learning model.

Abstract: This document generally relates to wireless communication that includes a location management function (LMF) and at least one radio access network (RAN) node that perform an interaction associated with at least one sidelink positioning reference signal (SL-PRS) configuration. The LMF or the at least one RAN node transmits a plurality of non-overlapping SL-PRS configurations to a plurality of user devices based on the interaction.

Abstract: Systems, methods, and apparatus for wireless communications are described. A wireless communication method includes transmitting, by a network node, a request for input data. The method further includes receiving, by the network node and in response to the request, input data. The described techniques may be adopted by a network device or by a wireless device.

Abstract: Disclosed are a network optimization method and apparatus, an electronic device, and a storage medium. The network optimization method may include: sending data analytics request information to a core network; receiving data analytics response information fed back by the core network and determining a model processing result according to an artificial intelligence learning model; and performing a network optimization operation according to the model processing result.

Abstract: An effect video determining method, an effect video determining apparatus, an electronic device, and a storage medium are provided by embodiments of the present disclosure. The method includes: obtaining an uploaded image in response to an effect trigger operation; determining, according to position information of a capturing device, a target perspective image from a 3D image surrounding scenario corresponding to the uploaded image; and generating and displaying an effect video frame based on the target perspective image and a target object, until receiving an operation to stop capturing an effect video.

Abstract: Provided are a twist-bend nematic (NTB) LC dimer-based material and use thereof, and an LC-based cholesteric heliconical (CH) material and use thereof. The NTB LC dimer-based material is at least one selected from the group consisting of CBnCB, CBnOCB, and CBOnOCB, with n being a positive integer of 3 to 15. Based on ultra-stable properties of the material, the disclosure further provides the LC-based CH material, which uses the LC dimer-based material as a key raw material and integrates a conventional nematic LC monomer material and a chiral molecule.

Abstract: A semiconductor device can include: a substrate; a well region located in the substrate and having a first doping type; a body region located in the substrate and having a second doping type that is opposite to the first doping type; a source region located in the body region and having the first doping type; a drain region located in the well region and having the first doping type; an isolation structure located on the substrate and between the drain region and the source region; and a gate structure located on the isolation structure and including a first gate region and a second gate region, where the first gate region is of the first doping type, and the second gate region is of the second doping type.

Abstract: A method and apparatus for determining an effect video, an electronic device, and a storage medium are provided. The method includes: in response to an effect triggering operation, adding a virtual effect model for a target object; and based on audio information collected, controlling a target virtual part of a virtual effect model corresponding to the target object to move, and adjusting a target entity part of the target object to a preset state to obtain a target effect video.

Abstract: Provided are a handover method, a handover device, and a network system. The handover method includes: receiving cell information of a second cell sent by a second network element, wherein the second cell is a cell managed by the second network element, and the cell information includes predicted cell load information of the second cell; and sending a handover instruction to a terminal in a case where the cell information satisfies a preset condition, wherein the handover instruction is used for instructing the terminal to perform handover to the second cell, and the case where the cell information satisfies the preset condition at least indicates that the predicted cell load information of the second cell is lower than a configured first threshold.

Abstract: The present disclosure relates to wireless communications, including receiving, by a Base Station (BS), authorized information for at least one of ranging or Sidelink (SL) positioning service for a first wireless communication device and storing, by the BS, the authorized information in a device context for the first wireless communication device.

Abstract: This patent document describes, among other things, techniques, and apparatuses for providing artificial intelligence to improve wireless network efficiency and performance. In one aspect, a method of wireless communication is disclosed. The method includes transmitting, from a first network node to a second network node, a first network control message requesting to start an artificial intelligence process comprising an artificial intelligence objective or an identification code. The method further includes receiving, at the first network node from the second network node, a first reply message indicating at least one of the artificial intelligence process has started, the identifier, a request indicator for a model for the artificial intelligence process, or a failure message.

Abstract: In wireless communications, accuracy in positioning methods may be important. Sidelink positioning communications with sidelink positioning reference signal may be used. Including sidelink positioning information in those communications may improve the positioning. The sidelink positioning information may include a sidelink positioning reference signal configuration and/or a sidelink communication resource. The communications may be with a location management function and/or between a basestation centralized unit and a basestation distributed unit. Further, the communications may be through transmission/reception point communications or through sidelink positioning reference signal communications.

Abstract: Disclosed are a location prediction method and apparatus, a network element, a base station and a non-transitory computer-readable storage medium. The position prediction method may include: receiving, by a location service network element, a Minimization of Drive Tests (MIDT) measurement information message sent by a base station, wherein the location service network element is a separate network element or a network element inside the base station, and the MDT measurement information message carries history location measurement information of at least one user equipment (UE); determining, by the location service network element, predicted location information of the at least one UE for a first time point or a first time period according to the history location measurement information of the at least one UE; and sending, by the location service network element, the predicted location information to the base station.

Abstract: A device for supplementary doping on monocrystalline silicon alloy and methods for supplementary doping are provided. The device includes a hoisting member, a connecting member, and a containing member which are arranged in sequence from top to bottom in a vertical direction, wherein the hoisting member is connected with one end of the connecting member, and another end of the connecting member is movably connected with the containing member, so that the containing member is rotatable with respect to the connecting member. The containing member is provided with a first through-hole and a second through-hole, and the connecting member and the containing member are connected at a joint. A distance between the first through-hole and the joint is less than a distance between the second through-hole and the joint in the vertical direction.

Abstract: A bandwidth extension (BWE) method includes: determining parameters of a low-frequency spectrum of a narrowband signal; inputting the parameters of the low-frequency spectrum into a neural network model, and obtaining a correlation parameter based on an output of the neural network model; obtaining a target high-frequency amplitude spectrum based on the correlation parameter and a low-frequency amplitude spectrum; obtaining a high-frequency spectrum based on a low-frequency phase spectrum and the target high-frequency amplitude spectrum of the narrowband signal; and obtaining a broadband signal after BWE based on the low-frequency spectrum and the high-frequency spectrum.

Abstract: A water environment temperature measurement tool includes measurement boxes and a counterweight box; a plurality of groups of the measurement boxes are provided; the counterweight box is movably connected with a group of measurement boxes; and each measurement box is provided with a temperature measurement instrument inside. The water environment temperature measurement tool further comprises: control mechanisms, each comprising a water inlet pipe, a water retaining member, an elastic member, a control assembly, a rotating seat, a rotating shaft, a second screw rod, a control seat and a rotary assembly. In the water environment temperature measurement tool of the present invention, the control mechanisms can achieve extraction and temperature measurement of water at different water body depths by cooperating with the measurement boxes and the temperature measurement instruments.

Abstract: Disclosed are a network optimization method and apparatus, an electronic device, and a storage medium. The network optimization method may include: sending data analytics request information to a core network; receiving data analytics response information fed back by the core network and determining a model processing result according to an artificial intelligence learning model; and performing a network optimization operation according to the model processing result.