Abstract: Method, system, medium, and implementation for robot-guided instrument insertion. A preplanned path between a three-dimensional (3D) entry pose on skin of a patient to a 3D pose of a target is generated for a surgery with a target inside the patient. The preplanned path is used by a robot as guidance to insert a surgical instrument from the 3D entry pose to reach the 3D pose of the target. During the surgery, a next pose is determined based on a current pose of the surgical instrument and the preplanned path as well as spatial relationship to surrounding anatomical structures and is used to move the surgical instrument thereto. An updated current pose of the instrument is then obtained via tracking when the robot is advancing the surgical instrument to the next pose. The process repeats until the instrument reaches the target pose.

Abstract: The present disclosure relates to a new generation mobile network, and particularly to the generation of analytics information in the network. To this end, the disclosure proposes a first network entity for generating the analytics information, and proposes a second network entity and a third network entity, respectively, for supporting the analytics generation. The first network entity is configured to obtain, from the second network entity or from one or more third network entities, past and/or current association information for an area of interest. Further, it is configured to provide analytics information based on the obtained association information for the area of interest. The past and/or current association information indicates one or more other network entities and/or network properties that, respectively, have been and/or are mapped to or serving the area of interest.

Abstract: The present teaching relates to automated trocar/robot base location determination. An input related to a surgical operation includes a three-dimensional (3D) model for an organ with cut points on the organ forming a surgical trajectory. A surgical instrument is controlled by a robot to reach the cut points to carry out the operation. An insertion location for inserting the surgical instrument is identified. Based on the identified insertion location, a robot base location is determined with respect to the identified insertion location to deploy the robot for controlling the surgical instrument to reach the cut points. Signals for configuring the surgical setting are then generated based on the insertion location for the surgical instrument and the base location for the robot.

Abstract: The present invention relates to performing mobile network configurations or changes. The invention presents a first device for performing the mobile network configuration or change, and a second device for generating feedback for supporting the mobile network configuration or change. The first device is configured to send a support request to the second device, wherein the support request specifies a reusable or specific feedback type and a target information. The second device is configured to send reusable or specific feedback about the target information in response to the support request. The first device is then configured to determine a configuration or change of the mobile network based on the reusable or specific feedback. The reusable feedback includes a value or set of values of the target information and at least one coordination parameter indicating how the reusable feedback is to be used by multiple second devices.

Abstract: The present disclosure relates to handover (HO) of a user equipment (UE), which consumes a quality of service (QoS) flow that is associated with multiple QoS profiles. The disclosure proposes a network entity for supporting HO of the UE, and proposes a second network entity that is the target of HO of the UE. The network entity is configured to: obtain multiple QoS profiles associated with a QoS flow; obtain QoS capability information indicating whether the second network entity supports more than one QoS profile and/or whether a first network entity supports more than one QoS profile; and provide at least one message to the second network entity, wherein the at least one message includes at least one QoS profile according to the QoS capability information.

Abstract: Method and system for estimating 3D camera pose based on 2D features. 3D virtual camera poses are generated, each of which is used to determine a perspective to project a 3D model of a target organ to create a 2D image of the target organ. 2D features are extracted from each 2D image and paired with the corresponding 3D virtual camera pose to represent a mapping. A 2D feature-camera pose mapping model is obtained based on the pairs. Input 2D features extracted from a real-time 2D image of the target organ are used to map, via the 2D feature-camera pose mapping model, to a 3D pose estimate of a laparoscopic camera, which is then refined to derive an estimated 3D camera pose of the laparoscopic camera via differential rendering of the 3D model with respect to the 3D pose estimate.

Abstract: The disclosure relates to a network entity for determining at least one model parameter of a model for digitally analyzing input data depending on the at least one model parameter of a model, the network entity being configured to receive a model request from a requesting entity over the communication network, the model request requesting the at least one model parameter of the model, to obtain the requested at least one model parameter by at least one of the following: executing a machine-learning model training algorithm, the machine-learning model training algorithm being configured to train the model with input data in order to determine at least one of the requested model parameter; searching a local data base for an existing model; or requesting the at least one model parameter from a further network entity; and to send the requested model parameter towards the requesting entity over the communication network.

Abstract: A method for suppressing a narrow pulse is provided. The method is applied to a bridge switch circuit having at least one bridge arm which has an upper switch transistor and a lower switch transistor, and includes: detecting whether an original comparison value of a modulated wave in a current cycle is in a preset narrow pulse interval of the upper switch transistor, and if so, determining an adjustment interval of the upper switch transistor to which the original comparison value of the modulated wave currently pertains; and adjusting the original comparison value of the modulated wave to an adjusted comparison value of the modulated wave corresponding to the adjustment interval of the upper switch transistor to which the original comparison value of the modulated wave currently pertains according to a corresponding relationship between adjustment intervals of the upper switch transistor and adjusted comparison values of the modulated wave.

Abstract: An entity, particularly a Radio Access Network (RAN) entity, adjusts Quality of Service (QoS) of at least one QoS flow in a RAN. The entity is configured to: obtain assistance information for an adjustment of at least one QoS profile for the at least one QoS flow of at least one wireless communication device, particularly of at least one user equipment (UE); and provide, to a second entity, particularly to a Core Network (CN) entity, a request for an adjustment or QoS information for the adjustment from a first QoS profile to a second QoS profile of a first QoS flow. The request or the QoS information is based on the assistance information.

Abstract: Analytics information is generated in a new generation mobile network. A first network entity generates the analytics information, and a second network entity and a third network entity support the analytics generation. The first network entity is configured to obtain, from the second network entity or from one or more third network entities, past and/or current association information for an area of interest. Further, it is configured to provide analytics information based on the obtained association information for the area of interest. The past and/or current association information indicates one or more other network entities and/or network properties that, respectively, have been and/or are mapped to or serving the area of interest.

Abstract: The present disclosure provides a network entity for a wireless network system. The network entity is configured to obtain an ingress time of a received packet, the ingress time indicating the time at which the packet enters the network system, determine time information regarding the packet based on the ingress time, and provide the time information to another network entity. A further network entity for a wireless network system is configured to obtain time information regarding a received packet from another network entity, and obtain an egress time of the packet, the egress time indicating a time at which the packet leaves the network system, based on the time information. This disclosure also relates to the network entities that are configured to synchronize an internal time valid at the network entities with an external time valid at an external network entity.

Abstract: The present invention relates to the generation of analytics information in a mobile network. To this end, the invention proposes network entities and corresponding methods that support the analytics generation. In particular, the network entities and methods facilitate the gathering of information required for the analytics generation. In particular, a network entity for analytics generation is configured to obtain network slice association (NSA information and/or user plane association (UPA) information from one or more other network entities, wherein the NSA information indicates a relation between an Access Network (AN) property and a Core Network (CN) property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network. Further, the network entity is configured to provide analytics information, the analytics information being based on the obtained NSA information and/or UPA information.

Abstract: The present disclosure relates to time-aware Quality-of-Service (QoS), in particular techniques for providing time-aware QoS in communication systems such as 5G NR (New Radio). In particular the disclosure relates to a device for translating between a first communication network, in particular a deterministic communication network, and a second communication network, in particular a mobile communication network, in particular a 5G communication network, wherein the device comprises: an application function that is configured to translate between Quality-of-Service (QoS) parameters of the first communication network and QoS parameters of the second communication network; a QoS profile comprising the QoS parameters of the first communication network translated by the application function and, optionally, additional QoS parameters originating from the second communication network; and a signaling procedure configured to exchange the translated QoS parameters within the second communication network.

Abstract: The present disclosure relates to performing mobile network configurations or changes. A first device is presented for performing the mobile network configuration or change, and a second device is presented for generating feedback for supporting the mobile network configuration or change. The first device is configured to send a support request to the second device, wherein the support request specifies a reusable or specific feedback type and a target information. The second device is configured to send reusable or specific feedback about the target information in response to the support request. The first device is then configured to determine a configuration or change of the mobile network based on the reusable or specific feedback. The reusable feedback includes a value or set of values of the target information and at least one coordination parameter indicating how the reusable feedback is to be used by multiple second devices.

Abstract: The present application provides fusion proteins that have two polypeptides, each having an extracellular domain and an intracellular domain, and the two extracellular domains form a binding site for TGF? and the two intracellular domains form the intracellular domain of an IL-23 receptor complex. The present application also provides nucleic acids encoding the fusion proteins, vectors comprising the nucleic acids, and engineered cells expressing the fusion proteins. Method of producing the engineered cells and methods of treatment that involves administering engineered cells are also provided.

Abstract: A first entity for a communication network is provided. The first entity is configured to receive a feature mapping indication from a second entity of the communication network. The feature mapping indication comprises characteristics of a relationship between a set of data samples and properties of data in the data samples of the set of data samples for an analytics model at an analytics stage, wherein the feature mapping indication comprises a request for a feature mapping data structure. The feature mapping data structure includes a second set of data samples based on the relationship between the set of data samples and the properties of the data in the data samples of the set of data samples for use with the analytics model at the analytics stage for an analytics consumer.

Abstract: An egress traffic disambiguation system receives a request with source egress location metadata identifying the source egress location. The source egress location can include authentication context data and local area subnetwork identifying metadata. The egress traffic disambiguation system disambiguates the source location of the request and provides the source location to a traffic data aggregation system which aggregates the request to the identified source location.

Abstract: Analytics information can be used in a mobile network. Network entities and corresponding methods support the generation of such analytics information. In particular, network entities and methods can facilitate the gathering of information required for the analytics generation. A network entity for analytics generation may be configured to obtain network slice association (NSA) information and/or user plane association (UPA) information from one or more other network entities, where the NSA information indicates a relation between an Access Network (AN) property and a Core Network (CN) property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network. Further, the network entity may be configured to provide analytics information, the analytics information being based on the obtained NSA information and/or UPA information.

Abstract: A network entity determines at least one model parameter of a model for digitally analyzing input data depending on the at least one model parameter of a model, the network entity being configured to receive a model request from a requesting entity over the communication network, the model request requesting the at least one model parameter of the model, to obtain the requested at least one model parameter by at least one of the following: executing a machine-learning model training algorithm, the machine-learning model training algorithm being configured to train the model with input data in order to determine at least one of the requested model parameter; searching a local data base for an existing model; or requesting the at least one model parameter from a further network entity; and to send the requested model parameter towards the requesting entity over the communication network.

Abstract: Implementations are described herein for augmenting a traditional search session with stateful chat—via what will be referred to as a “generative companion”—to facilitate more interactive searching. In various implementations, a query may be received, e.g., from a client device operated by a user. Contextual information associated with the user or the client device may be retrieved. Generative model (GM) output may be generated based on processing, using a generative model, data indicative of the query and the contextual information. Synthetic queries may be generated using the GM output, and search result documents (SRDs) may be selected. State data indicative of: the query, contextual information, one or more of the synthetic queries, and the set of search result documents, may be processed to identify a classification of the query. Based on the classification downstream GM(s) may be selected and used to generate one or more additional GM outputs.