Abstract: Embodiments of the present disclosure describe systems, methods, and computer program products for redacting sensitive data within a database. An example method can include receiving a masking policy for a column of a database, the masking policy identifying a category of sensitive data, examining a column of a database to identify a category of sensitive data in a first location of the column, and, in response to a data query accessing the column, the first location of the column exceeding a threshold probability of comprising sensitive data, executing a redaction operation to redact the category of sensitive data from the first location of the column to generate redacted data for a response to the data query.

Abstract: Provided is a bispecific antibody, comprising a first antigen-binding moiety and a second antigen-binding moiety, wherein a paired domain of the first antigen-binding moiety comprises an amino acid sequence of engineered HLA-I ?3 and an amino acid sequence of engineered ?2M. Also provided are an expression method for the bispecific antibody, a polynucleotide encoding the bispecific antibody, a vector and host cell containing the polynucleotide, a pharmaceutical composition containing the bispecific antibody, a fusion protein, and a conjugate.

Abstract: The disclosure relates to the technical field of batteries, and discloses a cathode material and a preparation method thereof, a cathode plate and an O3-type layered sodium ion battery. The chemical formula of the cathode material is NaM1-x-y-zNixFeyMnzO2, wherein M comprises a first metal element, and the first metal element has at least one f electron orbital. Ni, Fe and Mn elements in the cathode material are elements containing a d electron orbital. By doping the element M, on the one hand, the f electron orbital and the d electron orbitals are mutually entangled, properties of the cathode material are synergistically improved, so that the structure and air stability of the material are improved; and on the other hand, interaction of all elements in the material can be facilitated, so that ions can move away from original positions to generate vacancies, ion diffusion channels of sodium ions are enlarged, and the rate capability of the material is improved.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object detection predictions from a neural network. In some implementations, an input characterizing a first region of an environment is obtained. The input includes a projected laser image generated from a three-dimensional laser sensor reading of the first region, a camera image patch generated from a camera image of the first region, and a feature vector of features characterizing the first region. The input is processed using a high precision object detection neural network to generate a respective object score for each object category in a first set of one or more object categories. Each object score represents a respective likelihood that an object belonging to the object category is located in the first region of the environment.

Abstract: Provided is a method for presenting resources. The method includes: playing, in response to a launch operation on an application, a first media resource of a target activity in an initialization page of the application, wherein an activity interaction control is presented in a resource screen of the first media resource; displaying, in response to an interaction operation on the activity interaction control, the activity interaction control performing an action corresponding to the interaction operation; and presenting a second media resource of the target activity.

Abstract: A method is provided for displaying resources. The method includes: displaying a multimedia resource of a target activity in an initialization interface of an application in response to a launch operation on the application; displaying a target account in the initialization interface, and sending an invitation request to a server based on the target account to trigger the server to send invitation information to a terminal corresponding to the target account, so as to invite the target.

Abstract: A method and apparatus for generating electricity and producing carbon and heat via biomass fixed bed gasification, said method and apparatus utilising medium calorific value combustible gas to satisfy high-temperature high-pressure boiler heat requirements, and increasing overall electricity generation efficiency. The method and apparatus have low nitrogen oxides amounts, satisfy environmental protection requirements, and do not require denitrification treatment. The method comprises the following steps: feeding a biomass raw material into a gasification apparatus to prepare a medium calorific value biomass combustible gas, and performing gasification on the biomass raw material at 700-850° C. under the effect of an air/water vapour pre-mixed gasification agent to produce a combustible gas, the calorific value of the combustible gas being 1600-1800 kcal, the temperature being 200-300° C.

Abstract: Systems, methods, and non-transitory computer-readable media configured to obtain one or more series of successive sensor data frames during a navigation of a vehicle. Disengagement data is obtained. The disengagement data indicates whether a vehicle is in autonomous mode. A training dataset with which train a machine learning model is determined based on the one or more series of successive sensor data frames and the disengagement data. The training dataset includes a subset of the one or more series of successive sensor data frames and a subset of the disengagement data, the machine learning model being trained to identify unsafe driving conditions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object detection predictions from a neural network. In some implementations, an input characterizing a first region of an environment is obtained. The input includes a projected laser image generated from a three-dimensional laser sensor reading of the first region, a camera image patch generated from a camera image of the first region, and a feature vector of features characterizing the first region. The input is processed using a high precision object detection neural network to generate a respective object score for each object category in a first set of one or more object categories. Each object score represents a respective likelihood that an object belonging to the object category is located in the first region of the environment.

Abstract: An environmentally friendly combustion chamber for stable combustion of biomass gasification combustible gas. The combustion chamber is divided into a first stage cavity body (45) and a second stage cavity body (48) by a honeycomb-shaped heat storage body (46). A combustion pipe (41) is connected to a biomass gas inlet and a primary air distribution pipe (54), the combustion pipe (41) is connected to the first stage cavity body (45), and an ignition gun (42) and a thermocouple T1 are arranged on the first stage cavity body (45). A secondary air distribution pipe (47), opposite the honeycomb-shaped heat storage body (46), and a thermocouple T2 are arranged within the second stage cavity body (48), and the second stage cavity body (48) is connected to an outlet high temperature flue gas pipe (51).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object detection predictions from a neural network. In some implementations, an input characterizing a first region of an environment is obtained. The input includes a projected laser image generated from a three-dimensional laser sensor reading of the first region, a camera image patch generated from a camera image of the first region, and a feature vector of features characterizing the first region. The input is processed using a high precision object detection neural network to generate a respective object score for each object category in a first set of one or more object categories. Each object score represents a respective likelihood that an object belonging to the object category is located in the first region of the environment.

Abstract: A method and apparatus for generating electricity and producing carbon and heat via biomass fixed bed gasification, said method and apparatus utilising medium calorific value combustible gas to satisfy high-temperature high-pressure boiler heat requirements, and increasing overall electricity generation efficiency. The method and apparatus have low nitrogen oxides amounts, satisfy environmental protection requirements, and do not require denitrification treatment. The method comprises the following steps: feeding a biomass raw material into a gasification apparatus to prepare a medium calorific value biomass combustible gas, and performing gasification on the biomass raw material at 700-850° C. under the effect of an air/water vapour pre-mixed gasification agent to produce a combustible gas, the calorific value of the combustible gas being 1600-1800 kcal, the temperature being 200-300° C.

Abstract: An environmentally friendly combustion chamber for stable combustion of biomass gasification combustible gas. The combustion chamber is divided into a first stage cavity body (45) and a second stage cavity body (48) by a honeycomb-shaped heat storage body (46). A combustion pipe (41) is connected to a biomass gas inlet and a primary air distribution pipe (54), the combustion pipe (41) is connected to the first stage cavity body (45), and an ignition gun (42) and a thermocouple T1 are arranged on the first stage cavity body (45). A secondary air distribution pipe (47), opposite the honeycomb-shaped heat storage body (46), and a thermocouple T2 are arranged within the second stage cavity body (48), and the second stage cavity body (48) is connected to an outlet high temperature flue gas pipe (51).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object detection predictions from a neural network. In some implementations, an input characterizing a first region of an environment is obtained. The input includes a projected laser image generated from a three-dimensional laser sensor reading of the first region, a camera image patch generated from a camera image of the first region, and a feature vector of features characterizing the first region. The input is processed using a high precision object detection neural network to generate a respective object score for each object category in a first set of one or more object categories. Each object score represents a respective likelihood that an object belonging to the object category is located in the first region of the environment.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object detection predictions from a neural network. In some implementations, an input characterizing a first region of an environment is obtained. The input includes a projected laser image generated from a three-dimensional laser sensor reading of the first region, a camera image patch generated from a camera image of the first region, and a feature vector of features characterizing the first region. The input is processed using a high precision object detection neural network to generate a respective object score for each object category in a first set of one or more object categories. Each object score represents a respective likelihood that an object belonging to the object category is located in the first region of the environment.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object detection predictions from a neural network. In some implementations, an input characterizing a first region of an environment is obtained. The input includes a projected laser image generated from a three-dimensional laser sensor reading of the first region, a camera image patch generated from a camera image of the first region, and a feature vector of features characterizing the first region. The input is processed using a high precision object detection neural network to generate a respective object score for each object category in a first set of one or more object categories. Each object score represents a respective likelihood that an object belonging to the object category is located in the first region of the environment.