Abstract: The present disclosure provides a mowing control method, a setting method, a lawn mower, a setting apparatus and an electronic device. The mowing control method is applied to a lawn mower, and the lawn mower includes a first sensor, where the first sensor is a non-contact sensor, and the non-contact sensor is used to distinguish between a grass area and a non-grass area. The mowing control method includes: controlling the lawn mower to avoid the non-grass area to walk; receiving first position information of an ineffective area; when it is determined according to the first position information that the lawn mower walks to the ineffective area, controlling the lawn mower to pass and perform mowing within the ineffective area. Since there is no need to avoid the ineffective area, the walking path of the lawn mower is simpler, thereby improving the mowing efficiency of the lawn mower.

Abstract: Disclosed is a variable-parameter stiffness identification and modeling method for an industrial robot. An effective working space of a robot is divided into a plurality of cubic regions. For an operating task in a certain machining region, different loads are applied to an end effector at multiple positions and multiple postures in the region, and robot joint stiffness in this section is identified and acquired according to the relationship between the loads and an end deformation, thereby realizing accurate stiffness control of the robot in different operating sections during a machining process.

Abstract: Disclosed is a decision-making and planning integrated method for a nonconservative intelligent vehicle in a complex heterogeneous environment, including the following steps: offline establishing and training a social interaction knowledge learning model; obtaining state data of the traffic participants and state data of an intelligent vehicle online in real time, and splicing the state data to obtain an environmental state; using the environmental state as an input to the trained social interaction knowledge learning model to obtain predicted trajectories of all traffic participants including the nonconservative intelligent vehicle; updating the environmental state based on the predicted trajectories; and inputting the updated environmental state to the social interaction knowledge learning model to complete trajectory decision-making and planning for the nonconservative intelligent vehicle by iteration, where a planned trajectory of the nonconservative intelligent vehicle is a splicing result of a first poi

Abstract: Provided are antibodies that recognize the B-Cell Maturation Antigen (BCMA) and methods of use thereof.

Abstract: The present invention provides a real-time path planning method taking into account dynamic properties of vehicles; the method includes calculation without connecting to internet of a reachable set and an online path planning; in the calculation without connecting to internet of the reachable set, all vehicle safety states are traversed by means of the vehicle model and the wheel model, thereby predicting the position set capable of being reached by the vehicle at a next moment; in the online path planning, by means of calculating the position set capable of being reached by the vehicle at the next moment with connecting to internet, non-linear dynamic constraints are provided for the exploration of the artificial potential field method, achieving the purpose of real-time planning while taking into account dynamic properties of the vehicles.

Abstract: Disclosed is a method for predicting a trajectory of a traffic participant in a complex heterogeneous environment, including the following steps: obtaining traffic participant information in a complex heterogeneous environment; arranging and numbering traffic participant classes based on the class information, to obtain serial numbers of the traffic participant classes; establishing a position graph, a velocity graph, an acceleration graph, and a class graph, into each of which expert experience is introduced; and capturing topological structure relationships and time dependence relationships to obtain a position hidden state, a velocity hidden state, an acceleration hidden state, and a class hidden state; classifying the position hidden state, the velocity hidden state, the acceleration hidden state, and the class hidden state to obtain a hidden state set of traffic participants; and decoding hidden states of the traffic participants separately using a corresponding decoder to obtain future trajectory predic

Abstract: Disclosed is a decision-making and planning integrated method for a nonconservative intelligent vehicle in a complex heterogeneous environment, including the following steps: offline establishing and training a social interaction knowledge learning model; obtaining state data of the traffic participants and state data of an intelligent vehicle online in real time, and splicing the state data to obtain an environmental state; using the environmental state as an input to the trained social interaction knowledge learning model to obtain predicted trajectories of all traffic participants including the nonconservative intelligent vehicle; updating the environmental state based on the predicted trajectories; and inputting the updated environmental state to the social interaction knowledge learning model to complete trajectory decision-making and planning for the nonconservative intelligent vehicle by iteration, where a planned trajectory of the nonconservative intelligent vehicle is a splicing result of a first poi

Abstract: A system and a method of optimizing an optical proximity correction (OPC) model for a mask pattern of a photo mask is disclosed. A machine learning (ML) based model builder includes an OPC model, measurement data and a random term generator. Random terms are generated in a M-dimensional space by the random term generator. The ML based model builder classifies the random terms to clusters by applying a classifying rule. A representative subset of the random terms is determined among the classified clusters, and the representative subset is added to the OPC model.

Abstract: Disclosed is a method for predicting a trajectory of a traffic participant in a complex heterogeneous environment, including the following steps: obtaining traffic participant information in a complex heterogeneous environment; arranging and numbering traffic participant classes based on the class information, to obtain serial numbers of the traffic participant classes; establishing a position graph, a velocity graph, an acceleration graph, and a class graph, into each of which expert experience is introduced; and capturing topological structure relationships and time dependence relationships to obtain a position hidden state, a velocity hidden state, an acceleration hidden state, and a class hidden state; classifying the position hidden state, the velocity hidden state, the acceleration hidden state, and the class hidden state to obtain a hidden state set of traffic participants; and decoding hidden states of the traffic participants separately using a corresponding decoder to obtain future trajectory predic

Abstract: Vectors and nucleic acid constructs for improved antibody production are provided. Also provided are methods of making and using the vectors and constructs.

Abstract: Described herein are techniques, devices, and systems for managing, by service providers, telecommunication network selection data, which can include user equipment (UE) data and carrier configuration data. The UE data, which can be identified based on user selections of toggles displayed in user interfaces (UIs) of UEs, and the carrier configuration data, can be utilized for selections of networks and/or network services for the UEs. The carrier configuration data can be utilized to override the UE data.

Abstract: Lactoferrin (Lf) is used in the prophylaxis and treatment of Alzheimer's disease (AD), and is used as an active agent in the preparation of drugs for preventing or treating AD. By designing an in vitro model of AD, it has been proved that Lf can reduce the cell damage caused by A?, and play the role of anti-Alzheimer's disease by improving the anti-inflammatory ability, inhibiting the inflammation and regulating apoptosis. Meanwhile, using the APP/PS1 transgenic mouse model, it has been confirmed that Lf can reduce the phosphorylation level of Tau protein, shorten the time for mice to escape from the water maze, and improve learning and cognitive functions.

Abstract: A vehicle state estimation method based on adaptive total variation denoising (TVD) filtering includes the following steps: step 1: collection and preprocessing of an original signal of a vehicle; step 2: noise level evaluation; step 3: Teager-Kaiser energy evaluation; step 4: optimization problem construction; and step 5: application of a filtered signal in the step 4 in the estimation of a vehicle state. The vehicle state estimation method is mainly based on the global noise level characteristic and the local intensity change characteristic of the vehicle system state data, and adaptive filtering of parameters is achieved by means of a TVD filtering method. The signal is denoised to the maximum extent, peak information of the signal is retained while the data smoothness is maintained, and then the signal is used for vehicle state estimation, working condition identification and the like.

Abstract: A driving module includes a first driving circuit and a first conversion circuit; n is a positive integer; the first driving circuit includes a plurality of stages of first driving sub-circuits; the first conversion circuit includes a plurality of first conversion sub-circuits; an nth stage of first driving sub-circuit outputs an nth stage of first driving signal; an (n?1)th stage of first driving sub-circuit outputs an (n?1)th stage of first driving signal; the nth first conversion sub-circuit is configured to control the nth stage of second driving signal output terminal to output the nth stage of second driving signal under the control of the (n?1)th stage of first driving signal and the nth stage of first driving signal according to the first voltage signal and the second voltage signal.

Abstract: Provided are a method and apparatus for controlling power consumption of an ONU, an electronic device, and a storage medium. The method includes: monitoring a current state of the ONU in real time, wherein the state at least includes a deep energy saving state, and data flow of the ONU in the deep energy saving state is lower than a preset threshold; and performing message processing on received data through a CPU channel and performing a power-off operation on a hardware module in an acceleration channel of the ONU when the ONU is currently in the deep energy saving state; wherein the acceleration channel is connected to a data ingress of the ONU, and the hardware module in the acceleration channel is configured to perform message processing on the received data of the ONU.

Abstract: The present disclosure provides a display device. The display device includes: a liquid crystal display panel; a liquid crystal light control panel located on the light incident side of the liquid crystal display panel; and at least two haze layers located on the light emitting side of the liquid crystal display panel.

Abstract: A vehicle state estimation method based on adaptive total variation denoising (TVD) filtering includes the following steps: step 1: collection and preprocessing of an original signal of a vehicle; step 2: noise level evaluation, step 3: Teager-Kaiser energy evaluation; step 4: optimization problem construction; and step 5: application of a filtered signal in the step 4 in the estimation of a vehicle state. The vehicle state estimation method is mainly based on the global noise level characteristic and the local intensity change characteristic of the vehicle system state data, and adaptive filtering of parameters is achieved by means of a TVD filtering method. The signal is denoised to the maximum extent, peak information of the signal is retained while the data smoothness is maintained, and then the signal is used for vehicle state estimation, working condition identification and the like.

Abstract: A texture recognition apparatus and an opposite substrate are provided. The texture recognition apparatus includes a light source array, an image sensor array and a light shielding layer. The light source array includes a plurality of light sources; the image sensor array includes a plurality of image sensors, an orthographic projection of the light shielding layer on a plane where the light source array is located is between two adjacent light sources, an orthographic projection of the light shielding layer on a plane where the image sensor array is located at least partially overlaps with the plurality of image sensors; the light shielding layer has at least one opening, and at least a part of an orthographic projection of the first opening on the plane where the image sensor array is located is at least on one side of the first image sensor or overlaps with the first image sensor.