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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Population Count on Intel® CPU, GPU, and FPGA

Population count is a primitive used in many applications. Commodity processors have dedicated instructions for achieving high-performance population count. Motivated by the productivity of high-level synthesis and the importance of population count, in this paper we investigated the OpenCL implementations of population count algorithms, and evaluated their performance and resource utilizations on an FPGA. Based on the results, we select the most efficient implementation. Then we derived a reduction pattern from a representative application of population count. We parallelized the reduction with atomic functions, and optimized it with vectorized memory accesses, tree reduction, and compute-unit duplication. We evaluated the performance of the reduction kernel on an Intel (R) Xeon (R) CPU and an Intel (R) IrisT Pro integrated GPU, and an FPGA card that features an Intel (R) Arria (R) 10 FPGA. When DRAM memory bandwidth is comparable on the three computing platforms, the FPGA can achieve the highest kernel performance for large workload. On the other hand, we described performance bottlenecks on the FPGA. To make FPGAs more competitive in raw performance compared to high-performant CPU and GPU platforms, it is important to increase external memory bandwidth, minimize data movement between a host and a device, and reduce OpenCL runtime overhead on an FPGA.

heterogeneous computing↗
DOE OSTI2022

A Comparison of Infectious Disease Forecasting Methods across Locations, Diseases, and Time

Accurate infectious disease forecasting can inform efforts to prevent outbreaks and mitigate adverse impacts. This study compares the performance of statistical, machine learning (ML), and deep learning (DL) approaches in forecasting infectious disease incidences across different countries and time intervals. We forecasted three diverse diseases: campylobacteriosis, typhoid, and Q-fever, using a wide variety of features (n = 46) from public datasets, e.g., landscape, climate, and socioeconomic factors. We compared autoregressive statistical models to two tree-based ML models (extreme gradient boosted trees [XGB] and random forest [RF]) and two DL models (multi-layer perceptron and encoder–decoder model). The disease models were trained on data from seven different countries at the region-level between 2009–2017. Forecasting performance of all models was assessed using mean absolute error, root mean square error, and Poisson deviance across Australia, Israel, and the United States for the months of January through August of 2018. The overall model results were compared across diseases as well as various data splits, including country, regions with highest and lowest cases, and the forecasted months out (i.e., nowcasting, short-term, and long-term forecasting). Overall, the XGB models performed the best for all diseases and, in general, tree-based ML models performed the best when looking at data splits. There were a few instances where the statistical or DL models had minutely smaller error metrics for specific subsets of typhoid, which is a disease with very low case counts. Feature importance per disease was measured by using four tree-based ML models (i.e., XGB and RF with and without region name as a feature). The most important feature groups included previous case counts, region name, population counts and density, mortality causes of neonatal to under 5 years of age, sanitation factors, and elevation. This study demonstrates the power of ML approaches to incorporate a wide range of factors to forecast various diseases, regardless of location, more accurately than traditional statistical approaches.

59 BASIC BIOLOGICAL SCIENCES↗
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↗
NASA NTRS2017

Improving Estimation of Ground Casualty Risk From Reentering Space Objects

A recent improvement to the long-term estimation of ground casualties from reentering space debris is the further refinement and update to the human population distribution. Previous human population distributions were based on global totals with simple scaling factors for future years, or a coarse grid of population counts in a subset of the world's countries, each cell having its own projected growth rate. The newest population model includes a 5-fold refinement in both latitude and longitude resolution. All areas along a single latitude are combined to form a global population distribution as a function of latitude, creating a more accurate population estimation based on non-uniform growth at the country and area levels. Previous risk probability calculations used simplifying assumptions that did not account for the ellipsoidal nature of the Earth. The new method uses first, a simple analytical method to estimate the amount of time spent above each latitude band for a debris object with a given orbit inclination and second, a more complex numerical method that incorporates the effects of a non-spherical Earth. These new results are compared with the prior models to assess the magnitude of the effects on reentry casualty risk.

Ostrom, Chris L.↗
NASA NTRS2017

Improving Estimation of Ground Casualty Risk from Reentering Space Objects

A recent improvement to the long-term estimation of ground casualties from reentering space debris is the further refinement and update to the human population distribution. Previous human population distributions were based on global totals with simple scaling factors for future years, or a coarse grid of population counts in a subset of the world's countries, each cell having its own projected growth rate. The newest population model includes a 5-fold refinement in both latitude and longitude resolution. All areas along a single latitude are combined to form a global population distribution as a function of latitude, creating a more accurate population estimation based on non-uniform growth at the country and area levels. Previous risk probability calculations used simplifying assumptions that did not account for the ellipsoidal nature of the earth. The new method uses first, a simple analytical method to estimate the amount of time spent above each latitude band for a debris object with a given orbit inclination, and second, a more complex numerical method that incorporates the effects of a non-spherical Earth. These new results are compared with the prior models to assess the magnitude of the effects on reentry casualty risk.

Ostrom, C.↗
DOE OSTI2026

Synthesizing land use and demographic change in Southeast Asia’s smaller urbanized areas from 2000–2015

The majority of the human population now reside in urban areas today. The United Nations estimates that nearly half of all urban dwellers currently live in cities smaller than 500 000 persons and the majority of future urban growth will take place in Asia and Africa, likely in these smaller urban areas, not mega cities. Thus, understanding the factors that influence urban demographic trajectories in small urban areas is critical to address sustainable and equitable policy initiatives related to food security, changing climate hazard exposure, and economic opportunities. Here we focus on Southeast Asia—a region historically characterized by lower urban population proportions, yet with a rapidly shifting dynamic demographic—to examine correlates of demographic change among smaller cities. We combine two open-source satellite-informed datasets: GHS urban center database (2015) and age-sex gridded data from WorldPop to calculate socio-demographic characteristics to model drivers of change in annualized urban population growth from 2000–2015 for 505 urbanized places. We find a general pattern of decreasing dependency ratios as city-size increases for most urban areas in Southeast Asia. Higher rates of growth and more variation is observed for smaller cities—those with fewer than 300 000 persons, the lowest population limit for UN data on urbanization. When examining covariates of urban population growth, we find significant statistical associations of population change in smaller urbanized areas with climatic, economic, and land cover/land use variables, but with country-specific variations. Characterizing a continuum of urban population development in the context of changing environmental, economic and climate conditions has been an important sustainable development and equity issue for decades, but newer analysis of city-level drivers allows for systematic inquiry thus moving beyond total population counts for policy-relevant insight.

Southeast Asia synthesis↗
DOE OSTI2020

SIGNAL Game Manual

SIGNAL is a first of its kind experimental wargame developed as part of the Project on Nuclear Gaming (PoNG). In this document we describe the rules and game mechanics associated with the online version of SIGNAL created by team members from the University of California, Berkeley, Sandia National Laboratories, and Lawrence Livermore National Laboratory and sponsored by the Carnegie Corporation of New York. The game was developed as part of a larger research project to develop the experimental wargaming methodology and explore its use on a model scenario: the impact of various military capabilities on conflict escalation dynamics. We discuss the results of this research in a forthcoming paper that will include this manual as an appendix. It is our hope that this manual will both contribute to our players' understanding of the game prior to play and that it will allow for replication of the SIGNAL game environment for future research purposes. The manual begins by introducing the terminology used throughout the document. It then outlines the technical requirements required to run SIGNAL. The following section provides a description of the map, resources, infrastructure, tokens, and action cards used in the game environment. The manual then describes the user interface including the chat functions, trade mechanism, currency and population counts necessary for players to plan their actions. It then turns to the sequence of player actions in the game describing the signaling, action, and upkeep phases that comprise each round of play. It then outlines the use of diplomacy including alliances with minor states and trade between players. The manual also describes the process for scoring the game and determining the winner. The manual concludes with tips for players to remember as they embark upon playing the game.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Spatio-temporal Estimates of Disease Transmission Parameters for COVID-19 with a Fully-Coupled, County-Level Model of the United States

Sandia National Laboratories has developed a capability to estimate parameters of epidemiological models from case reporting data to support responses to the COVID-19 pandemic. A differentiating feature of this work is the ability to simultaneously estimate county-specific disease transmission parameters in a nation-wide model that considers mobility between counties. The approach is focused on estimating parameters in a stochastic SEIR model that considers mobility between model patches (i.e., counties) as well as additional infectious compartments. The inference engine developed by Sandia includes (1) reconstruction and (2) transmission parameter inference. Reconstruction involves estimating current population counts within each of the compartments in a modified SEIR model from reported case data. Reconstruction produces input for the inference formulations, and it provides initial conditions that can be used in other modeling and planning efforts. Inference involves the solution of a large-scale optimization problem to estimate the time profiles for the transmission parameters in each county. These provide quantification of changes in the transmission parameter over time (e.g., due to impact of intervention strategies). This capability has been implemented in a Python-based software package, epi_inference, that makes extensive use of Pyomo [5] and IPOPT [10] to formulate and solve the inference formulations.

42 ENGINEERING↗
NASA NTRS1981

The nature of compensatory and restorative processes in the livers of animals irradiated during hypokinesia

The nature of postirradiation repair in the livers of rats irradiated during hypokinesia is investigated. Hepatocyte population counts, mitotic activity, binuclear cell content, and karyometric studies were done to ascertain the effects of combined hypokinesia and radiation. Hypokinesia is shown to change the nature and rate of post-irradiation changes in the liver, the effect varying with the timing of irradiation relative to the length of hypokinesia. It is concluded that the changes in the compensatory and restorative processes are caused by stress developed in response to isolation and restricted mobility. By changing neuroendocrine system activity, the stress stimulates cell and tissue repair mechanisms at a certain stage essential to the body's reaction of subsequent irradiation.

Chernov, I. P.↗
NASA NTRS1979

Airborne surveys of USA urban areas at 121.5/243 MHz

In situ, aircraft flight measurements were made in 1976 and 1977 by NASA of the radio-frequency environment over USA urban areas within the emergency distress search and rescue frequency bands at 121.5 and 243.0 MHz. This paper analyzes test results reported previously for USA East Coast and Midwest flight surveys; presented also are test results obtained in May 1977 for the USA West Coast during the NASA, ASSESS-II, Space Shuttle/Spacelab simulation aircraft flights. The USA West Coast flight include data at 121.5/243 MHz during an extensive series of aircraft passes for the Los Angeles urban area. The USA East Coast/Midwest measurements show correlation with population count.

Taylor, R. E.↗
NASA NTRS1996

Microbial Diffraction Gratings as Optical Detectors for Heavy Metal Pollutants

As a significant industrial pollutant, cadmium is implicated as the cause of itai-itai disease. For biological detection of cadmium toxicity, an assay device has been developed using the motile response of the protozoa species, Tetrahymena pyriformis. This mobile protozoa measures 50 microns in diameter, swims at 10 body lengths per second, and aggregates into macroscopically visible patterns at high organism concentrations. The assay demonstrates a Cd(+2) sensitivity better than 1 micro-M and a toxicity threshold to 5 micro-M, thus encouraging the study of these microbial cultures as viable pollution detectors. Using two-dimensional diffraction patterns within a Tetrahymena culture, the scattered light intensity varies with different organism densities (population counts). The resulting density profile correlates strongly with the toxic effects at very low dosages for cadmium (less than 5 ppm) and then for poison protection directly (with nickel and copper antagonists competing with cadmium absorption). In particular, copper dosages as low as 0.1-0.5 mM Cu have shown protective antagonism against cadmium, have enhanced density variability for cultures containing 1 mM Cd(+2) and therefore have demonstrated the sensitivity of the optical detection system. In this way, such microbial diffraction patterns give a responsive optical measure of biological culture changes and toxicity determination in aqueous samples of heavy metals and industrial pollutants.

Noever, David↗
NASA NTRS2014

Climate Change and Vector Borne Diseases on NASA Langley Research Center

Increasing global temperature, weather patterns with above average storm intensities, and higher sea levels have been identified as phenomena associated with global climate change. As a causal system, climate change could contribute to vector borne diseases in humans. Vectors of concern originate from the vicinity of Langley Research Center include mosquitos and ticks that transmit disease that originate regionally, nationwide, or from outside the US. Recognizing changing conditions, vector borne diseases propagate under climate change conditions, and understanding the conditions in which they may exist or propagate, presents opportunities for monitoring their progress and mitigating their potential impacts through communication, continued monitoring, and adaptation. Personnel comprise a direct and fundamental support to NASA mission success, continuous and improved understanding of climatic conditions, and the resulting consequence of disease from these conditions, helps to reduce risk in terrestrial space technologies, ground operations, and space research. This research addresses conditions which are attributed to climatic conditions which promote environmental conditions conducive to the increase of disease vectors. This investigation includes evaluation of local mosquito population count and rainfall data for statistical correlation and identification of planning recommendations unique to LaRC, other NASA Centers to assess adaptation approaches, Center-level planning strategies.

Cole, Stuart K.↗
DOE OSTI2025

Terra-Populus v0.1: A Python Library for LandScan High-Definition Population Analysis and Modeling

The terra-populus library is designed for use by the LandScan HD technical team, offering a streamlined set of tools for generating and updating LandScan HD datasets from foundational building-level data, referred to as 'molecules,' provided by the building-level attribution team. This document serves as the primary technical documentation for terra-populus. Version 0.1 of the library includes the core modeling components necessary for LandScan HD production. It enables the generation of the LandScan HD Baseline dataset as well as corresponding confidence measures for the occupancy rates used. Parameters have been included for incorporating damaged building indicators and changes in population, to faciliate the creation of rapid updates for LandScan HD. Future iterations of terra-populus will introduce tools for creating a confidence index, and quantifying and propagating uncertainty, facilitating the creation of probabilistic LandScan HD outputs. This report provides an overview of the tools available in the library and the corresponding code implementations. One of the key advancements implemented in terra-populus is a redefinition of the atomic modeling unit for LandScan HD. Traditionally, the LandScan HD vector analytical framework has generated population estimates at the building sub-component (molecule) level. However, terra-populus adopts a building-level modeling approach. This shift is an operational decision aimed at aligning LandScan HD outputs with confidence measures, which are computed and validated at the building level (confidence measures are not included in this version of terra-populus, aside from those associated with the occupancy rates). Additional advancements to the LandScan HD modeling, as implemented by terra-populus, include a minimum population value parameter and an auto assignment of building floor counts. The population minimum value was implemented to prevent buildings and subsequent LandScan HD pixels that contained small values that may not rasterize in production. An 'auto' value has been included as a method for dealing with buildings lacking floor count information, where it is the average floor count of all other buildings with a residential building use type tag. The logic behind this is to remain consistent with the current logic employed for dealing with building use type null instances, where a null use type is defaulted to residential since it is the most common building type. The auto logic is intended to apply the most common building floor count of the most common type of buildings. The tools provided in terra-populus represent a significant step forward in improving the efficiency, reproducibility, and transparency of the LandScan HD modeling process. As the library evolves, it will continue to serve as a foundational resource for high-resolution population modeling.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1994

The luminosity function for different morphological types in the CfA Redshift Survey

We derive the luminosity function for different morphological types in the original CfA Redshift Survey (CfA1) and in the first two slices of the CfA Redshift Survey Extension (CfA2). CfA1 is a complete sample containing 2397 galaxies distributed over 2.7 steradians with m(sub z) less than or equal 14.5. The first two complete slices of CfA2 contain 1862 galaxies distributed over 0.42 steradians with m(sub z)=15.5. The shapes of the E-S0 and spiral luminosity functions (LF) are indistinguishable. We do not confirm the steeply decreasing faint end in the E-S0 luminosity function found by Loveday et al. for an independent sample in the southern hemisphere. We demonstrate that incomplete classification in deep redshift surveys can lead to underestimates of the faint end of the elliptical luminosity function and could be partially responsible for the difference between the CfA survey and other local field surveys. The faint end of the LF for the Magellanic spirals and irregulars is very steep. The Sm-Im luminosity function is well fit by a Schechter function with M*=-18.79, alpha=-1.87, and phi*=0.6x10(exp -3) for M(sub z) less than or equal to -13. These galaxies are largely responsible for the excess at the faint end of the general CfA luminosity function. The abundance of intrinsically faint, blue galaxies nearby affects the interpretation of deep number counts. The dwarf population increases the expected counts at B=25 in a no-evolution, q(sub 0)=0.05 model by a factor of two over standard no-evolution estimates. These dwarfs change the expected median redshift in deep redshift surveys by less than 10 percent . Thus the steep Sm-Im LF may contribute to the reconciliation of deep number counts with deep redshift surveys.

Marzke, Ronald O.↗
DOE OSTI2020

A Search for Neutrino Point-source Populations in 7 yr of IceCube Data with Neutrino-count Statistics

The presence of a population of point sources in a data set modifies the underlying neutrino-count statistics from the Poisson distribution. This deviation can be exactly quantified using the non-Poissonian template fitting technique, and in this work we present the first application of this approach to the IceCube high-energy neutrino data set. Using this method, we search in 7 yr of IceCube data for point-source populations correlated with the disk of the Milky Way, the Fermi bubbles, the Schlegel, Finkbeiner, and Davis dust map, or with the isotropic extragalactic sky. No evidence for such a population is found in the data using this technique, and in the absence of a signal, we establish constraints on population models with source-count distribution functions that can be described by a power law with a single break. Here, the derived limits can be interpreted in the context of many possible source classes. In order to enhance the flexibility of the results, we publish the full posterior from our analysis, which can be used to establish limits on specific population models that would contribute to the observed IceCube neutrino flux.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2003

ATP as a biomarker of viable microorganisms in clean-room facilities

A new firefly luciferase bioluminescence assay method that differentiates free extracellular ATP (dead cells, etc.) from intracellular ATP (viable microbes) was used to determine the viable microbial cleanliness of various clean-room facilities. For comparison, samples were taken from both clean-rooms, where the air was filtered to remove particles >0.5 microm, and ordinary rooms with unfiltered air. The intracellular ATP was determined after enzymatically degrading the sample's free ATP. Also for comparison, cultivable microbial populations were counted on nutrient-rich trypticase soy agar (TSA) plates. Both the cultivable and ATP-based determinations indicate that the microbial burden was lower in clean-room facilities than in ordinary rooms. However, there was no direct correlation between the two sets of measurements because the two assays measured very different populations. A large fraction of the samples yielded no colony formers on TSA, but were positive for intracellular ATP. Subsequently, genomic DNA was isolated directly from selected samples and 16S rDNA fragments were cloned and sequenced, identifying nearest neighbors, many of which are known to be noncultivable in the media employed. It was concluded that viable microbial contamination can be reliably monitored by measurement of intracellular ATP, and that this method may be considered superior to cultivable colony counts due to its speed and its ability to report the presence of viable but noncultivable organisms. When the detection of nonviable microbes is of interest, the ATP assay can be supplemented with DNA analysis.

NASA Discipline Environmental Health↗
DOE OSTI2025

Axenisation of oleaginous microalgal cultures via anoxic photosensitisation

Growing interest in sustainable food and biofuel research has necessitated high quality axenic oleaginous microalgal strains. Unfortunately, most strains available in culture banks contain commensal microbes such as bacteria and the default decontamination method involves antibiotic treatment which has begun to exacerbate the emergence of antibiotic resistance. To overcome this problem, anoxic photosensitisation was investigated as an alternate approach. Four oleaginous microalgal species (Tetradesmus obliquus, Desmodesmus armatus, Chlorella vulgaris and Nannochloropsis limnetica) were incubated in varying concentrations of Rose Bengal (0 μM, 1 μM, 3 μM or 9 μM) either in normal (oxic) or anoxic conditions, for 72 h under light (8.85 ± 0.4 W/m 2 ) in a specially designed heterotrophic growth complex (HGC) medium, followed by 72 h in standard Bold's Basal Medium (BBM). Commonly used antibiotics-based protocol was used as the control method. Post treatment, cell numbers and percentage populations were counted with Flow Cytometry, and viability was tested using standard plating methods using BBM and LB. Additionally, the contaminating microbes in the cultures were profiled using 16Ss rRNA sequencing. Anoxic conditions were able to significantly decrease bacterial content, albeit with an equally detrimental effect on the microalgal population. Although the responses differed between the microalgae, anoxic incubation along with Rose Bengal at 3 μM was able to completely decontaminate N. limnetica and C. vulgaris, while D. armatus and T. obliquus could be decontaminated with an additional streak-plating step. None of the cultures could be decontaminated using antibiotics treatment. These results suggest that axenisation of microalgal cultures was largely due to anoxy, that was synergistically enhanced by Rose Bengal at a concentration of ≥3 μM.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2002

Ion Storage Tests with the High Performance Antimatter Trap (HiPAT)

The NASA/Marshall Space Flight Centers (NASA/MSFC) Propulsion Research Center (PRC) is evaluating an antiproton storage system, referred to as the High Performance Antiproton Trap (HiPAT). This interest stems from the sheer energy represented by matter/antimatter annihilation process with has an energy density approximately 10 order of magnitude above that of chemical propellants. In other terms, one gram of antiprotons contains the equivalent energy of approximately 23 space shuttle external tanks or ET's (each ET contains roughly 740,000 kgs of fuel and oxidizer). This incredible source of stored energy, if harnessed, would be an enabling technology for deep space mission where both spacecraft weight and propulsion performance are key to satisfying aggressive mission requirements. The HiPAT hardware consists of a 4 Tesla superconductor system, an ultra high vacuum test section (vacuum approaching 10(exp -12) torr), and a high voltage confinement electrode system (up to 20 kvolts operation). The current laboratory layout is illustrated. The HiPAT designed objectives included storage of up to 1 trillion antiprotons with corresponding lifetimes approaching 18 days. To date, testing has centered on the storage of positive hydrogen ions produced in situ by a stream of high-energy electrons that passes through the trapping region. However, due to space charge issues and electron beam compression as it passes through the HiPAT central field, current ion production is limited to less then 50,000 ions. Ion lifetime was determined by counting particle populations at the end of various storage time intervals. Particle detection was accomplished by destructively expelling the ions against a micro-channel plate located just outside the traps magnetic field. The effect of radio frequency (RF) stabilization on the lifetime of trapped particles was also examined. This technique, referred to as a rotating wall, made use of a segmented electrode located near the center of the trap on which various phases of a particular frequency were applied. Various experiments were performed illustrating the ability of an RF drive to both prolong and reduced the lifetimes of various ion species depending on the selected frequency. HiPAT is now being reconfigured for testing with an ion source that will provide both positive and negative hydrogen ions from an external source. This ion system shall provide higher fill capacity (order of million of ions per shot), stacking of multiple shots, and injection schemes typical of a realistic antiproton delivery system.

Martin, James J.↗