Abstract: A method of video processing, including performing a conversion between a video unit of a video and a bitstream of the video according to a rule, wherein the rule specifies that whether a cross-component adaptive loop filter (CC-ALF) mode and an adaptive loop filter (ALF) mode are enabled for coding the video unit are indicated in the bitstream in a mutually independent manner.

Abstract: A method for controlling a traffic light, a method and apparatus for navigating an unmanned vehicle and a method and apparatus for training a model are provided. An implementation comprises: generating a reinforced traffic light state parameter according to vehicle state representation information of an unmanned vehicle currently contained in a preset area of a target traffic light and a current traffic light state parameter of the target traffic light; and generating a traffic light control action according to the reinforced traffic light state parameter; where the reinforced traffic light state parameter is used to cause an unmanned vehicle navigation end to generate a reinforced vehicle state parameter according to a reinforced traffic light state and a current vehicle state parameter of a target unmanned vehicle, and generate an unmanned vehicle navigation action according to the reinforced vehicle state parameter.

Abstract: An example method of video processing includes determining, for a conversion between a block of a chroma component of a video and a bitstream representation of the video, whether or how to apply a filtering process to an edge of the block based on a first quantization information for a first video region including samples on one side of the edge and/or a second quantization information for a second video region including samples on the other side of the edge according to a rule that is based on a coding mode applicable to the block for coding the samples on the one side or the samples on the other side of the edge. The rule specifies that multiple QP offsets at different video unit levels are used to determine the first quantization information or the second quantization information. The method also includes performing the conversion based on the determining.

Abstract: Extensions of intra coding modes in video coding are described. One example is a method for video processing, comprising: generating, for a conversion between a current video block of a video and a bitstream representation of a video, a set of extended intra prediction modes (IPMs) associated with the current video block by revising a set of existing IPMs to include at least one new coding method, wherein the new coding method is different from coding methods in the existing IPMs and is to be treated as IPM; and performing the conversion based on the set of extended IPMs.

Abstract: Video processing methods, systems and apparatus are described. One example method includes performing a conversion between a video block of a video and a bitstream of the video using a palette mode in which samples of the video block are represented using a palette of representative color values. A size of the palette of the video block is determined based on whether a local dual tree is applied for the conversion.

Abstract: The invention discloses a mixing process for preparing a high nickel cathode material and its use. The mixing process is to add a precursor and a lithium source to a mixing device for mixing to obtain a mixture. After the mixture is uniformly mixed, the mixture is mixed. While the material equipment continues to operate, spray the liquid into the mixture. After the liquid spray is completed, the material is discharged, and the obtained mixture is put into a sagger for sintering. The liquid is pure water, ethanol, nitrogen methyl pyrrolidone, and additive solution. Or one or more of additive dispersions. The spray mixing process of the present invention can make the mixture more uniform, and because of the presence of a proper amount of mist droplets, the surface of the lithium source is slightly soluble in water and can adsorb the precursor.

Abstract: Disclosed herein are methods for diagnosing acute cellular rejection (ACR) of an allograft by analysis of predictive gene sets and kits for practicing these methods.

Abstract: A method and apparatus for training an information adjustment model of a charging station, an electronic device, and a storage medium are provided. An implementation comprises: acquiring a battery charging request, and determining environment state information corresponding to each charging station in a charging station set; determining, through an initial policy network, target operational information of each charging station in the charging station set for the battery charging request, according to the environment state information; determining, through an initial value network, a cumulative reward expectation corresponding to the battery charging request according to the environment state information and the target operational information; training the initial policy network and the initial value network by using a deep deterministic policy gradient algorithm; and determining the trained policy network as an information adjustment model corresponding to each charging station.

Abstract: Disclosed herein are gene signature sets expressed by kidney allograft recipients prior to transplant that determine the risk for acute rejection (AR) post-transplant and methods of using the gene signature sets for identifying renal allograft recipients at risk for acute rejection. Also disclosed herein are kits for use in the invention which comprise primer pairs for the gene signature sets.

Abstract: A method for identifying a renal allograft recipient at risk for chronic allograft damage or interstitial fibrosis and tubular atrophy (IF/TA) by comparing the transcription level of a preselected gene signature set with the transcription level of a comparison standard, and diagnosing the recipient as being at risk for chronic allograft damage if the transcription level of the preselected gene signature set is significantly higher than the transcription level of the comparison standard.

Abstract: The invention discloses an indoor adaptive ventilation system and method based on multi-vent ventilation modules, comprising at least one multi-vent ventilation module, the multi-vent ventilation modules comprise air reversing valves and ventilation ducts, the multi-vent ventilation ducts are connected with the air reversing valves, the air reversing valve comprises a box body, a box cover, a reversing mechanism, a supply air main duct, a return air main duct, a fixed supply air branch duct and multiple variable air direction branch ducts; a plurality of variable air direction branch ducts are evenly arranged in the circumferential direction of the box body. The invention can divide the indoor space into different sub-spaces, control pollutants in a smaller area, reduce the possibility of large-scale pollutant diffusion, and realize that the supply air outlets and the return air outlets can be switched mutually to adapt to different usage scenarios and needs.

Abstract: A method of training a model, a method of determining an asset valuation, a device, a storage medium, and a program product, which relate to a field of artificial intelligence, in particular to fields of deep learning and natural language understanding. A specific implementation can include: determining an event-level representation according to a first set of feature data; performing a multi-task learning for a first model according to the event-level representation, to obtain first price distribution data, and transmitting the first price distribution data to a central server; determining a first intra-region representation according to a second set of feature data; adding a noise signal to the first intra-region representation, and transmitting the noised intra-region representation to a client; and adjusting a parameter of the first model according to a noised parameter gradient in response to the noised parameter gradient being received from the central server.

Abstract: A parking lot free parking space predicting method, apparatus, electronic device and storage medium are provided. The method comprises: building a parking lot association graph for parking lots in a region to be processed; aggregating environment context features of neighboring parking lots according to weights of edges between the neighboring parking lots and a parking lot i to obtain a representation vector of the parking lot i at a current time; and pre-training a graph attention neural network model using the environment context features of the neighboring parking lots and free parking space information, and a gated recurrent neural model according to the representation vector of the parking lot it at the current time.

Abstract: Disclosed herein are gene signature sets expressed by kidney allograft recipients prior to transplant that determine the risk for acute rejection (AR) post-transplant and methods of using the gene signature sets for identifying renal allograft recipients at risk for acute rejection. Also disclosed herein are kits for use in the invention which comprise primer pairs for the gene signature sets.

Abstract: Disclosed herein are methods for diagnosing acute cellular rejection (ACR) of an allograft by analysis of predictive gene sets and kits for practicing these methods.

Abstract: A parking lot free parking space predicting method, apparatus, electronic device and storage medium are provided. The method comprises: building a parking lot association graph for parking lots in a region to be processed; as for any parking lot i, performing the following processing respectively: determining local space correlation information of the parking lot i at a current time according to environment context features of the parking lot i and neighboring parking lots which are in the parking lot association graph and connected to the parking lot i through edges; determining time correlation information of the parking lot i at the current time according to the local space correlation information, and predicting free parking space information of the parking lot i at at least one future time step according to the time correlation information of the parking lot i at the current time.

Abstract: A training method for a point-of-interest recommendation model and a method for recommending a point of interest are provided.

Abstract: Disclosed herein are gene signature sets expressed by kidney allograft recipients prior to transplant that determine the risk for acute rejection (AR) post-transplant and methods of using the gene signature sets for identifying renal allograft recipients at risk for acute rejection. Also disclosed herein are kits for use in the invention which comprise primer pairs for the gene signature sets.

Abstract: A method for recommending a station for a vehicle, a device, and a storage medium are provided. The method comprises: receiving, by a server, an access request from a vehicle; obtaining, based on the access request, a plurality of observation values from a plurality of stations associated with the vehicle, respectively, each observation value is based on a corresponding pre-trained recommendation model, each observation value includes factors associated with access of the vehicle to the station corresponding to the observation value; determining, an action value for the station based on the observation value and the pre-trained recommendation model for the station, the action value for the station indicates a matching degree between the access request and the station; determining a recommended station among the plurality of stations based on the action values of the plurality of stations; and sending to the vehicle an instruction of driving to the recommended station.

Abstract: A method and apparatus for complementing a depth image are provided. The method includes obtaining a color image and a corresponding depth image, obtaining a first depth image based on the color image, using a first deep neural network (DNN), obtaining a second depth image based on the depth image and an intermediate feature image generated by each intermediate layer of the first DNN, using a second DNN, and obtaining a final depth image by merging the first depth image and the second depth image.