Abstract: The present disclosure relates to a ligand for a quantum dot, a ligand quantum dot, a quantum dot layer and a method for patterning the same. The surface of the ligand quantum dot of the present disclosure is connected with the cleavage-type ligand including a first ligand unit A, a cleavage unit B, and an adhesion adjusting unit C. The method includes: providing a substrate; coating a mixture containing the ligand quantum dot on the substrate to form a quantum dot film; exposing a preset region of the quantum dot film to ultraviolet light, so that the cleavage unit B in the cleavage-type ligand undergoes a photolysis reaction, and a molecular segment containing the adhesion adjusting unit C and obtained after decomposition is detached from a surface of the quantum dot; and washing off an unexposed region of the quantum dot film with an organic solvent, followed by drying.

Abstract: There is provided systems and methods for generating 3D structure estimation of at least one target from a set of 2D Cryo-electron microscope particle images. The method includes: receiving the set of 2D particle images of the target from a Cryo-electron microscope; splitting the set of particle images into at least a first half-set and a second half-set; iteratively performing: determining local resolution estimation and local filtering on at least a first half-map associated with the first half-set and a second half-map associated with the second half-set; aligning 2D particles from each of the half-sets using at least one region of the associated half-map; for each of the half-maps, generating an updated half-map using the aligned 2D particles from the associated half-set; and generating a resultant 3D map using all the half-maps.

Abstract: A system predicts a value estimate for a user who provides a service that involves moving among geographical regions (e.g., a transportation service). The system determines the value estimate by identifying a sequence of time periods, each time period having an associated set of geographical regions. Possible transitions between geographical regions in different time periods are analyzed, for example, using statistical or machine-learned models, to determine likelihoods that the user will move between the geographical regions from one time period to another, and to determine expected values for a transition. Such models may be trained or developed using historical service data and user profile data stored by the system. Transitions are analyzed over a sequence of time periods to determine accumulated values associated with estimated overall values for each geographical region. The system predicts an overall value estimate for the user based on the accumulated values.

Abstract: There is provided systems and methods for generating 3D structure estimation of at least one target from a set of 2D Cryo-electron microscope particle images. The method includes: receiving the set of 2D particle images of the target from a Cryo-electron microscope; splitting the set of particle images into at least a first half-set and a second half-set; iteratively performing: determining local resolution estimation and local filtering on at least a first half-map associated with the first half-set and a second half-map associated with the second half-set; aligning 2D particles from each of the half-sets using at least one region of the associated half-map; for each of the half-maps, generating an updated half-map using the aligned 2D particles from the associated half-set; and generating a resultant 3D map using all the half-maps.

Abstract: A system predicts a value estimate for a user who provides a service that involves moving among geographical regions (e.g., a transportation service). The system determines the value estimate by identifying a sequence of time periods, each time period having an associated set of geographical regions. Possible transitions between geographical regions in different time periods are analyzed, for example, using statistical or machine-learned models, to determine likelihoods that the user will move between the geographical regions from one time period to another, and to determine expected values for a transition. Such models may be trained or developed using historical service data and user profile data stored by the system. Transitions are analyzed over a sequence of time periods to determine accumulated values associated with estimated overall values for each geographical region. The system predicts an overall value estimate for the user based on the accumulated values.

Abstract: A system predicts a value estimate for a user who provides a service that involves moving among geographical regions (e.g., a transportation service). The system determines the value estimate by identifying a sequence of time periods, each time period having an associated set of geographical regions. Possible transitions between geographical regions in different time periods are analyzed, for example, using statistical or machine-learned models, to determine likelihoods that the user will move between the geographical regions from one time period to another, and to determine expected values for a transition. Such models may be trained or developed using historical service data and user profile data stored by the system. Transitions are analyzed over a sequence of time periods to determine accumulated values associated with estimated overall values for each geographical region. The system predicts an overall value estimate for the user based on the accumulated values.

Abstract: Provided is a user side load response method based on adjustment and control on temperature of load clusters. The user side load response method includes: performing thermodynamic modeling on a temperature control load to obtain a temperature control model in direct load control; constructing a mapping quantity to describe the change state of a temperature control load relay switch; obtaining adjustable capacity of the temperature control load through the mapping quantity; introducing temperature control load clusters to solve the problem that control precision cannot satisfy condition requirements; and finally calculating the influence of each load cluster in different load cluster control schemes on comfort degree.

Abstract: A system predicts a value estimate for a user who provides a service that involves moving among geographical regions (e.g., a transportation service). The system determines the value estimate by identifying a sequence of time periods, each time period having an associated set of geographical regions. Possible transitions between geographical regions in different time periods are analyzed, for example, using statistical or machine-learned models, to determine likelihoods that the user will move between the geographical regions from one time period to another, and to determine expected values for a transition. Such models may be trained or developed using historical service data and user profile data stored by the system. Transitions are analyzed over a sequence of time periods to determine accumulated values associated with estimated overall values for each geographical region. The system predicts an overall value estimate for the user based on the accumulated values.

Abstract: Provided is a power grid adjustment method based on a load of a variable frequency air conditioner. The method includes: establishing a mathematical simulation model of a virtual synchronous motor in a variable frequency air conditioner controller; establishing a virtual inertia control segment and a droop control segment of power grid adjustment according to the mathematical simulation model; obtaining a reference value ?? of rotation speed variation of a compressor by the virtual inertia control segment; obtaining a reference value ?ref of rotational angular frequency of the compressor by the droop control segment; and inputting a sum of the reference value ?ref of rotational angular frequency of the compressor and the reference value ?? of rotation speed variation of the compressor into a field-oriented controller (FOC) to control rotation of a motor.

Abstract: There is provided systems and methods for generating 3D structure estimation of at least one target from a set of 2D Cryo-electron microscope particle images. The method includes: receiving the set of 2D particle images of the target from a Cryo-electron microscope; splitting the set of particle images into at least a first half-set and a second half-set; iteratively performing: determining local resolution estimation and local filtering on at least a first half-map associated with the first half-set and a second half-map associated with the second half-set; aligning 2D particles from each of the half-sets using at least one region of the associated half-map; for each of the half-maps, generating an updated half-map using the aligned 2D particles from the associated half-set; and generating a resultant 3D map using all the half-maps.

Abstract: Computer systems and methods for training and/or testing a self-driving vehicle. The systems and methods, via in-car cameras and sensors, capture video of conditions surrounding the vehicle, driving data related to control of the vehicle, and driver behavior data representing actions by a human controlling the vehicle. The systems and methods analyze the captured video data and driving data to derive decisions a computer would make to control the vehicle. The systems and methods analyze the captured driver behavior data to determine decisions made by the human to control the vehicle. The systems and methods evaluate the derived computer decisions in comparison to the determined human decisions to detect data indicating discrepancies between the derived computer decisions and the determined human decisions for controlling the vehicle. The systems and methods provide the detected data as input to a model for training and/or testing a self-driving vehicle.

Abstract: Provided is a user side load response method based on adjustment and control on temperature of load clusters. The user side load response method includes: performing thermodynamic modeling on a temperature control load to obtain a temperature control model in direct load control; constructing a mapping quantity to describe the change state of a temperature control load relay switch; obtaining adjustable capacity of the temperature control load through the mapping quantity; introducing temperature control load clusters to solve the problem that control precision cannot satisfy condition requirements; and finally calculating the influence of each load cluster in different load cluster control schemes on comfort degree.

Abstract: A connected camera system and computer-implemented method for processing visual data. The camera system and method provides control data to a mobile application of a mobile device. The camera system and method transmits the control data from the mobile device (via a cloud service) to a camera device. The camera device configured with a camera housing comprising a camera sensor that captures visual data (e.g., image or video data) in view of a lens. The camera device further configured with a processor coupled to a motor for rotating a shaft. The camera system and method receive the control data, and based on the control data, the processor controls the motor to rotate the shaft. The rotating of the shaft, in turn, rotates the camera housing, such that the camera sensor captures the visual data in view of the lens through a 360-degree plane of rotation.

Abstract: A system predicts a value estimate for a user who provides a service that involves moving among geographical regions (e.g., a transportation service). The system determines the value estimate by identifying a sequence of time periods, each time period having an associated set of geographical regions. Possible transitions between geographical regions in different time periods are analyzed, for example, using statistical or machine-learned models, to determine likelihoods that the user will move between the geographical regions from one time period to another, and to determine expected values for a transition. Such models may be trained or developed using historical service data and user profile data stored by the system. Transitions are analyzed over a sequence of time periods to determine accumulated values associated with estimated overall values for each geographical region. The system predicts an overall value estimate for the user based on the accumulated values.

Abstract: A system predicts a value estimate for a user who provides a service that involves moving among geographical regions (e.g., a transportation service). The system determines the value estimate by identifying a sequence of time periods, each time period having an associated set of geographical regions. Possible transitions between geographical regions in different time periods are analyzed, for example, using statistical or machine-learned models, to determine likelihoods that the user will move between the geographical regions from one time period to another, and to determine expected values for a transition. Such models may be trained or developed using historical service data and user profile data stored by the system. Transitions are analyzed over a sequence of time periods to determine accumulated values associated with estimated overall values for each geographical region. The system predicts an overall value estimate for the user based on the accumulated values.

Abstract: Provided is a power grid adjustment method based on a load of a variable frequency air conditioner. The method includes: establishing a mathematical simulation model of a virtual synchronous motor in a variable frequency air conditioner controller; establishing a virtual inertia control segment and a droop control segment of power grid adjustment according to the mathematical simulation model; obtaining a reference value ?? of rotation speed variation of a compressor by the virtual inertia control segment; obtaining a reference value ?ref of rotational angular frequency of the compressor by the droop control segment; and inputting a sum of the reference value ?ref of rotational angular frequency of the compressor and the reference value ?? of rotation speed variation of the compressor into a field-oriented controller (FOC) to control rotation of a motor.

Abstract: A computing system can detect a session trigger corresponding to execution of a service application on a computing device of a user, the session trigger initiating a user session of an application-based service. The system can execute one or more of a plurality of models corresponding to a unique objective for the application-based service, wherein each model runs real-time session data corresponding to the user session. The system can generate, from each model of the plurality of models, a session score indicating a priority level for the unique objective corresponding to the model. Based on the session score from each of the plurality of models, the system can transmit treatment data to the computing device of the user, the treatment data causing treatment content to be displayed on the computing device of the user.

Abstract: A network computer system maintains a service profile for each user in a population of users for a network service, where the service profile identifies multiple service parameters, and each service parameter of the service profile is based at least in part on one or more predefined usage events. The network computer system can identify a service signal in connection with providing the network service, where the service signal identifies an intent for a group of users. The network computer system can determine, using the service profile of individual users of the population, a group of users that is likely to include more users that are to perform an action in accordance with the intent of the service signal, as compared to a baseline value.

Abstract: A system predicts a value estimate for a user who provides a service that involves moving among geographical regions (e.g., a transportation service). The system determines the value estimate by identifying a sequence of time periods, each time period having an associated set of geographical regions. Possible transitions between geographical regions in different time periods are analyzed, for example, using statistical or machine-learned models, to determine likelihoods that the user will move between the geographical regions from one time period to another, and to determine expected values for a transition. Such models may be trained or developed using historical service data and user profile data stored by the system. Transitions are analyzed over a sequence of time periods to determine accumulated values associated with estimated overall values for each geographical region. The system predicts an overall value estimate for the user based on the accumulated values.