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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

AAPM Truth‐based CT (TrueCT) reconstruction grand challenge

Background: This Special Report summarizes the 2022, AAPM grand challenge on Truth-based CT image reconstruction. Purpose: To provide an objective framework for evaluating CT reconstruction methods using virtual imaging resources consisting of a library of simulated CT projection images of a population of human models with various diseases. Methods: Two hundred unique anthropomorphic, computational models were created with varied diseases consisting of 67 emphysema, 67 lung lesions, and 66 liver lesions. The organs were modeled based on clinical CT images of real patients. The emphysematous regions were modeled using segmentations from patient CT cases in the COPDGene Phase I dataset. For the lung and liver lesion cases, 1–6 malignant lesions were created and inserted into the human models, with lesion diameters ranging from 5.6 to 21.9 mm for lung lesions and 3.9 to 14.9 mm for liver lesions. The contrast defined between the liver lesions and liver parenchyma was 82 ± 12 HU, ranging from 50 to 110 HU. Similarly, the contrast between the lung lesions and the lung parenchyma was defined as 781 ± 11 HU, ranging from 725 to 805 HU. For the emphysematous regions, the defined HU values were −950 ± 17 HU ranging from −918 to −979 HU. The developed human models were imaged with a validated CT simulator. The resulting CT sinograms were shared with the participants. The participants reconstructed CT images from the sinograms and sent back their reconstructed images. Further, the reconstructed images were then scored by comparing the results against the corresponding ground truth values. The scores included both task-generic (root mean square error [RMSE] and structural similarity matrix [SSIM]), and task-specific (detectability index [d’] and lesion volume accuracy) metrics. For the cases with multiple lesions, the measured metric was averaged across all the lesions. To combine the metrics with each other, each metric was normalized to a range of 0 to 1 per disease type, with “0” and “1” being the worst and best measured values across all cases of the disease type for all received reconstructions. Results: The True-CT challenge attracted 52 participants, out of which 5 successfully completed the challenge and submitted the requested 200 reconstructions. Across all participants and disease types, SSIM absolute values ranged from 0.22 to 0.90, RMSE from 77.6 to 490.5 HU, d’ from 0.1 to 64.6, and volume accuracy ranged from 1.2 to 753.1 mm3. The overall scores demonstrated that participant “A” had the best performance in all categories, except for the metrics of d’ for lung lesions and RMSE for liver lesions. Participant “A” had an average normalized score of 0.41 ± 0.22, 0.48 ± 0.32, and 0.42 ± 0.33 for the emphysema, lung lesion, and liver lesion cases, respectively. Conclusions: The True-CT challenge successfully enabled objective assessment of CT reconstructions with the unique advantage of access to a diverse population of diseased human models with known ground truth. This study highlights the significant potential of virtual imaging trials in objective assessment of medical imaging technologies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model

The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. Determining if and how the features of these exogenous variables (e.g., sound frequency, reach angle) are reflected in population neural activity is important for understanding how the brain operates. Often, high-dimensional neural population activity is confined to low-dimensional latent spaces. However, many current methods fail to extract latent spaces that are clearly structured by exogenous variables. This has contributed to a debate about whether or not brains should be thought of as dynamical systems or representational systems. Here, we developed a new latent process Bayesian regression framework, the orthogonal stochastic linear mixing model (OSLMM) which introduces an orthogonality constraint amongst time-varying mixture coefficients, and provide Markov chain Monte Carlo inference procedures. We demonstrate superior performance of OSLMM on latent trajectory recovery in synthetic experiments and show superior computational efficiency and prediction performance on several real-world benchmark data sets. We primarily focus on demonstrating the utility of OSLMM in two neural data sets: μ ECoG recordings from rat auditory cortex during presentation of pure tones and multi-single unit recordings form monkey motor cortex during complex arm reaching. We show that OSLMM achieves superior or comparable predictive accuracy of neural data and decoding of external variables (e.g., reach velocity). Most importantly, in both experimental contexts, we demonstrate that OSLMM latent trajectories directly reflect features of the sounds and reaches, demonstrating that neural dynamics are structured by neural representations. Together, these results demonstrate that OSLMM will be useful for the analysis of diverse, large-scale biological time-series datasets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Inferring demographic and selective histories from population genomic data using a 2-step approach in species with coding-sparse genomes: an application to human data

Abstract The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Soni, Vivak (ORCID:0000000294969562)↗
NASA NTRS1976

The stellar content of the nuclear regions of Sc galaxies

Stellar-population syntheses based on absolute spectral energy distributions over the wavelength range from 3300 to 10,400 A are used to determine the stellar content of the nuclear regions of seven nearby Sc galaxies (NGC 628, 1073, 1084, 1637, 2903, 4321, and 5194). A linear-programming procedure is employed to construct models of the overall stellar populations whose spectra closely match those of the seven galaxies. Absolute measurements of the emission-line spectra of the nuclear regions are also provided. It is found that: (1) intrinsic reddening is probably present in each nuclear region; (2) the upper main sequence is substantially populated in most of the models; (3) the lower main sequence contributes insignificantly to the luminosity in all optimal solutions; (4) substantial contributions are made by evolved M stars at long wavelengths in all the models; (5) the model photometric M/L ratios are low, of the order of unity; and (6) the O-B stars arising naturally in the population models are just sufficient to provide the observed nuclear ionization in all the galaxies except NGC 5194, which may be collisionally ionized. The properties of the nuclear regions are shown to be consistent with the existence of a common initial mass function for star formation and a variety of time dependences for the star-formation process. A possibly significant correlation is noted between nuclear stellar content and overall dynamical properties in four of the galaxies.

Turnrose, B. E.↗
DOE OSTI2022

Improving Predictive Capability in REHEDS Simulations with Fast, Accurate, and Consistent Non-Equilibrium Material Properties

Predictive design of REHEDS experiments with radiation-hydrodynamic simulations requires knowledge of material properties (e.g. equations of state (EOS), transport coefficients, and radiation physics). Interpreting experimental results requires accurate models of diagnostic observables (e.g. detailed emission, absorption, and scattering spectra). In conditions of Local Thermodynamic Equilibrium (LTE), these material properties and observables can be pre-computed with relatively high accuracy and subsequently tabulated on simple temperature-density grids for fast look-up by simulations. When radiation and electron temperatures fall out of equilibrium, however, non-LTE effects can profoundly change material properties and diagnostic signatures. Accurately and efficiently incorporating these non-LTE effects has been a longstanding challenge for simulations. At present, most simulations include non-LTE effects by invoking highly simplified inline models. These inline non-LTE models are both much slower than table look-up and significantly less accurate than the detailed models used to populate LTE tables and diagnose experimental data through post-processing or inversion. Because inline non-LTE models are slow, designers avoid them whenever possible, which leads to known inaccuracies from using tabular LTE. Because inline models are simple, they are inconsistent with tabular data from detailed models, leading to ill-known inaccuracies, and they cannot generate detailed synthetic diagnostics suitable for direct comparisons with experimental data. This project addresses the challenge of generating and utilizing efficient, accurate, and consistent non-equilibrium material data along three complementary but relatively independent research lines. First, we have developed a relatively fast and accurate non-LTE average-atom model based on density functional theory (DFT) that provides a complete set of EOS, transport, and radiative data, and have rigorously tested it against more sophisticated first-principles multi-atom DFT models, including time-dependent DFT. Next, we have developed a tabular scheme and interpolation methods that compactly capture non-LTE effects for use in simulations and have implemented these tables in the GORGON magneto-hydrodynamic (MHD) code. Finally, we have developed post-processing tools that use detailed tabulated non-LTE data to directly predict experimental observables from simulation output.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Integrated modeling methodology for ash agglomeration in poly-disperse fluidized beds using particle population framework

This article discusses a unique agglomeration modeling methodology developed based on binary collisions to combine the effects of heterogeneity in ash chemistry and granular physics. A simple population balance is defined to find changes in the particle size distribution (PSD) of a fluidized bed. Thermodynamic equilibrium calculations and a computational fluid dynamics (CFD) code, are used to obtain hydrodynamic parameters. A method to calculate and use a distribution of collision frequencies in fluidized beds, corresponding to a poly-disperse particle size distribution, was developed in order to incorporate the particle level heterogeneities. A distribution of collision frequencies obtained for poly-dispersed particles showed a three orders of magnitude higher collision frequency amongst the smaller particles than the coarser ones, at the initiation of agglomeration. Ash agglomeration occurred when the slag amount (binder) was less than 10 wt% at temperatures <850 °C for Pittsburgh No. 8 coal.

42 ENGINEERING↗
NASA NTRS1993

The nature of faint emission-line galaxies

One of the results of faint galaxy redshift surveys is the increased fraction of galaxies which have strong emission-line spectra. These faint surveys find that roughly 50 percent of the galaxies have an equivalent width of (OII), W sub 3727, greater than 20 A while this fraction is less than 20 percent in the DARS survey. This has been interpreted as evidence for strong evolution in the galaxy population at redshifts less than 0.5. In order to further investigate the properties of the galaxies in faint redshift surveys, two important factors must be addressed. The first is the observed correlation between color, luminosity, and W sub 3727. There is a correlation between color and the strength of emission lines, bluer galaxies having stronger emission features, as evident for Markarian galaxies and for galaxies in Kennicutt's spectrophotometric atlas. This correlation also applies galaxies in faint redshift surveys. In addition, low luminosity galaxies have a larger average W sub 3727 (and bluer colors) than higher luminosity galaxies. This is illustrated for Kennicutt's low z late-type galaxies, for the Durham Faint Surveys, and for galaxies in SA68. The second factor which must be incorporated into any interpretation of the faint emission galaxies is the different luminosity functions for galaxies depending on color. This is usually modeled by varying M* for different color classes (or morphological types); however, the shape of the luminosity function is different for galaxies with different colors. Low luminosity, blue galaxies have a much larger number density than low luminosity, red galaxies. Furthermore, the low luminosity end of the blue galaxy luminosity function is not well fit by a Schechter function. These two factors have been included in a very simple, no-evolution, model for the galaxy population. This model uses the luminosity functions from Shanks (1990) and spectral energy distributions (SED's) from Bruzual (1988). W sub 3727 is predicted using the correlation (including dispersion) with color.

Smetanka, John J.↗
NASA NTRS2005

Thermal and Non-thermal Nature of the Soft Excess Emission from Sersic 159-03 observed with XMM-Newton

Several nearby clusters exhibit an excess of soft X-ray radiation which cannot be attributed to the hot virialized intra-cluster medium. There is no consensus to date on the origin of the excess emission: it could be either of thermal origin, or due to an inverse Compton scattering of the cosmic microwave background. Using high resolution XMM-Newton data of Sersic 159-03 we first show that strong soft excess emission is detected out to a radial distance of 0.9 Mpc. The data are interpreted using the two viable models available, i.e., by invoking a warm reservoir of thermal gas, or relativistic electrons which are part of a cosmic ray population. The thermal model leads to a better goodness-of-fit, and the emitting warm gas must be high in mass and low in metallicity.

Bonamente, Massimiliano↗
NASA NTRS2005

Doclet To Synthesize UML

The RoseDoclet computer program extends the capability of Java doclet software to automatically synthesize Unified Modeling Language (UML) content from Java language source code. [Doclets are Java-language programs that use the doclet application programming interface (API) to specify the content and format of the output of Javadoc. Javadoc is a program, originally designed to generate API documentation from Java source code, now also useful as an extensible engine for processing Java source code.] RoseDoclet takes advantage of Javadoc comments and tags already in the source code to produce a UML model of that code. RoseDoclet applies the doclet API to create a doclet passed to Javadoc. The Javadoc engine applies the doclet to the source code, emitting the output format specified by the doclet. RoseDoclet emits a Rose model file and populates it with fully documented packages, classes, methods, variables, and class diagrams identified in the source code. The way in which UML models are generated can be controlled by use of new Javadoc comment tags that RoseDoclet provides. The advantage of using RoseDoclet is that Javadoc documentation becomes leveraged for two purposes: documenting the as-built API and keeping the design documentation up to date.

Barry, Matthew R.↗
NASA NTRS2010

Simulation of Micron-Sized Debris Populations in Low Earth Orbit

The update of ORDEM2000, the NASA Orbital Debris Engineering Model, to its new version ORDEM2010, is nearly complete. As a part of the ORDEM upgrade, this paper addresses the simulation of micro-debris (greater than 10 m and smaller than 1 mm in size) populations in low Earth orbit. The principal data used in the modeling of the micron-sized debris populations are in-situ hypervelocity impact records, accumulated in post-flight damage surveys on the space-exposed surfaces of returned spacecrafts. The development of the micro-debris model populations follows the general approach to deriving other ORDEM2010-required input populations for various components and types of debris. This paper describes the key elements and major steps in the statistical inference of the ORDEM2010 micro-debris populations. A crucial step is the construction of a degradation/ejecta source model to provide prior information on the micron-sized objects (such as orbital and object-size distributions). Another critical step is to link model populations with data, which is rather involved. It demands detailed information on area-time/directionality for all the space-exposed elements of a shuttle orbiter and damage laws, which relate impact damage with the physical properties of a projectile and impact conditions such as impact angle and velocity. Also needed are model-predicted debris fluxes as a function of object size and impact velocity from all possible directions. In spite of the very limited quantity of the available shuttle impact data, the population-derivation process is satisfactorily stable. Final modeling results obtained from shuttle window and radiator impact data are reasonably convergent and consistent, especially for the debris populations with object-size thresholds at 10 and 100 m.

Xu, Y.-L.↗
NASA NTRS2010

Simulation of Micron-Sized Debris Populations in Low Earth Orbit

The update of ORDEM2000, the NASA Orbital Debris Engineering Model, to its new version . ORDEM2010, is nearly complete. As a part of the ORDEM upgrade, this paper addresses the simulation of micro-debris (greater than 10 micron and smaller than 1 mm in size) populations in low Earth orbit. The principal data used in the modeling of the micron-sized debris populations are in-situ hypervelocity impact records, accumulated in post-flight damage surveys on the space-exposed surfaces of returned spacecrafts. The development of the micro-debris model populations follows the general approach to deriving other ORDEM2010-required input populations for various components and types of debris. This paper describes the key elements and major steps in the statistical inference of the ORDEM2010 micro-debris populations. A crucial step is the construction of a degradation/ejecta source model to provide prior information on the micron-sized objects (such as orbital and object-size distributions). Another critical step is to link model populations with data, which is rather involved. It demands detailed information on area-time/directionality for all the space-exposed elements of a shuttle orbiter and damage laws, which relate impact damage with the physical properties of a projectile and impact conditions such as impact angle and velocity. Also needed are model-predicted debris fluxes as a function of object size and impact velocity from all possible directions. In spite of the very limited quantity of the available shuttle impact data, the population-derivation process is satisfactorily stable. Final modeling results obtained from shuttle window and radiator impact data are reasonably convergent and consistent, especially for the debris populations with object-size thresholds at 10 and 100 micron.

Xu, Y.-L.↗
DOE OSTI2025

Population structure limits the use of genomic data for predicting phenotypes and managing genetic resources in forest trees

There is overwhelming evidence that forest trees are locally adapted to climate. Thus, genecological models based on population phenotypes have been used to measure local adaptation, infer genetic maladaptation to climate, and guide assisted migration. However, instead of phenotypes, there is increasing interest in using genomic data for gene resource management. We used whole-genome resequencing and common-garden experiments to understand the genetic architecture of adaptive traits in black cottonwood. We studied the potential of using genome-wide association studies (GWAS) and genomic prediction to detect causal loci, identify climate-adapted phenotypes, and inform gene resource management. We analyzed population structure by partitioning phenotypic and genomic (single-nucleotide polymorphism) variation among 840 genotypes collected from 91 stands along 16 rivers. Most phenotypic variation (60 to 81%) occurred among populations and was strongly associated with climate. Population phenotypes were predicted well using genomic data (e.g., predictive abilityr> 0.9) but almost as well using climate or geography (r> 0.8). In contrast, genomic prediction within populations was poor (r< 0.2). We identified many GWAS associations among populations, but most appeared to be spurious based on pooled within-population analyses. Hierarchical partitioning of linkage disequilibrium and haplotype sharing suggested that within-population genomic prediction and GWAS were poor because allele frequencies of causal loci and linked markers differed among populations. Given the urgent need to conserve natural populations and ecosystems, our results suggest that climate variables alone can be used to predict population phenotypes, delineate seed zones and deployment zones, and guide assisted migration.

Science & Technology - Other Topics↗
DOE OSTI2024

Modelling the ejection of primary aerosols during the fast pyrolysis of biomass anisotropic particles

A model for the fast pyrolysis of anisotropic biomass particles is presented which considers bubbling dynamics within the liquid intermediate phase (metaplast) and aerosol ejection from this phase. The model employs the population balance equation and the method of moments to estimate the production rate and resultant size distribution of aerosol ejections, incorporating a detailed CRECK reaction mechanism, and considers the effect of anisotropic biomass microstructure on the intraparticle transport of mass and energy. Here, this study investigates the impact of particle size, heating rate (heat transfer coefficient), and lignocellulosic composition on aerosol ejection. The model predicts that, at high heating rates (convective heat transfer coefficient of 359 W/m 2 .K), aerosols can contribute over 20% to the heavy fraction yield in bio-oil for small particles (1 mm diameter, 4 mm length). The model can predict aerosol size distribution and surface area, indicating an average size of 20 μm for bubbles and 5 μm for aerosols during increased bubble production and aerosol ejection rates. These findings are consistent with prior experimental results and provide essential information for future modeling of extra-particle reactions of the aerosols as they progress through the reactor.

09 BIOMASS FUELS↗
NASA NTRS1971

On quasar evolution.

We examine the consequences for quasar statistics of a class of models describing the evolution of individual strong sources. The continuity equation for the change of density and luminosity with cosmological epoch determines the population, once a model for the evolution of an individual object is chosen. A dynamical model of spinning objects seems to agree satisfactorily with the present observational sample, both in density and in luminosity function; such a model requires that an individual object strongly brightens as time goes on. A genetic relationship between quasars and radio galaxies which qualitatively fits the observations is suggested by the model.

Cavaliere, A.↗
NASA NTRS1990

A structure for maturing intelligent tutoring system student models

A special structure is examined for evolving a detached model of the user of an intelligent tutoring system. Tutoring is used in the context of education and training devices. A detached approach to populating the student model data structure is examined in the context of the need for time dependent reasoning about what the student knows about a particular concept in the domain of interest. This approach, to generating a data structure for the student model, allows an inference engine separate from the tutoring strategy determination to be used. This methodology has advantages in environments requiring real-time operation.

Holmes, Willard M.↗
NASA NTRS2005

A model-based executive for commanding robot teams

The paper presents a way to robustly command a system of systems as a single entity. Instead of modeling each component system in isolation and then manually crafting interaction protocols, this approach starts with a model of the collective population as a single system. By compiling the model into separate elements for each component system and utilizing a teamwork model for coordination, it circumvents the complexities of manually crafting robust interaction protocols. The resulting systems are both globally responsive by virtue of a team oriented interaction model and locally responsive by virtue of a distributed approach to model-based fault detection, isolation, and recovery.

domain compilations↗
NASA NTRS2013

Population Pharmacokinetics of Intranasal Scopolamine

Introduction: An intranasal gel dosage formulation of scopolamine (INSCOP) was developed for the treatment of Space Motion Sickness (SMS).The bioavailability and pharmacokinetics (PK) was evaluated using data collected in Phase II IND protocols. We reported earlier statistically significant gender differences in PK parameters of INSCOP at a dose level of 0.4 mg. To identify covariates that influence PK parameters of INSCOP, we examined population covariates of INSCOP PK model for 0.4 mg dose. Methods: Plasma scopolamine concentrations versus time data were collected from 20 normal healthy human subjects (11 male/9 female) after a 0.4 mg dose. Phoenix NLME was employed for PK analysis of these data using gender, body weight and age as covariates for model selection. Model selection was based on a likelihood ratio test on the difference of criteria (-2LL). Statistical significance for base model building and individual covariate analysis was set at P less than 0.05{delta(-2LL)=3.84}. Results: A one-compartment pharmacokinetic model with first-order elimination best described INSCOP concentration ]time profiles. Inclusion of gender, body weight and age as covariates individually significantly reduced -2LL by the cut-off value of 3.84(P less than 0.05) when tested against the base model. After the forward stepwise selection and backward elimination steps, gender was selected to add to the final model which had significant influence on absorption rate constant (ka) and the volume of distribution (V) of INSCOP. Conclusion: A population pharmacokinetic model for INSCOP has been identified and gender was a significant contributing covariate for the final model. The volume of distribution and Ka were significantly higher in males than in females which confirm gender-dependent pharmacokinetics of scopolamine after administration of a 0.4 mg dose.

Wu, L.↗
DOE OSTI2022

Impact of Variable Gas Mixtures on Bubble Size Distribution and Mass Transfer in Gas Fermentation Reactors

Gas fermentation has emerged as a promising new technology for the generation of fuels and chemicals from mixtures of greenhouse and energy rich gas streams (CO2/CH4/H2/CO) via microbial bioreaction. Example pathways include biomethanation (CO2/H2 to CH4), biogas upgrading, CO fermentation and wet-waste conversion. Effective Gas-liquid mass-transfer is an important physical phenomenon that determines the design and scale-up of these systems. There is currently a knowledge-gap regarding bubble-size distributions when using a mixture of gases with vastly different properties, which can have a significant impact on overall mass-transfer. For example, hydrogen bubbles are more buoyant compared to other relatively heavier gases (CO2/CH4/CO), resulting in a large distribution of residence times and bubble sizes. This work therefore develops a deeper understanding of bubble dynamics and interphase mass transfer in such heterogenous gas mixtures through well-resolved computational models. We use a detailed multiphase computational-fluid-dynamics (CFD) model to study the impact of gas-mixtures on overall mass-transfer in bubble column and air-lift reactors. The CFD tool previously developed by the authors (1) for simulating aerobic fermentation reactors at scale is used in this study. The Reynolds-averaged mass, momentum, energy, and species transport equations are solved for interpenetrating gas and liquid phase in this model. We use a population balance-based bubble-size-distribution model that is validated against small-scale experiments in our solver. Results pertaining to multiple simulations of gas-fermentation reactors are presented where gas mixtures with varying compositions of CO2/CH4/CO/H2 are imposed at the sparger boundaries. The spatio-temporal variations in bubble-size distribution and mass transfer coefficient is analyzed for varying superficial velocities and gas-compositions for varying sizes of bubble-column and airlift reactors.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗