Abstract: Controlling and provisioning a robot of a virtual machine (VM) includes transmitting a connection request between a first service installed in a virtual machine and a second service. The robot is associated with at least one process running on the virtual machine. The virtual machine is authenticated based on a token associated with the second service and the virtual machine. A connection is established between the first service and the second service. A command is transmitted associated with the controlling of the robot from the second service to the first service based on the authentication of the virtual machine. The command is associated with a corresponding command identifier for identifying a type of the command. The command is then executed for controlling the robot.

Abstract: An array substrate includes a substrate, a first metal layer and an active layer disposed on the substrate, an interlayer insulating layer, and a second metal layer. The first metal layer forms at least one first trace, the interlayer insulating layer is disposed on the first metal layer and the active layer, the second metal layer is disposed on the interlayer insulating layer, the interlayer insulating layer is formed with a first contact hole, and the second metal layer is connected to the first trace through the first contact hole. The first metal layer includes a conductive layer and a first protective layer stacked in sequence.

Abstract: A tissue resection system and a method for determining a cutting parameter, the method comprising the following steps: acquiring a three-dimensional ultrasonic image of a target tissue; slicing the three-dimensional ultrasonic image to form a series of two-dimensional slice images, according to a preset step size; determining contour information the two-dimensional slice images; and calculating a cutting parameter on the basis of the determined contour information comprising contour information of an ablation tool and contour information of the target tissue, the cutting parameter comprising at least one of: a cutting position parameter (L), a cutting depth parameter (R), and a cutting angle parameter (?). Therefore, a cutting parameter can be calculated more efficiently, and a more reasonable and larger cutting range can be planned more precisely, thus resection efficiency, the resection area, and safety are all achieved.

Abstract: The present application discloses a display panel and an electrical terminal. The display panel includes: an underlay; an array driver layer located on the underlay and including a gate electrode layer and a source and drain electrode layer; a signal line including an adaptor portion located in the non-display region, wherein the adaptor portion includes a first wire section disposed in a same layer with the gate electrode layer, a second wire section disposed in a same layer with the source and drain electrode layer, and a bridge portion electrically connected to the first wire section and the second wire section; wherein the first wire section, the second wire section, and the bridge portion are disposed in different layers.

Abstract: A sensor control method includes: obtaining first indication information, where the first indication information indicates a first scenario; determining a configuration parameter of at least one sensor based on the first indication information, where the configuration parameter is corresponding to the first scenario; and sending the configuration parameter to the at least one sensor. The sensor control method may be applied to automatic driving or intelligent driving, and may be specifically applied to assisted driving or unmanned driving. The sensor can be flexibly controlled through configurable parameters of sensors such as radar or a camera.

Abstract: Techniques for carbon sequestration and storage site selection are presented.

Abstract: A mounting beam includes a beam body provided with a plurality of mounting areas configured to mount a front cabin accessory. The beam body includes a first cross beam, a second cross beam, a first oblique beam and a second oblique beam. The first and second cross beams are arranged in parallel and spaced apart from each other, and both the first and second cross beams are configured to couple a left shock absorber tower to a right shock absorber tower. Each of the first and second oblique beams intersects with the second cross beam, first ends of the first and second oblique beams are coupled to the first cross beam, and second ends of the first and second oblique beams are coupled to each other to form a first joint. The first joint is configured to be coupled to a dash panel.

Abstract: This disclosure provides methods and apparatuses for training a neural network model. One example method performed by a terminal device includes: obtaining annotation data of a service, wherein the service is to be processed by a first neural network model and a second neural network model, and wherein precision of the first neural network model is lower than precision of the second neural network model, training a second neural network model by using the annotation data of the service to obtain a trained second neural network model, and updating a first neural network model based on the trained second neural network model.

Abstract: A vehicle body frame includes a front bumper beam assembly, first and second frame assemblies, and a front compartment triangular beam. The front bumper beam assembly extends along a width direction of a vehicle body. The first and second frame assemblies are coupled to the front bumper beam assembly, and spaced apart in the width direction of the vehicle body. Each of the first and second frame assemblies includes a front longitudinal beam, an upper beam and a front damper tower. The front longitudinal beam is coupled to the front bumper beam assembly, the upper side beam is coupled to the front longitudinal beam. The front damper tower is coupled between the upper side beam and the front longitudinal beam. The front compartment triangular beam is coupled between the front damper tower of the first frame assembly and the front damper tower of the second frame assembly.

Abstract: This application discloses a method for controlling traffic in a packet-based network. In the method, after receiving a control packet from a transmit end, an intermediate node between the transmit end and the receive end sends a control packet at the head of a first control queue based on a first duration, wherein the first duration is obtained based on a committed burst size (CBS) and a first committed information rate (CIR), and the intermediate node is configured to send a packet of a first transmit end to a first receive end in the packet-based network. After sending the control packet in the control queue, the intermediate node sends a first data packet set at the head of a data queue based on the sent control packet, wherein the first data packet set comprises C data packets, and C is an integer greater than or equal to 1.

Abstract: Controlling and provisioning a robot of a virtual machine (VM) includes transmitting a connection request between a first service installed in a virtual machine and a second service. The robot is associated with at least one process running on the virtual machine. The virtual machine is authenticated based on a token associated with the second service and the virtual machine. A connection is established between the first service and the second service. A command is transmitted associated with the controlling of the robot from the second service to the first service based on the authentication of the virtual machine. The command is associated with a corresponding command identifier for identifying a type of the command. The command is then executed for controlling the robot.

Abstract: The invention relates to a lift table with an intelligent adjusting function and a method for intelligently adjusting the lift table. The lift table comprises a lift table body and an intelligent adjusting device arranged on the lift table. The intelligent adjusting device comprises an infrared pyroelectric detection unit, an infrared thermopile detection unit and a table-top height adjusting unit. The table-top height adjusting unit comprises a driving unit and a motor unit. The motor unit comprises a motor and a transmission device. The transmission device is connected between the motor and an adjustable table-top of the lift table body. The infrared pyroelectric detection unit and the infrared thermopile detection unit both are connected to the driving unit. The method is realized based on the lift table. The present invention can solve a health problem due to long-time use of the table by a user at a single posture.

Abstract: Disclosed are a lifting desk control system with an imperceptible intelligent adjustment function and a control method for imperceptible intelligent adjustment of the lifting desk. The system includes an imperceptible control system module configured to control lifting of the lifting desk in an imperceptible mode, a switching module electrically connected with the imperceptible control system module, a motor module configured to drive the lifting desk to do a lifting action, a motor drive module electrically connected between the imperceptible control system module and the motor module, a desktop, a transmission module configured to be mechanically connected with the motor module and the desktop, and a power module configured to supply power. The power module is respectively electrically connected with the switching module, the imperceptible control system module and the motor drive module.

Abstract: Systems and methods for allocating computing environments for completing an RPA (robotic process automation) workload are provided. A request for completing an RPA workload is received. A number of computing environments to allocate for completing the RPA workload is calculated based on a selected one of a plurality of RPA autoscaling strategies. The calculated number of computing environments is allocated for allocating one or more RPA robots to complete the RPA workload. The computing environments may be virtual machines.

Abstract: The invention relates to the technical field of oil and gas field development, in particular to a staged multi-cluster fracturing sliding sleeve system and method based on smart key label. The system includes at least one multi-cluster sliding correspondingly placed in each fracturing stage, an end sliding sleeve, and a smart key label. The method includes: step S1, performing fracturing stage by stage from a first stage to a last stage, placing the smart key label through a wellhead and pumping the smart key label to the target fracturing stage; step S2, opening the multi-cluster sliding sleeves of the current fracturing stage one by one through the smart key label, and finally blocking the smart key label in the end sliding sleeve when the multi-cluster sliding sleeve and the end sliding sleeve of the current fracturing stage are opened; and step S3, repeating the steps S1 and S2 until the fracturing operations of all the stages are completed.

Abstract: A controller may generate a packet, and send the packet to an electronic control unit. The packet includes a plurality of bits and control information. The plurality of bits may indicate whether the electronic control unit controls a plurality of objects (for example, actuators or functions) based on the control information. The plurality of bits are in a one-to-one correspondence with the plurality of objects. In this way, the electronic control unit associated with the plurality of objects can control the plurality of objects based on the control information.

Abstract: A method may include acquiring NMR data and sonic data for a borehole in a subsurface geologic region; inverting the NMR data and the sonic data to determine volume fractions for a number of classes of pore types, where the classes include shape and size-based classes; and characterizing the subsurface geologic region based on the volume fractions for the number of classes.

Abstract: Systems and methods for allocating computing environments for completing an RPA (robotic process automation) workload are provided. A request for completing an RPA workload is received. A number of computing environments to allocate for completing the RPA workload is calculated based on a selected one of a plurality of RPA autoscaling strategies. The calculated number of computing environments is allocated for allocating one or more RPA robots to complete the RPA workload. The computing environments may be virtual machines.

Abstract: This application provides a method for training a neural network model and an apparatus. The method includes: obtaining annotation data that is of a service and that is generated by a terminal device in a specified period; training a second neural network model by using the annotation data that is of the service and that is generated in the specified period, to obtain a trained second neural network model; and updating a first neural network model based on the trained second neural network model. In the method, training is performed based on the annotation data generated by the terminal device, so that in an updated first neural network model compared with a universal model, an inference result has a higher confidence level, and a personalized requirement of a user can be better met.