Abstract: Non-human animals comprising a human or humanized IL-4 and/or IL-4R? nucleic acid sequence are provided. Non-human animals that comprise a replacement of the endogenous IL-4 gene and/or IL-4R? gene with a human IL-4 gene and/or IL-4R? gene in whole or in part, and methods for making and using the non-human animals, are described. Non-human animals comprising a human or humanized IL-4 gene under control of non-human IL-4 regulatory elements is also provided, including non-human animals that have a replacement of non-human IL-4-encoding sequence with human IL-4-encoding sequence at an endogenous non-human IL-4 locus. Non-human animals comprising a human or humanized IL-4R? gene under control of non-human IL-4R? regulatory elements is also provided, including non-human animals that have a replacement of non-human IL-4R?-encoding sequence with human or humanized IL-4R?-encoding sequence at an endogenous non-human C IL-4R? locus.

Abstract: The present disclosure describes methods, system, and devices for configuring a user equipment (UE) with priority information for measurement task. One method includes sending, by the RAN node, a configuration message to the UE, the configuration message comprising the priority information, so that the UE performs a measurement task and reports at least one measurement result according to the priority information; and receiving, by the RAN node, the at least one measurement result from the UE. Another method includes receiving, by the UE, a configuration message from a radio access network (RAN) node, the configuration message comprising the priority information; and performing, by the UE, a measurement task and reporting at least one measurement result according to the priority information.

Abstract: Copper-tin-nickel brazing material prepared by alloys recycled from E-waste, preparation method therefor, and system thereof are provided. A preparation method for the copper-tin-nickel brazing material includes the following steps: (a) spreading nano-SiO2 on the bottom of crucible and then adding a crude copper-tin-iron-nickel alloy recycled from E-waste; (b) heating the crucible to melt the crude alloy into a metal liquid so that Zn and Pb in the metal liquid react with the SiO2 to form a slag that floats out; (c) introducing a refining gas to the bottom of metal liquid in step (b), thereby removing the scums or gases formed by Pb, Fe, S, and O in the metal liquid; (d) performing heat-preserving directional solidification on the metal liquid, to bias-aggregate the Fe and Sb at one end and remove the same to obtain a copper-based intermediate alloy; and smelting and powdering the copper-based intermediate alloy.

Abstract: The technology of this disclosure relates to a method, an apparatus, a device, a storage medium, and a system for determining a collection period. The technology relates to the field of machine learning technologies. In this disclosure, a machine learning model is obtained by using a training dataset collected based on candidate collection periods of X features, and a candidate collection period of each of the X features is determined as a target collection period of each feature based on the obtained machine learning model and a first condition. Because the target collection period of each feature is greater than a minimum collection period of each feature, subsequently, if data is collected based on the target collection period of each feature, an amount of the collected data is reduced, to reduce collection load of a device and memory occupied by sampled data, thereby reducing time redundancy.

Abstract: A method for implementing a generic routing encapsulation (GRE) tunnel, an access point (AP), and a network system. The method includes establishing a Control And Provisioning of Wireless Access Points (CAPWAP) tunnel with an access controller (AC), receiving addresses of at least two gateways, establishing at least two GRE tunnels coupled to the gateways respectively according to the addresses of the at least two gateways, and selecting one of the at least two GRE tunnels to transmit data.

Abstract: This application provides a method, an apparatus, and a system for determining data flow information. The method includes: obtaining flow parameters of a plurality of data flows within a first time period; obtaining at least one data flow group according to the flow parameters of the plurality of data flows and a flow parameter rule of at least one preset access mode, where a relationship between data flows in each data flow group satisfies a flow parameter rule of one preset access mode; and determining group parameters of each data flow group.

Abstract: A device identification method, apparatus, and system are provided. A management device or a collection device first determines a network traffic feature of a to-be-identified device based on a first dataset. The first dataset includes a plurality of pieces of first data, and each piece of first data includes a data amount of a data packet that is of the to-be-identified device and that is collected within one first periodicity. Then, the management device or the collection device determines a device type of the to-be-identified device based on a device identification model and the network traffic feature of the to-be-identified device.

Abstract: A method, an apparatus, a system, a device, and a storage medium for implementing terminal verification are provided. In this method, a transmission feature of a terminal is reconstructed to verify the terminal. For example, if a difference between the transmission feature obtained through reconstruction and the transmission feature of the terminal is relatively large, it indicates that the transmission feature of the terminal is abnormal, and the terminal is an abnormal terminal. In this case, it is determined that the verification of the terminal fails.

Abstract: This application provides a data collection method and a device. A data collection device determines, based on a threshold corresponding to a target indicator, a collection interval for to-be-collected data of the target indicator from a plurality of available collection intervals; and the data collection device collects the data of the target indicator based on the collection interval.

Abstract: In an embodiment, a data collection method includes: collecting, by a data collection device, performance indicator data of a target device based on a collection periodicity; detecting change amplitude of the collected performance indicator data that is in a change detection window, where the change detection window includes multiple collection periodicities; and when it is detected that change amplitude of the performance indicator data that is in the change detection window is greater than or equal to a change detection threshold, sending the performance indicator data that is in the change detection window to a data analysis device.

Abstract: A method, an apparatus, and a device for obtaining an artificial intelligence model, and a storage medium are provided. A client receives a first artificial intelligence AI model sent by a service end (303). The first AI model includes a plurality of neurons. The client determines, from the plurality of neurons, a target neuron participating in a current round of training, where the current round of training is a non-first round of training, and a quantity of target neurons is less than a total quantity of the plurality of neurons (304). The client trains the target neuron based on local data (305). The client returns parameter data corresponding to the target neuron to the service end (306). The parameter data corresponding to the target neuron is used by the service end to obtain a converged target AI model.

Abstract: This application provides network device capacity expansion methods and devices. One method includes: obtaining network performance data of a target network device, determining a state of the target network device based on the network performance data of the target network device, and determining, based on the state of the target network device, whether to perform capacity expansion for the target network device. In the foregoing technical solution, whether a capacity expansion operation needs to be performed on a network device can be determined in a timely manner based on a state of the network device.

Abstract: A network quality determining method includes, when experience quality represented by a customer experience index of a target user within a first time period is lower than experience quality represented by a customer experience index threshold, determining, using a first parameter value that is of a network key performance indicator (KPI) parameter of the target user within a second time period and that is collected by a collection device in a carrier network, a second parameter value of the network KPI parameter of the target user within the second time period in a home network, and when network quality represented by the second parameter value of the network KPI parameter is lower than network quality represented by a first threshold corresponding to the network KPI parameter in the home network, determining that quality of the home network is poor.

Abstract: A method and an apparatus for updating an application identification model, and a storage medium are provided. A client device may determine a plurality of training samples based on identification results of a plurality of pieces of data traffic, and train an application identification model using the training samples. Then, the client device may upload model data of the trained application identification model to a server, and the server performs joint update based on the model data uploaded by a plurality of client devices. Then, the client device may obtain a jointly updated application identification model based on jointly updated model data delivered by the server.

Abstract: A network device includes: a network interface configured to receive target data, a first processor configured to determine feature information of the target data, a second processor configured to perform preprocessing on the feature information, and a third processor configured to perform inference on a preprocessing result. In addition, the second processor is further configured to perform policy analysis based on an inference result.

Abstract: A method for implementing a generic routing encapsulation (GRE) tunnel, an access point (AP), and a network system. The method includes establishing a Control And Provisioning of Wireless Access Points (CAPWAP) tunnel with an access controller (AC), receiving addresses of at least two gateways, establishing at least two GRE tunnels coupled to the gateways respectively according to the addresses of the at least two gateways, and selecting one of the at least two GRE tunnels to transmit data.

Abstract: A forwarding device receives at least one service flow; the forwarding device obtains service information of the at least one service flow, where the service information of the service flow includes identification information of a network object to which the service flow belongs and M key performance indicators KPIs of the service flow, M is an integer greater than 0, and the network object includes one or more devices; and the forwarding device sends training information to a first device, where the training information includes the service information of the at least one service flow or a feature set obtained based on the service information of the at least one service flow, the training information is used to train a fault detection model, and the fault detection model is used to detect whether the network object is in a faulty state.

Abstract: In certain embodiments, a forwarding device receives at least one service flow. The forwarding device obtains service information of the at least one service flow, where the service information of the service flow includes identification information of a network object to which the service flow belongs and M key performance indicators KPIs of the service flow. M is an integer greater than o, and the network object includes one or more devices. The forwarding device sends detection information to a first device, where the detection information includes the service information of the at least one service flow or a feature set obtained based on the service information of the at least one service flow. The detection information is used to detect whether the network object is in a faulty state.

Abstract: A fault localization method includes: obtaining user experience data, network topology data, and resource management data that are of a video service; where the network topology data is used to represent a connection relationship between network devices, and the resource management data is used to represent a connection relationship between user equipment and the network devices; determining a QoE experience indicator of a network device based on the user experience data, the network topology data, and the resource management data; and when QoE represented by the QoE experience indicator of the network device is lower than QoE represented by a device screening threshold, determining the network device as a possible questionable device.

Abstract: A model update system, which may be applied to the network control field, includes a site analysis device and a first analysis device. The site analysis device is configured to: receive a first model sent by the first analysis device; train the first model by using a first training sample to obtain a second model, where the first training sample includes first feature data of a network device in a site network corresponding to the site analysis device; obtain differential data between the first model and the second model; and send the differential data to the first analysis device. The first analysis device is configured to: send the first model to the site analysis device; receive the differential data sent by the site analysis device; and update the first model based on the differential data to obtain a third model.