Abstract: The present disclosure generally relates to displaying information related to a physical activity. In some embodiments, methods and user interfaces for managing the display of information related to a physical activity are described.

Abstract: The present disclosure generally relates to methods for managing charging of an electronic device.

Abstract: A deep tendon reflex-eliciting device actuated by pressure against a patient's skin, which releases a spring-loaded mass that delivers an impulse through a fully-enclosed housing. This device includes a weight contained within the casings, and a mainspring in communication with the weight. The mainspring has a bias toward expansion. In the compressed position, the mainspring is also compressed, and the weight is pushed backwards into the rear casing. The weight is released to be driven forward by the mainspring. The weight strikes the inside of the forward casing, delivering an impulse to a surface against Which the device is pressed. A reset spring can push apart the forward and rear casings to reset the device to its expanded position. A case screw is also included which is able to consistently set the impact force of the device.

Abstract: A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Abstract: A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Abstract: An integrated circuit may include a memory controller circuit for communicating with an off-chip memory device. The memory controller is operable in a read-write major mode that is capable of dynamically adapting to any memory traffic pattern, which results in improved memory scheduling efficiency across different user applications. The memory controller may include at least a write command queue, a read command queue, an arbiter, and a command scheduler. The command scheduler may monitor a write command count, a read command count, a write stall count, and a read stall count to determine whether to dynamically adjust a read burst threshold setting and a write burst threshold setting.

Abstract: A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Abstract: A contactor includes a first actuator, a compressive element moveably coupling the first actuator to a rigid portion of the contactor, a shaft configured to move toward the rigid portion when the contactor is in an energized state and to move away from the rigid portion when the contactor is in a de-energized state, a second actuator fixedly coupled to the shaft, and a common contact extending between the first actuator and the second actuator, the common contact being moveable with respect to a first contact, wherein the compressive element is configured to press the first actuator against the common contact, and wherein the first actuator is configured to electrically connect the common contact and the first contact when the contactor is in the de-energized state, and the second actuator is configured to electrically disconnect the common contact and the first contact when the contactor is in the energized state.

Abstract: An industrial data analytics service facilitates gathering, manipulation, and presentation of data obtained from one or more disparate sources and streaming devices. The data analytics service enables users to specify a data source through which to obtain operational data and other information (e.g., gathered data). Subsequent to forming a connection with the data source, a sample data set is obtained by the data analytics service and used to determine an inventory of categories prior to saving the gathered data at the data analytics service. A user may then tailor the inventory of categories so that the data needed to meet business requirements is stored by the data analytics service. The data analytics service may analyze the stored data to determine one or more contexts (e.g., relationships, etc.) and present the contextual information in a storyboard.

Abstract: A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Abstract: A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Abstract: A contactor includes a first actuator, a compressive element moveably coupling the first actuator to a rigid portion of the contactor, a shaft configured to move toward the rigid portion when the contactor is in an energized state and to move away from the rigid portion when the contactor is in a de-energized state, a second actuator fixedly coupled to the shaft, and a common contact extending between the first actuator and the second actuator, the common contact being moveable with respect to a first contact, wherein the compressive element is configured to press the first actuator against the common contact, and wherein the first actuator is configured to electrically connect the common contact and the first contact when the contactor is in the de-energized state, and the second actuator is configured to electrically disconnect the common contact and the first contact when the contactor is in the energized state.

Abstract: A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Abstract: An integrated circuit may include a memory controller circuit for communicating with an off-chip memory device. The memory controller is operable in a read-write major mode that is capable of dynamically adapting to any memory traffic pattern, which results in improved memory scheduling efficiency across different user applications. The memory controller may include at least a write command queue, a read command queue, an arbiter, and a command scheduler. The command scheduler may monitor a write command count, a read command count, a write stall count, and a read stall count to determine whether to dynamically adjust a read burst threshold setting and a write burst threshold setting.

Abstract: A deep tendon reflex-eliciting device actuated by pressure against a patient's skin, which releases a spring-loaded mass that delivers an impulse through a fully-enclosed housing. This device includes a weight contained within the casings, and a mainspring in communication with the weight. The mainspring has a bias toward expansion. In the compressed position, the mainspring is also compressed, and the weight is pushed backwards into the rear casing. The weight is released to be driven forward by the mainspring. The weight strikes the inside of the forward casing, delivering an impulse to a surface against Which the device is pressed. A reset spring can push apart the forward and rear casings to reset the device to its expanded position. A case screw is also included which is able to consistently set the impact force of the device.

Abstract: A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Abstract: A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Abstract: A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Abstract: An Enterprise Resource Planning (ERP) gateway is provided for routing of ERP messages to Manufacturing Execution System (MES) applications. The gateway can receive a message from an ERP system via a manufacturing services bus specifying a business objective requiring action at a control level of an enterprise. The received message can be routed to a selected MES application capable of carrying out the business objective based on attributes within the message. Message routing can be based on location tags contained in the message. The message can also be routed to a selected subset of MES applications based on an analysis of respective capabilities and control contexts of the MES applications. Messages can be routed between the ERP system and the MES applications via the manufacturing services bus, which can manage protocol transformations for a heterogeneous set of applications.

Abstract: A Manufacturing Execution System (MES) is provided that leverages industry-specific workflows to process business requests. The MES system can maintain activity sets representing industry-specific workflows that can be selected and executed in order to satisfy business-driven goals. The activity sets can comprise both business-level and control-level operations, and can be configured using an intuitive graphical interface that mitigates the need for low-level programming by the end user. Some features of the MES system are enabled or disabled based on data type compatibility with devices in communication with the MES system.