Abstract: A refrigerant testing device and method for testing refrigerant diverted from a refrigeration system. The method comprises: diverting refrigerant from said refrigeration system to a container; changing a temperature of said refrigerant within said container; measuring a pressure and temperature of said refrigerant as said temperature changes; comparing said measured pressure and temperature values with reference values and where said comparing indicates a difference between said measured values and said stored reference values of more than a predetermined amount, generating a warning indication.

Abstract: A semiconductor wafer cooling system and method and a pressure regulating apparatus for mitigating pressure increases in a semiconductor wafer conditioning circuit are disclosed. The pressure regulating apparatus comprises: a buffer vessel, the buffer vessel comprising an inlet and outlet channel; wherein the inlet channel is configured in operation to be in fluid communication with a higher pressure location of the semiconductor wafer conditioning circuit, and the outlet channel is configured in operation to be in fluid communication with a lower pressure location. the inlet channel comprises a pressure controlled valve configured to close the inlet channel during normal operation such that the buffer vessel is isolated from the higher pressure location of the conditioning circuit and to open the inlet channel in response to the pressure within the semiconductor conditioning circuit rising above a predetermined level.

Abstract: A method or system for noninvasive evaluating and monitoring of abnormal cardiopulmonary vibrations includes obtaining one or more signals using one or more noninvasive heart and/or lung vibration signal sensors or transducers that provide a measure of physiological effects that are correlated with cardiopulmonary functions, recording, by a processor and one or more heart and/or lung vibration signal sensors or transducers for turbulence recordings between a first and second cardiopulmonary sounds, analyzing the turbulence recordings for unique vibration signatures associated with cardiopulmonary disease by searching deviations from an average beat, and presenting an assessment of cardiopulmonary disease upon finding that the deviations are above a predetermined threshold. In some embodiments, the system and method further include seeking a largest mean absolute error of a specific segment between an average beat and each beat from a subject to provide a murmur level indicative of cardiopulmonary disease.

Abstract: A control system for controlling the flow of refrigerant includes: an inlet valve configured to selectively isolate or couple a supply path for supplying refrigerant from a refrigeration system with an inlet of a cooling loop; an outlet valve configured to selectively isolate or couple a return path for returning refrigerant to the refrigeration system with an outlet of the cooling loop; a refrigerant collection valve configured to selectively isolate or couple a refrigerant collection path for collecting refrigerant for the refrigeration system with the cooling loop; a pressure sensor for determining a pressure of refrigerant in the cooling loop; an input for receiving cooling loop disconnect and connect commands; and control circuitry configured to receive signals from the pressure sensor and the commands from the input and to generate control signals for controlling the opening and closing of the inlet, outlet and refrigerant collection valves in response thereto.

Abstract: A system for noninvasive extraction, identification, and marking of the heart valve signals to evaluate and monitor elevated left ventricular end-diastolic pressure (LVEDP) or pulmonary capillary wedge pressure (PCWP) using at rest assessment of hemodynamic performance, based on quantitative measurements of heart and lung related parameters and cardiac events for diagnostic and therapeutic purposes includes one or more signals from one or more noninvasive sensors or transducers that measure one or more physiological effects that are correlated with cardiopulmonary functions, transmission of the data to a computing device and analysis software where a trained algorithm processes the data to determine the state or condition of elevated LVEDP or PCWP and provides an output indicative of the state or condition of the analysis.

Abstract: A semiconductor wafer cooling system and method and a pressure regulating apparatus for mitigating pressure increases in a semiconductor wafer conditioning circuit are disclosed. The pressure regulating apparatus comprises: a buffer vessel, the buffer vessel comprising an inlet and outlet channel; wherein the inlet channel is configured in operation to be in fluid communication with a higher pressure location of the semiconductor wafer conditioning circuit, and the outlet channel is configured in operation to be in fluid communication with a lower pressure location. the inlet channel comprises a pressure controlled valve configured to close the inlet channel during normal operation such that the buffer vessel is isolated from the higher pressure location of the conditioning circuit and to open the inlet channel in response to the pressure within the semiconductor conditioning circuit rising above a predetermined level.

Abstract: A health sensor system and method can include a wearable non-invasive biosensor for capturing cardiac waveform signals such as electrocardiogram (ECG) signals and composite vibration objects over one or more channels, one or more processors operatively coupled to the wearable non-invasive biosensor, and memory having computer instructions which causes the system to perform certain operations. In some embodiments, the operations can include powering the health sensor system in response to receiving a radio frequency signal using a near field communication protocol, monitoring pulmonary artery pressures based on cardiac time intervals during a period when the health sensor system is powered by the radio frequency signal, performing a heart and lung function assessment based on the monitoring of the pulmonary artery pressures, and presenting the heart and lung function assessment. In some embodiments, the biosensor can be a single NFC patch biosensor.

Abstract: A temperature control apparatus for supplying fluid to control a temperature of at least one semiconductor wafer within a semiconductor processing chamber, the temperature control apparatus comprising: a mixed refrigerant refrigeration system; the temperature control apparatus being configured to supply the mixed refrigerant to at least one conditioning circuit within the semiconductor processing chamber and to receive the mixed refrigerant from the at least one conditioning circuit. The temperature control apparatus comprises a temperature control circuitry for controlling a temperature of the at least one conditioning circuit to one of a plurality of predetermined temperatures, at least one of the temperatures being below -100° C., the temperature control circuitry being configured to control the temperature of the at least one conditioning circuit by controlling at least one of a mass flow rate, composition or temperature of the mixed refrigerant supplied to the at least one conditioning circuit.

Abstract: A system for marking cardiac time intervals from heart valve signals includes a non-invasive sensor unit for capturing electrical signals and composite vibration objects, a memory containing computer instructions, and one or more processors coupled to the memory. The one or more processors causes the one or more processors to perform operations including separating a plurality of individual heart vibration events into heart valve signals from the composite vibration objects, and marking cardiac time interval from the heart valve signals by detecting individual heartbeats using at least one or more of a PCA algorithm or deep learning.

Abstract: A system for marking cardiac time intervals from heart valve signals includes a non-invasive sensor unit for capturing electrical signals and composite vibration objects, a memory containing computer instructions, and one or more processors coupled to the memory. The one or more processors causes the one or more processors to perform operations including separating a plurality of individual heart vibration events into heart valve signals from the composite vibration objects, and marking cardiac time interval from the heart valve signals by detecting individual heartbeats using at least one or more of a PCA algorithm or deep learning.

Abstract: A system for marking cardiac time intervals from heart valve signals includes a non-invasive sensor unit for capturing electrical signals and composite vibration objects, a memory containing computer instructions, and one or more processors coupled to the memory. The one or more processors causes the one or more processors to perform operations including separating a plurality of individual heart vibration events into heart valve signals from the composite vibration objects, and marking cardiac time interval from the heart valve signals by detecting individual heartbeats and processing cumulative energy within the individual heartbeat to set a threshold to set a marking point.

Abstract: A sensor device and a method using the sensor device includes a portable device (110) configured to capture composite vibration objects from at least one sensor (102b) and further configured to communicate data to a wireless node (105) in some embodiments. The sensor device further includes at least one or more processors (103, 105, or 106) operatively coupled to the portable device and configured to separate and identify separated vibration sources and further configured to identify a plurality of individual heart vibration events (302, 303, 304, 305) from the composite vibration objects where the one or more processors is further configured to mark individual heart events from the plurality of individual heart vibration events. In some embodiments, the one or more processors marks and presents individual heart events from the plurality of individual heart vibration events.

Abstract: A system (100) for monitoring and diagnosing heart conditions includes a sensor array (102) with accelerometers, an electrocardiogram sensor, and a system to synchronously capture and process (103, 105, or 106) composite heart signals. The system performs separation, identification and marking (201-205 or 501-509) of the signals, to extract information in cardiac vibrations. Machine learning, auditory scene analysis, or spare coding approaches can be used to resolve source separation problems. Analysis of the composite signals separates different vibration signals (302, 303, 304, 305), identifies streams for particular valve signal, and marks them with event time information with respect to a synchronous electrocardiogram signal (306). The psychoacoustic analysis mimics human auditory processing to enhance hearing of heart valve sounds by separating valve vibrations from the composite signal, and providing extraction, identification, marking and display of individual valve signals.

Abstract: A method and system of assessing and monitoring of cardiopulmonary diseases can include the steps of receiving a composite signal representative of individual events from a plurality of sources associated with a patients cardio-pulmonary system and separating an individual signal as a separate component of the composite signal where the individual signal i s representative of an individual event from one of a plurality of cardio-pulmonary events. The method and system can further include and deriving clinical findings responsive from the separating and presenting the clinical findings.

Abstract: A system for monitoring and diagnosing heart conditions includes a sensor array with accelerometers, an electrocardiogram sensor, and a system to capture and process the composite heart signals. The system performs source separation to extract information contained in cardio pulmonic vibrations. The system can use machine learning, auditory scene analysis, spare coding, determined Models, Principal Component Analysis (PCA), Independent Component Analysis ICA, Singular Value Decomposition (SVD), Bin-wise Clustering and Permutation posterior probability alignment, Undetermined Models, Sparseness condition, Dictionary learning, Convolutive models, K-SVD Matching Pursuit, Non-negative matrix factorization and Deep Belief Networks (Restricted Boltzmann Machine) approaches to the source separation problem. Other embodiments are disclosed.

Abstract: A system for monitoring and diagnosing heart conditions includes a sensor array with accelerometers, an electrocardiogram sensor, and a system to capture and process the composite heart signals. The system performs source separation to extract information contained in cardio pulmonic vibrations. The system can use machine learning, auditory scene analysis, spare coding, determined Models, Principal Component Analysis (PCA), Independent Component Analysis ICA, Singular Value Decomposition (SVD), Bin-wise Clustering and Permutation posterior probability alignment, Undetermined Models, Sparseness condition, Dictionary learning, Convolutive models, K-SVD Matching Pursuit, Non-negative matrix factorization and Deep Belief Networks (Restricted Boltzmann Machine) approaches to the source separation problem. Other embodiments are disclosed.

Abstract: A system and method for monitoring and diagnosing heart conditions may include capturing and processing a composite heart signal and isolating individual components of such a composite signal. The disclosed techniques of measuring hemodynamic parameters may extract information contained in cardio-pulmonic vibrations. In operation, a system and method may separate different vibration signals along with event time information with respect to a synchronous electrocardiogram signal, and may provide for measurement of hemodynamic parameters from these separated signals.

Abstract: A system for marking cardiac time intervals from heart valve signals includes a non-invasive sensor unit for capturing electrical signals and composite vibration objects, a memory containing computer instructions, and one or more processors coupled to the memory. The one or more processors causes the one or more processors to perform operations including separating a plurality of individual heart vibration events into heart valve signals from the composite vibration objects, and marking cardiac time interval from the heart valve signals by detecting individual heartbeats and processing cumulative energy within the individual heartbeat to set a threshold to set a marking point.

Abstract: A system for identifying heart valve signals includes a non-invasive sensor unit for capturing electrical signals and composite vibration objects, a memory containing computer instructions, and one or more processors coupled to the memory, where the one or more processors are configured to perform the steps of separating a plurality of individual heart vibration events from the composite vibration objects by using at least one among bin-wise clustering and permutation alignment, or non-negative matrix factorization, or deep belief networks and tagging the plurality of individual heart vibration events using at least one among principal component analysis, Gabor filtering, generalized cross correlation, phase transform, smoothed coherent transformation, Roth correlation or band filtering.