Abstract: An automatic shift control method, apparatus, device and storage medium. A vehicle is controlled to perform an elastic release operation in response to a drive switching request. When unloading torque of a first electric machine of the vehicle is completed, a moving component of a disengaging and engaging apparatus of the vehicle is controlled to perform a position adaptive operation. Meshing direction and separation control is performed on the moving component when a rotational speed of the moving component reaches a stable state, to cause the moving component to move in a disengaging direction to a completely disengaged position, and switch of the vehicle from a four-wheel drive power mode to a two-wheel drive mode is completed.

Abstract: A method for preparing a carbon source for wastewater treatment by using kitchen waste, comprises: adding a complex microbial inoculant into the kitchen waste; and phase-change degrading the kitchen waste into a phase-change liquid under aerobic fermentation of the complex microbial inoculant; wherein the phase-change liquid is the carbon source for wastewater treatment; the complex microbial inoculant comprises: a microbial agent comprising aerobic bacteria; and an excipient comprising an Fe-based MOF (metal-organic framework) nanocomposite. According to the method, the kitchen waste is treated under aerobic fermentation to prepare the carbon source, a carbon-nitrogen ratio is greater than 40, and the carbon source is used to supplement a carbon source in a sewage treatment process of a sewage plant, which significantly improves nitrogen and phosphorus removal effects of sewage treatment in the sewage plant, and provides theoretical foundation and basis for resource utilization of the kitchen waste.

Abstract: A moving state reporting method includes communicating, by a terminal, with a network device using a beam to carry a signal reporting, by the terminal, moving state information of the terminal to the network device, where the moving state information includes a speed flag, and the speed flag indicates that a speed of the terminal exceeds a speed threshold, and receiving, by the terminal, beam management information from the network device.

Abstract: Disclosed are a consistency evaluation method for a vehicle battery cell, a device, an equipment, and a storage medium. The method includes: acquiring vehicle operation data, and selecting effective cell data in the vehicle operation data according to a preset effective data standard; processing the effective cell data according to a preset cell consistency index processing method to obtain cell consistency index data; determining a total index deviation value of all battery cells in the current vehicle according to the cell consistency index data; and if the total index deviation value exceeds a preset deviation threshold, determining a consistency risk of the current vehicle.

Abstract: The embodiments of the present disclosure provide systems and methods for outbound forecasting, comprising receiving an initial distribution of priority values to each fulfillment center (FC) in each region, running a simulation, using a simulation algorithm, of the initial distribution, calculating an outbound capacity utilization value of each FC, determining a number of FCs comprising an outbound capacity utilization value that exceeds a predetermined threshold, feeding the simulation algorithm with the determined number of FCs to generate one or more additional distributions of priority values, generating a FC priority filter comprising an optimal set of priority values based on the one or more additional distributions of priority values, and modifying an allocation of a plurality of SKUs among a plurality of FCs based on the generated FC priority filter.

Abstract: System and method for prediction using a machine learning model. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: obtain parameters of the machine learning model; retrieve an instance from the local data; sample a random direction of the instance; compute a dot product of the random direction and the instance, and calculate a random feature; compute predicted values of the instance in the active and passive computing devices and summarize them to obtain a final predicted value; determine a model coefficient using the random feature, the final predicted value, and a target value of the instance; update the machine learning model using the model coefficient; and predict a value for a new instance.

Abstract: System and method for training a federated learning model asynchronously. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: train the federated learning model in the active computing device using dimensions of an instance in the active computing device; and instruct the at least one passive computing device to train the federated learning model in the at least one passive computing device using dimensions of the instance in the at least one passive computing device. The training instances in the active and the at least one passive computing devices do not correspond to each other at the same training time.

Abstract: A moving state reporting method includes communicating, by a terminal, with a network device using a beam to carry a signal reporting, by the terminal, moving state information of the terminal to the network device, where the moving state information includes a speed flag, and the speed flag indicates that a speed of the terminal exceeds a speed threshold, and receiving, by the terminal, beam management information from the network device.

Abstract: The invention provides pharmaceutical compositions and methods of use thereof for preventing or ameliorating disorders of the nervous system. More specifically, the invention provides pharmaceutical compositions, including phosphopeptides that when administered disrupt the physical interaction of TrkB with its signaling effector, phospholipase C?1 (PLC?1). The invention further provides method of treatment comprising administering phosphopeptides that uncouple TrkB from PLC?1 in order to prevent and/or ameliorate nervous system disorders such as epilepsy, anxiety, and seizures.

Abstract: System and method for training a federated learning model asynchronously. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: train the federated learning model in the active computing device using dimensions of an instance in the active computing device; and instruct the at least one passive computing device to train the federated learning model in the at least one passive computing device using dimensions of the instance in the at least one passive computing device. The training instances in the active and the at least one passive computing devices do not correspond to each other at the same training time.

Abstract: System and method for prediction using a machine learning model. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: obtain parameters of the machine learning model; retrieve an instance from the local data; sample a random direction of the instance; compute a dot product of the random direction and the instance, and calculate a random feature; compute predicted values of the instance in the active and passive computing devices and summarize them to obtain a final predicted value; determine a model coefficient using the random feature, the final predicted value, and a target value of the instance; update the machine learning model using the model coefficient; and predict a value for a new instance.

Abstract: An electronic device may receive or provide power using bidirectional wired and wireless power converters. A bypass path may be included to bypass the battery charger and to allow direct power transfers from a connector of the electronic device to the wireless power converter or from the wireless power converter to the connector of the electronic device. Current limiting and regulation circuitry may also be included.

Abstract: A method for executing multiple versions of an application within a computing environment. The method includes a computer processor identifying a request to execute an instance of a first version of an application within a computing environment and determining that an instance of a second version of the application is active within the computing environment. The method further includes accessing a data structure including information associated with the application to obtain a first set of data corresponding to the first version of the application. The method further includes copying one or more executable objects associated with the first version of the application based, at least in part, on the first set of data to the computing environment. The method further includes executing the copied one or more executable objects associated with the first version that comprise the requested instance of the first version of the application within the computing environment.

Abstract: A deployment specification for implementing a requested cloud service is received by a server. A resource pool is queried by the server for available resources required by the deployment specifications. The resource pool includes a plurality of pre-configured resources for implementing one or more cloud services. A first resource required by the deployment specification is determined to be available within the resource pool. First resource metadata associated with the first resource is requested from a database. The resource metadata includes a resource identifier and a resource type of the first resource. The resource metadata associated with the first resource is received from the database. The first resource is deployed from the resource pool according to the deployment specification to implement the requested cloud service.

Abstract: The invention provides pharmaceutical compositions and methods of use thereof for preventing or ameliorating disorders of the nervous system. More specifically, the invention provides pharmaceutical compositions, including phosphopeptides that when administered disrupt the physical interaction of TrkB with its signaling effector, phospholipase C?1 (PLC?1). The invention further provides method of treatment comprising administering phosphopeptides that uncouple TrkB from PLC?1 in order to prevent and/or ameliorate nervous system disorders such as epilepsy, anxiety, and seizures.

Abstract: The embodiments of the present disclosure provide systems and methods for outbound forecasting, comprising receiving an initial set of solutions comprising receiving a prediction of a regional sales forecast indicative of a customer demand for each stock keeping unit (SKU) in a plurality of regions, receiving a prediction of a correlation of one or more SKUs that will be combined in customer orders in the plurality of regions, receiving a prediction of a size of customer orders in the plurality of regions, wherein a customer order profile is simulated based on the predicted correlation and the predicted size, applying a fulfillment center (FC) priority filter to the simulated customer order profile, predicting a FC for managing outbound of each SKU based on the predicted regional sales forecast and the simulated customer order profile, and modifying a database to assign the predicted FC to each corresponding SKU.

Abstract: The embodiments of the present disclosure provide systems and methods for outbound forecasting, comprising receiving an initial distribution of postal codes mapped to each region, running a simulation of the initial distribution, calculating an outbound capacity utilization value of each FC, determining a number of FCs comprising an outbound capacity utilization value that exceeds a predetermined threshold, feeding an optimization heuristic with at least one of the postal codes mapped to a region from the initial distribution to generate one or more additional distributions of postal codes, generating an optimal distribution of postal codes mapped to each region based on the one or more additional distributions of postal codes, and modify an allocation of customer orders among a plurality of FCs based on the generated optimal distribution of postal codes. Running the simulation may comprise simulating an allocation of customer orders based on the initial distribution of postal codes.

Abstract: The embodiments of the present disclosure provide systems and methods for outbound forecasting, comprising receiving an initial set of solutions comprising receiving a prediction of a regional sales forecast indicative of a customer demand for each stock keeping unit (SKU) in each region, receiving a prediction of a correlation of one or more SKUs that will be combined in customer orders in each region, receiving a prediction of a size of customer orders in each region, wherein a customer order profile is simulated based on the predicted correlation and the predicted size, receiving an inventory stow model that is generated using at least one of open purchase orders or past customer orders; and, predicting a FC for managing outbound of each SKU based on the predicted regional sales forecast, the simulated customer order profile, and the inventory stow model, and modifying a database to assign the predicted FC to each corresponding SKU.

Abstract: The embodiments of the present disclosure provide systems and methods for outbound forecasting, comprising receiving an initial distribution of priority values to each fulfillment center (FC) in each region, running a simulation, using a simulation algorithm, of the initial distribution, calculating an outbound capacity utilization value of each FC, determining a number of FCs comprising an outbound capacity utilization value that exceeds a predetermined threshold, feeding the simulation algorithm with the determined number of FCs to generate one or more additional distributions of priority values, generating a FC priority filter comprising an optimal set of priority values based on the one or more additional distributions of priority values, and modifying an allocation of a plurality of SKUs among a plurality of FCs based on the generated FC priority filter.

Abstract: The embodiments of the present disclosure provide systems and methods for outbound forecasting, comprising receiving an initial distribution of priority values to each fulfillment center (FC) in each region, running a simulation, using a simulation algorithm, of the initial distribution, calculating an outbound capacity utilization value of each FC, determining a number of FCs comprising an outbound capacity utilization value that exceeds a predetermined threshold, feeding the simulation algorithm with the determined number of FCs to generate one or more additional distributions of priority values, generating a FC priority filter comprising an optimal set of priority values based on the one or more additional distributions of priority values, and modifying an allocation of a plurality of SKUs among a plurality of FCs based on the generated FC priority filter.