Abstract: A video monitoring system can include multiple collectors to receive video beacon data from multiple video monitoring interface modules. At least one beacon stream is connected to receive data from multiple collectors. A processing module receives the beacon stream and provides a real-time event stream used for real-time data analysis and a video view stream used for long-term data analysis.

Abstract: In some embodiments, a computer-implemented method for predicting agronomic field property data for one or more agronomic fields using a trained machine learning model is disclosed. The method comprises receiving, at an agricultural intelligence computer system, agronomic training data; training a machine learning model, at the agricultural intelligence computer system, using the agronomic training data; in response to receiving a request from a client computing device for agronomic field property data for one or more agronomic fields, automatically predicting the agronomic field property data for the one or more agronomic fields using the machine learning model configured to predict agronomic field property data; based on the agronomic field property data, automatically generating a first graphical representation; and causing to display the first graphical representation on the client computing device.

Abstract: The present invention provides compounds, compositions thereof, and methods of using the same for the inhibition of HPK1, and the treatment of HPK1-mediated disorders.

Abstract: A method for producing a tandem sub for a perforating gun system includes positioning an electrically conductive signal bar in a central passage of a tubular housing of the tandem sub, and injecting a mold material into an annulus formed between an outer surface of the signal bar and an inner surface of the tubular housing that sealably adheres to both the signal bar and the tubular housing.

Abstract: A video monitoring system can include multiple collectors to receive video beacon data from multiple video monitoring interface modules. At least one beacon stream is connected to receive data from multiple collectors. A processing module receives the beacon stream and provides a real-time event stream used for real-time data analysis and a video view stream used for long-term data analysis.

Abstract: An embodiment of a perforating gun system deployable in a wellbore extending through a subterranean earthen formation includes a tandem sub including a sub housing and a signal pod receivable in the sub housing, wherein the signal pod includes a detonator and a receptacle; and a perforating gun including a charge carrier configured to receive one or more shaped charges, the charge carrier including a detonator cord housing configured to receive a terminal end of a detonator cord, and wherein the detonator cord housing is receivable in the receptacle of the signal pod to ballistically couple the detonator cord with the detonator.

Abstract: A system and method are disclosed for detecting remaining battery voltage or capacity in an infusion device and generating alarms based on the detection. A battery lifetime extension method includes providing an infusion device that derives its power from a rechargeable battery. The infusion device may derive its power from a rechargeable battery. Furthermore, the infusion device receives, at predetermined intervals of time in real-time sensor data comprising a voltage, a change in the voltage over the predetermined interval of time, an average current, a temperature, and a remaining voltage or capacity reported by a battery gas gauge integrated circuit (“IC”) associated with the rechargeable battery. A customized neural network model utilizes the sensor data to determine an indicia of the actual remaining voltage or capacity of the rechargeable battery in real-time. The indicia may be used to lengthen and/or abate ongoing medical infusion therapy.

Abstract: A system and method is disclosed for detecting remaining battery voltage or capacity in an infusion device and generating alarms based on the detection. The battery lifetime extension method includes providing an infusion device that derives its power from a rechargeable battery. The infusion device may derive its power from a rechargeable battery. Furthermore, the infusion device receives, at predetermined intervals of time in real-time sensor data comprising: a voltage, a change in the voltage over the predetermined interval of time, an average current, a temperature, and a remaining voltage or capacity reported by a battery gas gauge integrated circuit (“IC”) associated with the rechargeable battery. An improved and customized neural network model utilizes the sensor data to determine an indicia of the actual remaining voltage or capacity of the rechargeable battery in real-time. The indicia may be used to lengthen and/or abate ongoing medical infusion therapy.

Abstract: An infusion pump includes a housing with a door pivotally mounted to the housing, a tube channel on the housing configured to hold a tube in the infusion pump, a pumping mechanism including a shuttle, and a slide clamp ejection device.

Abstract: An infusion pump includes a housing with a door pivotally mounted to the housing, a tube channel on the housing configured to hold a tube in the infusion pump, a pumping mechanism including a shuttle, and a slide clamp ejection device.

Abstract: The present disclosure provides a new and innovative method and system for flow rate compensation in devices, such as medical devices and other electronic devices. In various embodiments, a computer-implemented method includes dispensing, by a pump controlled by a controller, a fluid from a fluid supply in a pulse mode over a period by determining a pulse volume for a pulse, determining a pulse cycle time, and for the period: controlling the position of the pump to perform a delay and perform a pulse to dispense an amount of the fluid, the pulse performed for the pulse cycle time, calculating an overshoot or undershoot of the amount of the fluid dispensed relative to the pulse volume, adjusting the pulse cycle time based on the calculated overshoot or undershoot, and repeating the dispensing until the period has elapsed.

Abstract: Hybrid 3D geocellular grids are generated to represent a subset of a natural fracture network (“NFN”) directly in the simulation, while the remainder of the NFN is approximated by a multi-continuum formulation. The resulting output is a 3D geocellular grid that possesses a higher level of mesh resolution in those areas surrounding the first fracture subsets, and lower mesh resolution in the areas of the second fracture subset.

Abstract: In an embodiment, a computer-implemented method for predicting subfield soil properties for an agricultural field comprises: receiving satellite remote sensing data that includes a plurality of images capturing imagery of an agricultural field in a plurality of optical domains; receiving a plurality of environmental characteristics for the agricultural field; generating a plurality of preprocessed images based on the plurality of satellite remote sensing data and the plurality of environmental characteristics; identifying, based on the plurality preprocessed images, a plurality of features of the agricultural field; generating a subfield soil property prediction for the agricultural field by executing one or more machine learning models on the plurality of features; transmitting the subfield soil property prediction to an agricultural computer system.

Abstract: A system and method for controlling a gas supply to provide gas lift for a production wellbore makes use of Bayesian optimization. A computing device controls a gas supply to inject gas into one or more wellbores. The computing device receives reservoir data associated with a subterranean reservoir to be penetrated by the wellbores and can simulate production using the reservoir data and using a physics-based or machine learning or hybrid physics-based machine learning model for the subterranean reservoir. The production simulation can provide production data. A Bayesian optimization of an objective function of the production data subject to any gas injection constraints can be performed to produce gas lift parameters. The gas lift parameters can be applied to the gas supply to control the injection of gas into the wellbore or wellbores.

Abstract: Systems and methods for detecting an occlusion in an infusion device are disclosed. One method includes generating, during an infusion session at predetermined intervals, a feature vector comprising an initial measurement of a physical force caused by fluid motion through an infusion device at the start of an infusion session, a current measurement of the physical force, a long term change in the measurement of the physical force, and a short term change in the measurement of the physical force. The feature vector is inputted, during the predetermined intervals, into a support vector machine (“SVM”) to output an indication of a presence or an absence of an occlusion in the infusion device. The SVM may be trained using reference data from reference infusion sessions having known consequences regarding the presence or the absence of an occlusion at various times during the reference infusion sessions.

Abstract: A system and method is disclosed for detecting remaining battery voltage or capacity in an infusion device and generating alarms based on the detection. The battery lifetime extension method includes providing an infusion device that derives its power from a rechargeable battery. The infusion device may derive its power from a rechargeable battery. Furthermore, the infusion device receives, at predetermined intervals of time in real-time sensor data comprising: a voltage, a change in the voltage over the predetermined interval of time, an average current, a temperature, and a remaining voltage or capacity reported by a battery gas gauge integrated circuit (“IC”) associated with the rechargeable battery. An improved and customized neural network model utilizes the sensor data to determine an indicia of the actual remaining voltage or capacity of the rechargeable battery in real-time. The indicia may be used to lengthen and/or abate ongoing medical infusion therapy.

Abstract: In some embodiments, a scalable geospatial platform for an integrated data synthesis and artificial intelligence based exploration is disclosed. The platform is configured to implement various techniques for collecting data from different sources and different entities, and processing the data using various approaches, including, for example, the artificial intelligence based approaches.

Abstract: A system and method for controlling a gas supply to provide gas lift for a production wellbore makes use of Bayesian optimization. A computing device controls a gas supply to inject gas into one or more wellbores. The computing device receives reservoir data associated with a subterranean reservoir to be penetrated by the wellbores and can simulate production using the reservoir data and using a physics-based or machine learning or hybrid physics-based machine learning model for the subterranean reservoir. The production simulation can provide production data. A Bayesian optimization of an objective function of the production data subject to any gas injection constraints can be performed to produce gas lift parameters. The gas lift parameters can be applied to the gas supply to control the injection of gas into the wellbore or wellbores.

Abstract: A phosphate-free automatic dishwashing composition including an amine and an enzyme.

Abstract: In some embodiments, a computer-implemented method for predicting agronomic field property data for one or more agronomic fields using a trained machine learning model is disclosed. The method comprises receiving, at an agricultural intelligence computer system, agronomic training data; training a machine learning model, at the agricultural intelligence computer system, using the agronomic training data; in response to receiving a request from a client computing device for agronomic field property data for one or more agronomic fields, automatically predicting the agronomic field property data for the one or more agronomic fields using the machine learning model configured to predict agronomic field property data; based on the agronomic field property data, automatically generating a first graphical representation; and causing to display the first graphical representation on the client computing device.