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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Future global mortality from changes in air pollution attributable to climate change

Ground-level ozone and fine particulate matter (PM2.5) are associated with premature human mortality(1-4); their future concentrations depend on changes in emissions, which dominate the near-term(5), and on climate change(6,7). Previous global studies of the air-quality-related health effects of future climate change(8,9) used single atmospheric models. But, in related studies, mortality results differ among models(10-12). Here we use an ensemble of global chemistry-climate models(13) to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP8.5 (ref. 14), is probably positive. We estimate 3,340 (-30,300 to 47,100) ozone-related deaths in 2030, relative to 2000 climate, and 43,600 (-195,000 to 237,000) in 2100 (14% of the increase in global ozone-related mortality). For PM2.5, we estimate 55,600 (-34,300 to 164,000) deaths in 2030 and 215,000 (-76,100 to 595,000) in 2100 (countering by 16% the global decrease in PM2.5-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Finally, most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation is likely to reduce air-pollution-related mortality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A non-parametric consistency test of the ΛCDM model with Planck CMB data

Non-parametric reconstruction methods, such as Gaussian process (GP) regression, provide a model-independent way of estimating an underlying function and its uncertainty from noisy data. We demonstrate how GP-reconstruction can be used as a consistency test between a given data set and a specific model by looking for structures in the residuals of the data with respect to the model's best-fit. Applying this formalism to the Planck temperature and polarisation power spectrum measurements, we test their global consistency with the predictions of the base ΛCDM model. Our results do not show any serious inconsistencies, lending further support to the interpretation of the base ΛCDM model as cosmology's gold standard.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Unsupervised Process Anomaly Detection and Identification Using the Leave-One-Variable-Out Approach

Automated anomaly detection and identification can signal equipment issues and pinpoint causes in large-scale industrial systems. For systems with limited failure history, unsupervised machine learning methods can be utilized as they do not require past failures. This study introduces the leave-one-variable-out (LOVO) model, which masks one variable at a time to predict the others, learning underlying process correlations. Detection performance was assessed with synthetic and experimental data, while identification performance used only synthetic data due to its ability to generate labeled anomaly types. For detection using synthetic data, the LOVO model generally outperformed comparative models; while using experimental data, the comparative methods outperformed the LOVO model. However, the comparative methods required selecting a latent size, and these conclusions pertain to using the optimal size. In practice, it would not be feasible to always select the optimal value, and incorrect selections impacted performance. In contrast, the LOVO model does not require a latent space. For identification using synthetic data, the LOVO model was slightly outperformed in interpretability and repeatability but still demonstrated impressive results. These outcomes suggest that the LOVO model is an effective model and may be more easily implemented without the challenging tuning process of selecting a latent size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1980

Research on lunar Mare emplacement and impact cratering experiments

A model was derived enabling the interpretation of lunar styles of volcanism through the analysis of various surface features. The model was applied to several areas on the Moon, including the Orientale Basin, the Smythii Basin, the Herigonious region, and several highland areas. Concurrent with the application of the model, several topical studies of various aspects of lunar volcanism were completed. A series of impact crater experiments was conducted at NASA Ames in order to determine the effect that viscous targets would have on cratering mechanics and morphology for application in studies of Martian ejecta flow craters. The results of the experiments led to a model that can account for the formation of multiple flow lobes and the general morphology of some aspects of Martian craters.

Greeley, R.↗
NASA NTRS1993

Multispectral studies of selected crater- and basin-filling lunar Maria from Galileo Earth-Moon encounter 1

New visible and near-infrared multispectral data of the Moon were obtained by the Galileo spacecraft in December, 1990. These data were calibrated with Earth-based spectral observations of the nearside to compare compositional information to previously uncharacterized mare basalts filling craters and basins on the western near side and eastern far side. A Galileo-based spectral classification scheme, modified from the Earth-based scheme developed by Pieters, designates the different spectral classifications of mare basalt observed using the 0.41/0.56 micron reflectance ratio (titanium content), 0.56 micron reflectance values (albedo), and 0.76/0.99 micron reflectance ratio (absorption due to Fe(2+) in mafic minerals and glass). In addition, age determinations from crater counts and results of a linear spectral mixing model were used to assess the volcanic histories of specific regions of interest. These interpreted histories were related to models of mare basalt petrogenesis in an attempt to better understand the evolution of lunar volcanism.

Williams, D. A.↗
NASA NTRS2017

Future Global Mortality from Changes in Air Pollution Attributable to Climate Change

Ground-level ozone and fine particulate matter (PM (sub 2.5)) are associated with premature human mortality; their future concentrations depend on changes in emissions, which dominate the near-term, and on climate change. Previous global studies of the air-quality-related health effects of future climate change used single atmospheric models. However, in related studies, mortality results differ among models. Here we use an ensemble of global chemistry-climate models to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP (Representative Concentration Pathway) 8.5, is probably positive. We estimate 3,340 (30,300 to 47,100) ozone-related deaths in 2030, relative to 2000 climate, and 43,600 (195,000 to 237,000) in 2100 (14 percent of the increase in global ozone-related mortality). For PM (sub 2.5), we estimate 55,600 (34,300 to 164,000) deaths in 2030 and 215,000 (76,100 to 595,000) in 2100 (countering by 16 percent the global decrease in PM (sub 2.5)-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation is likely to reduce air-pollution-related mortality.

Atmohspheric chemistry↗
DOE OSTI2025

Q -score as a reliability measure for protein, nucleic acid and small-molecule atomic coordinate models derived from 3DEM maps

Atomic coordinate models are important for the interpretation of 3D maps produced with cryoEM and cryoET (3D electron microscopy; 3DEM). In addition to visual inspection of such maps and models, quantitative metrics can inform about the reliability of the atomic coordinates, in particular how well the model is supported by the experimentally determined 3DEM map. A recently introduced metric, Q-score, was shown to correlate well with the reported resolution of the map for well fitted models. Here, we present new statistical analyses of Q-score based on its application to ∼10 000 maps and models archived in the EMDB (Electron Microscopy Data Bank) and PDB (Protein Data Bank). Further, we introduce two new metrics based on Q-score to represent each map and model relative to all entries in the EMDB and those with similar resolution. We explore through illustrative examples of proteins, nucleic acids and small molecules how Q-scores can indicate whether the atomic coordinates are well fitted to 3DEM maps and also whether some parts of a map may be poorly resolved due to factors such as molecular flexibility, radiation damage and/or conformational heterogeneity. These examples and statistical analyses provide a basis for how Q-scores can be interpreted effectively in order to evaluate 3DEM maps and atomic coordinate models prior to publication and archiving.

B factors↗
NASA NTRS1994

Tidal disruption and the appearance of periodic comet Shoemaker-Levy 9

A unified model is formulated to interpret quantitatively the observed characteristics of the nuclear train, the two dust trails, and the tail region of P/Shoemaker-Levy 9 in terms of a collisionally modified rotation velocity distribution of the comet's debris. Since there is no evidence for the comet's out-gassing, the model does not assume activity. The discruption of the parent comet was due primarily to tidal stesses during its extremely close approach to Juptier in July 1992. The original nucleus is found to have been most probably approximately 5 km in radius or, equivalently, approximately 10(exp 17) g in mass. The dynamical separation of the debris occurred apparently approximately 2.2 hr after the perijove passage, even though the actual fragmentation of the original mass is likely to have begun before closest approach. Physical breakp was accompanied by ubiquitous low-velocity collisions among the particulates, resulting in a rearrangement of the initial rotaional velocities into a rapidly 'thermalized' distribution, characterized by a long tail of relatively high velocities for the debris that populates the dust trails far from the nuclear train. Compelling evidence is presented for secondary fragmentation events, indicative of the comet's continuing disintegration. Secondary fragmentation may be caused by rotational bursting of the massive fragments that had been cracked but unbroken during the tidal disruption. Impact conditions and possible interactions of the comet's debris with the jovian system during the encounter in July 1994 are described.

Sekanina, Z.↗
NASA NTRS2022

Spectral Power-law Formation by Sequential Particle Acceleration in Multiple Flare Magnetic Islands

We present a first-principles model of pitch-angle and energy distribution function evolution as particles are sequentially accelerated by multiple flare magnetic islands. Data from magnetohydrodynamic (MHD) simulations of an eruptive flare/coronal mass ejection provide ambient conditions for the evolving particle distributions. Magnetic islands, which are created by sporadic reconnection at the self-consistently formed flare current sheet, contract and accelerate the particles. The particle distributions are evolved using rules derived in our previous work. In this investigation, we assume that a prescribed fraction of particles sequentially "hops" to another accelerator and receives an additional boost in energy and anisotropy. This sequential process generates particle number spectra that obey an approximate power law at mid-range energies and presents low- and high-energy breaks. We analyze these spectral regions as functions of the model parameters. We also present a fully analytic method for forming and interpreting such spectra, independent of the sequential acceleration model. The method requires only a few constrained physical parameters, such as the percentage of particles transferred between accelerators, the energy gain in each accelerator, and the number of accelerators visited. Our investigation seeks to bridge the gap between MHD and kinetic regimes by combining global simulations and analytic kinetic theory. The model reproduces and explains key characteristics of observed flare hard X-ray spectra as well as the underlying properties of the accelerated particles. Our analytic model provides tools to interpret high-energy observations for missions and telescopes, such as RHESSI, FOXSI, NuSTAR, Solar Orbiter, EOVSA, and future high-energy missions.

magnetic reconnection↗
DOE OSTI2019

Evaluation and Validation Approaches for Simulation of Social Behavior: Challenges and Opportunities

While models of social systems have grown in scope to represent increasingly complex phenomena, efforts to validate these models against observations suffer from a number of challenges that include the lack of shared approaches, the use of single-dimensional evaluation criteria, and the difficulty in evaluating causal mechanisms. Moreover, current evaluation approaches suffer from sensitivity of the existing measurements to initial conditions and model assumptions, and failure to account for uncertainty. These effects lead to the lack of generalizability to new contexts, inability to replicate the validation approach for new models, and difficulties in interpretation of validation results. These challenges can be addressed by building a set of diverse and robust evaluation metrics and by developing best practices for comparative, reproducible validation of varied social simulation approaches against real-world data. Herein, we outline several best practices for data-drive model validation, such as defining evaluation strategies consistent with the intended use case and defining broad comparison criteria to highlight both model strengths and weaknesses. Leveraging common validation practices will enable robust analysis of simulation performance across diverse social scenarios and modeling approaches.

Saldanha, Emily G.↗
NASA NTRSDate not supplied

Triple Oxygen Isotope Kinetics of Sulfate From Pyrite Oxidation

Sulfates from low temperature terrestrial and marine environments are out of equilibrium with their oxygen sources. Instead, oxygen isotope compositions of sulfate imply they are dominated by kinetic signatures of oxidative and reductive processes (Killingsworth et al., 2022) that are under-constrained compared to equilibrium effects (Hayles and Killingsworth, 2022). Consequently, the specific role of pyrite oxidation in setting the oxygen isotope composition of sulfate is also under-constrained. This scenario inhibits a more nuanced understanding of small variations in the oxygen isotopes of sulfate and their implications for tracing oxygen sources and sulfur cycle transformations, particularly in low-temperature relatively sulfate-limited freshwater systems such as rivers, lakes, aquifers, and mining-affected environments. To alleviate these knowledge gaps, we conduct pyrite oxidation experiments at time scales spanning minutes to years, analyze the triple oxygen isotope compositions (∆ 17 O and δ 18 O) of sulfate products, and interpret results using molecular modeling. Our preliminary results show isotopic relationships of 1) pyrite-derived sulfate ∆ 17 O reaching above the meteoric water line as its δ 18 O becomes lighter than water, and 2) sulfate ∆ 17 O and δ 18 O extending between water and O 2 . From these results we interpret a kinetic isotope effect between sulfate and water and mixing between sulfate end members containing most of their oxygen atoms from water and from O 2 .

Oxygen isotopes↗
NASA NTRS2005

Aerosols, Chemistry, and Radiative Forcing: A 3-D Model Analysis of Satellite and ACE-Asia data (ACMAP)

We propose a research project to incorporate a global 3-D model and satellite data into the multi-national Aerosol Characterization Experiment-Asia (ACE-Asia) mission. Our objectives are (1) to understand the physical, chemical, and optical properties of aerosols and the processes that control those properties over the Asian-Pacific region, (2) to investigate the interaction between aerosols and tropospheric chemistry, and (3) to determine the aerosol radiative forcing over the Asia-Pacific region. We will use the Georgia TecWGoddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model to link satellite observations and the ACE-Asia measurements. First, we will use the GOCART model to simulate aerosols and related species, and evaluate the model with satellite and in-situ observations. Second, the model generated aerosol vertical profiles and compositions will be used to validate the satellite products; and the satellite data will be used for during- and post- mission analysis. Third, we will use the model to analyze and interpret both satellite and ACE- Asia field campaign data and investigate the aerosol-chemistry interactions. Finally, we will calculate aerosol radiative forcing over the Asian-Pacific region, and assess the influence of Asian pollution in the global atmosphere. We propose a research project to incorporate a global 3-D model and satellite data into

Chin, Mian↗
NASA NTRS2021

Tree-ring cellulose δ(18)O records similar large-scale climate influences as precipitation δ(18)O in the Northwest Territories of Canada

Stable oxygen isotopes measured in tree rings are useful for reconstructing climate variability and explaining changes in physiological processes occurring in forests, complementing other tree-ring parameters such as ring width. Here, we analyzed the relationships between different climate parameters and annually resolved tree-ring δ(18)O records (δ(18)O(TR)) from white spruce (Picea glauca [Moench]Voss) trees located near Tungsten (Northwest Territories, Canada) and used the NASA GISS ModelE2 isotopically-equipped general circulation model (GCM) to better interpret the observed relationships. We found that the δ(18)O(TR) series were primarily related to temperature variations in spring and summer, likely through temperature effects on the precipitation δ(18)O in spring, and evaporative enrichment at leaf level in summer. The GCM simulations showed significant positive relationships between modelled precipitation δ(18)O over the study region and surface temperature and geopotential height over northwestern North America, but of stronger magnitudes during fall-winter than during spring–summer. The modelled precipitation δ(18)O was only significantly associated with moisture transport during the fall-winter season. The δ(18)O(TR) showed similar correlation patterns to modelled precipitation δ(18)O only during spring–summer when water matters more for trees, with significant positive correlations with surface temperature and geopotential height, but no correlations with moisture transport. Overall, the δ(18)O(TR) records for northwestern Canada reflect the same significant large-scale climate patterns as precipitation δ(18)O for spring–summer, and therefore have potential for reconstructing past atmospheric dynamics in addition to temperature variability in the region.

paleoclimate↗
DOE OSTI2022

Integrating multimodal data through interpretable heterogeneous ensembles

Motivation: Integrating multimodal data represents an effective approach to predicting biomedical characteristics, such as protein functions and disease outcomes. However, existing data integration approaches do not sufficiently address the heterogeneous semantics of multimodal data. In particular, early and intermediate approaches that rely on a uniform integrated representation reinforce the consensus among the modalities but may lose exclusive local information. The alternative late integration approach that can address this challenge has not been systematically studied for biomedical problems. Results: We propose Ensemble Integration (EI) as a novel systematic implementation of the late integration approach. EI infers local predictive models from the individual data modalities using appropriate algorithms and uses heterogeneous ensemble algorithms to integrate these local models into a global predictive model. We also propose a novel interpretation method for EI models. We tested EI on the problems of predicting protein function from multimodal STRING data and mortality due to coronavirus disease 2019 (COVID-19) from multimodal data in electronic health records. We found that EI accomplished its goal of producing significantly more accurate predictions than each individual modality. It also performed better than several established early integration methods for each of these problems. The interpretation of a representative EI model for COVID-19 mortality prediction identified several disease-relevant features, such as laboratory test (blood urea nitrogen and calcium) and vital sign measurements (minimum oxygen saturation) and demographics (age). These results demonstrated the effectiveness of the EI framework for biomedical data integration and predictive modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

PS1-14bj: a hydrogen-poor superluminous supernova with a long rise and slow decay

We present photometry and spectroscopy of PS1-14bj, a hydrogen-poor superluminous supernova (SLSN) at redshift z = 0.5215 discovered in the last months of the Pan-STARRS1 Medium Deep Survey. PS1-14bj stands out because of its extremely slow evolution, with an observed rise of ≳125 rest-frame days, and exponential decline out to ∼250 days past peak at a measured rate of 0.01 mag day{sup −1}, consistent with fully trapped {sup 56}Co decay. This is the longest rise time measured in an SLSN to date, and the first SLSN to show a rise time consistent with pair-instability supernova (PISN) models. Compared to other slowly evolving SLSNe, it is spectroscopically similar to the prototype SN 2007bi at maximum light, although lower in luminosity (L{sub peak}≃4.6×10{sup 43} erg s{sup −1}) and with a flatter peak than previous events. PS1-14bj shows a number of peculiar properties, including a near-constant color temperature for >200 days past peak, and strong emission lines from [O iii] λ5007 and [O iii] λ4363 with a velocity width of ∼3400 km s{sup −1} in its late-time spectra. These both suggest there is a sustained source of heating over very long timescales, and are incompatible with a simple {sup 56}Ni-powered/PISN interpretation. A modified magnetar model including emission leakage at late times can reproduce the light curve, in which case the blue continuum and [O iii] features are interpreted as material heated and ionized by the inner pulsar wind nebula becoming visible at late times. Alternatively, the late-time heating could be due to interaction with a shell of H-poor circumstellar material.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1979

Starspots as the cause of the intrinsic light variations in RS Canum Venaticorum type stars

A starspot model is proposed to interpret the light curves of three RS CVn type binary systems. Two of the systems are RS CVn and SZ Psc, which are detached, while the third system, RT Lac, is semidetached. Solar activity and the surface activity of the RS CVn type stars are compared. It is found that the spot model permits the detailed fitting of both the out-of-eclipse complications and the distorted shapes of the secondary eclipses in the light curves of these stars.

Eaton, J. A.↗
NASA NTRS1994

Convective flow effects on protein crystal growth

The long-term stability of the interferometric setup for the monitoring of protein morphologies has been improved. Growth or dissolution of a crystal on a 100 A scale can now be clearly distinguished from dimensional changes occurring within the optical path of the interferometer. This capability of simultaneously monitoring the local interfacial displacement at several widely-spaced positions on the crystal surface with high local depth resolution, has already yielded novel results. We found with lysozyme that (1) the normal growth rate is oscillatory, and (2) the mean growth step density is greater at the periphery of a facet than in its center. The repartitioning of Na(+) and Cl(-) ions between lysozyme solutions and crystals was studied for a wide range of crystallization conditions. A nucleation-growth-repartitioning model was developed to interpret the large body of data in a unified way. The results strongly suggests that (1) the ion to lysozyme ratio in the crystal depends mostly on kinetic rather than crystallographic parameters, and (2) lysozyme crystals possess a salt-rich core with a diameter on the order of 10 microns. The computational model for diffusive-convective transport in protein crystallization (see the First Report) has been applied to a realistic growth cell geometry, taking into account the findings of the above repartitioning studies. These results show that some elements of a moving boundary problem must be incorporated into the model in order to obtain a more realistic description. Our experimental setup for light scattering investigations of aggregation and nucleation in protein solutions has been extensively tested. Scattering intensity measurements with a true Rayleigh scatterer produced systematically increased forward scattering, indicating problems with glare. These have been resolved. Preliminary measurements with supersaturated lysozyme solutions revealed that the scatterers grow with time. Work has begun on a computer program for the unified evaluation of simultaneously obtained, multi-angle static and dynamic light scattering data.

Rosenberger, Franz↗
NASA NTRS2000

Coronal Physics and the Chandra Emission Line Project

With the launch of the Chandra X-ray Observatory, high resolution X-ray spectroscopy of cosmic sources has begun. Early, deep observations of three stellar coronal sources Capella, Procyon, and HR 1099 are providing not only invaluable calibration data, but also benchmarks for plasma spectral models. These models are needed to interpret data from stellar coronae, galaxies and clusters of galaxies, supernova, remnants and other astrophysical sources. They have been called into question in recent years as problems with understanding low resolution ASCA and moderate resolution Extreme Ultraviolet Explorer Satellite (EUVE) data have arisen. The Emission Line Project is a collaborative effort, to improve the models, with Phase I being the comparison of models with observed spectra of Capella, Procyon, and HR 1099. Goals of these comparisons are (1) to determine and verify accurate and robust diagnostics and (2) to identify and prioritize issues in fundamental spectroscopy which will require further theoretical and/or laboratory work. A critical issue in exploiting the coronal data for these purposes is to understand the extent, to which common simplifying assumptions (coronal equilibrium, negligible optical depth) apply. We will discuss recent, advances in our understanding of stellar coronae, in this context.

Brickhouse, N. S.↗