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2453results about "Investigating moving fluids/granular solids" patented technology

Monitoring and control system for blood processing

The invention relates generally to methods of monitoring and controlling the processing of blood and blood samples, particularly the separation of blood and blood samples into its components. In one aspect, the invention relates to optical methods, devices and device components for measuring two-dimensional distributions of transmitted light intensities, scattered light intensities or both from a separation chamber of a density centrifuge. In embodiment, two-dimensional distributions of transmitted light intensities, scattered light intensities or both measured by the methods of the present invention comprise images of a separation chamber or component thereof, such as an optical cell of a separation chamber. In another aspect, the present invention relates to multifunctional monitoring and control systems for blood processing, particularly blood processing via density centrifugation. Feedback control systems are provided wherein two-dimensional distributions of transmitted light intensities, scattered light intensities or both are measured, processed in real time and are used as the basis of output signals for controlling blood processing. In another aspect, optical cells and methods of using optical cells for monitoring and control blood processing are provided.
Owner:TERUMO BCT

Augmented classical least squares multivariate spectral analysis

InactiveUS6842702B2Accurate and precise prediction modelAccurate and precise predictionInvestigating moving fluids/granular solidsScattering properties measurementsAlternating least squaresSpectral analysis
A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.
Owner:NAT TECH & ENG SOLUTIONS OF SANDIA LLC
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