Abstract: The present invention comprises a computer-implemented zero-trust authentication method that utilizes the Bitcoin Lightning Network, which is the sole protocol offering immediate, immutable, and cost-free Bitcoin settlement. A user requests access to the resource of a service provider and the user provides authentication material necessary to securely access the service provider. The service provider initiates a Hold Invoice via a cryptographic function to generate a pre-image hash, instructing the user to authorize release of Bitcoin in an amount stipulated by the Hold Invoice. Bitcoin is held in the Hold Invoice until an authentication attempt is either successful or unsuccessful. If successful, the user is issued an access token to login into the resource, the Hold Invoice is canceled and Bitcoin is released to the user. If unsuccessful, the pre-image is revealed, the user is denied access, and Bitcoin is transferred to the service provider as a settled payment transaction.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: A vascular testing system includes a pressure applicator, a pressure source for generating fluid pressure at the pressure applicator; a variable orifice valve, and a valve control. The variable orifice valve is in fluid communication with the pressure applicator, and has an orifice size capable of dynamically changing. The valve control controls the variable orifice valve as a function of sensed pressure to produce substantially linear changes in pressure at the pressure applicator. Further, a method of vascular pressure measurement according to the present invention includes providing an applied pressure higher than a patient's systolic blood pressure at a vascular location, substantially linearly decreasing the applied pressure at the vascular location, and dynamically detecting vascular pressure oscillations at the vascular location as the applied pressure is decreased.

Abstract: A vascular sensing system includes blood flow restricting means, a sensor, and means for producing an output representing a return of blood flow after the blood vessel has been temporarily collapsed by the blood flow restricting means. The blood flow restricting means is capable of placement on a human toe having a blood vessel, and is capable of manipulating the blood vessel. The sensor is operably connected to the blood flow restricting means and is physically spaced from the toe. Further, a method of vascular sensing includes taking pressure measurements with an pressure cuff positioned on a toe, and conducting a waveform analysis of the pressure measurements to determine a return of blood flow pressure.

Abstract: A method of vascular testing includes inflating a cuff at a vascular location, controllably deflating the cuff, producing a pressure waveform while deflating the cuff, and producing an output representing a pressure at which blood flow returns, while deflating the cuff, based upon analysis of the pressure waveform. Further, a testing system for measuring vascular pressures according to the present invention includes a pressure applicator, a pressure sensor, and a diagnostic test unit. The pressure applicator is positionable along exterior portions of a human body for dynamically applying pressure to a desired vascular location. The pressure sensor is capable of detecting oscillations in a pressure at the pressure applicator.