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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Real-time breath analysis towards a healthy human breath profile

Abstract The direct analysis of molecules contained within human breath has had significant implications for clinical and diagnostic applications in recent decades. However, attempts to compare one study to another or to reproduce previous work are hampered by: variability between sampling methodologies, human phenotypic variability, complex interactions between compounds within breath, and confounding signals from comorbidities. Towards this end, we have endeavored to create an averaged healthy human ‘profile’ against which follow-on studies might be compared. Through the use of direct secondary electrospray ionization combined with a high-resolution mass spectrometry and in-house bioinformatics pipeline, we seek to curate an average healthy human profile for breath and use this model to distinguish differences inter- and intra-day for human volunteers. Breath samples were significantly different in PERMANOVA analysis and ANOSIM analysis based on Time of Day, Participant ID, Date of Sample, Sex of Participant, and Age of Participant ( p < 0.001). Optimal binning analysis identify strong associations between specific features and variables. These include 227 breath features identified as unique identifiers for 28 of the 31 participants. Four signals were identified to be strongly associated with female participants and one with male participants. A total of 37 signals were identified to be strongly associated with the time-of-day samples were taken. Threshold indicator taxa analysis indicated a shift in significant breath features across the age gradient of participants with peak disruption of breath metabolites occurring at around age 32. Forty-eight features were identified after filtering from which a healthy human breath profile for all participants was created.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1971

Digital adaptive sampling.

Discussion of digital adaptive sampling, which is consistently better than fixed sampling in noise-free cases. Adaptive sampling is shown to be feasible and, it is considered, should be studied further. It should be noted that adaptive sampling is a class of variable rate sampling in which the variability depends on system signals. Digital rather than analog laws should be studied, because cases can arise in which the analog signals are not even available. An extremely important problem is implementation.

Breazeale, G. J.↗
DOE OSTI2021

Scalable Techniques for Stochastic Power Flow Problems (Final Report)

The proposed research focuses on developing scalable algorithms for two-stage security-constrained OPF problems with AC power flow constraints, a class of problems complicated by (i) scale arising from a scenario representation; and (ii) the presence of nonlinearity, nonconvexity, and possibly second-stage discreteness or complementarity. Unfortunately, most existing solvers cannot contend with both challenges simultaneously; accordingly, the proposed research focuses on developing solution techniques that can both scale with the number of scenarios and contend with nonconvexity and second-stage complementarity. We consider three avenues for addressing such problems: (i) Variable sample-size SQP (VS-SQP) methods that combine sparse Quasi-Newton updates with a scalable variance-reduced stochastic gradient scheme for stochastic QP subproblems, allowing for contending with second-stage complementarity via regularization; (ii) Variable sample-size stochastic Interior-point (VS-sIP) schemes that propose a sampling-based regularized (to allow for contending with complementarity) interior-point schemes in which a Schur-complement technique is employed for decomposing the Newton direction computation step; (iii) Variable sample-size tractable ADMM (VS-tADMM) schemes combine variable sample-sizes with carefully designed techniques for resolving each of the nonconvex updates (by leveraging the QCQP structures). We intend to compare the three schemes using performance profiles in terms of solution quality, scalability, etc. and then select one scheme which will then be developed and further refined in Python for purposes of the GO competition.

42 ENGINEERING↗
NASA NTRS1975

Stability of multirate sampled-data systems

Current adaptive sampling schemes that can be used in sampled-data systems with variable rate sampling does not guarantee the stability of the resulting closed-loop system. A study was undertaken with the objective of finding a stable control law for multirate sampled-data systems. The problem is formulated such that the sampling interval is selected from a set of fixed number of sample intervals. A necessary and sufficient condition under which these types of systems can be stabilized is given. For a certain subclass of these types of systems, a sampling selection algorithm is given which results in a stable closed-loop system.

Stanford, D. P.↗
NASA NTRS1977

Digital flight control systems

The design of stable feedback control laws for sampled-data systems with variable rate sampling was investigated. These types of sampled-data systems arise naturally in digital flight control systems which use digital actuators where it is desirable to decrease the number of control computer output commands in order to save wear and tear of the associated equipment. The design of aircraft control systems which are optimally tolerant of sensor and actuator failures was also studied. Detection of the failed sensor or actuator must be resolved and if the estimate of the state is used in the control law, then it is also desirable to have an estimator which will give the optimal state estimate even under the failed conditions.

Caglayan, A. K.↗
NASA NTRS2013

Laboratory Instruments Available to Support Space Station Researchers at Marshall Space Flight Center

A number of research instruments are available at NASA's Marshall Space Flight Center (MSFC) to support ISS researchers and their investigations. These modern analytical tools yield valuable and sometimes new informative resulting from sample characterization. Instruments include modern scanning electron microscopes equipped with field emission guns providing analytical capabilities that include angstron-level image resolution of dry, wet and biological samples. These microscopes are also equipped with silicon drift X-ray detectors (SDD) for fast yet precise analytical mapping of phases, as well as electron back-scattered diffraction (EBSD) units to map grain orientations in crystalline alloys. Sample chambers admit large samples, provide variable pressures for wet samples, and quantitative analysis software to determine phase relations. Advances in solid-state electronics have also facilitated improvements for surface chemical analysis that are successfully employed to analyze metallic materials and alloys, ceramics, slags, and organic polymers. Another analytical capability at MSFC is a mganetic sector Secondary Ion Mass Spectroscopy (SIMS) that quantitatively determines and maps light elements such as hydrogen, lithium, and boron along with their isotopes, identifies and quantifies very low level impurities even at parts per billion (ppb) levels. Still other methods available at MSFC include X-ray photo-electron spectroscopy (XPS) that can determine oxidation states of elements as well as identify polymers and measure film thicknesses on coated materials, Scanning Auger electron spectroscopy (SAM) which combines surface sensitivity, spatial lateral resolution (approximately 20 nm), and depth profiling capabilities to describe elemental compositions in near surface regions and even the chemical state of analyzed atoms. Conventional Transmission Electron Microscope (TEM) for observing internal microstructures at very high magnifications and the Electron Probe Micro-analyzer (EPMA) for very precise microanalysis are available as needed by the researcher. Space Station researchers are invited to work with MSFC in analyzing their samples using these techniques.

Panda, Binayak↗
NASA NTRS1996

A Self Calibrating Emissivity and/or Transmissivity Independent Multiwavelength Pyrometer

Pyrometer is a favorite method to do remote temperature measurement in research and development. One-color, two-color and the disappearing filament pyrometers are most common, multicolor and multiwavelength pyrometers are being introduced recently. All these pyrometers invariably require, in one form or another, information concerning emissivity, the medium transmissivity, their ratio at some two spectral regions, the instrument's calibration constant, etc. for their operation. This information can come from hand books, from the manufacturer or in some instances, from results of dedicated separate experiments. Often this information is sample or instrument specific. Sometimes this information, though obtained from a special experiment, is obtained using a separate sample rather than the one pursued for temperature measurement. Then, there would be the question of variability from sample to sample and variability from batch to batch in the sample used. Also, previously determined calibrations can change with time, and the only way to reduce uncertainty is to perform the calibration more frequently or even immediately before the experiment. We have developed a multiwavelength pyrometer, which eliminates the need to supply the necessary emissivity and/or transmissivity information and the instrument calibration constants ahead of time. The pyrometer calibrates itself from its first cycle data.

Ng, Daniel↗
NASA NTRS1994

The ensemble variability properties of faint QSOs

A refined sample of 64 variable objects with stellar image structure has been identified in SA 57 to B approximately = 22.5, over a time baseline of 15 yr, sampled at 11 distinct epochs. The photometric data typically have a root-mean-square (rms) error at B = 22 of only 0.05 mag. Thirty-five quasars in this field have already been spectroscopically confirmed, 34 of which are among the sample of variables. Of the other variables, six are known spectroscopically to be stars, 10 additional objects are stars based on reliable detection of proper motion, and one is spectroscopically a narrow emission line galaxy. Of the 13 remaining variables, it is argued that they are a mixture of distant halo subdwarfs and quasars with starlike colors. We compute the ensemble average structure function and autocorrelation function from the light curves in the respective quasar rest frames, which are used to investigate the general dependences on apparent magnitude, absolute magnitude, and redshift.

Trevese, Dario↗
NASA NTRS2004

Variability of collagen crosslinks: impact of sample collection period

Because of the variability of collagen crosslinks, their use as markers for bone resorption is often criticized. We hypothesized that the variability could be reduced by collecting urine for 24 hours (or longer) instead of using single voids, and by not normalizing to creatinine. Urine samples were collected from 22 healthy subjects during two or more 24-hour periods. Each 24-hour pool and each 2nd void of the day were analyzed for N-telopeptide (NTX), pyridinium (PYD), and deoxypyridinoline (DPD) crosslinks. Data were analyzed by using linear regression. For NTX, R2 for the two, 2nd-void samples (n = 38) was 0.55, whereas R2 for the two 24-hour pools was 0.51 or 0.52, expressed per day or per creatinine. For PYD and DPD, R2 for the 2nd-void samples was 0.26 and 0.18, R2 for the 24-hour pools expressed per day was 0.58 and 0.74, and R2 for the 24-hour pools expressed per creatinine was 0.65 and 0.76, respectively. Regression of the 2nd void and the corresponding 24-hour pool, expressed per day, yielded R2 = 0.19, 0.19, and 0.08, for NTX, PYD, and DPD, respectively (n = 76 each). For the 2nd-void sample and its corresponding 24-hour pool, expressed per creatinine, R2 = 0.24, 0.33, and 0.08, respectively. In a separate study, the coefficient of variation for NTX was reduced (P < 0.05) when data from more than one 24-hour collection were combined. Thus, the variability inherent in crosslink determinations can be reduced by collecting urine for longer periods. In research studies, the high variability of single-void collections, compounded by creatinine normalization, may alter or obscure findings.

Specimen Handling/methods↗
DOE OSTI2024

Fracture Network Influence on Rock Damage and Gas Transport following an Underground Explosion

Simulations of rock damage and gas transport following underground explosions that omit preexisting fracture networks in the subsurface cannot fully characterize the influence of geo-structural variability on gas transport. Previous studies do not consider the impact that fracture network structure and variability have on gas seepage. In this study, we develop a sequentially coupled, axi-symmetric model to look at the damage pattern and resulting gas breakthrough curves following an underground explosion given different fracture network realizations. We simulate 0.327 and 0.164 kT chemical explosives with burial depths of 100 m for 90 stochastically generated fracture networks. Gases quickly reach the surface in 30% of the higher yield simulations and 5% of the lower yield simulations. The fast breakthrough can be attributed to the formation of connected pathways between fractures to the surface. The formation of a connected damage pathway to the surface is not clearly correlated with the fracture intensity (P32) in our simulations. Breakthrough curves with slower transport are highly variable depending on the fracture network sample. The variability in the breakthrough behavior indicates that ignoring the influence of fracture networks on rock damage, which strongly influences the hydraulic properties following an underground explosion, will likely lead to a large underestimation of the uncertainty in the gas transport to the surface. This work highlights the need for incorporation of fracture networks into models for accurately predicting gas seepage following underground explosions.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Interpretable Machine Learning Models for Autonomous Characterization of Analogue Ocean World Seawater Chemistry and Biosignature Potential Using Isotope Ratio Data

Background: Future missions to ocean worlds, such as Enceladus and Europa, will attempt to characterize the subsurface seawater chemistry and assess the potential for life. Such missions will be equipped with capabilities to precisely measure volatile isotopes in plumes, atmospheres, and exospheres. Motivation: While large isotopic fractionations can indicate a biological source, there are signatures resulting from abiotic geochemical processes that mimic isotopic biosignatures. While machine learning (ML) has the potential to disentangle competing effects and biotic mimicry, high-dimensional isotope ratio mass spectrometry (IRMS) data is likely to contain noise/irrelevant features and involve complex statistical interactions that make human inference and interpretation difficult. Further, ML predictions with as far-reaching implications as an extraterrestrial biosignature on an ocean world requires the use of interpretable models (i.e., not “black box” models) with physically and mathematically meaningful feature spaces along with false positive diagnostics. Methods: We use volatile CO2 IRMS data of analogue ocean world seawaters to validate an ML approach to provide biogeochemical context for biosignature detection. We employ a feature selection method called nearest-neighbor projected distance regression (NPDR) that detects statistical interactions and helps elucidate the mechanisms of the Random Forest classification models. Results: We train and validate predictive ML models on volatile CO2 IRMS data of analogue ocean world seawaters to predict major salt components (e.g., MgSO4, NaHCO3), pH, ionic strength, and the presence of biosignatures. Features derived from IRMS measurements are augmented with extracted time-series features. Our results show high test accuracy and interpretability, which is increased by interaction network visualization, sample-wise variable importance scores, and single-sample class probability estimates. We demonstrate an ML mission software solution that triggers autonomous data transmission and biogeochemical sample prediction.

geochemistry↗
NASA NTRS1980

Optimal regulation in systems with stochastic time sampling

An optimal control theory that accounts for stochastic variable time sampling in a distributed microprocessor based flight control system is presented. The theory is developed by using a linear process model for the airplane dynamics and the information distribution process is modeled as a variable time increment process where, at the time that information is supplied to the control effectors, the control effectors know the time of the next information update only in a stochastic sense. An optimal control problem is formulated and solved for the control law that minimizes the expected value of a quadratic cost function. The optimal cost obtained with a variable time increment Markov information update process where the control effectors know only the past information update intervals and the Markov transition mechanism is almost identical to that obtained with a known and uniform information update interval.

Montgomery, R. C.↗
NASA NTRS1987

A systematic search for long-term variability in a large sample of X-ray sources

A method which uses the correct measurement error distribution (Poisson) and which naturally takes into account detections as well as upper limits has been developed to search for flux variability in X-ray sources. The method is applied to 256 sources observed at least twice with the Einstein Observatory Imaging Proportional Counter. These sources have, in the very large majority of cases, an X-ray flux in the range 1 x 10 to the -13th to 6 x 10 to the -12th erg/sq cm/s (0.2-3.5 keV). Thirty-one sources show flux variations with amplitude ranging from about 20 percent to a factor of 6. Flux variations of small amplitude seem to be fairly common, but can be detected only in bright sources or in sources observed with very long exposures. Variations of a factor of 2 or more are seen in about 15 percent of the sources for which variations of such an amplitude are detectable.

Maccacaro, Tommaso↗
DOE OSTI2020

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Variable resolution Poisson-disk sampling for meshing discrete fracture networks

Here, we present the near-Maximal Algorithm for Poisson-disk Sampling (nMAPS) to generate point distributions for variable resolution Delaunay triangular and tetrahedral meshes in two and three-dimensions, respectively. nMAPS consists of two principal stages. In the first stage, an initial point distribution is produced using a cell-based rejection algorithm. In the second stage, holes in the sample are detected using an efficient background grid and filled in to obtain a near-maximal covering. Extensive testing shows that nMAPS generates a variable resolution mesh in linear run time with the number of accepted points. We demonstrate nMAPS capabilities by meshing three-dimensional discrete fracture networks (DFN) and the surrounding volume. The discretized boundaries of the fractures, which are represented as planar polygons, are used as the seed of 2D-nMAPS to produce a conforming Delaunay triangulation. The combined mesh of the DFN is used as the seed for 3D-nMAPS, which produces conforming Delaunay tetrahedra surrounding the network. Under a set of conditions that naturally arise in maximal Poisson-disk samples and are satisfied by nMAPS, the two-dimensional Delaunay triangulations are guaranteed to only have well-behaved triangular faces. While nMAPS does not provide triangulation quality bounds in more than two dimensions, we found that low-quality tetrahedra in 3D are infrequent, can be readily detected and removed, and a high-quality balanced mesh is produced.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Review of Soil Organic Carbon Measurement Protocols: A US and Brazil Comparison and Recommendation

Soil organic carbon (SOC) change influences the life-cycle assessment (LCA) calculations for globally traded bio-based products. Broad agreement on the importance of SOC measurement stands in contrast with inconsistent measurement methods. This paper focuses on published SOC research on lands managed for maize ( Zea mays L.) in the U.S. and sugarcane ( Saccharum officinarum L.) in Brazil. A literature review found that reported SOC measurement protocols reflect different sampling strategies, measurement techniques, and laboratory analysis methods. Variability in sampling techniques (pits versus core samples), depths, increments for analysis, and analytical procedures (wet oxidation versus dry combustion) can influence reported SOC values. To improve consistency and comparability in future SOC studies, the authors recommend that: (a) the methods applied for each step in SOC studies be documented; (b) a defined protocol for soil pits or coring be applied; (c) samples be analyzed at 10 cm intervals for the full rooting depth and at 20 cm intervals below rooting until reaching 100 cm; (d) stratified sampling schemes be applied where possible to reflect variability across study sites; (e) standard laboratory techniques be used to differentiate among labile and stable SOC fractions; and (f) more long-term, diachronic approaches be used to assess SOC change. Here, we conclude with suggestions for future research to further improve the comparability of SOC measurements across sites and nations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Sulfur isotope analysis of microcrystalline iron sulfides using secondary ion mass spectrometry imaging: Extracting local paleo-environmental information from modern and ancient sediments

Rationale: Sulfur isotope ratio measurements of bulk sulfide from marine sediments have often been used to reconstruct environmental conditions associated with their formation. In situ microscale spot analyses by secondary ion mass spectrometry (SIMS) and laser ablation multiple-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) have been utilized for the same purpose. However, these techniques are often not suitable for studying small (≤10 μm) grains or for detecting intra-grain variability. Methods: In this work, we present a method for the physical extraction (using lithium polytungstate heavy liquid) and subsequent sulfur isotope analysis (using SIMS; CAMECA IMS 7f-GEO) of microcrystalline iron sulfides. SIMS sulfur isotope ratio measurements were made via Cs + bombardment of raster squares with sides of 20–130 μm, using an electron multiplier (EM) detector to collect counts of 32 S - and 34 S - for each pixel (128 × 128 pixel grids) for between 20 and 960 cycles. Results: The extraction procedure did not discernibly alter pyrite grain-size distributions. The apparent inter-grain variability in 34 S/ 32 S in 1–4 μm-sized pyrite and marcasite fragments from isotopically homogeneous hydrothermal crystals was ~ ±2‰ (1σ), comparable with the standard error of the mean for individual measurements (≤ ±2‰, 1σ). In contrast, grain-specific 34 S/ 32 S ratios in modern and ancient sedimentary pyrites and marcasites can have inter- and intra-grain variability >60‰. The distributions of intra-sample isotopic variability are consistent with bulk 34 S/ 32 S values. Conclusions: SIMS analyses of isolated iron sulfide grains yielded distributions that are isotopically representative of bulk 34 S/ 32 S values. Populations of iron sulfide grains from sedimentary samples record the evolution of the S-isotopic composition of pore water sulfide in their S-isotopic compositions. These data allow past local environmental conditions to be inferred.

59 BASIC BIOLOGICAL SCIENCES↗