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Results for “Quantitative analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Neurochemical phenotype of corticocortical connections in the macaque monkey: quantitative analysis of a subset of neurofilament protein-immunoreactive projection neurons in frontal, parietal, temporal, and cingulate cortices

The neurochemical characteristics of the neuronal subsets that furnish different types of corticocortical connections have been only partially determined. In recent years, several cytoskeletal proteins have emerged as reliable markers to distinguish subsets of pyramidal neurons in the cerebral cortex of primates. In particular, previous studies using an antibody to nonphosphorylated neurofilament protein (SMI-32) have revealed a consistent degree of regional and laminar specificity in the distribution of a subpopulation of pyramidal cells in the primate cerebral cortex. The density of neurofilament protein-immunoreactive neurons was shown to vary across corticocortical pathways in macaque monkeys. In the present study, we have used the antibody SMI-32 to examine further and to quantify the distribution of a subset of corticocortically projecting neurons in a series of long ipsilateral corticocortical pathways in comparison to short corticocortical, commissural, and limbic connections. The results demonstrate that the long association pathways interconnecting the frontal, parietal, and temporal neocortex have a high representation of neurofilament protein-enriched pyramidal neurons (45-90%), whereas short corticocortical, callosal, and limbic pathways are characterized by much lower numbers of such neurons (4-35%). These data suggest that different types of corticocortical connections have differential representation of highly specific neuronal subsets that share common neurochemical characteristics, thereby determining regional and laminar cortical patterns of morphological and molecular heterogeneity. These differences in neuronal neurochemical phenotype among corticocortical circuits may have considerable influence on cortical processing and may be directly related to the type of integrative function subserved by each cortical pathway. Finally, it is worth noting that neurofilament protein-immunoreactive neurons are dramatically affected in the course of Alzheimer's disease. The present results support the hypothesis that neurofilament protein may be crucially linked to the development of selective neuronal vulnerability and subsequent disruption of corticocortical pathways that lead to the severe impairment of cognitive function commonly observed in age-related dementing disorders.

Non-NASA Center↗
NASA NTRS2005

Influence of a fat layer on the near infrared spectra of human muscle: quantitative analysis based on two-layered Monte Carlo simulations and phantom experiments

The influence of fat thickness on the diffuse reflectance spectra of muscle in the near infrared (NIR) region is studied by Monte Carlo simulations of a two-layer structure and with phantom experiments. A polynomial relationship was established between the fat thickness and the detected diffuse reflectance. The influence of a range of optical coefficients (absorption and reduced scattering) for fat and muscle over the known range of human physiological values was also investigated. Subject-to-subject variation in the fat optical coefficients and thickness can be ignored if the fat thickness is less than 5 mm. A method was proposed to correct the fat thickness influence. c2005 Optical Society of America.

NASA Discipline Life Sciences Technologies↗
NASA NTRS2012

Thermal Imaging with Novel Infrared Focal Plane Arrays and Quantitative Analysis of Thermal Imagery

We have developed a single long-wavelength infrared (LWIR) quantum well infrared photodetector (QWIP) camera for thermography. This camera has been used to measure the temperature profile of patients. A pixel coregistered simultaneously reading mid-wavelength infrared (MWIR)/LWIR dual-band QWIP camera was developed to improve the accuracy of temperature measurements especially with objects with unknown emissivity. Even the dualband measurement can provide inaccurate results due to the fact that emissivity is a function of wavelength. Thus we have been developing a four-band QWIP camera for accurate temperature measurement of remote object.

Thermography↗
NASA NTRS2016

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account risks attributable to manufacturing, assembly, and process controls. These sources often dominate component level reliability or risk of failure probability. While consequences of failure is often understood in assessing risk, using predicted values in a risk model to estimate the probability of occurrence will likely underestimate the risk. Managers and decision makers often use the probability of occurrence in determining whether to accept the risk or require a design modification. Due to the absence of system level test and operational data inherent in aerospace applications, the actual risk threshold for acceptance may not be appropriately characterized for decision making purposes. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗
NASA NTRS2016

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account system integration risks such as those attributable to manufacturing and assembly. These sources often dominate component level risk. While consequence of failure is often understood, using predicted values in a risk model to estimate the probability of occurrence may underestimate the actual risk. Managers and decision makers use the probability of occurrence to influence the determination whether to accept the risk or require a design modification. The actual risk threshold for acceptance may not be fully understood due to the absence of system level test data or operational data. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗
NASA NTRS2018

A Quantitative Analysis of Systematic Differences in the Positions and Proper Motions of Gaia DR2 with Respect to VLBI

We have analysed the differences in positions of 9081 matched sources between the GaiaData Release 2 (DR2) and very long baseline interferometry (VLBI) catalogues. The medianposition uncertainty of matched sources in the VLBI catalogue is a factor of two larger thanthe median position uncertainty in Gaia DR2. There are 9 per cent matched sources withstatistically significant offsets between both catalogues. We found that the reported positionalerrors should be rescaled by a factor of 1.3 for VLBI and 1.06 for Gaia and, in addition, the Gaiaerrors should be multiplied by the square root of chi squared per degree of freedom in order tobest fit the normalized position differences to the Rayleigh distribution. We have establishedthat the major contributor to statistically significant position offsets is the presence of opticaljets. Among the sources for which the jet direction was determined, the position offsets areparallel to the jet directions for 62 per cent of the outliers. Among the matched sources withsignificant proper motion, the fraction of objects with proper motion directions parallel tojets is a factor of three greater than on average. Such sources have systematically higher chisquared per degree of freedom. We explain these proper motions as a manifestation of thesource position jitter caused by flares, which we predicted earlier. Therefore, the assumptionthat quasars are fixed points, and thus that differential proper motions determined with respectto quasar photocentres can be regarded as absolute proper motions, should be treated withgreat caution.

Petrov, L.↗
NASA NTRSDate not supplied

A Quantitative Analysis On the Use Of Supervised Machine Learning in Earth Science

Several recent papers have investigated different challenges in applying machine learning (ML) techniques to Earth science problems. The challenges listed range from interpretability of the results to computational demand to data issues. In this paper, we focus on specific challenges listed in the review papers that are centered around training data, as the size of training data is important in applying deep learning (DL) techniques. We are in the process of conducting a literature survey to better understand these challenges as well as to understand any trends. As part of this survey, our review has encompassed Earth science papers from AGU, AMS, IEEE and SPIE journals covering the last ten years and focused on papers that utilize supervised ML techniques.

Katrina S Virts↗
NASA NTRSDate not supplied

A Quantitative Analysis on the Use of Supervised Machine Learning in Earth Science

Recent review papers (Ball et al., 2017; Reichstein et al., 2019) have investigated the opportunities and challenges in applying supervised machine learning (ML) techniques to Earth science problems. A common challenge is the lack of training (or labeled) data. Supervised ML, and especially deep learning (DL), require large training datasets. While there are large, open access Earth science archives, the data typically require preprocessing in preparation for supervised ML, frequently including manual labeling. Our objective is to understand the landscape of supervised ML in the Earth sciences, including which research communities have most rapidly adopted supervised ML, which algorithms are applied, and what data are used to train these algorithms. We conducted a literature survey of Earth science papers published during the last 10 years in journals from the American Geophysical Union (AGU), American Meteorological Society (AMS), the Institute of Electrical and Electronics Engineers(IEEE), and the Society of Photo-Optical Instrumentation Engineers (SPIE). We identified papers containing the terms ML, DL, or the names of individual supervised ML algorithms. "Earth science" is an additional required search term for IEEE and SPIE. We investigate trends in supervised ML usage during the 10-year study period, and manually analyzed AGU papers from 2018-2019 to enable deep-dive statistics.

Katrina S Virts↗
NASA NTRS2000

Quantitative analysis of charge injection and discharging of Si nanocrystals and arrays by electrostatic force microscopy

NASA requirements for computing and memory for microspacecraft emphasizes high density, low power, small size, and radiation hardness. The distributed nature of a storage elements in nanocrystal floating-gate memories leads to instrinsic fault tolerance and radiation-hardness. Nanocrystal-based memories also offer the possibility of a faster, lower power operation.

atomic↗
NASA NTRSDate not supplied

Quantitative Analysis of Spaceflight Drug Stability Data to Support a Predictive Pharmaceutical Testing Strategy

To systematically quantify the time-dependent effect of spaceflight on active pharmaceutical ingredient (API) degradation, data were extracted from available published and unpublished spaceflight drug stability studies. Seven studies were identified that investigated the stability of individual medications following storage aboard crewed spacecraft. Medications stored for up to 2.4 years in low earth orbit (LEO) show limited change in API potency that, in all cases, falls within 10% of matched terrestrial controls, and within 5% of controls for the most drugs. This investigation shows that spaceflight is associated with a ~1.5-fold increase in the degradation rate relative to lot-matched terrestrial controls. Spaceflight is associated with an increased probability of drug failure over time; however, the incremental increase in degradation risk associated with spaceflight is minor compared to the baseline risk associated with terrestrial controls. Since most drugs across all NASA-supported studies were repackaged solid oral formulations that had been removed from protective manufacturer packaging, it is likely that prolonged exposure to atmospheric factors during both terrestrial and spaceflight treatments is a key contributor to degradation. Unique spaceflight environmental factors, particularly ionizing radiation and elevated CO2, may contribute to the additional cumulative effect of spaceflight. The results of this study show that the effect of spaceflight on drug stability is minor relative to the terrestrial baseline; however, the degradation rate and time-dependent failure of terrestrial controls highlights an extremely critical need to evaluate the effect of current repackaging methods and development of operationally appropriate methods to protected repackaged solid oral medications from environmental factors that mediate degradation.

J F Reichard↗
NASA NTRS2005

Applying Qualitative Hazard Analysis to Support Quantitative Safety Analysis for Proposed Reduced Wake Separation Conops

This paper describes a scenario-driven hazard analysis process to identify, eliminate, and control safety-related risks. Within this process, we develop selective criteria to determine the applicability of applying engineering modeling to hypothesized hazard scenarios. This provides a basis for evaluating and prioritizing the scenarios as candidates for further quantitative analysis. We have applied this methodology to proposed concepts of operations for reduced wake separation for closely spaced parallel runways. For arrivals, the process identified 43 core hazard scenarios. Of these, we classified 12 as appropriate for further quantitative modeling, 24 that should be mitigated through controls, recommendations, and / or procedures (that is, scenarios not appropriate for quantitative modeling), and 7 that have the lowest priority for further analysis.

Shortle, John F.↗
NASA NTRS1998

Hypergravity exposure decreases gamma-aminobutyric acid immunoreactivity in axon terminals contacting pyramidal cells in the rat somatosensory cortex: a quantitative immunocytochemical image analysis

Quantitative evaluation of gamma-aminobutyric acid immunoreactivity (GABA-IR) in the hindlimb representation of the rat somatosensory cortex after 14 days of exposure to hypergravity (hyper-G) was conducted by using computer-assisted image processing. The area of GABA-IR axosomatic terminals apposed to pyramidal cells of cortical layer V was reduced in rats exposed to hyper-G compared with control rats, which were exposed either to rotation alone or to vivarium conditions. Based on previous immunocytochemical and behavioral studies, we suggest that this reduction is due to changes in sensory feedback information from muscle receptors. Consequently, priorities for muscle recruitment are altered at the cortical level, and a new pattern of muscle activity is thus generated. It is proposed that the reduction observed in GABA-IR of the terminal area around pyramidal neurons is the immunocytochemical expression of changes in the activity of GABAergic cells that participate in reprogramming motor outputs to achieve effective movement control in response to alterations in the afferent information.

Non-NASA Center↗