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At least 109 records · Page 6

Initial blood storage experiment

The design of the Initial Blood Storage Experiment (IBSE) was based upon a carefully controlled comparison between identical sets of human blood cell suspensions - red cells, white cell, and platelets - one set of which was transported aboard the Columbia on a 6 day 11 hour mission, and the other held on the ground. Both sets were carried inside stainless steel dewars within specially fabricated flight hardware. Individual bags of cell suspensions were randomly assigned with respect to ground vs orbit status, dewar chamber, and specific location within the dewar. To foster optimal preservation, each cell type was held under specific optimal conditions of pH, ionic strength, solute concentration, gas tension, and temperature. An added variable in this initial experiment was provided by the use of three different polymer/plasticizer formulations for the sealed bags which held the blood cells. At termination of the experiment, aliquots of the suspensions, identified only by code, were distributed to be assayed. Assays were selected to constitute a broad survey of cellular properties and thereby maximize the chances of detection of gravitational effects. A total of 74 different outcome measurements were reported for statistical analysis. When the measurements were completed, the results were entered into the IBSE data base, at which time the data were matched with the original blood bag numbers to determine their status with respect to polymer/plasticizer type, orbit status (orbit or ground), and storage position within the experimental hardware. The data were studied by analysis of variance. Initially, type of bag and orbital status were main factors; later more detailed analyses were made on specific issues such as position in the hardware and specific plastic. If the analysis of variance indicated a statistical significance at the 5 percent level the corresponding p-value was reported.

Surgenor, Douglas MACN.↗

Repeated-Measures Analysis of Image Data

It is suggested that using a modified analysis of variance procedure on data sampled systematically from a rectangular array of image data can provide a measure of homogeneity of means over that array in single directions and how variation in perpendicular directions interact. The modification of analysis of variance required to account for spatial correlation is described theoretically and numerically on simulated data.

Newton, H. J.↗

Display format, highlight validity, and highlight method: Their effects on search performance

Display format and highlight validity were shown to affect visual display search performance; however, these studies were conducted on small, artificial displays of alphanumeric stimuli. A study manipulating these variables was conducted using realistic, complex Space Shuttle information displays. A 2x2x3 within-subjects analysis of variance found that search times were faster for items in reformatted displays than for current displays. Responses to valid applications of highlight were significantly faster than responses to non or invalidly highlighted applications. The significant format by highlight validity interaction showed that there was little difference in response time to both current and reformatted displays when the highlight validity was applied; however, under the non or invalid highlight conditions, search times were faster with reformatted displays. A separate within-subject analysis of variance of display format, highlight validity, and several highlight methods did not reveal a main effect of highlight method. In addition, observed display search times were compared to search time predicted by Tullis' Display Analysis Program. Benefits of highlighting and reformatting displays to enhance search and the necessity to consider highlight validity and format characteristics in tandem for predicting search performance are discussed.

Donner, Kimberly A.↗

Impact of Damping Uncertainty on SEA Model Response Variance

Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

Schiller, Noah↗

Evolution of the Antarctic Ice Sheet from 2000–2300 and beyond: model sensitivity and uncertainty analysis using MPAS-Albany Land Ice

We present a description of the Antarctic Ice Sheet model configuration submitted to the ISMIP6-Antarctica-2300 experiment using the MPAS-Albany Land Ice model, along with three new sets of simulations: (1) a set of extended simulations to 2500 for three forced experiments and to 2775 for the control experiment; (2) a sensitivity analysis of our model configuration to parameters controlling basal sliding and sub-shelf melt, and to model structural choices including the choice of the energy and stress balances; and (3) a 72-member ensemble run on graphics processing units (GPUs) and analysis of variance to determine the primary sources of uncertainty in our ice-sheet model projections. Our extended simulations predict rapid retreat beginning after 2300 for SSP1-2.6 forcing and after 2500 for present-day (control) forcing, primarily in the Amundsen Sea Embayment. We find that varying the sub-shelf melt parameter between the 5th to 95th percentile values for a mean-Antarctic calibration target results in an up to ∼ ± 40 % change in sea-level contribution relative to our baseline simulations that used the median value. Using a linear basal sliding law reduces sea-level contribution by 51 %–73 % relative to our baseline nonlinear sliding law with an exponent of 1/5. When using basal sliding law exponents of 1/3 and 1/10, the overall difference from our baseline simulations at 2300 is on the order of 10 %. The Amundsen Sea Embayment region displays a strongly non-linear dependence of mass loss on the sliding law exponent, with no discernible relationship between the sliding law exponent and the mass loss by 2300, while the sectors feeding the Ross and Filchner-Ronne ice shelves exhibit more mass loss with a more-plastic sliding law. Our model fidelity sensitivity experiments reveal a 9 %–31 % increase in sea-level contribution when using a depth-integrated stress balance approximation relative to our three-dimensional solver, while using a fixed-in-time temperature field increases sea-level contribution by 14 %–88 % relative to two thermomechanically coupled configurations. Our 72-member ensemble and analysis of variance show that the uncertainty in long-term projections is dominated by the choice of Earth system model forcing and the presence or absence of hydrofracture forcing, rather than uncertainty in sliding and sub-shelf melt parameters.

58 GEOSCIENCES↗

A further analysis for the minimum-variance deconvolution filter performance

Chi and Mendel (1984) analyzed the performance of minimum-variance deconvolution (MVD). In this correspondence, a further analysis of the performance of the MVD filter is presented. It is shown that the MVD filter performs like an inverse filter and a whitening filter as SNR goes to infinity, and like a matched filter as SNR goes to zero. The estimation error of the MVD filter is colored noise, but it becomes white when SNR goes to zero. This analysis also conects the error power-spectral density of the MVD filter with the spectrum of the causal-prediction error filter.

Chi, Chong-Yung↗

Finite Element Model Calibration Approach for Area I-X

Ares I-X is a pathfinder vehicle concept under development by NASA to demonstrate a new class of launch vehicles. Although this vehicle is essentially a shell of what the Ares I vehicle will be, efforts are underway to model and calibrate the analytical models before its maiden flight. Work reported in this document will summarize the model calibration approach used including uncertainty quantification of vehicle responses and the use of non-conventional boundary conditions during component testing. Since finite element modeling is the primary modeling tool, the calibration process uses these models, often developed by different groups, to assess model deficiencies and to update parameters to reconcile test with predictions. Data for two major component tests and the flight vehicle are presented along with the calibration results. For calibration, sensitivity analysis is conducted using Analysis of Variance (ANOVA). To reduce the computational burden associated with ANOVA calculations, response surface models are used in lieu of computationally intensive finite element solutions. From the sensitivity studies, parameter importance is assessed as a function of frequency. In addition, the work presents an approach to evaluate the probability that a parameter set exists to reconcile test with analysis. Comparisons of pretest predictions of frequency response uncertainty bounds with measured data, results from the variance-based sensitivity analysis, and results from component test models with calibrated boundary stiffness models are all presented.

Horta, Lucas G.↗

Finite Element Model Calibration Approach for Ares I-X

Ares I-X is a pathfinder vehicle concept under development by NASA to demonstrate a new class of launch vehicles. Although this vehicle is essentially a shell of what the Ares I vehicle will be, efforts are underway to model and calibrate the analytical models before its maiden flight. Work reported in this document will summarize the model calibration approach used including uncertainty quantification of vehicle responses and the use of nonconventional boundary conditions during component testing. Since finite element modeling is the primary modeling tool, the calibration process uses these models, often developed by different groups, to assess model deficiencies and to update parameters to reconcile test with predictions. Data for two major component tests and the flight vehicle are presented along with the calibration results. For calibration, sensitivity analysis is conducted using Analysis of Variance (ANOVA). To reduce the computational burden associated with ANOVA calculations, response surface models are used in lieu of computationally intensive finite element solutions. From the sensitivity studies, parameter importance is assessed as a function of frequency. In addition, the work presents an approach to evaluate the probability that a parameter set exists to reconcile test with analysis. Comparisons of pre-test predictions of frequency response uncertainty bounds with measured data, results from the variance-based sensitivity analysis, and results from component test models with calibrated boundary stiffness models are all presented.

Horta, Lucas G.↗

Elliptically-Contoured Tensor-variate Distributions with Application to Image Learning

Statistical analysis of tensor-valued data has largely used the tensor-variate normal (TVN) distribution that may be inadequate for data arising from distributions with heavier or lighter tails. We study a general family of elliptically contoured (EC) TV distributions and derive its characterizations, moments, marginal, and conditional distributions. We describe procedures for maximum likelihood estimation from data that are (1) uncorrelated draws from an EC distribution, (2) from a scale mixture of the TVN distribution, and (3) from an underlying but unknown EC distribution, for which we extend Tyler’s robust estimator. A detailed simulation study highlights the benefits of choosing an EC distribution over the TVN for heavier-tailed data. We develop TV classification rules using discriminant analysis and EC errors and show that they better predict cats and dogs from images in the Animal Faces-HQ dataset than the TVN-based rules. A novel tensor-on-tensor regression and TV analysis of variance (TANOVA) framework under EC errors is also demonstrated to better characterize gender, age, and ethnic origin than the usual TVN-based TANOVA in the celebrated labeled faces of the wild dataset.

97 MATHEMATICS AND COMPUTING↗

Effects of 40Ar and 56Fe ions on retinal photoreceptor cells of the rabbit: implications for manned missions to Mars

Losses of photoreceptor cells (rods) from the retinas of New Zealand white (NZW) rabbits were detectable within 2 years after localized acute irradiation of optic and proximal tissues with > or = 7 Gy of 530 MeV u-1 40Ar ions or > or = 2 Gy of 465 MeV u-1 56Fe ions in the Bragg plateau region of energy deposition. Those limits were determined only from an analysis of variance of dose groups because the shapes of the dose response curves at early post-irradiation times are not known, a concern being addressed by experiments in progress. Losses of photoreceptor cells for the period 0.5-2.5 years post-irradiation, determined by provisional linear regression analysis, were approximately 1.7% Gy-1 and 2.5% Gy-1 for 40Ar and 56Fe ions, respectively.

NASA Discipline Radiation Health↗

Left ventricular outflow tract mean systolic acceleration as a surrogate for the slope of the left ventricular end-systolic pressure-volume relationship

OBJECTIVE: The goal of this study was to analyze left ventricular outflow tract systolic acceleration (LVOT(Acc)) during alterations in left ventricular (LV) contractility and LV filling. BACKGROUND: Most indexes described to quantify LV systolic function, such as LV ejection fraction and cardiac output, are dependent on loading conditions. METHODS: In 18 sheep (4 normal, 6 with aortic regurgitation, and 8 with old myocardial infarction), blood flow velocities through the LVOT were recorded using conventional pulsed Doppler. The LVOT(Acc) was calculated as the aortic peak velocity divided by the time to peak flow; LVOT(Acc) was compared with LV maximal elastance (E(m)) acquired by conductance catheter under different loading conditions, including volume and pressure overload during an acute coronary occlusion (n = 10). In addition, a clinically validated lumped-parameter numerical model of the cardiovascular system was used to support our findings. RESULTS: Left ventricular E(m) and LVOT(Acc) decreased during ischemia (1.67 +/- 0.67 mm Hg.ml(-1) before vs. 0.93 +/- 0.41 mm Hg.ml(-1) during acute coronary occlusion [p < 0.05] and 7.9 +/- 3.1 m.s(-2) before vs. 4.4 +/- 1.0 m.s(-2) during coronary occlusion [p < 0.05], respectively). Left ventricular outflow tract systolic acceleration showed a strong linear correlation with LV E(m) (y = 3.84x + 1.87, r = 0.85, p < 0.001). Similar findings were obtained with the numerical modeling, which demonstrated a strong correlation between predicted and actual LV E(m) (predicted = 0.98 [actual] -0.01, r = 0.86). By analysis of variance, there was no statistically significant difference in LVOT(Acc) under different loading conditions. CONCLUSIONS: For a variety of hemodynamic conditions, LVOT(Acc) was linearly related to the LV contractility index LV E(m) and was independent of loading conditions. These findings were consistent with numerical modeling. Thus, this Doppler index may serve as a good noninvasive index of LV contractility.

Non-NASA Center↗

Unbalanced Nested Random Effects Estimation of Variance Components

To investigate the contributing factors of variance in the measurement of an iodine 127 (127I) sample, we implement a nested random effects analysis of variance (ANOVA). Historically, the reported uncertainty on a measurement of 127I has been obtained by methods of forward uncertainty propagation because there is typically only one replicate of a given sample for which to estimate the uncertainty. When samples are processed there are several types of quality control (QC) standards analyzed along-side the unknown samples with two to five replicates for each. Assuming the variance observed in these replicate QC standards is representative of that of the unknown samples, we use these data in a nested random effects ANOVA to estimate the total uncertainty of a measurement. We demonstrate this approach with two sets of measurements from Idaho National Laboratory and compare the results with the forward uncertainty propagation approach. Variance component estimates for the coarsest level of the nesting structure were most imprecise because replicates were most limited at these levels. We find that the results largely agree between forward propagation and ANOVA, and the greatest contributors of variance are due to instrument variation and chemical processing, with human processing being among the smallest contributors. This analysis provides reassurance that the reported uncertainties using forward propagation are reasonable and the process is well controlled. We propose a future designed experiment to increase replicates at the coarsest level of the hierarchy to improve estimates of these variance components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of secondary gas-phase reactions (SGR) in pyrolysis of carbon feedstocks for anisotropic carbon materials production – 2: Effects of SGR on tars produced from varying ranks of coal

Herein, this work explores the extent to which secondary gas-phase reactions (SGR) in pyrolysis can be used to modify coal tar chemistries from coals of different ranks in favor of improved anisotropy formation in their respective pitches. Pyrolysis was performed on four different coals of varying bituminous rank (Utah Sufco, Wyoming PRB Black Thunder, Illinois #6, and West Virginia Flying Eagle), with SGR temperatures ranging from 800 to 900° C and nominal SGR gas-phase residence times from 1 to 2.5 s. The oxygen content, aliphatic content, and molecular weight distributions of the coal tar samples were measured to indicate the changes with increasing levels of SGR, and microscopy was also used to measure changes in anisotropy formation in the resulting pitch samples. Generally, for all coals tested, increased levels of pyrolysis SGR led to decreased oxygen and aliphatic content, increased molecular weight sizes, and improved anisotropy formation. However, it was clear that the extent of these property changes depended on the chemistry and rank of the starting coal feedstock. Despite the relatively high rank of the Illinois #6 coal, its respective pitch samples performed poorly in improving anisotropy formation, due to its high sulfur content. The PRB, Sufco, and Flying Eagle coals performed better in their anisotropy formation than Illinois #6, depending on their respective coal ranks. Statistical analysis (analysis of variance, ANOVA) performed on the sample characterization data also suggests that SGR temperature is consistently the most dominant and significant effect on the resulting coal products.

01 COAL, LIGNITE, AND PEAT↗

Interannual variability and predictability of 500 mb geopotential heights over the Northern Hemisphere

The interannual variability of monthly mean 500 mb heights in a 15-year sample of observed data is compared to the variance expected from sampling errors associated with high-frequency fluctuations using the analysis of variance approach. The monthly mean 'signal' stands out significantly from the 'noise' over a substantial fraction of the Northern Hemisphere during the winter. The expected spectrum of variance at very low frequencies is assumed to be white at frequencies lower than per (30 days) rather than the per (96 days) cutoff used by Madden. This difference is justified by observing that the effective time between independent samples T(0) is relatively insensitive to changes in the maximum lag over which the local autocorrelation is integrated to calculate T(0). Further non-randomness in the variance of 500 mb heights is evidenced by the correlation between monthly mean height and contemporaneous daily variability.

Shukla, J.↗

Influence of the helicopter environment on patient care capabilities: flight crew perceptions

INTRODUCTION: Flight crew perceptions of the effect of the rotary-wing environment on patient-care capabilities have not been subject to statistical analysis. We hypothesized that flight crew members perceived significant difficulties in performing patient-care tasks during air medical transport. METHODS: A survey was distributed to a convenience sample of flight crew members from 20 flight programs. Respondents were asked to compare the difficulty of performing patient-care tasks in rotary-wing and standard (emergency department or intensive care unit) settings. Demographic data collected on respondents included years of flight experience, flights per month, crew duty position and primary aircraft in which the respondent worked. Statistical analysis was performed as appropriate using Student's t-test, type III sum of squares, and analysis of variance. Alpha was defined as p < 0.05. RESULTS: Fifty-five percent of programs (90 individuals) responded. All tasks were significantly rated more difficult in the rotary-wing environment. Ratings were not significantly correlated with flight experience, duty position, flights per month or aircraft used. CONCLUSIONS: We conclude that the performance of patient-care tasks are perceived by air medical flight crew to be significantly more difficult during rotary-wing air medical transport than in hospital settings.

Noise, Transportation/adverse effects↗

Impact of lossy compression on diagnostic accuracy of radiographs for periapical lesions

OBJECTIVES: The purpose of this study was to evaluate the lossy Joint Photographic Experts Group compression for endodontic pretreatment digital radiographs. STUDY DESIGN: Fifty clinical charge-coupled device-based, digital radiographs depicting periapical areas were selected. Each image was compressed at 2, 4, 8, 16, 32, 48, and 64 compression ratios. One root per image was marked for examination. Images were randomized and viewed by four clinical observers under standardized viewing conditions. Each observer read the image set three times, with at least two weeks between each reading. Three pre-selected sites per image (mesial, distal, apical) were scored on a five-scale score confidence scale. A panel of three examiners scored the uncompressed images, with a consensus score for each site. The consensus score was used as the baseline for assessing the impact of lossy compression on the diagnostic values of images. The mean absolute error between consensus and observer scores was computed for each observer, site, and reading session. RESULTS: Balanced one-way analysis of variance for all observers indicated that for compression ratios 48 and 64, there was significant difference between mean absolute error of uncompressed and compressed images (P <.05). After converting the five-scale score to two-level diagnostic values, the diagnostic accuracy was strongly correlated (R (2) = 0.91) with the compression ratio. CONCLUSION: The results of this study suggest that high compression ratios can have a severe impact on the diagnostic quality of the digital radiographs for detection of periapical lesions.

NASA Discipline Space Human Factors↗

Predictive Modeling of NOx Emissions from Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blends Using Flame Imaging and Machine Learning

This research paper explores the use of machine learning to relate images of flame structure and luminosity to measured NOx emissions. Images of reactions produced by 16 aero-engine derived injectors for a ground-based turbine operated on a range of fuel compositions, air pressure drops, preheat temperatures and adiabatic flame temperatures were captured and postprocessed. The experimental investigations were conducted under atmospheric conditions, capturing CO, NO and NOx emissions data and OH* chemiluminescence images from 27 test conditions. The injector geometry and test conditions were based on a statistically designed test plan. These results were first analyzed using the traditional analysis approach of analysis of variance (ANOVA). The statistically based test plan yielded 432 data points, leading to a correlation for NOx emissions as a function of injector geometry, test conditions and imaging responses, with 70.2% accuracy. As an alternative approach to predicting emissions using imaging diagnostics as well as injector geometry and test conditions, a random forest machine learning algorithm was also applied to the data and was able to achieve an accuracy of 82.6%. This study offers insights into the factors influencing emissions in ground-based turbines while emphasizing the potential of machine learning algorithms in constructing predictive models for complex systems.

08 HYDROGEN↗