Abstract: Disclosed are chemically end-capped polypiperazine pyrophosphate-modified ammonium polyphosphate with high temperature resistance and precipitation resistance, a preparation method therefor, and an apparatus and application thereof. The chemically end-capped polypiperazine pyrophosphate-modified ammonium polyphosphate flame retardant is formed by polypiperazine pyrophosphate modification based on ammonium polyphosphate, followed by end capping; and the polypiperazine pyrophosphate is prepared by polymerization of an intermediate piperazine diphosphate obtained through dehydration condensation of phosphoric acid and piperazine. The chemically end-capped polypiperazine pyrophosphate-modified ammonium polyphosphate flame retardant of the present solution is prepared by using special equipment, which ensures whiteness and thermal stability of product, and improves properties of ammonium polyphosphate.

Abstract: Disclosed are chemically end-capped melamine pyrophosphate with high temperature resistance and precipitation resistance, a preparation method and apparatus thereof, and an application thereof in flame-retardant nylon. End-capping treatment of melamine pyrophosphate enhances flame retardancy and precipitation resistance of a flame retardant, and melamine pyrophosphate is used for producing high-strength flame-retardant nylon, which improves product performance. A special flame-retardant preparation device is also used, and appropriate process flow and parameter design further improves comprehensive properties of the flame retardant, including whiteness and a 1% thermal decomposition temperature. The present technical solution can overcome technical defects of the melamine pyrophosphate flame retardant in the prior art including non-ideal properties in a flame retardant effect and stability, as well as difficulty to improve the comprehensive properties of the flame-retardant nylon.

Abstract: The present disclosure describes a circuit having a current source and a load circuit coupled to the current source. The current source can include a transistor electrically coupled to a voltage supply and can be configured to generate a first current with a first current rate-of-change during a time interval, where the first current can be a cancellation current. In addition, the load circuit can be configured to generate a second current with a second current rate-of-change during the same time interval, where the second current can be a load current. The second current rate-of-change can be substantially an inverse of the first current rate-of-change. A power system can include a power management unit configured to generate a power supply voltage at an output, a current source and a load circuit electrically coupled to the output, and a control circuit controls the first current rate-of-change during the time interval.

Abstract: The present disclosure relates to a method for alleviating and/or treating a coronavirus disease in a subject in need thereof, including administering an effective amount of Ganoderma immunomodulatory protein, a recombinant thereof or a fragment thereof to the subject.

Abstract: An optimization method for turbines of a thermal power unit based on sparse big data mining in the technical field of turbine optimization. The optimization method comprises: acquiring historical operating data of a unit; selecting a set of controllable operating parameters highly correlated with the heat rate of turbines as optimized parameters; constructing a new sparse data-oriented pattern-growth association rule mining algorithm based on binary matrixes and the hyperlink technique; proposing a load balancing strategy based on matrix operation on an Apache Spark platform, and parallelly implementing the global calculation-balanced pattern-growth association rule mining algorithm; and discretizing the historical operating data by clustering, parallelly mining the discretized historical operating data to obtain an association rule, and performing de-discretization to obtain target values of the optimized parameters of the turbines under boundary conditions.

Abstract: Methods and systems for reinforcement learning with dynamic agent grouping include gathering information at a first agent using one or more sensors. Shared information is received at the first agent from a second agent. An agent model is trained at the first agent using the gathered information and the shared information. A contribution of the shared information is weighted according to a degree of similarity between the first agent and the second agent. An action is generated using the trained agent model responsive to the gathered information.

Abstract: An optimization method for turbines of a thermal power unit based on sparse big data mining in the technical field of turbine optimization. The optimization method comprises: acquiring historical operating data of a unit; selecting a set of controllable operating parameters highly correlated with the heat rate of turbines as optimized parameters; constructing a new sparse data-oriented pattern-growth association rule mining algorithm based on binary matrixes and the hyperlink technique; proposing a load balancing strategy based on matrix operation on an Apache Spark platform, and parallelly implementing the global calculation-balanced pattern-growth association rule mining algorithm; and discretizing the historical operating data by clustering, parallelly mining the discretized historical operating data to obtain an association rule, and performing de-discretization to obtain target values of the optimized parameters of the turbines under boundary conditions.

Abstract: The present disclosure describes a circuit having a current source and a load circuit coupled to the current source. The current source can include a transistor electrically coupled to a voltage supply and can be configured to generate a first current with a first current rate-of-change during a time interval, where the first current can be a cancellation current. In addition, the load circuit can be configured to generate a second current with a second current rate-of-change during the same time interval, where the second current can be a load current. The second current rate-of-change can be substantially an inverse of the first current rate-of-change. A power system can include a power management unit configured to generate a power supply voltage at an output, a current source and a load circuit electrically coupled to the output, and a control circuit controls the first current rate-of-change during the time interval.

Abstract: A method and system obtaining positioning data from an object traveling on a plurality of routes; mapping the data into a plurality of points on a digital map; identifying points that are unmatched to the stored route trajectory; obtaining candidate transition points from the unmatched points; aggregating the candidate transition points by applying a clustering algorithm; selecting a first cluster of points and a plurality of second clusters of points, determining a confidence level that the first cluster of points are transition points indicating a transition between the routes, classifying the first cluster of points as a first plurality of traveling points having a first direction in response to the confidence being below a threshold confidence and automatically adjusting the stored route trajectory to indicate that the first cluster of points are on the route trajectory.

Abstract: This disclosure provides embodiments for context based vehicular traffic prediction. A trained neural network modeling a relationship between historical traffic data and associated historical contextual data for a roadway link is obtained. Expected contextual data for a future time period for the roadway link is acquired. Predicted traffic data for the future time period for the roadway link is generated with the trained neural network based on the expected contextual data.

Abstract: Techniques facilitating resolution-based spatial computing are provided. In one example, a computer-implemented method comprises traversing, by a device operatively coupled to a processor, a data structure corresponding to a land area for a location having an index; and determining, by the device, whether the location is at least partially within the land area based on a result of the traversing. In some embodiments, the traversing comprises: obtaining a threshold number of levels based at least in part on a resolution parameter; scanning a first level of the data structure for a node having an index corresponding to the index of the location; and iterating the scanning for respective subsequent levels of the data structure based on the scanning returning a node having subordinate nodes and a number of levels for which the scanning and iterating have been performed being less than the threshold number of levels.

Abstract: The present disclosure relates to a method for alleviating and/or treating a coronavirus disease in a subject in need thereof, including administering an effective amount of Ganoderma immunomodulatory protein, a recombinant thereof or a fragment thereof to the subject.

Abstract: A mechanism is provided for controlling the internal air-quality of a vehicle, including configuring a control policy that controls an internal air-quality of a vehicle and performing an action dictated by the control policy according to a window status of the vehicle.

Abstract: A method and/or system for managing a database that stores space-time context objects is provided. The system receives a query range in a multi-dimensional space. The system maps the query range into a set of fragments of a space-filling curve that fills the multi-dimensional space in all dimensions of the multi-dimensional space. The system uses each mapped fragment in the set of mapped fragments as a key to query the database for space-time context objects that are mapped to the space-filling curve. The system queries the database by identifying one or more context objects that intersect the mapped fragment at the space-filling curve.

Abstract: Blockchain based IoT data management can include receiving IoT data are with one or more processing units. At least one aggregation pattern of the IoT data can be determined by one or more processing units. The IoT data can be hashed, based upon the at least one aggregation pattern to obtain hash values of the IoT data by one or more processing units. The hash values can be sent to a blockchain system for storing by one or more processing units.

Abstract: Multi-level objectives improve efficiency of multi-objective automated machine learning. A hyperband framework is established with a kernel density estimator to shrink the search space based on evaluation of lower-level objectives. A Gaussian prior assumption directly shrinks the search space to find a main objective.

Abstract: A method for optimizing a neural network architecture by estimating an inference time for each operator in the neural network architecture is provided. The method may include determining a benchmark time for at least one single-path architecture out of a plurality of single-path architectures associated with the neural network by sampling the at least one single-path architecture from the neural network, wherein the at least one single-path architecture comprises one or more operators. The method may further include, based on the benchmark time for the at least one single-path architecture, determining an estimated inference time for an operator, wherein determining the estimated inference time for the operator comprises, applying an operator function, wherein the operator function comprises a function based on a difference between the benchmark time associated with the at least one single-path architecture and the estimated latency of the neural network.

Abstract: A method, system, and computer program product for obtaining a first route traversed by a target object, performing at least one prediction for a second route to be traversed by the target object based on the first route, the at least one prediction being performed with at least one of an object-specific prediction model, an object group-specific prediction model, and an object-independent prediction model, and determining, according to a decision rule, a prediction result of the second route based on the at least one prediction.