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At least 1,099 records · Page 61

Pulmonary toxicity of simulated lunar and Martian dusts in mice: II. Biomarkers of acute responses after intratracheal instillation

Volcanic ashes from Arizona and Hawaii, with chemical and mineral properties similar to those of lunar and Martian soils, respectively, are used by the National Aeronautics and Space Administration (NASA) to simulate lunar and Martian environments for instrument tests. NASA needs toxicity data on these volcanic soils to assess health risks from potential exposures of workers in facilities where these soil simulants are used. In this study we investigated the acute effects of lunar soil simulant (LSS) and Martian soil simulant (MSS), as a complement to a histopathological study assessing their subchronic effects (Lam et al., 2002). Fine dust of LSS, MSS, TiO(2), or quartz suspended in saline was intratracheally instilled into C57Bl/6J mice (4/group) in single doses of 0.1 mg/mouse or 1 mg/mouse. The mice were euthanized 4 or 24 h after the dust treatment, and bronchoalveolar lavage fluid (BALF) was obtained. Statistically significant lower cell viability and higher total protein concentration in the BALF were seen only in mice treated with the high dose of quartz for 4 h and with the high dose of MSS or quartz for 24 h, compared to mice treated only with saline. A significant increase in the percentage of neutrophils was not observed with any dust-treated group at 4 h after the instillation, but was observed after 24 h in all the dust-treated groups. This observation indicates that these dusts were not acutely toxic and the effects were gradual; it took some time for neutrophils to be recruited into and accumulate significantly in the lung. A statistically significant increase in apoptosis of lavaged macrophages from mice 4 h after treatment was found only in the high-dose silica group. The overall results of this study on the acute effects of these dusts in the lung indicate that LSS is slightly more toxic than TiO(2), and that MSS is comparable to quartz. These results were consistent with the subchronic histopathological findings in that the order of severity of lung toxicity was TiO(2) < LSS < MSS < quartz.

Non-programmatic↗

An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter. In order to increase overall robustness, the vehicle also has an alternate method of triggering the drogue parachute deployment based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this velocity-based trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers excellent performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

Smith, Kelly M.↗

An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions Using Inaccurate or Scarce Information

In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

Smith, Kelly M.↗

An Alternative Flight Software Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles

Smith, Kelly↗

Evaluation of GEOS-Simulated L-Band Microwave Brightness Temperature using Aquarius Observations over Non-Frozen Land across North America

L-band brightness temperature (T(sub b)) is one of the key remotely-sensed variables that provides information regarding surface soil moisture conditions. In order to harness the information in T(sub b) observations, a radiative transfer model (RTM) is investigated for eventual inclusion into a data assimilation framework. In this study, T(sub b) estimates from the RTM implemented in the NASA Goddard Earth Observing System (GEOS) were evaluated against the nearly four-year record of daily T(sub b) observations collected by L-band radiometers onboard the Aquarius satellite. Statistics between the modeled and observed T(sub b) were computed over North America as a function of soil hydraulic properties and vegetation types. Overall, statistics showed good agreement between the modeled and observed T(sub b) with a relatively low, domain-average bias (0.79 K (ascending) and -2.79 K (descending)), root mean squared error (11.0 K (ascending) and 11.7 K (descending)), and unbiased root mean squared error (8.14 K (ascending) and 8.28 K (descending)). In terms of soil hydraulic parameters, large porosity and large wilting point both lead to high uncertainty in modeled T(sub b) due to the large variability in dielectric constant and surface roughness used by the RTM. The performance of the RTM as a function of vegetation type suggests better agreement in regions with broadleaf deciduous and needleleaf forests while grassland regions exhibited the worst accuracy amongst the five different vegetation types.

L-band radiometry↗

An auditory display in a dual-axis tracking task.

Results of a study in which subjects were presented concurrently with the primary task of controlling a second-order plant and the secondary task of controlling a first-order plant. The plant errors for the two tasks were shown on separate visual displays. An auditory display, whose output varied in frequency and volume with the error, was used to supplement the secondary task in half of the runs. To study the effects of the auditory display, two performance measures were obtained: (1) the integral of the squared error (ISE) and (2) the describing functions of the human operator. Statistical analysis of the ISE measures indicated that when the secondary task was supplemented with an auditory display, there was a significant improvement in performance on the secondary task. The performance on the primary task improved on the average, but not significantly. The variances of the ISE values decreased for both the tasks, indicating a more consistent behavior with the auditory display. The describing function analysis showed that supplementing the secondary task with the auditory display increased the low frequency gain of the human operator for this task. The describing functions for the primary task did not show any apparent changes.

Mirchandani, P. B.↗

Large Ca-48 anomalies are associated with Ti-50 anomalies in Murchison and Murray hibonites

Ion microprobe measurements of the Ca isotopic compositions of eight individual hibonite grains from the Ca chondrites Murray and Murchison are reported. Large Ca-48 anomalies two orders of magnitude larger than those observed in normal inclusions and at least a factor of four larger than in the FUN inclusions are found. These anomalies are qualitatively correlated with the Ti-50 anomalies in the sense that the delta Ca-48 and delta Ti-50 values have the same sign. These results confirm previous conclusions concerning the presence of a nucleosynthetic component produced by neutron-rich nuclear statistical equilibrium processes. They suggest the preservation of the isotopic anomalies with interstellar dust grains as carriers of the n-rich Ca and Ti components. The large variation in the delta Ca-48/delta Ti-50 ratios indicates multiple nucleosynthetic components and/or chemical fractionation between Ca and Ti prior to hibonite formation.

Zinner, Ernst K.↗

Remote sensing of Earth terrain

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

Kong, Jin AU↗

Space debris characterization in support of a satellite breakup model

The Space Kinetic Impact and Debris Branch began an ambitious program to construct a fully analytical model of the breakup of a satellite under hypervelocity impact. In order to provide empirical data with which to substantiate the model, debris from hypervelocity experiments conducted in a controlled laboratory environment were characterized to provide information of its mass, velocity, and ballistic coefficient distributions. Data on the debris were collected in one master data file, and a simple FORTRAN program allows users to describe the debris from any subset of these experiments that may be of interest to them. A statistical analysis was performed, allowing users to determine the precision of the velocity measurements for the data. Attempts are being made to include and correlate other laboratory data, as well as those data obtained from the explosion or collision of spacecraft in low earth orbit.

Fortson, Bryan H.↗

Preliminary Results from a New Analysis Method for EGRET Data

In order to extend the life of EGRET, the gas in the spark chamber was allowed to deteriorate more than was originally planned for the nominal two year Compton Observatory mission. Gamma ray events are lost because the pattern recognition analysis rules are not optimized for the poorer quality data. By changing the rules used by the data analysts, we can recover a significant fraction of the lost events, allowing improved statistics for detection and study of sources. Preliminary results from the Crab, Geminga, and BL Lacertae indicate the feasibility of this analysis.

Thompson, D. J.↗

Statistical Models of Landscape Pattern and the Effects of Coarse Resolution of Satellite Imagery on Estimation of Area

Analysis of classified satellite imagery was conducted to characterize errors in estimates of area based on coarse resolution satellite imagery which are due to distortions in sizes of small fragments, and to explore the feasibility of correcting for these errors using a statistical modeling approach. Sizes of bodies of open water on ERS-1 SAR and fire scars on Landsat MSS imagery were measured. Statistical analysis of the smaller scars and ponds as observed with this imagery of relatively fine resolution demonstrated that the distribution of the sizes could be modeled by either of two types of statistical distributions - a power distribution related to fractal processes or a simple exponential distribution. Comparison of the distribution of small bum scars as observed with Landsat to the distribution observed with AVHRR showed distortions due to the coarse spatial resolution of AVHRR caused a net overestimation of bum area. This bias was primarily caused by detection in 2 or 3 AVHRR pixels of bums whose true size was on the order of an AVHRR pixel.

Hlavka, Christine A.↗

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗

Interannual and Decadal Variability of Ocean Surface Latent Heat Flux as Seen from Passive Microwave Satellite Algorithms

Ocean surface turbulent fluxes are critical links in the climate system since they mediate energy exchange between the two fluid systems (ocean and atmosphere) whose combined heat transport determines the basic character of Earth's climate. Deriving physically-based latent and sensible heat fluxes from satellite is dependent on inferences of near surface moisture and temperature from coarser layer retrievals or satellite radiances. Uncertainties in these "retrievals" propagate through bulk aerodynamic algorithms, interacting as well with error properties of surface wind speed, also provided by satellite. By systematically evaluating an array of passive microwave satellite algorithms, the SEAFLUX project is providing improved understanding of these errors and finding pathways for reducing or eliminating them. In this study we focus on evaluating the interannual variability of several passive microwave-based estimates of latent heat flux starting from monthly mean gridded data. The algorithms considered range from those based essentially on SSM/I (e.g. HOAPS) to newer approaches that consider additional moisture information from SSM/T-2 or AMSU-B and lower tropospheric temperature data from AMSU-A. On interannual scales, variability arising from ENSO events and time-lagged responses of ocean turbulent and radiative fluxes in other ocean basins (as well as the extratropical Pacific) is widely recognized, but still not well quantified. Locally, these flux anomalies are of order 10-20 W/sq m and present a relevant "target" with which to verify algorithm performance in a climate context. On decadal time scales there is some evidence from reanalyses and remotely-sensed fluxes alike that tropical ocean-averaged latent heat fluxes have increased 5-10 W/sq m since the early 1990s. However, significant uncertainty surrounds this estimate. Our work addresses the origin of these uncertainties and provides statistics on time series of tropical ocean averages, regional space / time correlation analysis, and separation of contributions by variations in wind and near surface humidity deficit. Comparison to variations in reanalysis data sets is also provided for reference.

Robertson, Franklin R.↗

Biasing and hierarchical statistics in large-scale structure

In this paper we consider the consequences for galaxy formation of an arbitrary, effectively local biasing transformation of a hierarchical underlying matter distribution. We show that a general form of such a transformation preserves the hierarchical properties and the shape of the dispersion in the limit of small fluctuations, i.e., on large scales, although the values of the hierarchical amplitudes may change arbitrarily. We present expressions for the induced hierarchical amplitudes S(g,j) of the galaxy distribution in terms of the matter amplitudes S(j) and biasing parameters for j = 3-7. For higher order correlations, j greater than 2, restricting to a linear bias is not a consistent approximation even at very large scales. To draw any conclusions from the galaxy distribution about matter correlations of order j, properties of biasing must be specified completely to order j - 1.

Fry, J. N.↗

Observation and analysis of abrupt changes in the interplanetary plasma velocity and magnetic field.

This paper presents a limited study of the physical nature of abrupt changes in the interplanetary plasma velocity and magnetic field based on 19 day's data from the Pioneer 6 spacecraft. The period was chosen to include a high-velocity solar wind stream and low-velocity wind. Abrupt events were accepted for study if the sum of the energy density in the magnetic field and velocity changes was above a specified minimum. A statistical analysis of the events in the high-velocity solar wind stream shows that Alfvenic changes predominate. This conclusion is independent of whether steady state requirements are imposed on conditions before and after the event. Alfvenic changes do not dominate in the lower-speed wind. This study extends the plasma field evidence for outwardly propagating Alfvenic changes to time scales as small as 1 min (scale lengths on the order of 20,000 km).

Martin, R. N.↗

Solar particle fluxes and the ancient sun

The implications of the statistical data on solar flare particle fluxes, for the present and the ancient sun, considering modern data from the past two solar cycles, C-14 data from the past 7000 years, and Al-26 and Mn-53 data in lunar samples for the last 10-million years are reviewed. All of these records suggest that there is a maximum proton fluence (greater than 10 MeV) from a solar flare on the order of 10 to the 10th p/sq cm, above which the size-frequency distribution steepens sharply. From this it is extremely unlikely that energetic particles from solar flares could have contributed to extinction catastrophes in the fossil record.

Lingenfelter, R. E.↗

Ice depolarization on low-angle 2 GHz satellite downlinks

The impact of ice depolarization on the statistical performance of satellite downlinks were investigated. Propagation data recorded during 1979 and 1980 to see what impact of ice depolarization on link performance were analyzed. The effects on the cross polarization discrimination (XPD) statistics amounted to at most a 2 to 4 dB reduction in the XPD values which rain would have produced for a given percentage of time. Ice depolarization had no effect on the statistics of XPD values below the 0.01% level. Most of the severe ice depolarization events were associated with drops in barometric pressure and the passage of intense cold fronts through our area. Ice contents as the product of three individually undetermined quantities were defined: ice particle density, ice cloud thickness, and the average volume of the ice crystals. It is indicated that populations of ice particle with ice contents on the order of 0.002 m4/m3 are probably responsible for the lower values of measured XPD.

Stutzman, W. L.↗

Cosmic rays near the heliospheric current sheet. II - An ensemble approach to comparing theory and observation

A quantitative comparison is carried out between theoretical predictions and observations of the intensity of galactic cosmic rays near the interplanetary current sheet. Model calculations are compared with a statistical analysis of observations of galactic cosmic rays at the earth and the simultaneous position of the current sheet. Since the observations were made over a period of several years, the inclination of the current sheet varied considerably, and comparison with any one model calculation referring to a given inclination would not be appropriate. An ensemble of different current sheet inclinations are used to generate expected values with the model in order to make the analysis of the computations approximate the method used to analyze the data. Agreement is found between theory and observation at energies of the order of a few GeV.

Jokipii, J. R.↗