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NASA NTRS1991

Acridine orange staining reaction as an index of physiological activity in Escherichia coli

The assumption that the acridine orange (AO) color reaction may be used as an index of physiological activity was investigated in laboratory grown Escherichia coli. Spectrofluorometric observations of purified nucleic acids, ribosomes and the microscopic color of bacteriophage-infected cells stained with AO confirmed the theory that single-stranded nucleic acids emit orange to red fluorescence while those that are double-stranded fluoresce green in vivo. Bacteria growing actively in a rich medium could be distinguished from cells in stationary phase by the AO reaction. Cells from log phase appeared red, whereas those in stationary phase were green. However, this differentiation was not seen when the bacteria were grown in a minimal medium or when a variation of the staining method was used. Also, shifting bacteria in stationary phase to starvation conditions rapidly changed their AO staining reaction. Boiling and exposure to lethal concentrations of azide and formalin resulted in stationary-phase cells that appeared red after staining but bacteria killed with chlorine remained green. These findings indicate that the AO staining reaction may be suggestive of physiological activity under defined conditions. However, variables in staining and fixation procedures as well as uncertainties associated with mixed bacterial populations in environmental samples may produce results that are not consistent with the classical interpretation of this reaction. The importance of validating the putative physiological implications of this staining reaction is stressed.

NASA Discipline Number 04-10↗

NASA NTRS2001

NASA/American Cancer Society High-Resolution Flow Cytometry Project-I

BACKGROUND: The NASA/American Cancer Society (ACS) flow cytometer can simultaneously analyze the electronic nuclear volume (ENV) and DNA content of cells. This study describes the schematics, resolution, reproducibility, and sensitivity of biological standards analyzed on this unit. METHODS: Calibrated beads and biological standards (lymphocytes, trout erythrocytes [TRBC], calf thymocytes, and tumor cells) were analyzed for ENV versus DNA content. Parallel data (forward scatter versus DNA) from a conventional flow cytometer were obtained. RESULTS: ENV linearity studies yielded an R value of 0.999. TRBC had a coefficient of variation (CV) of 1.18 +/- 0.13. DNA indexes as low as 1.02 were detectable. DNA content of lymphocytes from 42 females was 1.9% greater than that for 60 males, with a noninstrumental variability in total DNA content of 0.5%. The ENV/DNA ratio was constant in 15 normal human tissue samples, but differed in the four animal species tested. The ENV/DNA ratio for a hypodiploid breast carcinoma was 2.3 times greater than that for normal breast tissue. CONCLUSIONS: The high-resolution ENV versus DNA analyses are highly reliable, sensitive, and can be used for the detection of near-diploid tumor cells that are difficult to identify with conventional cytometers. ENV/DNA ratio may be a useful parameter for detection of aneuploid populations.

NASA Center JSC↗

NASA NTRS2016

Streamlining the Design Tradespace for Earth Imaging Constellations

Science Data Processing↗

NASA NTRS2017

Navigating the Deployment and Downlink Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the different types of constellations that TAT-C’s Tradespace Search Iterator is capable of enumerating (homogeneous Walker, heterogeneous Walker, precessing type, ad-hoc) and their impact on key performance metrics such as revisit statistics, time to global access and coverage. We will also discuss the ability to simulate phased deployment of the given constellations, as a function of launch availabilities and/or vehicle capability, and show the impact on performance. All performance metrics are calculated by the Data Reduction and Metric Computation module within TAT-C, which issues specific requests and processes results from the Orbit and Coverage module. Our TSI is also capable of generating tradespaces for downlinking imaging data from the constellation, based on permutations of available ground station networks - known (default) or customized (by the user). We will show the impact of changing ground station options for any given constellation, on data latency and required communication bandwidth, which in turn determines the responsiveness of the space system.

Nag, Sreeja↗

NASA NTRSDate not supplied

Assessing the Viability of Using GEOS-Forecast Product for Landslides Forecasting: A Step Toward Early Warning System

Landslides across the globe are mostly triggered by extreme rainfall events affecting infrastructure, transportation and livelihoods. The risks are rarely quantified due to lack of data, analytical skills and limited modeling techniques. Knowledge of local to global scale landslide risks provides communities and national agencies the ability to adapt disaster management practices to mitigate and recover from these hazards. In order to minimize the risks and improve characterization of community resilience to landslides, it is vital to have reliable information about the factors triggering landslides such as rainfall, well ahead in time. Forecasting potential landslide activity and impacts can be achieved through reliable precipitation forecast models. However, it is challenging because of the temporal and spatial variability of precipitation, an important factor in triggering landslides. Evaluation of the precipitation field, associated errors, and sampling uncertainties is integral for development of efficient and reliable landslide forecasting and early warning system. This study develops a methodology to assess the viability of using a precipitation field provided by a global model and its potential integration in the landslide forecasting system. The study focuses on the comparison between the IMERG (Integrated Multi-satellitE Retrievals for Global Precipitation Mission) and GEOS (NASA Goddard Earth Observing System)-Forecast product over contiguous United States (CONUS). GEOS model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The framework is tested on the GEOS-Forecast Model initialized at 00 UTC using daily IMERG early product as reference using both categorical and continuous statistics. The categorical statistics includes the probability of detection (POD), success ratio (SR), critical success index (CSI), and the hit bias. Continuous statistics such as correlation, normalized standard deviation, and root-mean-square error are also evaluated. Overall, GEOS-Forecast precipitation field over the analysis period (~1 year) show underestimation with respect to IMERG early for the daily accumulated rainfall. However, the probability distribution function and cumulative distribution function of both show similar patterns. In terms of correlations, POD, SR, CSI, hit bias, the performance varies with respect to the rainfall threshold used.

Sana Khan↗

NASA NTRSDate not supplied

Evaluation of CFD as a Surrogate for Wind-Tunnel Testing: Experimental Uncertainty Quantification for the UPWT Flow Survey Test

A series of wind tunnel tests are being performed at the Unitary Plan Wind Tunnel (UPWT)at NASA Langley Research Center to assess the validity of using computational fluid dynamics(CFD) as a surrogate for wind tunnel testing. In order to make proper comparisons, uncertainties in CFD results and experimental data must be well understood. The material presented highlights the methods, assumptions, and inputs used to achieve experimental uncertainty estimates. Results for a small subset of tunnel conditions and variables of interest from the first test in the series, the Flow Survey Test, are highlighted and sample CFD comparisons are shown. The bulk of the results from this work are used for comparisons in other AIAA conference papers related to this test series.

Erin P Hubbard↗

NASA NTRS2022

Si5345, SY88422L, LT3482, and MSK130 components Total Ionizing Dose Test Report

The purpose of this test was to characterize the SI-5345, SY88422L, LT3482 and MSK130 parameter degradation for total dose response. The components are associated with REAG ID #21-024. In the test, each device was exposed to high dose rate (HDR) irradiation using gamma radiation. Device parameters such as leakage currents, timing, and overall chip health were investigated. These devices were tested for an interstellar mission on a trajectory between 0.9 AU and 5.3 AU with a 2.5-year mission, yielding an expected overall dose of 29 krad(Si)behind 1 mm of aluminum shielding (at 95% confidence; environment and dose determined through SPENVIS). This test report gives an initial look at candidate parts. Extremely small sample sizes (only 1 or 2 devices tested) do not allow consideration of part-to-part variability. High dose rates were used despite LT3482 and MSK130 having potential enhanced low dose rate sensitivity (ELDRS). Care should be taken in interpreting results given these limitations.

Total Ionizing Dose (TID)↗

NASA NTRS2004

Signal Processing Variables for Optimization of Flaw Detection in Composites Using Ultrasonic Guided Wave Scanning

This study analyzes the effect of signal processing variables on the ability of the ultrasonic guided wave scan method at NASA Glenn Research Center to distinguish various flaw conditions in ceramic matrix composites samples. In the ultrasonic guided wave scan method, several time- and frequency-domain parameters are calculated from the ultrasonic guided wave signal at each scan location to form images. The parameters include power spectral density, centroid mean time, total energy (zeroth moment), centroid frequency, and ultrasonic decay rate. A number of signal processing variables are available to the user when calculating these parameters. These signal processing variables include 1) the time portion of the time-domain waveform processed, 2) integration type for the properties requiring integrations, 3) bounded versus unbounded integrations, 4) power spectral density window type, 5) and the number of time segments chosen if using the short-time fourier transform to calculate ultrasonic decay rate. Flaw conditions examined included delamination, cracking, and density variation.

Roth, Don J.↗

NASA NTRS2010

Robustness-Based Design Optimization Under Data Uncertainty

This paper proposes formulations and algorithms for design optimization under both aleatory (i.e., natural or physical variability) and epistemic uncertainty (i.e., imprecise probabilistic information), from the perspective of system robustness. The proposed formulations deal with epistemic uncertainty arising from both sparse and interval data without any assumption about the probability distributions of the random variables. A decoupled approach is proposed in this paper to un-nest the robustness-based design from the analysis of non-design epistemic variables to achieve computational efficiency. The proposed methods are illustrated for the upper stage design problem of a two-stage-to-orbit (TSTO) vehicle, where the information on the random design inputs are only available as sparse point and/or interval data. As collecting more data reduces uncertainty but increases cost, the effect of sample size on the optimality and robustness of the solution is also studied. A method is developed to determine the optimal sample size for sparse point data that leads to the solutions of the design problem that are least sensitive to variations in the input random variables.

Zaman, Kais↗

NASA NTRS1976

Toward the modeling of land use change: A spatial analysis using remote sensing and historical data

It was hypothesized that the chronological observation of land use change could be shown to follow a predictable pattern and these patterns could be correlated with other statistical data to develop transition probabilities suitable for modeling purposes. A literature review and preliminary research, however, indicated a totally stochastic approach was not practical for simulating land use change and thus a more deterministic approach was adopted. The approach used assumes the determinants of the land use conversion process are found in the market place, where land transactions among buyers and sellers occur. Only one side of the market transaction process is studied, however, namely, the purchaser's desires in securing an ideal or suitable site. The problem was to identify the ideal qualities, quantities or attributes desired in an industrial site (or housing development), and to formulate a general algorithmic statement capable of identifying potential development sites. Research procedures involved developing a list of variables previously noted in the literature to be related to site selection and streamlining the list to a set suitable for statistical testing. A sample of 157 industries which have located (or relocated) in the 16-county Knoxville metropolitan region since 1950 was selected for industrial location analysis. Using NASA color infrared photography and Tennessee Valley Authority historical aerial photography, data were collected on the spatial characteristics of each industrial location event. These data were then subjected to factor analysis to determine the interrelations of variables.

Honea, R. B.↗

NASA NTRS2019

Lidar-Polarimeter Retrieval OSSEs in Support of NASA's Aerosols and Clouds-Convection-Precipitation (ACCP) Study

The 2017 Decadal Survey (DS) highlighted Earth System Science themes, science and application questions, and several high priority objectives that have led to the inclusion of Aerosols (A) and Clouds-Convection-Precipitation (CCP) as Designated Observables (DOs). On June 1, 2018, several NASA centers (GSFC, LaRC, JPL, MSFC, GRC and ARC) submitted a joint Study Plan to the NASA Earth Science Division for the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Pre-formulation Study (A-CCP). The DS and the A-CCP team recognized the science merit in combining the A and CCP DOs for both enhancing the ability to address a number of science objectives and also to provide an expanded capability to address additional objectives beyond those addressed by individual DOs.A critical element of the A-CCP observing strategy is to make extensive use of new passive and active sensors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. Central to this observing system design is the adoption of a Value Framework in which quantitative assessment of the science benefits of space-and air-borne assets is a key element. Given pre-defined A-CCP science objectives and geophysical variables with desired accuracies, A-CCP relies on a spectrum of Observing System Simulation Experiments (OSSEs) aimed at addressing pixel level retrieval uncertainties and sampling trade-offs. In this talk we will discuss a subset of Retrieval OSSEs being considered for A-CCP, namely, synergistic lidar-polarimeter retrievals of particular relevance for the A-CCP aerosol science objectives. Starting with aerosol states from the GEOS-5 Nature Run (G5NR) sampled along specific satellite orbits, we simulate polarized radiances at the desired polarimeter wavelengths with the Vector Linearized Direct Ordinate Radiative Transfer (VLIDORT) model, alongside the lidar signal for the relevant lidars with realistic error characterization. Next, inversions are performed with the Generalized Retrieval of Aerosol and Surface Properties (GRASP) system and the accuracy of the retrieved geophysical variables are assessed. In this presentation we will highlight results for key architectures being considered for A-CCP.

da Silva, Arlindo↗

NASA NTRS1982

The absence of rapid X-ray variability in active galaxies

Variations on time scales ranging from minutes to several hours in the X-ray flux from 54 observations of 38 active galaxies are identified. The sample is composed mostly of Seyfert I galaxies but also includes radio galaxies, NELG's BL Lacs and 3C 273. Only NGC 6814 varied on time scales as short as 100 sec. No other source was observed to vary with a time scale of less than 12 hours. Large amplitude short term variations are not a characteristic of the X-ray emission from active galaxies. Upper limits on sigma sub I/I ranged from 2% for Cen A, 5% for NGC 4151, to approximately 20% for sources giving 1 ct/sec in the detector. Three objects NGC 3227, NGC 4151 and MCG 5-23-16 show variability consistent with a time scale of approximately 1 day. Ways to reconcile the rapid variability seen for NGC 6814 (and NGC 4051) with the general stability observed for the other objects are considered.

Tennant, A. F.↗

NASA NTRS1990

Radiative properties of Cirrus clouds: FIRE IFO case October 28, 1986

A description of the radiative properties of two cirrus clouds sampled on 10/28/88 in the FIRE cirrus IFO is presented. The clouds are characterized in terms of the broadband infrared effective emittance, cloud fractional absorptance, shortwave heating rate, cloud albedo and vertical velocity. The broadband fluxes used in these calculations were obtained from measurements made by pyranometers and pyrgeometers. The shortwave irradiances were corrected to a horizontal plane and normalized to the same time by taking into account Sabreliner flight information (i.e., pitch, roll, heading and angle of attack), as well as sun-earth geometry considerations. Since only one aircraft was used, broadband fluxes at different levels in the cloud were not measured simultaneously. As a result, sampling errors may occur due to the nonsteady state of the cloud field or due to the possibility that the flight legs were not flown directly above or below each other. To minimize these errors and to simplify the analysis, the necessary variables were averaged and the averages used in the calculations. The downwelling shortwave and longwave irradiances were used as selection criteria to remove cloud free data encountered along the data sampling leg.

Hein, Paul F.↗

NASA NTRS2011

Combining Satellite and in Situ Data with Models to Support Climate Data Records in Ocean Biology

The satellite ocean color data record spans multiple decades and, like most long-term satellite observations of the Earth, comes from many sensors. Unfortunately, global and regional chlorophyll estimates from the overlapping missions show substantial biases, limiting their use in combination to construct consistent data records. SeaWiFS and MODIS-Aqua differed by 13% globally in overlapping time segments, 2003-2007. For perspective, the maximum change in annual means over the entire Sea WiFS mission era was about 3%, and this included an El NinoLa Nina transition. These discrepancies lead to different estimates of trends depending upon whether one uses SeaWiFS alone for the 1998-2007 (no significant change), or whether MODIS is substituted for the 2003-2007 period (18% decline, P less than 0.05). Understanding the effects of climate change on the global oceans is difficult if different satellite data sets cannot be brought into conformity. The differences arise from two causes: 1) different sensors see chlorophyll differently, and 2) different sensors see different chlorophyll. In the first case, differences in sensor band locations, bandwidths, sensitivity, and time of observation lead to different estimates of chlorophyll even from the same location and day. In the second, differences in orbit and sensitivities to aerosols lead to sampling differences. A new approach to ocean color using in situ data from the public archives forces different satellite data to agree to within interannual variability. The global difference between Sea WiFS and MODIS is 0.6% for 2003-2007 using this approach. It also produces a trend using the combination of SeaWiFS and MODIS that agrees with SeaWiFS alone for 1998-2007. This is a major step to reducing errors produced by the first cause, sensor-related discrepancies. For differences that arise from sampling, data assimilation is applied. The underlying geographically complete fields derived from a free-running model is unaffected by solar zenith angle requirements and obscuration from clouds and aerosols. Combined with in situ dataenhanced satellite data, the model is forced into consistency using data assimilation. This approach eliminates sampling discrepancies from satellites. Combining the reduced differences of satellite data sets using in situ data, and the removal of sampling biases using data assimilation, we generate consistent data records of ocean color. These data records can support investigations of long-term effects of climate change on ocean biology over multiple satellites, and can improve the consistency of future satellite data sets.

Gregg, Watson↗

NASA NTRS1995

Another look at the UBV variability of T Tauri stars

The UBV variability of classical T Tauri stars is investigated using a large data set compiled by Herbst et al. (1994). The analysis is based on the covariance of the UBV colors, which is independent of the obscuration and the temporal sampling, and is a powerful tool for finding trends that otherwise would be hidden in the complex time-dependence of the data. I find that there are two types of UBV variability and introduce the nomenclature 'ortho-' and 'para-UBV' variations, or in short 'type-O' and 'type-P' variations. Objects with a predominance of ortho-UBV variability show strong variability in both the Balmer and Paschen continua, whereas objects dominated by para-UBV changes vary mostly in the Paschen continuum. I show that type-O variations can be explained in terms of rotating spots, variable obscuration, or changes intrinsic to the source that obey the law Delta T(sub S)/T(sub S) varies as Delta n(sub H)/n(sub H), where T(sub S) and n(sub H) are, respectively, the gas temperature and the number density of hydrogen nuclei. Type-P variations can be explained only by changes intrinsic to the source with Delta T(sub S)/T(sub S) varies as - Delta n(sub H)/n(sub H), and I speculate on a possible origin for these changes. The covariance ellipse of the UBV colors is a versatile tool for studying the connection between variability and other spectral signatures of classical T Tauri stars; its use for this purpose is illustrated by studying the correlation between the presence of CO first-overtone bands in emission and the type of variability. I find that objects with CO band emission are also those with type-P variability and propose an observational test to validate this conclusion.

Safier, Pedro N.↗

NASA NTRS2005

Using IKONOS Imagery to Estimate Surface Soil Property Variability in Two Alabama Physiographies

Knowledge of surface soil properties is used to assess past erosion and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to evaluate high resolution IKONOS multispectral data as a soil- mapping tool. Imagery was acquired over conventionally tilled fields in the Coastal Plain and Tennessee Valley physiographic regions of Alabama. Acquisitions were designed to assess the impact of surface crusting, roughness and tillage on our ability to depict soil property variability. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic Rhodic Paleudults at the Tennessee Valley site. Soils were sampled in 0.20 ha grids to a depth of 15 cm and analyzed for % sand (0.05 - 2 mm), silt (0.002 -0.05 mm), clay (less than 0.002 mm), citrate dithionite extractable iron (Fe(sub d)) and soil organic carbon (SOC). Four methods of evaluating variability in soil attributes were evaluated: 1) kriging of soil attributes, 2) co-kriging with soil attributes and reflectance data, 3) multivariate regression based on the relationship between reflectance and soil properties, and 4) fuzzy c-means clustering of reflectance data. Results indicate that co-kriging with remotely sensed data improved field scale estimates of surface SOC and clay content compared to kriging and regression methods. Fuzzy c-means worked best using RS data acquired over freshly tilled fields, reducing soil property variability within soil zones compared to field scale soil property variability.

Sullivan, Dana↗

NASA NTRS1995

Validation of satellite retrievals of cloud microsphysics and liquid water path using observations from FIRE

Cloud effective radii (r(sub e)) and cloud liquid water path (LWP) are derived from ISCCP spatially sampled satellite data and validated with ground-based pyranometer and microwave radiometer measurements taken on San Nicolas Island during the 1987 FIRE IFO. Values of r(sub e) derived from the ISCCP data are also compared to values retrieved by a hybrid method that uses the combination of LWP derived from microwave measurement and optical thickness derived from GOES data. The results show that there is significant variability in cloud properties over a 100 km x 80 km area and that the values at San Nicolas Island are not necessarily representative of the surrounding cloud field. On the other hand, even though there were large spatial variations in optical depth, the r(sub e) values remained relatively constant (with sigma less than or equal to 2-3 microns in most cases) in the marine stratocumulus. Furthermore, values of r(sub e) derived from the upper portion of the cloud generally are representative of the entire stratiform cloud. When LWP values are less than 100 g m(exp -2), then LWP values derived from ISCCP data agree well with those values estimated from ground-based microwave measurements. In most cases LWP differences were less than 20 g m(exp -2). However, when LWP values become large (e.g., greater than or equal to 200 g m(exp -2)), then relative differences may be as large as 50%- 100%. There are two reasons for this discrepancy in the large LWP clouds: (1) larger vertical inhomogeneities in precipitating clouds and (2) sampling errors on days of high spatial variability of cloud optical thicknesses. Variations of r(sub e) in stratiform clouds may indicate drizzle: clouds with droplet sizes larger than 15 microns appear to be associated with drizzling, while those less than 10 microns are indicative of nonprecipitating clouds. Differences in r(sub e) values between the GOES and ISCCP datasets are found to be 0.16 +/- 0.98 micron.

Rossow, W.↗

NASA NTRS1975

Snow survey and vegetation growth in high mountains (Swiss Alps) and additional ERTS investigations in Switzerland

The author has identified the following significant results. Two different methods, an analog and a digital one, have been developed for rapid and accurate mapping of the areal extent and changes in snow cover in high mountains. The quick-look method is based on individual visual control of each image using a photo quantizer which provides exact references for density slicing with high resolution lith-film. The digital snow classification system is based on discriminant analysis with the data of the four multispectral bands as variables and contains all preprocessing, feature extraction, and mapping steps for an operational application. Two different sets of sampling groups were established which apply to different conditions of snow cover. The first one serves for the normal situation with a uniform dry and new cover. The second one serves for situations with partly thawing and/or frozen snow.

Haefner, H.↗