Abstract: The present disclosure provides a service resource configuration method, including: configuring resource parameters for a service to be configured according to an action policy, calculating a timely reward in a current state, performing IV analysis according to the action policy, and ending one episode after the IV analysis is completed; calculating and updating, according to the timely reward in each state, an optimization objective policy parameter in each state; iterating a preset number of episodes to calculate and update the optimization objective policy parameter in each state; determining, according to the optimization objective policy parameter in each state in the preset number of episodes, an optimal optimization objective policy parameter in each state; and updating the action policy according to the optimal optimization objective policy parameter in each state.

Abstract: Techniques for top-down scene discrimination are discussed. A system receives scene data associated with an environment proximate a vehicle. The scene data is input to a convolutional neural network (CNN) discriminator trained using a generator and a classification of the output of the CNN discriminator. The CNN discriminator generates an indication of whether the scene data is a generated scene or a captured scene. If the scene data is data generated scene, the system generates a caution notification indicating that a current environmental situation is different from any previous situations. Additionally, the caution notification is communicated to at least one of a vehicle system or a remote vehicle monitoring system.

Abstract: An apparatus for dismounting and mounting a high-voltage line T-connector in a hot-line operation includes a lifting platform, a four-axis platform and an end-effector mechanism; the four-axis platform and the end-effector mechanism are both electrically conductive structures; the four-axis platform is fixedly mounted on the top of the lifting platform, and an insulating layer is provided between the four-axis platform and the lifting platform; the four-axis platform is movable in the X direction, the Y direction, and the Z direction, and is rotatable around the Z direction; the four-axis platform is provided with an equipotential mechanism; the end-effector mechanism is detachably fastened to the four-axis platform; and a bolt loosening/tightening mechanism or a nut cutting device capable of moving in the X direction, the Y direction, and the Z direction is provided on the end-effector mechanism.

Abstract: The present disclosure provides a method for optimizing OTN resources, including: determining and creating, according to an action policy, a service to be created in a current service creation state, calculating a timely reward in the current service creation state, entering a next service creation state until an episode is ended, and calculating and updating, according to the timely reward in each service creation state, an optimized objective policy parameter in each service creation state; iterating a preset number of episodes to calculate and update the optimized objective policy parameter in each service creation state; determining, according to the optimized objective policy parameter in each service creation state in the preset number of episodes, a resultant optimized objective policy parameter in each service creation state; and updating the action policy according to the resultant optimized objective policy parameter in each service creation state.

Abstract: Techniques for top-down scene generation are discussed. A generator component may receive multi-dimensional input data associated with an environment. The generator component may generate, based at least in part on the multi-dimensional input data, a generated top-down scene. A discriminator component receives the generated top-down scene and a real top-down scene. The discriminator component generates binary classification data indicating whether an individual scene in the scene data is classified as generated or classified as real. The binary classification data is provided as a loss to the generator component and the discriminator component.

Abstract: Techniques for modeling the probability distribution of errors in perception systems are discussed herein. For example, techniques may include modeling error distribution for attributes such as position, size, pose, and velocity of objects detected in an environment, and training a mixture model to output specific error probability distributions based on input features such as object classification, distance to the object, and occlusion. The output of the trained model may be used to control the operation of a vehicle in an environment, generate simulations, perform collision probability analyses, and to mine log data to detect collision risks.

Abstract: The present invention relates to a metal complex, an organic electroluminescent element containing same, and a consumer product. The metal complex of the present invention is used as a luminescent material to obtain a green phosphorescent material with a high luminescent efficiency. In addition, the prepared luminescent material has a good thermal stability. The organic electroluminescent element of the present invention emits a green phosphorescence and has advantages of a narrow emission spectrum, a high stability, and a high efficiency. An electronic device comprising the organic electroluminescent element of the present invention can enable a consumer product having green electroluminescence and an improved luminous efficiency.

Abstract: A glycosylation-modified erythropoietin, containing a glycan structure incorporated into an N-glycosylation site, wherein the glycan structure contains FA4G4L2S4.

Abstract: A method of manufacturing a high molecular weight heparin (HMWH) compound is disclosed. The method comprises dissolving heparin to form a heparin solution and fractionating the heparin solution via tangential flow filtration (TFF) using a membrane with a molecular weight cut off (MWCO) between about 8 kDa and about 12 kDa. The TFF yields a retentate comprising fractionated heparin with a weight average molecular weight of about 20 kDa or greater, i.e., a high molecular weight heparin compound. A substantial proportion of heparin chains in the fractionated heparin may have a high molecular weight, e.g., 50% of the heparin chains or greater may have a molecular weight of 20 kDa or greater.

Abstract: The present disclosure provides a method for optimizing OTN network resources, including: determining and creating a service to be created in a current service creating state according to an action policy, calculating a timely reward, entering a next service creating state, until an Episode is finished, calculating a comprehensive optimization parameter according to the timely reward, and calculating and updating a quantization index weight vector according to the comprehensive optimization parameter, where the action policy is a probability function related to the quantization index weight vector, and the quantization index weight vector corresponds to a plurality of quantization indexes; iterating a preset number of Episodes to obtain an optimized quantization index weight vector; and updating the action policy according to the optimized quantization index weight vector.

Abstract: A method and device for temperature monitoring of a power transistor formed in a semiconductor die comprising are disclosed. A side of a temperature-sensing resistor disposed in the semiconductor die is coupled to a voltage input side of the power transistor. A controller coupled to a second side of the temperature-sensing resistor is configured to detect a voltage across the resistor and trigger a temperature related corrective action using the detected voltage.

Abstract: A sea creature cleaning robot for an intake tunnel for a nuclear power plant includes a frame, cutter assemblies, and walking wheel assemblies; the frame is used for mounting and fixing cutter mounting seats and crawler wheels; the walking wheel assemblies mounted on the frame enable the entire device to normally walk in a tunnel; the cutter assemblies control the height of cutters by means of hydraulic cylinders to make the cutters contact the inner wall of the tunnel, and the hydraulic cylinders drive the saw-toothed cutters to move back and forth to remove sea creatures attached to the inner wall of the tunnel; the cutter assemblies are uniformly distributed on the frame, so as to ensure full coverage of the cleaning range of the cross section of the tunnel. The robot can clean sea creatures in tunnels in place of manual work to significantly improve the cleaning efficiency.

Abstract: Disclosed are a resource scheduling method, an electronic device and a storage medium. The resource scheduling method may include: acquiring an intelligent application processing request acquiring current resource usage information; matching an intelligent application instance according to the intelligent application processing request and creating a task according to the resource usage information and the intelligent application instance, to process the intelligent application processing request.

Abstract: Techniques for determining predictions on a top-down representation of an environment based on object movement are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) may capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle, a pedestrian, a bicycle). A multi-channel image representing a top-down view of the object(s) and the environment may be generated based in part on the sensor data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) may also be encoded in the image. Multiple images may be generated representing the environment over time and input into a prediction system configured to output a trajectory template (e.g., general intent for future movement) and a predicted trajectory (e.g., more accurate predicted movement) associated with each object. The prediction system may include a machine learned model configured to output the trajectory template(s) and the predicted trajector(ies).

Abstract: A method implemented via execution of computing instructions configured to run at one or more processors and stored at one or more non-transitory computer-readable media. The method can include receiving, via a computer network, a delivery request for an order. The method further can include determining a base delivery price for the delivery request. The method also can include determining, by a desirability machine learning model, a desirability score for the base delivery price based at least in part on a source location, an order size group, a distance group, and delivery timing information for the delivery request. The method additionally can include determining an elasticity coefficient for the desirability score. Moreover, the method can include determining a delivery offer price for the delivery request based at least in part on the base delivery price, the desirability score, and the elasticity coefficient.

Abstract: A method of manufacturing a high molecular weight heparin (HMWH) compound is disclosed. The method comprises dissolving heparin to form a heparin solution and fractionating the heparin solution via tangential flow filtration (TFF) using a membrane with a molecular weight cut off (MWCO) between about 8 kDa and about 12 kDa. The TFF yields a retentate comprising fractionated heparin with a weight average molecular weight of about 20 kDa or greater, i.e., a high molecular weight heparin compound. A substantial proportion of heparin chains in the fractionated heparin may have a high molecular weight, e.g., 50% of the heparin chains or greater may have a molecular weight of 20 kDa or greater.

Abstract: Techniques to predict object behavior in an environment are discussed herein. For example, such techniques may include determining a trajectory of the object, determining an intent of the trajectory, and sending the trajectory and the intent to a vehicle computing system to control an autonomous vehicle. The vehicle computing system may implement a machine learned model to process data such as sensor data and map data. The machine learned model can associate different intentions of an object in an environment with different trajectories. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on object's intentions and trajectories.

Abstract: This disclosure provides a communication method and a communication apparatus. The method is applied to a software baseband architecture receiver, and the method includes: receiving a first signal; allocating a processing resource to the first signal based on parameter information of the first signal, where the processing resource includes at least one of a processing algorithm for channel estimation (CE) or a processing algorithm for multiple-input multiple-output (MIMO) detection; and performing CE and MIMO detection on the first signal based on the processing resource.

Abstract: A separator including a porous substrate layer, an intermediate layer, and a ceramic coating layer is provided. The ceramic coating layer is disposed on a side of the intermediate layer away from the porous substrate layer. The intermediate layer includes a metal oxide powder. The particle diameter of the metal oxide powder is less than the pore diameter of the porous substrate layer, and at least a portion of the metal oxide powder is embedded in the porous substrate layer. A method of preparing the separator and a lithium-ion battery including the separator are also provided.

Abstract: Disclosed is an optimizing method for multi-source municipal solid waste combinations based on machine learning, including obtaining relevant property data, classifying the feature variables and obtaining a raw materials pre-combination from the classified feature variables according to a classification ratio, followed by cooperative combustion treatment to obtain data after combustion, summarizing the obtained data into a database, constructing a matrix of raw material components, operating conditions and pollutant distribution according to the database, obtaining matrix data; performing principal component analysis on the matrix data, constructing an information processing model, obtaining a data set of samples; carrying out training according to the data set to construct a relational model, obtaining processed parameters; training the obtained processed parameters to construct a regression module, an optimal parameter, and performing regression calculation using the optimal parameter together with the matr