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

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Population Genomics of Pseudocercospora griseola Reveals New Groups in the Middle American Clade and the Presence of the Endophytic Bacterium Achromobacter xylosoxidans

Angular leaf spot (ALS), caused by Pseudocercospora griseola is an important disease of common beans. P. griseola, is highly variable and has co-evolved with its host. In this study, 48 isolates of P. griseola from Puerto Rico, Guatemala, Honduras and Tanzania were sequenced (3RADseq), resulting in the de novo assembly of 42,214 contigs. Phylogenomic, population genetic structure and principal component analyses using 1,260 SNPs divided these isolates into two populations, Andean and Middle American, while the Middle American population was further divided into three sub-populations. There were moderate to high levels of differentiation between P. griseola populations, with pairwise Fst values ranging from 0.11 to 0.95. The Andean population was composed of isolates from Tanzania, and was separated from the Middle American population (Fst = 0.95). The Middle American population was separated into 3 subpopulations including isolates from: 1. Guatemala and Honduras, 2. Tanzania, and 3. Puerto Rico. Pathogenicity testing of 27 isolates from Puerto Rico, using 12 common bean differential lines, identified ten races, but these races were not associated with SNPs found in virulence genes. DNA of an endophytic bacterium (Achromobacter xylosoxidans) was found in seven mildly virulent isolates suggesting a possible role of the bacterium in the observed virulence patterns. To understand the evolution and diversity of P. griseola, further study of the virulence genes and the interactions among the endophytic bacterium, the fungus, and the host plant is required. Such information is critical to inform breeding strategies for the development of resistant germplasm and cultivars.

Serrato-Diaz, Luz M. [U.S. Department of Agricultu↗
DOE OSTI2026

Satellite Embedding-Based Population Imputation for Areas with Missing Building Footprint Data: A Computer Vision-Based Approach

High-resolution population modeling is important for supporting effective decision-making across diverse sectors. LandScan Mosaic generates population estimates at the level of individual buildings and aggregates them to 3 arc-second grids, and this approach performs well in regions where building footprint data are comprehensive and reliable. However, large portions of the globe still suffer from incomplete, sparse, or entirely missing building stock datasets, creating a structural limitation for strictly building-based population models. To address this research gap, this study proposes a computer vision-based framework that employs Google Earth Engine satellite embeddings and UNet, which allows us to directly impute grid-level population estimates in building-data-deficient areas. Applied to Taiwan as a case study, the framework achieved strong predictive performance with R$^{2}$ of 0.89, RMSE of 18.70, and MAE of 8.41, outperforming traditional machine learning approaches. Notably, the proposed framework effectively addressed building false-positive errors inherent in Global Human Settlement Layer (GHSL) data, correctly identifying uninhabited areas that were erroneously classified as populated. The framework also offers significant advantages for global population mapping, particularly in terms of scalability and temporal consistency, thereby extending the coverage and accuracy of high-resolution population products in data-scarce regions worldwide. Urban planners, decision makers, and related stakeholders can obtain granular population distributions to support more accurate and targeted infrastructure investment, service delivery, resource allocation, and risk assessment decisions.

97 MATHEMATICS AND COMPUTING↗
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.↗
NASA NTRS2013

NASA Orbital Debris Baseline Populations

The NASA Orbital Debris Program Office has created high fidelity populations of the debris environment. The populations include objects of 1 cm and larger in Low Earth Orbit through Geosynchronous Transfer Orbit. They were designed for the purpose of assisting debris researchers and sensor developers in planning and testing. This environment is derived directly from the newest ORDEM model populations which include a background derived from LEGEND, as well as specific events such as the Chinese ASAT test, the Iridium 33/Cosmos 2251 accidental collision, the RORSAT sodium-potassium droplet releases, and other miscellaneous events. It is the most realistic ODPO debris population to date. In this paper we present the populations in chart form. We describe derivations of the background population and the specific populations added on. We validate our 1 cm and larger Low Earth Orbit population against SSN, Haystack, and HAX radar measurements.

Krisko, Paula H.↗
NASA NTRS2023

Territory and Population Attributes Affect Florida Scrub-Jay Fecundity in Fire Adapted Ecosystems

Fecundity, the number of young produced by a breeding pair during a breeding season, is a primary component in evolutionary and ecological theory and applications. Fecundity can be influenced by many environmental factors and requires long-term study due to the range of variation in ecosystem dynamics. Fecundity data often include a large proportion of zeros when many pairs fail to produce any young during a breeding season due to nest failure or when all young die independently after fledging. We conducted color banding and monthly censuses of Florida scrub-jays (Aphelocoma coerulescens) across 31 years, 15 populations, and 761 territories along central Florida’s Atlantic coast. We quantified how fecundity (juveniles/pair-year) was influenced by habitat quality, presence/absence of nonbreeders, population density, breeder experience, and rainfall, with a zero-inflated Bayesian hierarchical model including both a Bernoulli (e.g., brood success) and a Poisson (counts of young) submodel, and random effects for year, population, and territory. The results identified the importance of increasing “strong” quality habitat, which was a mid-successional state related to fire frequency and extent, because strong territories, and the proportion of strong territories in the overall population, influenced fecundity of breeding pairs. Populations subject to supplementary feeding also had greater fecundity. Territory size, population density, breeder experience, and rainfall surprisingly had no or small effects. Different mechanisms appeared to cause annual variation in fecundity, as estimates of random effects were not correlated between the success and count submodels. The increased fecundity for pairs with nonbreeders, compared to pairs without, identified empirical research needed to understand how the proportion of low-quality habitats influences population recovery and sustainability, because dispersal into low-quality habitats can drain nonbreeders from strong territories and decrease overall fecundity. We also describe how long term study resulted in reversals in our understanding because of complications involving habitat quality, sociobiology, and population density.

Long-term studies↗
DOE OSTI2025

LandScan HD: a high-resolution gridded ambient population methodology for the world

Unwarned population distributions accounting for routine human activities are needed to address many global human security challenges, including disasters, conflict, and infrastructure demand. LandScan High Definition (LSHD) supports this need through gridded ambient population estimates that measure average human presence between daytime and nighttime at a high spatial resolution of 3 arcseconds (approximately 90 m). Although LSHD has traditionally been produced on a country-specific basis, advances in global foundational data and computational resources now enable scaling its methodology to the world. Combining aspects of top-down and bottom-up gridded population methods, LSHD allocates subnational population totals from authoritative statistics to built-up areas based on occupancy estimates for multiple facility types (e.g., residential, commercial) and then reaggregates these estimates to a global population grid. We scale this approach by organizing the LSHD data stack into a 1° resolution tileset of vector analytic features, enabling an efficient and repeatable workflow for all countries worldwide. Examining the Philippines as an output of the global LSHD baseline dataset, we contrast unwarned and residential (WorldPop) population distributions by (1) exploring a practical application of flood risk assessment and (2) evaluating their congruence with outcomes of collective human activities (subnational CO 2 emissions). Finally, we discuss plans to address current LSHD limitations through data/modeling and uncertainty quantification improvements and provide outlook for workflow automation and extending the model to social, demographic and economic population characteristics.

Building morphology↗
DOE OSTI2024

Bacterial population-level trade-offs between drought tolerance and resource acquisition traits impact decomposition

Microbes drive fundamental ecosystem processes, such as decomposition. Environmental stressors are known to affect microbes, their fitness, and the ecosystem functions that they perform; yet, understanding the causal mechanisms behind this influence has been difficult. We used leaf litter on soil surface as a model in situ system to assess changes in bacterial genomic traits and decomposition rates for 18 months with drought as a stressor. We hypothesized that genome-scale trade-offs due to investment in stress tolerance traits under drought reduce the capacity for bacterial populations to carry out decomposition, and that these population-level trade-offs scale up to impact emergent community traits, thereby reducing decomposition rates. We observed drought tolerance mechanisms that were heightened in bacterial populations under drought, identified as higher gene copy numbers in metagenome-assembled genomes. A subset of populations under drought had reduced carbohydrate-active enzyme genes that suggested—as a trade-off—a decline in decomposition capabilities. These trade-offs were driven by community succession and taxonomic shifts as distinct patterns appeared in populations. We show that trait–trade-offs in bacterial populations under drought could scale up to reduce overall decomposition capabilities and litter decay rates. Using a trait-based approach to assess the population ecology of soil bacteria, we demonstrate genome-level trade-offs in response to drought with consequences for decomposition rates.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2021

Population Viability Analysis (PVA) as a Platform for Predicting Outcomes of Management Options for the Florida Scrub-Jay in Brevard County

The Florida scrub-jay (FSJ) is a species in decline because of extinction debt caused by habitat fragmentation and degradation. Understanding and managing the species and its habitats is challenging due to the complex interactions among the social system, a dynamic mosaic of scrub habitat, and active management. To provide insights into the possible fates of the FSJ populations of mainland, cape, and island sections of Brevard County, we modeled the population dynamics using the Vortex population viability analysis (PVA) software. Vortex is an individual-based simulation that allowed us to include such factors as demographic rates dependent on habitat state, impact of helpers on breeding success, and helper to breeder transition probabilities responding to availability of nearby vacant optimal habitat and vacancies due to the death of breeders. Detailed modeling of the FSJ was possible only because a lot of data about the species and its habitats have been gathered over decades of intensive research. We followed a phased approach to constructing population models that incorporated the best available science and data to address a variety of conservation actions. The first phase focused on constructing a model that incorporates sociobiology and source-sink habitat dynamics. This model allowed us to address some of the most important questions about population size and habitat quality. Once the model framework was in place, we considered the real landscapes and actual local populations, rather than just generic representations of typical FSJ dynamics. After examining the viability of the metapopulations under current conditions, we explored the likely consequences of various management actions that might slow or reverse population declines.

Population Viability Analysis↗
NASA NTRS2023

Marsh Archive Reveals Human Population History and Future Implications for Estuarine Health in Long Island Sound

Coastal marshes are efficient ecosystems providing a multitude of benefits for invertebrates, birds, fish and humans alike. Yet despite these benefits, wetlands are threatened by anthropogenic inputs such as human wastewater which contain high levels of nitrogen (N). Increased nitrogen loads cause eutrophication and hypoxia in estuaries leading to further degradation of these valuable ecosystems that are already stressed by sea level rise and climate change. Policies to protect wetlands via wastewater treatments are reactive rather than proactive and a growing body of research shows that characteristics associated with population health and economic activity can be identified in wastewater. Analysis of a 2-m salt marsh sediment core reveals δN15 signatures indicative of human population rise and connects human impact to ecosystem health. Using key X-ray fluorescence (XRF), pollen, sediment and nitrogen signatures along the core, a robust chronology was produced dating back to 1700. This result was coupled with population data to observe the relationship between δN15 levels and population over three centuries. There is a statistically significant positive correlation between δN15 and population. Other external factors such as federal government policies (regulating clean water) show a clear reduction in this association but the use of synthetic nitrogen fertilizer masks the strength of this relationship. Further research to refine the relationship between population and δN15 could be beneficial in predicting nitrogen loads as human population grows, which in turn would create a proactive system to protect our coastal ecosystems.

Nitrogen↗
DOE OSTI2025

State-level suicide mortality insights: a comparative study of VHA veterans and the whole US population

Background: Suicide is a leading cause of death in the US Comparative State-level spatial analysis between Veterans Health Administration (VHA veterans) and the whole US population can reveal differences in conditions for targeted interventions and intricate geographical patterns. Methods: The study population contains 2018 and 2019 suicide deaths of VHA veterans and the whole US population. They were used to calculate state-level rates. States were classified by whether their VHA veteran and whole US population rates were above or below respective mean rates. Local Moran’s I was leveraged to examine spatial autocorrelation. Results: State-level suicide mortality rates and disparities among states were generally higher for VHA veterans (2018: 37.3 ± 7.2; 2019: 46.8 ± 8.3) than for the whole US population (2018: 16.6 ± 4.3; 2019: 16.4 ± 4.4). For both populations, there were statistically significant clusters with high suicide rates. Over one-fourth of states demonstrated inverse relationships, with rates above mean for one group but below for other. VHA veterans are at higher risk with over one-third of states had greater than average veteran suicide risk ratio. Conclusions: VHA veterans are at higher risk than the whole population across all states. Mortality disparities among states and clusters of states with high and low rates suggest targeted interventions and cooperative health strategies may help address these differences.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Intra- and inter-subtype HIV diversity between 1994 and 2018 in southern Uganda: a longitudinal population-based study

There is limited data on human immunodeficiency virus (HIV) evolutionary trends in African populations. We evaluated changes in HIV viral diversity and genetic divergence in southern Uganda over a 24-year period spanning the introduction and scale-up of HIV prevention and treatment programs using HIV sequence and survey data from the Rakai Community Cohort Study, an open longitudinal population-based HIV surveillance cohort. Gag (p24) and env (gp41) HIV data were generated from people living with HIV (PLHIV) in 31 inland semi-urban trading and agrarian communities (1994–2018) and four hyperendemic Lake Victoria fishing communities (2011–2018) under continuous surveillance. HIV subtype was assigned using the Recombination Identification Program with phylogenetic confirmation. Inter-subtype diversity was evaluated using the Shannon diversity index, and intra-subtype diversity with the nucleotide diversity and pairwise TN93 genetic distance. Genetic divergence was measured using root-to-tip distance and pairwise TN93 genetic distance analyses. Demographic history of HIV was inferred using a coalescent-based Bayesian Skygrid model. Evolutionary dynamics were assessed among demographic and behavioral population subgroups, including by migration status. 9931 HIV sequences were available from 4999 PLHIV, including 3060 and 1939 persons residing in inland and fishing communities, respectively. In inland communities, subtype A1 viruses proportionately increased from 14.3% in 1995 to 25.9% in 2017 (P < .001), while those of subtype D declined from 73.2% in 1995 to 28.2% in 2017 (P < .001). The proportion of viruses classified as recombinants significantly increased by nearly four-fold from 12.2% in 1995 to 44.8% in 2017. Inter-subtype HIV diversity has generally increased. While intra-subtype p24 genetic diversity and divergence leveled off after 2014, intra-subtype gp41 diversity, effective population size, and divergence increased through 2017. Intra- and inter-subtype viral diversity increased across all demographic and behavioral population subgroups, including among individuals with no recent migration history or extra-community sexual partners. This study provides insights into population-level HIV evolutionary dynamics following the scale-up of HIV prevention and treatment programs. Continued molecular surveillance may provide a better understanding of the dynamics driving population HIV evolution and yield important insights for epidemic control and vaccine development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

At Risk Population Estimates for Belarus, Poland and Slovakia with Machine Learning

High-resolution gridded population modeling is crucial for various applications, including disaster response planning, infectious disease spread modeling, climate change impact estimation, policy development, and more. Multiple gridded population datasets have been developed, each tailored to meet specific objectives. Among them, LandScan Global dataset is designed to represent ambient and unwarned population distributions. However, this dataset relies on a statistical approach that requires manual adjustments, making it time consuming and labour intensive. Existing machine learning (ML) methods often train and test at different spatial resolutions, potentially leading to inflated results, and they rely on Census population totals for disaggregation. To address these limitations, in this study we developed population estimates using ML models trained and tested at a consistent 30 arc-second resolution (≈1 square kilometer), specifically using Random Forest (RF) and XGBoost. These models were trained on 2020 datum to predict for 2021 for three countries: Belarus, Poland, and Slovakia. Our findings show that both RF (MAE varies from 5.75 to 13.25) and XGBoost (MAE varies from 8.15 to 23.44) model performance is close to LandScan Global estimates. Furthermore, neither of the models performed the best across all grid cells: the RF model was more effective in areas with lower populations, while XGBoost excelled in more densely populated regions. The proposed approach can be used for countries where the Census data is not available.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗
DOE OSTI2026

LandCast Mosaic: Reconstructing Global Population Distributions, 1975-2025

LandCast Mosaic (LCM) provides a global, high-resolution gridded population dataset spanning 1975–2025, representing annual, scenario-consistent estimates of daytime, nighttime, and ambient population distributions. LCM builds on the 2025 LandScan Mosaic (LSM) population data by backcasting to earlier years using historical changes in built-surface area derived from the Global Human Settlement Layer (GHSL) and authoritative population counts from international datasets. The workflow scales 2025 building-informed gridded population estimates according to observed changes in built surface, applies linear interpolation for intermediate years, and normalizes estimates to match administrative- and country-level totals. The resulting dataset offers consistent, globally gridded population estimates over fifty years, suitable for temporal analyses of population dynamics, disaster risk modeling, and urban planning applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Producing High-fidelity Synthetic Population Ensembles at Scale

Used within social simulations, synthetic population ensembles enable uncertainty quantification (UQ) methods for obtaining more robust model inference and prediction. A synthetic population ensemble is a series of plausible virtual reconstructions of an area’s population at the granularity of people and residences, generated stochastically to preserve privacy of the source population survey’s respondents. In this paper, we demonstrate the production of large synthetic population ensembles for the US via Oak Ridge National Laboratory’s UrbanPop framework to support modeling of high spatial resolution energy affordability metrics from nationwide social surveys in collaboration with the fusionACS project. Our initial task involves creating ensembles for 17 US metropolitan areas, each consisting of 41 population instances (a base realization and 40 replicates). To accomplish this task at scale, we configured an integrated system comprised of a research cloud, virtual containerization, GPU-enhanced functionality, and a dual API/CLI to interact with UrbanPop’s maturing Likeness Python ecosystem. We observe a reduction in theoretical execution time while maintaining high-fidelity approximations of residential totals by metropolitan area and the demographic characteristics of neighborhoods. We discuss expansion of our approach to produce synthetic population ensembles for the entire US, particularly plans to establish automated workflows for job orchestration to increase computational efficiency, as well as provide outlook for broadening applications of the ensembles.

Gaboardi, James [ORNL] (ORCID:0000000247766826)↗
NASA NTRS1979

Analysis of population mortality kinetics with application to the longevity followup of the Navy's '1,000 aviators'

A simple physiological model of mortality kinetics is used to assess the intuitive concept that the aging rates of populations are proportional to their mortality rates. It is assumed that the vitality of an individual can be expressed as a simple summation of the weighted functional capacities of its organs and homeostatic systems that are indispensable for survival. It is shown that the mortality kinetics of a population can be derived by a linear transformation of the frequency distribution of vitality, assuming a uniform constant rate of decline of the physiological functions. A simple comparison of two populations is not possible when they have different vitality frequency distributions. Analysis of the data using the model suggests that the differences in decline of survivorship with age between the military pilot population, a medically insured population, and the control population can be accounted for by the effect of physical selection on the vitality frequency distribution of the screened populations.

Economos, A. C.↗
NASA NTRS1993

Adaptively resizing populations: Algorithm, analysis, and first results

Deciding on an appropriate population size for a given Genetic Algorithm (GA) application can often be critical to the algorithm's success. Too small, and the GA can fall victim to sampling error, affecting the efficacy of its search. Too large, and the GA wastes computational resources. Although advice exists for sizing GA populations, much of this advice involves theoretical aspects that are not accessible to the novice user. An algorithm for adaptively resizing GA populations is suggested. This algorithm is based on recent theoretical developments that relate population size to schema fitness variance. The suggested algorithm is developed theoretically, and simulated with expected value equations. The algorithm is then tested on a problem where population sizing can mislead the GA. The work presented suggests that the population sizing algorithm may be a viable way to eliminate the population sizing decision from the application of GA's.

Smith, Robert E.↗
NASA NTRS1998

Beta-Adrenergic Receptor Population is Up-Regulated in Chicken Skeletal Muscle Cells Treated with Forskolin

Skeletal muscle hypertrophy is promoted by in vivo administration of beta-adrenergic receptor (betaAR) agonists. These compounds presumably exert their physiological action through the betaAR, and alterations in the population of betaAR could potentially change the ability of the cell to respond to the betaAR agonists. Since the intracellular chemical signal generated by the betaAR is cyclic AMP (cAMP), experiments were initiated in primary chicken muscle cell cultures to determine if artificial elevation of intracellular cAMP by treatment with forskolin would alter the population of functional betaAR expressed on the surface of muscle cells. Chicken skeletal muscle cells after 7 days in culture were employed for the experiments because muscle cells have attained a steady state with respect to muscle protein metabolism at this stage. Cells were treated with 0-10 microM forskolin for a total of three days. At the end of the 1, 2, and 3 day treatment intervals, the concentration of cAMP and the betaAR population were measured. Receptor population was measured in intact muscle cell cultures as the difference between total binding of [H-3]CGP-12177 and non-specific binding of [H-3]CGP-12177 in the presence of 1 microM propranolol. Intracellular cAMP concentration was measured by radioimmunoassay. The concentration of cAMP in forskolin-treated cells increased up to 10-fold in a dose dependent manner. Increasing concentrations of forskolin also led to an increase in betaAR population, with a maximum increase of approximately 50% at 10 microM. This increase in PAR population was apparent after only 1 day of treatment, and the pattern of increase was maintained for all 3 days of the treatment period. Thus, increasing the intracellular concentration of cAMP leads to up-regulation of betaAR population. The effect of forskolin on the quantity and apparent synthesis rate of the heavy chain of myosin (mhc) were also investigated. A maximum increase of 50% in the quantity of mhc was observed at 0.2 microM forskolin, but higher concentrations of forskolin reduced the quantity of mhc back to control levels.

Bridge, K. Y.↗