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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Inferring the Contribution of Microbial Taxa and Organic Matter Molecular Formulas to Ecological Assembly

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model β-nearest taxon index (βNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level βNTI (βNTI feat ), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using βNTI feat , we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that βNTI feat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate βNTI feat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that βNTI feat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Real-time inference and extrapolation with Time-Conditioned UNet: Applications in hypersonic flows, incompressible flows, and global temperature forecasting

Neural Operators are fast and accurate surrogates for nonlinear mappings between functional spaces within training domains. Extrapolation beyond the training domain remains a grand challenge across all application areas. We present Time-Conditioned UNet (TC-UNet) as an operator learning method to solve time-dependent PDEs continuously in time without any temporal discretization, including in extrapolation scenarios. TC-UNet incorporates the temporal evolution of the PDE into its architecture by combining a parameter conditioning approach with the attention mechanism from the Transformer architecture. After training, TC-UNet makes real-time inferences on an arbitrary temporal grid. We demonstrate its extrapolation capability on a climate problem by estimating the global temperature for several years and also for inviscid hypersonic flow around a double cone. We propose different training strategies involving temporal bundling and sub-sampling. We demonstrate performance improvements for several benchmarks, performing extrapolation for long time intervals and zero-shot super-resolution time.

Deep learning↗
NASA NTRS2000

The Evolution of Sulfide Tolerance in the Cyanobacteria

Understanding how the function of extant microorganisms has recorded both their evolutionary histories and their past interactions with the environment is a stated goal of astrobiology. We are taking a multidisciplinary approach to investigate the diversification of sulfide tolerance mechanisms in the cyanobacteria, which vary both in their degree of exposure to sulfide and in their capacity to tolerate this inhibitor of photosynthetic electron transport. Since conditions were very reducing during the first part of Earth's history and detrital sulfides have been found in Archean sediments, mechanisms conferring sulfide tolerance may have been important for the evolutionary success of the ancestors of extant cyanobacteria. Two tolerance mechanisms have been identified in this group: (1) resistance of photosystem II, the principal target of sulfide toxicity; and (2) maintenance of the ability to fix carbon despite photosystem II inhibition by utilizing sulfide as an electron donor in photosystem I - dependent, anoxygenic photosynthesis. We are presently collecting comparative data on aspects of sulfide physiology for laboratory clones isolated from a variety of habitats. These data will be analyzed within a phylogenetic framework inferred from molecular sequence data collected for these clones to test how frequently different mechanisms of tolerance have evolved and which tolerance mechanism evolved first. In addition, by analyzing these physiological data together with environmental sulfide data collected from our research sites using microelectrodes, we can also test whether the breadth of an organism's sulfide tolerance can be predicted from the magnitude of variation in environmental sulfide concentration it has experienced in its recent evolutionary past and whether greater average sulfide concentration and/or temporal variability in sulfide favors the evolution of a particular mechanism of sulfide tolerance.

Miller, Scott R.↗
DOE OSTI2025

Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification

In numerous applications, the integration of prior knowledge and historical information is essential, particularly for tasks requiring the solution of ordinary or partial differential equations (ODEs/PDEs) in data-sparse or noisy environments. For instance, achieving accurate solutions to time-dependent PDEs with limited initial condition measurements necessitates an effective strategy for embedding prior knowledge. Hard-parameter sharing architectures in neural networks (NNs) have demonstrated success in both traditional and scientific machine learning domains, facilitating the learning of informative representations. Here, in this study, we introduce a novel, yet efficient, method to enhance physics-informed neural networks (PINNs) by incorporating a multi-head structure that enables the learning of functional priors from both empirical data and governing physical laws. This prior information can then be used to address data sparsity and high-level noise in solving ODE/PDE problems with uncertainty quantification (UQ). The approach, termed Multi-Head PINN (MH-PINN), consists of a shared body NN and multiple head NNs, each corresponding to an individual PINN instance. Our framework for functional prior learning is carried out in two stages: (1) training the MH-PINNs to develop a shared body NN alongside multiple head NNs, and (2) employing these trained head NNs to estimate a prior distribution through a normalizing flow-based density estimator. The learned functional prior can then be applied as a regularization mechanism in deterministic contexts or as an informative prior within a Bayesian inference framework, aiding in the resolution of subsequent ODE/PDE tasks. We evaluate the efficacy of MH-PINNs across five benchmark problems, including a high-dimensional parametric PDE, all characterized by data sparsity or substantial noise levels. Our findings reveal that MH-PINNs deliver accurate solutions and robust UQ, demonstrating adaptability across a range of complex and challenging scenarios.

Bayesian inference↗
NASA NTRS1985

Why do we need detailed gravity over continents: Some Australian examples

Geophysical quantities available over a continent are gravity and components of the magnetic field. Direct inferences on crustal structure are difficult to make and strongly dependent on mechanical assumptions the isostatic state. The data for Australia represents one of the best continental scale gravity surveys. The gravity anomalies are generally bland over the continent which confirms that stress relaxation and erosion and rebound were instrumental in reducing nonhydrostatic stresses. In central Australia very large gravity anomalies occur and the region is out of isostatic equilibrium despite the fact that tectonic activity ceased 300 ma ago. The isostatic response functions points to a substantial horizontal compression in the crust. Similar conclusions are drawn for the large anomalies in western Australia. The tectonic implications of these anomalies are examined. In eastern Australia the gravity anomalies are explained in terms of a model of erosion of the highlands and concomitant regional isostatic rebound.

Lambeck, K.↗
NASA NTRS1988

Space station contamination study: Assessment of contaminant spectral brightness

The assessment of spectral brightness resulting from the ambient-contaminant interaction requires a knowledge of the details of cross sections and excitation mechanisms. The approach adopted was to utilize the spectral brightness measurements made on Spacelab 1 and on the S3-4 spacecraft to identify source mechanisms, key cross sections and hence, the abundance of contaminant species. These inferred abundances were then used to update the composition comprising the total column concentrations predicted by the Science and Engineering Associates' configuration contamination model for the Space Station and to scale the irradiances to four altitudes: 300, 350, 400, and 463 km. The concentration irradiances are compared with zodiacal natural background levels. The results demonstrate that emissive contamination is significantly more severe than anticipated. It is shown that spectral emissions can become competitive with the zodiacal background up to altitudes as high as 400 km for the vacuum ultraviolet and visible emissions.

Torr, D. G.↗
NASA NTRS1988

A simulation engine: Combining an expert system with a simulation language

Expert systems were applied in a number of ways to the field of simulation. One of these is the application of an expert system to drive a simulation, by making run-time decisions which effect the simulation. This approach was successful for a number of specific simulation models. The simulation engine extends this capability by supporting this type of interaction in a general purpose setting. A general purpose simulation language is provided for building models, and an inference engine is provided for knowledge processing. This combination results in a mechanism which allows general purpose models to be simulated in concert with interactive knowledge bases.

Spiegel, James R.↗
NASA NTRS1999

The Natural Thermoluminescence Survey of Antarctic Meteorites: Ordinary Chondrites at the Grosvenor Mountains, Macalpine Hills, Pecora Escarpment and Queen Alexandra Range, and New Data for the Elephant Moraine, Ice Fields

The natural TL (Thermoluminescence) survey of Antarctic meteorites was started in 1987 at the request of the Antarctic Meteorite Working Group in order to provide an initial description of radiation and thermal histories. It was intended to be a complement to the mineralogical and petrographic surveys performed at the Johnson Space Center and the Smithsonian Institution. All ANSMET (Antarctic Search for Meteorites) samples recovered since then, besides those that were heated throughout by atmospheric passage, have been measured. To date this amounts to about 1200 samples. As the data for each ice field reaches a significant level, we have been conducting a thorough examination of the data for that field with a view to identifying pairing, providing an estimate of terrestrial age and residence time on the ice surface, looking for differences in natural TL between ice fields, looking for variations in natural TL level with location on the ice, looking for meteorites with natural TL levels outside the normal range. Pairing is a necessary first step in ensuring the most productive use of the collection, while geographical variations could perhaps provide clues to concentration mechanisms. Samples with natural TL values outside the normal range are usually inferred to have had either small perihelia or recent changes in orbital elements. In addition, induced TL data have enabled us to look for evidence for secular variation in the nature of the flux of meteorites to Earth, and look for petrologically unusual meteorites, such as particularly primitive ordinary chondrites, heavily shocked meteorites, or otherwise anomalous meteorites. To date we have published studies of the TL properties of 167 ordinary chondrites from Allan Hills, 107 from Elephant Moraine and 302 from Lewis Cliff and we have discussed the TL properties of fifteen H chondrites collected at the Allan Hills by Euromet after a storm during the 1988 season. We now have additional databases for a reasonable number of ordinary chondrites from Grosvenor Mountains (39 meteorites), MacAlpine Hills (70 meteorites), Pecora Escarpment (60 meteorites), and Queen Alexandra Range (173 meteorites) and we have data for a further 101 samples from Elephant Moraine. The results are summarized. We also have fairly minimal databases (10-15 meteorites) for Dominion Range, Graves Nunataks, Reckling Peak and Wisconsin Range that will not be discussed here.

Benoit, Paul H.↗
NASA NTRS2000

The Natural Thermoluminescence Survey of Antarctic Meteorites: Ordinary Chondrites at the Grosvenor Mountains, MacAlpine Hills, Pecora Escarpment and Queen Alexandra Range, and New Data New Data for the Elephant Moraine, Ice Fields

The natural TL survey of Antarctic meteorites was started in 1987 at the request of the Antarctic Meteorite Working Group in order to provide an initial description of radiation and thermal histories. It was intended to be a complement to the mineralogical and petrographic surveys performed at the Johnson Space Center and the Smithsonian Institution. All ANSMET samples recovered since then, besides those that were heated throughout by atmospheric passage, have been measured. To date this amounts to about 1200 samples. As the data for each ice field reaches a significant level, we have been conducting a thorough examination of the data for that field with a view to (1) identifying pairing, (2) providing an estimate of terrestrial age and residence time on the ice surface, (3) looking for differences in natural TL between ice fields, (4) looking for variations in natural TL level with location on the ice, (5) looking for meteorites with natural TL levels outside the normal range. Pairing is a necessary first step in ensuring the @ost productive use of the collection, while geographical variations could perhaps provide clues to concentration mechanisms. Samples with natural TL values outside the normal range are usually inferred to have had either small perihelia or recent changes in orbital elements. In addition, induced TL data have enabled us to (5) look for evidence for secular variation in the nature of the flux of meteorites to Earth, and (6) look for petrologically unusual meteorites, such as particularly primitive ordinary chondrites, heavily shocked meteorites, or otherwise anomalous meteorites. To date we have published studies of the TL properties of 167 ordinary chondrites from Allan Hills, 107 from Elephant Moraine and 302 from Lewis Cliff and we have discussed the TL properties of fifteen H chondrites collected at the Allan Hills by Euromet after a storm during the 1988 season. We now have additional databases for a reasonable number of ordinary chondrites from Grosvenor Mountains (39 meteorites), MacAlpine Hills (70 meteorites), Pecora Escarpment (60 meteorites), and Queen Alexandra Range (173 meteorites) and we have data for a further 101 samples from Elephant Moraine. The results are summarized in Table 1. We also have fairly minimal databases (10-15 meteorites) for Dominion Range, Graves Nunataks, Reckling Peak and Wisconsin Range that will not be discussed here.

Benoit, Paul H.↗
DOE OSTI2021

Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma

Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to multiple lines of therapies. Therefore, we not only need the ability to predict which patients are at high risk for disease progression but also a means to understand the mechanisms underlying their risk. Here, we report a transcriptional regulatory network (TRN) for MM inferred from cross-sectional multi-omics data from 881 patients that predicts how 124 chromosomal abnormalities and somatic mutations causally perturb 392 transcription regulators of 8549 genes to manifest in distinct clinical phenotypes and outcomes. We identified 141 genetic programs whose activity profiles stratify patients into 25 distinct transcriptional states and proved to be more predictive of outcomes than did mutations. The coherence of these programs and accuracy of our network-based risk prediction was validated in two independent datasets. We observed subtype-specific vulnerabilities to interventions with existing drugs and revealed plausible mechanisms for relapse, including the establishment of an immunosuppressive microenvironment. Investigation of the t(4;14) clinical subtype using the TRN revealed that 16% of these patients exhibit an extreme-risk combination of genetic programs (median progression-free survival of 5 months) that create a distinct phenotype with targetable genes and pathways.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

Polar and Non-Polar Layers on Mars: A Single Mechanism for Formation?

The recent discovery of vast quantities of near-subsurface ice in both polar regions of Mars by the Mars Odyssey Gamma Ray Spectrometer (GRS) has presented us with an interesting quandary. On one hand, these deposits, found poleward of 60 deg in both hemispheres, are consistent with thermal models suggesting ice will be best protected in these regions during periods of high obliquity. On the other hand, the current paradigm regarding the placement of these deposits, i.e., diffusive deposition of water vapor, appears to be inconsistent with the large volume mixing ratios (approx. 90%) inferred from the GRS data. This incongruity argues that diffusion alone cannot be the primary mechanism for the creation of these reservoirs, and that an alternate, large-scale process should be considered.

Mischna, M. A.↗
DOE OSTI2023

A mechanistic model for creep and thermal aging in Alloy 709

This report describes a physics-based model for creep and thermal aging in Alloy 709. Alloy 709 is an advanced austenitic alloy, targeted for use in future Sodium Fast Reactors (SFRs) and other advanced reactors. The material has superior high temperature properties compared to currently qualified 316 and 304 stainless steels. However, the available creep and thermal aging test database for Alloy 709 is significantly more limited compared to the historical materials. The physics-based model developed here is one way to accelerate the qualification of the material by providing more accurate long-term predictions for creep properties and thermal aging, compared to current empirical time-extrapolate techniques. The crystal plasticity finite element model is used to predict the deformation and failure of alloy 709. The same setup for the CPFE model is used in both the baseline model calibration process and the simulation campaigns for parameter inference. Specific constitutive choices are made for Alloy 709 to capture the primary deformation mechanisms. The dislocation creep formulation developed by Hu and Cocks is extended to account for coupled precipitation formation and the grain boundary cavitation model developed by Sham, Needleman, et al. is used to model grain boundary cavitation-induced failure. A novel update algorithm is proposed to render the semi-discrete constitutive update for the Sham-Needleman model unconditionally stable. A progressive calibration approach is adopted based on the observations that several types of material responses can be effectively decoupled. A surrogate model is trained based on full-fledged CPFE simulations to accelerate the forward model evaluations, and stochastic variational inference (SVI) is used to calibrate the unknown microstructural model parameters. The calibrated mechanistic model is used to predict the long-term creep life of Alloy 709, and the predictions are compared against classical empirical approaches.

36 MATERIALS SCIENCE↗
NASA NTRS1983

The inference of tropical cyclone dynamics using GOES VISSR/VAS data

The sequence of events observed during tropical cyclone Emily, was suggested as a possible mechanism for cyclogenesis. Geostationary Operational Environmental Satellite (GOES) East VISSR/VAS sensors were used. The VISSR visible imagery obtained every 15 minutes was used to define the low tropospheric cyclonic vortex and upper tropospheric horizontal convergence. The VAS water vapor (channels 9 and 10) and carbon dioxide (channels 3 and 4) channels were used to infer upper and middle tropospheric subsidence by monitoring the Adiabatic compressional drying and warming, respectively, occurring within this layer. Evidence of an existing lower tropospheric cyclonic vortex was seen. The satellite derived wind vectors (length of vector is proportional to wind velocity, where the strongest winds were approximately 35 knots) are superimposed on the GOES visible image of tropical storm Emily. Vectors and low level clouds depict the center of the cyclonic vortex immediately south of the large convective cell in the center of the image. Upper tropospheric cloud tracers and rawinsonde reports along the Eastern United States suggest that the southwesterly environmental upper atmospheric flow is converging with the outflow from the convective cell north of the vortex.

Rodgers, E. B.↗
NASA NTRS1988

Collisionless shock formation and the prompt acceleration of solar flare ions

The formation mechanisms of collisionless shocks in solar flare plasmas are investigated. The priamry flare energy release is assumed to arise in the coronal portion of a flare loop as many small regions or 'hot spots' where the plasma beta locally exceeds unity. One dimensional hybrid numerical simulations show that the expansion of these 'hot spots' in a direction either perpendicular or oblique to the ambient magnetic field gives rise to collisionless shocks in a few Omega(i), where Omega(i) is the local ion cyclotron frequency. For solar parameters, this is less than 1 second. The local shocks are then subsequently able to accelerate particles to 10 MeV in less than 1 second by a combined drift-diffusive process. The formation mechanism may also give rise to energetic ions of 100 keV in the shock vicinity. The presence of these energetic ions is due either to ion heating or ion beam instabilities and they may act as a seed population for further acceleration. The prompt acceleration of ions inferred from the Gamma Ray Spectrometer on the Solar Maximum Mission can thus be explained by this mechanism.

Cargill, P. J.↗
DOE OSTI2025

A Unified Interpretation of Variability in Precipitation Isotope Ratios

Abstract Several mechanisms have been proposed to explain why the isotope ratios of precipitation vary in space and time and why they correlate with other climate variables like temperature and precipitation. Here, we argue that this behavior is best understood through the lens of radiative transfer, which treats the depletion of atmospheric vapor transport by precipitation as analogous to the attenuation of light by absorption or scattering. Building on earlier work by Siler et al., we introduce a simple model that uses the equations of radiative transfer to approximate the two-dimensional pattern of the oxygen isotope composition of precipitation ( δ p ) from monthly mean hydrologic variables. The model accurately simulates the spatial and seasonal variability in δ p within a state-of-the-art climate model and permits a simple decomposition of δ p variability into contributions from gradients in evaporation and the length scale of vapor transport. Outside the tropics, δ p is mostly controlled by gradients in evaporation, whose dependence on temperature explains the positive correlation between δ p and temperature (i.e., the temperature effect). At low latitudes, δ p is mostly controlled by gradients in the transport length scale, whose inverse relationship with precipitation explains the negative correlation between δ p and precipitation (i.e., the amount effect). This suggests that the temperature and amount effects are both mostly explained by the variability in upstream rainout, but they reflect distinct mechanisms governing rainout at different latitudes. Significance Statement The isotopic composition of precipitation has long been used to make inferences about past climates based on its observed relationship with precipitation in the tropics and with temperature at higher latitudes. These relationships—known as the “amount effect” and “temperature effect,” respectively—have been attributed to many different mechanisms, most of which are thought to operate at either high or low latitudes but not both. Here, we present a unified framework for interpreting the isotope variability that can explain the latitude dependence of the temperature and amount effects despite making no distinction between high and low latitudes. Although our results are generally consistent with certain interpretations of the amount effect, they suggest that the temperature effect is widely misunderstood.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference

Operator inference learns low-dimensional dynamical-system models with polynomial nonlinear terms from trajectories of high-dimensional physical systems (non-intrusive model reduction). Here, this work focuses on the large class of physical systems that can be well described by models with quadratic and cubic nonlinear terms and proposes a regularizer for operator inference that induces a stability bias onto learned models. The proposed regularizer is physics informed in the sense that it penalizes higher-order terms with large norms and so explicitly leverages the polynomial model form that is given by the underlying physics. This means that the proposed approach judiciously learns from data and physical insights combined, rather than from either data or physics alone. Additionally, a formulation of operator inference is proposed that enforces model constraints for preserving structure such as symmetry and definiteness in linear terms. Numerical results demonstrate that models learned with operator inference and the proposed regularizer and structure preservation are accurate and stable even in cases where using no regularization and Tikhonov regularization leads to models that are unstable.

97 MATHEMATICS AND COMPUTING↗