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NASA NTRS2002

Survival after aortic valve replacement for severe aortic stenosis with low transvalvular gradients and severe left ventricular dysfunction

OBJECTIVE: We sought to assess whether aortic valve replacement (AVR) among patients with severe aortic stenosis (AS), severe left ventricular (LV) dysfunction and a low transvalvular gradient (TVG) is associated with improved survival. BACKGROUND: The optimal management of patients with severe AS with severe LV dysfunction and a low TVG remains controversial. METHODS: Between 1990 and 1998, we evaluated 68 patients who underwent AVR at our institution (AVR group) and 89 patients who did not undergo AVR (control group), with an aortic valve area < or = 0.75 cm(2), LV ejection fraction < or = 35% and mean gradient < or = 30 mm Hg. Using propensity analysis, survival was compared between a cohort of 39 patients in the AVR group and 56 patients in the control group. RESULTS: Despite well-matched baseline characteristics among propensity-matched patients, the one- and four-year survival rates were markedly improved in patients in the AVR group (82% and 78%), as compared with patients in the control group (41% and 15%; p < 0.0001). By multivariable analysis, the main predictor of improved survival was AVR (adjusted risk ratio 0.19, 95% confidence interval 0.09 to 0.39; p < 0.0001). The only other predictors of mortality were age and the serum creatinine level. CONCLUSIONS: Among select patients with severe AS, severe LV dysfunction and a low TVG, AVR was associated with significantly improved survival.

NASA Discipline Cardiopulmonary↗

NASA NTRS1998

Effect of altered sensory conditions on multivariate descriptors of human postural sway

Multivariate descriptors of sway were used to test whether altered sensory conditions result not only in changes in amount of sway but also in postural coordination. Eigenvalues and directions of eigenvectors of the covariance of shnk and hip angles were used as a set of multivariate descriptors. These quantities were measured in 14 healthy adult subjects performing the Sensory Organization test, which disrupts visual and somatosensory information used for spatial orientation. Multivariate analysis of variance and discriminant analysis showed that resulting sway changes were at least bivariate in character, with visual and somatosensory conditions producing distinct changes in postural coordination. The most significant changes were found when somatosensory information was disrupted by sway-referencing of the support surface (P = 3.2 x 10(-10)). The resulting covariance measurements showed that subjects not only swayed more but also used increased hip motion analogous to the hip strategy. Disruption of vision, by either closing the eyes or sway-referencing the visual surround, also resulted in altered sway (P = 1.7 x 10(-10)), with proportionately more motion of the center of mass than with platform sway-referencing. As shown by discriminant analysis, an optimal univariate measure could explain at most 90% of the behavior due to altered sensory conditions. The remaining 10%, while smaller, are highly significant changes in posture control that depend on sensory conditions. The results imply that normal postural coordination of the trunk and legs requires both somatosensory and visual information and that each sensory modality makes a unique contribution to posture control. Descending postural commands are multivariate in nature, and the motion at each joint is affected uniquely by input from multiple sensors.

NASA Discipline Neuroscience↗

NASA NTRS2001

Noninvasive assessment of mitral inertness: clinical results with numerical model validation

Inertial forces (Mdv/dt) are a significant component of transmitral flow, but cannot be measured with Doppler echo. We validated a method of estimating Mdv/dt. Ten patients had a dual sensor transmitral (TM) catheter placed during cardiac surgery. Doppler and 2D echo was performed while acquiring LA and LV pressures. Mdv/dt was determined from the Bernoulli equation using Doppler velocities and TM gradients. Results were compared with numerical modeling. TM gradients (range: 1.04-14.24 mmHg) consisted of 74.0 +/- 11.0% inertial forcers (range: 0.6-12.9 mmHg). Multivariate analysis predicted Mdv/dt = -4.171(S/D (RATIO)) + 0.063(LAvolume-max) + 5. Using this equation, a strong relationship was obtained for the clinical dataset (y=0.98x - 0.045, r=0.90) and the results of numerical modeling (y=0.96x - 0.16, r=0.84). TM gradients are mainly inertial and, as validated by modeling, can be estimated with echocardiography.

NASA Discipline Cardiopulmonary↗

NASA NTRS1999

Evaluation of Meterorite Amono Acid Analysis Data Using Multivariate Techniques

The amino acid distributions in the Murchison carbonaceous chondrite, Mars meteorite ALH84001, and ice from the Allan Hills region of Antarctica are shown, using a multivariate technique known as Principal Component Analysis (PCA), to be statistically distinct from the average amino acid compostion of 101 terrestrial protein superfamilies.

meteorites Amino acids Multivariate Analysis↗

NASA NTRS1997

Chemical and physical gradients along the OMC-1 ridge

We present a survey of the distribution of 20 chemical and isotopic molecular species along the central ridge of the Orion molecular cloud from 6' north to 6' south of BN-KL observed with the QUARRY focal plane array on the FCRAO 14 m telescope, which provides an angular resolution of approximately 50" in the 3 mm wavelength region. We use standard tools of multivariate analysis for a systematic investigation of the similarities and differences among the maps of integrated intensities of the 32 lines observed. The maps fall in three broad classes: first, those strongly peaked toward BN-KL; second, those having rather flat distributions along the ridge; and third, those with a clear north-south gradient or contrast. We identify six positions or regions where we calculate relative abundances. Line velocities and line widths indicate that the optically thin lines generally trace the same volume of dense gas, except in the molecular bar, where C18O, C34S, H13CO+, CN, C2H, SO, and C3H2 have velocities characteristic of the bar itself, whereas the emission from other detected species is dominated by the background cloud. The strongest abundance variations in our data are the well-known enhancements seen in HCN, CH3OH, HC3N, and SO toward BN-KL and, less strongly, toward the Orion-South outflow 1'.3S. The principal result of this study is that along the extended quiescent ridge the chemical abundances, within factors of 3-4, exhibit an impressive degree of uniformity. The northern part of the ridge has a chemistry closest to that found in quiescent dense clouds. While temperature and density are similar around the northern radical-ion peak near 3'.5N and in the southern core near 4'.2S, some abundances, in particular, those of the ions HCO+ and N2H+, are significantly lower toward 4'.2S. The areas near 4.'2S and the molecular bar itself around (1'.7E, 2'.4S) stand out with peculiar and similar properties probably caused by stronger UV fields penetrating deeper into the clumpy molecular gas. This leads to higher electron abundances and thereby reduced abundances of the ions, as well as a lack of complex molecules.

NASA Discipline Exobiology↗

NASA NTRS1978

Analysis of vector wind change with respect to time for Cape Kennedy, Florida

Multivariate analysis was used to determine the joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from 15 years of twice-daily rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, that the joint distribution of wind component change with respect to time is univariate normal, that the joint distribution of wind component changes is bivariate normal, and that the modulus of vector wind change is Rayleigh are tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from 1 to 5 hours, calculated from Jimsphere data, are presented. Extension of the theoretical prediction (based on rawinsonde data) of wind component change standard deviation to time periods of 1 to 5 hours falls (with a few exceptions) within the 95 percentile confidence band of the population estimate obtained from the Jimsphere sample data. The joint distributions of wind change components, conditional wind components, and 1 km vector wind shear change components are illustrated by probability ellipses at the 95 percentile level.

Adelfang, S. I.↗

NASA NTRS1992

Analysis of airframe/engine interactions for a STOVL aircraft with integrated flight/propulsion control

A multivariable analysis technique is used to evaluate the effects of the dynamic cross coupling between the airframe and engine subsystems in an advanced STOVL configuration. A critical frequency range is identified along with potentially poor stability robustness due to the airframe/engine interactions. Within the critical frequency range, stability and performance are found to be sensitive to variations in the coupling between the airframe's flight path angle and the engine's fuel flow rate. A stability sensitivity study indicates that the interactions between the flight path angle and the fuel flow rate are potentially the most critical with respect to stability and performance robustness.

Schierman, John D.↗

NASA NTRS1970

A frequency domain approach to the design and analysis of linear multivariable systems

Frequency domain approach to design and analysis of linear multivariable systems

Wolovich, W. A.↗

NASA NTRS1974

An analysis of fracture trace patterns in areas of flat-lying sedimentary rocks for the detection of buried geologic structure

Two study areas in a cratonic platform underlain by flat-lying sedimentary rocks were analyzed to determine if a quantitative relationship exists between fracture trace patterns and their frequency distributions and subsurface structural closures which might contain petroleum. Fracture trace lengths and frequency (number of fracture traces per unit area) were analyzed by trend surface analysis and length frequency distributions also were compared to a standard Gaussian distribution. Composite rose diagrams of fracture traces were analyzed using a multivariate analysis method which grouped or clustered the rose diagrams and their respective areas on the basis of the behavior of the rays of the rose diagram. Analysis indicates that the lengths of fracture traces are log-normally distributed according to the mapping technique used. Fracture trace frequency appeared higher on the flanks of active structures and lower around passive reef structures. Fracture trace log-mean lengths were shorter over several types of structures, perhaps due to increased fracturing and subsequent erosion. Analysis of rose diagrams using a multivariate technique indicated lithology as the primary control for the lower grouping levels. Groupings at higher levels indicated that areas overlying active structures may be isolated from their neighbors by this technique while passive structures showed no differences which could be isolated.

Podwysocki, M. H.↗

NASA NTRS1981

Practical robustness measures in multivariable control system analysis

The robustness of the stability of multivariable linear time invariant feedback control systems with respect to model uncertainty is considered using frequency domain criteria. Available robustness tests are unified under a common framework based on the nature and structure of model errors. These results are derived using a multivariable version of Nyquist's stability theorem in which the minimum singular value of the return difference transfer matrix is shown to be the multivariable generalization of the distance to the critical point on a single input, single output Nyquist diagram. Using the return difference transfer matrix, a very general robustness theorem is presented from which all of the robustness tests dealing with specific model errors may be derived. The robustness tests that explicitly utilized model error structure are able to guarantee feedback system stability in the face of model errors of larger magnitude than those robustness tests that do not. The robustness of linear quadratic Gaussian control systems are analyzed.

Lehtomaki, N. A.↗

NASA NTRS1972

Automatic classification of soils and vegetation with ERTS-1 data

Preliminary results of a test of a computerized analysis method using ERTS 1 data are presented. The method consisted of a four-spectral-band supervised, maximum likelihood, Gaussian classifier with training statistics derived through a combination of clustering and manual methods. The multivariate analysis method leads to the assignment of each resolution element of the data to one of a preselected set of discrete classes. The data frame was an area over the Texas-Oklahoma border including Lake Texoma. The study suggests that multispectral scanner data coupled with machine processing shows promise for earth surface cover surveys. Futhermore, the processing time is short and consequently the costs are low; a full frame can be analyzed completely within 48 hours.

Landgrebe, D. A.↗

NASA NTRS1985

An Integrated Analysis of the Physiological Effects of Space Flight: Executive Summary

A large array of models were applied in a unified manner to solve problems in space flight physiology. Mathematical simulation was used as an alternative way of looking at physiological systems and maximizing the yield from previous space flight experiments. A medical data analysis system was created which consist of an automated data base, a computerized biostatistical and data analysis system, and a set of simulation models of physiological systems. Five basic models were employed: (1) a pulsatile cardiovascular model; (2) a respiratory model; (3) a thermoregulatory model; (4) a circulatory, fluid, and electrolyte balance model; and (5) an erythropoiesis regulatory model. Algorithms were provided to perform routine statistical tests, multivariate analysis, nonlinear regression analysis, and autocorrelation analysis. Special purpose programs were prepared for rank correlation, factor analysis, and the integration of the metabolic balance data.

Leonard, J. I.↗

NASA NTRS1973

Digital image processing for information extraction.

The modern digital computer has made practical image processing techniques for handling nonlinear operations in both the geometrical and the intensity domains, various types of nonuniform noise cleanup, and the numerical analysis of pictures. An initial requirement is that a number of anomalies caused by the camera (e.g., geometric distortion, MTF roll-off, vignetting, and nonuniform intensity response) must be taken into account or removed to avoid their interference with the information extraction process. Examples illustrating these operations are discussed along with computer techniques used to emphasize details, perform analyses, classify materials by multivariate analysis, detect temporal differences, and aid in human interpretation of photos.

Billingsley, F. C.↗

NASA NTRS1993

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance.

Iyer, Ravishankar, K.↗

NASA NTRSDate not supplied

Aircraft Icing Analysis of Alternatives

This paper provides a description of a recent comprehensive Analysis of Alternatives (AoA) for icing research. A team of NASA icing subject matter experts (SMEs) was assembled from NASA’s Glenn and Langley Research Centers, which began by gathering inputs from icing stakeholders in industry, Government, and academia. Those inputs, which were grouped into a number of themes, were used by the SMEs to identify needed icing technical elements. Each of these high-level technical elements included the icing physics, modeling capabilities, and experimental capabilities needed to address a particular element. A multivariable analysis technique called TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) was then applied to prioritize the technical elements for several potential future realities. A large number of icing research needs were identified and analyzed to determine the highest priorities for NASA key focus areas and those that will endure into the future. The primary outcome of the AoA is the identification of legacy and newly identified capability areas in priority order to guide future investment.

Icing↗

NASA NTRSDate not supplied

Aircraft Icing Analysis of Alternatives

Icing, Rotorcraft↗

NASA NTRS1992

Materials surface contamination analysis

The original research objective was to demonstrate the ability of optical fiber spectrometry to determine contamination levels on solid rocket motor cases in order to identify surface conditions which may result in poor bonds during production. The capability of using the spectral features to identify contaminants with other sensors which might only indicate a potential contamination level provides a real enhancement to current inspection systems such as Optical Stimulated Electron Emission (OSEE). The optical fiber probe can easily fit into the same scanning fixtures as the OSEE. The initial data obtained using the Guided Wave Model 260 spectrophotometer was primarily focused on determining spectra of potential contaminants such as HD2 grease, silicones, etc. However, once we began taking data and applying multivariate analysis techniques, using a program that can handle very large data sets, i.e., Unscrambler 2, it became apparent that the techniques also might provide a nice scientific tool for determining oxidation and chemisorption rates under controlled conditions. As the ultimate power of the technique became recognized, considering that the chemical system which was most frequently studied in this work is water + D6AC steel, we became very interested in trying the spectroscopic techniques to solve a broad range of problems. The complexity of the observed spectra for the D6AC + water system is due to overlaps between the water peaks, the resulting chemisorbed species, and products of reaction which also contain OH stretching bands. Unscrambling these spectral features, without knowledge of the specific species involved, has proven to be a formidable task.

Workman, Gary L.↗

NASA NTRS2022

An Advanced Open-Source Platform for Air Quality Analysis, Visualization, and Prediction

Ambient air pollution is the largest environmental health risk factor, leading to several million premature deaths globally per year. The challenge of combating poor air quality is exacerbated by growing urban populations, changing emissions, and a warming climate. While there have been many advances monitoring and modeling of atmospheric composition, reflected in the dramatic increase in archived Earth Observations, there is no single measurement or method that alone can provide an accurate depiction of the entire atmosphere. The rapidly growing collections of observational and modeling data require us to be smarter about what data to include, and how such data is used. In recent years, NASA has invested significantly in advancing the concepts for Analytics Collaborative Framework (ACF) [5] and New Observing Strategies (NOS) [4] to tackle our software infrastructure need for harmonized data management and dynamic acquisition of diverse measurements for on-demand, interactive, multivariate analysis, and access [3]. It is not enough to have a big data, standalone analytics solution; it is critical that we start integrating data from remote sensing, modeling, and in-situ networks in a harmonized manner that enables timely and data-driven decision-making for air quality management. This work presents the design and development of an Air Quality Analytics Collaborative Framework (AQ ACF), as part of NASA’s Advanced Information Systems Technology (AIST) effort, to establish a data, machine-learning, and numerically driven platform for air quality analysis, visualization, and prediction.

Liu, Qian↗