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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Temporal dynamics of emergency department and hospital admissions of pediatric asthmatics

Asthma is a chronic disease that can result in exacerbations leading to urgent care in emergency departments (EDs) and hospitals. We examined seasonal and temporal trends in pediatric asthma ED (1997-1999) and hospital (1986-1999) admission data so as to identify periods of increased risk of urgent care by age group, gender, and race. All pediatric ED and hospital admission data for Maryland residents occurring within the state of Maryland were evaluated. Distinct peaks in pediatric ED and hospital asthma admissions occurred each year during the winter-spring and autumn seasons. Although the number and timing of these peaks were consistent across age and racial groups, the magnitude of the peaks differed by age and race. The same number, timing, and relative magnitude of the major peaks in asthma admissions occurred statewide, implying that the variables affecting these seasonal patterns of acute asthma exacerbations occur statewide. Similar gross seasonal trends are observed worldwide. Although several environmental, infectious, and psychosocial factors have been linked with increases in asthma exacerbations among children, thus far they have not explained these seasonal patterns of admissions. The striking temporal patterns of pediatric asthma admissions within Maryland, as described here, provide valuable information in the search for causes.

Emergency Treatment/utilization↗
DOE OSTI2023

Influence of liquid conductance on the temporal evolution of self-organization patterns in atmospheric pressure DC glow discharges

Abstract Self-Organized Patterns (SOPs) at plasma-liquid interface in atmospheric pressure plasma discharges refer to the formation of intricate and puzzling structures due to the interplay of electrodynamic and hydrodynamic processes. Studies conducted to date have shown that this phenomenon results in the formation of distinctive patterns such as circular ring, star, gear, dots, spikes, etc., and primarily depends on working gas, electrolyte type, gap distance, current, conductivity, etc. However, an adequate understanding of how these patterns change from one type to another is still not available. This study aims to elucidate the influence of initial liquid conductance ( σ i ) on the temporal evolution of SOPs in liquid-anode discharges. The discharge was generated in a pin-to-liquid anode configuration at a constant helium (He) flow rate of 500 sccm and DC applied voltage of 6 kV at a gap distance of 12 mm. Through the gradual increment of σ i from 1.8 μ S to 4820 μ S, we observe that the trend in the evolution of SOPS takes place as solid discs, spikes, dots, rings, double rings, and stars. The continuous formation of reactive species onto the liquid anode in all conductive solutions results in a decrease in pH, an increase in bulk liquid temperature, and an increase in total dissolved solutes, and these have been confirmed through experimental measurements. Observations using optical emission spectroscopy show that the electrons at the plasma-liquid interface participate in the reduction of cations followed by their excitation & ionization due to which electron density as well as emissions from excited species (mainly hydroxyl radicals & excited nitrogen) decrease with time. Our investigation provides experimental evidence on the presence of cations at the plasma-liquid interface required for SOP formation.

Physics↗
NASA NTRS1986

Persistent anomalies of the extratropical Northern Hemisphere wintertime circulation - Structure

A study identifying horizontal and vertical structures of low patterns occurring with persistent 500 mb height anomalies in the central North Pacific, eastern North Atlantic, and northern Soviet Union regions is presented. The flow patterns of positive and negative anomalies are compared. The relationship between persistent anomalies and small recurrent anomaly patterns is examined. The temporal fluctuations of the persistent patterns are analyzed.

Dole, R. M.↗
DOE OSTI2022

Shifting temporal dynamics of human mobility in the United States

In this paper we analyze the average hourly temporal dynamics of human mobility in the United States from 2019 to 2020. We discuss how large decreases in human mobility nonuniformly effect the daily temporal dynamics of aggregate human behavior. The data used are weekly activity patterns for POIs from 2019 to 2020 in the United States, provided by SafeGraph and made openly available to academic and research institutions. We use clustering methods to create metrics describing how human activity changes throughout the day/week at the county and national levels. In response to significant mobility reductions starting March 2020, daily temporal patterns of human activity changed nonuniformly. Morning activity started later, and evening activity started earlier in 2020 compared to 2019, and temporal behavioral patterns on weekdays began to look more similar to weekends. The changes in daily temporal behavior persisted throughout the year even as total mobility levels recovered. The results provide insights on the changes in human behavior in response covid-19 policies and illustrate influences on social systems, health, and transportation networks.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Governing in Time: Temporal Capacity and the Feasibility of Energy Transitions

Energy systems function as both technological systems and temporal institutions that shape how societies coordinate, justify, and support collective choices over time. This paper introduces the concept of governance horizons to explain why energy transitions can remain morally supported yet become institutionally weak under increasing pressure. We argue that governability depends on institutions' capacity to synchronize across multiple timeframes - aligning short-term decisions with intermediate coordination and long-term commitments. When this synchronization fails, transitions struggle not because their goals are dismissed, but because governance lacks sufficient time to justify, coordinate, and uphold decisions. Comparative analysis of San Antonio, Texas, and Interior Alaska reveals how energy system pressures generate distinct temporal configurations: San Antonio exhibits governance horizon stretching, where institutions must simultaneously meet near-term reliability demands and long-term transformation goals, while Interior Alaska exhibits horizon compression, where extreme environmental constraints force decision-making into short stabilization cycles. In both contexts, public support for sustainability goals coexists with institutional strain because evaluative judgments are unevenly distributed over time. A temporal configuration analysis is introduced as a diagnostic analytic stance for identifying these patterns. By treating temporal alignment as an explanatory variable rather than a background condition, this approach clarifies how feasibility, sequencing, and legitimacy are shaped by constraints on institutional time. The analysis demonstrates that successful energy transitions depend not only on technological innovation or institutional support, but on governance systems’ ability to sustain credible coordination across multiple time horizons.

Comparative case study↗
NASA NTRS2010

Automated Discovery and Modeling of Sequential Patterns Preceding Events of Interest

The integration of emerging data manipulation technologies has enabled a paradigm shift in practitioners' abilities to understand and anticipate events of interest in complex systems. Example events of interest include outbreaks of socio-political violence in nation-states. Rather than relying on human-centric modeling efforts that are limited by the availability of SMEs, automated data processing technologies has enabled the development of innovative automated complex system modeling and predictive analysis technologies. We introduce one such emerging modeling technology - the sequential pattern methodology. We have applied the sequential pattern methodology to automatically identify patterns of observed behavior that precede outbreaks of socio-political violence such as riots, rebellions and coups in nation-states. The sequential pattern methodology is a groundbreaking approach to automated complex system model discovery because it generates easily interpretable patterns based on direct observations of sampled factor data for a deeper understanding of societal behaviors that is tolerant of observation noise and missing data. The discovered patterns are simple to interpret and mimic human's identifications of observed trends in temporal data. Discovered patterns also provide an automated forecasting ability: we discuss an example of using discovered patterns coupled with a rich data environment to forecast various types of socio-political violence in nation-states.

Rohloff, Kurt↗
NASA NTRS2004

Photophysics of Laser Dye-Doped Polymer Membranes for Laser-Induced Fluorescence Photogrammetry

Laser-induced fluorescence target generation in dye-doped polymer films has recently been introduced as a promising alternative to more traditional photogrammetric targeting techniques for surface profiling of highly transparent or reflective membrane structures. We investigate the photophysics of these dye-doped polymers to help determine their long-term durability and suitability for laser-induced fluorescence photogrammetric targeting. These investigations included experimental analysis of the fluorescence emission pattern, spectral content, temporal lifetime, linearity, and half-life. Results are presented that reveal an emission pattern wider than normal Lambertian diffuse surface scatter, a fluorescence time constant of 6.6 ns, a pump saturation level of approximately 20 micro J/mm(exp 2), and a useful lifetime of more than 300,000 measurements. Furthermore, two demonstrations of photogrammetric measurements by laser-induced fluorescence targeting are presented, showing agreement between photogrammetric and physically measured dimensions within the measurement scatter of 100 micron.

Dorrington, Adrian A.↗
DOE OSTI2025

Using Temporal Information from Human Mobility Data to Detect Anchor Points

Spatiotemporal mobility data are available in massive quantities, but large quantities of data typically include fewer variables or data fields. Often, the only available fields are User ID, Longitude, Latitude, Timestamp (ULLT). This raises an important question: how much can we infer about human mobility patterns using only these four fields? With ULLT data, we do not know individuals' socioeconomic status information or when they are visiting their anchor points (AP) or locations (such as homes, places of employment, or schools), and it is a modern challenge to use this data to infer these characteristics. When detecting anchor locations with limited input information, verification and validation (VV) are significant challenges. This paper addresses the problem of identifying individuals' anchor locations using only temporal information from spatiotemporal datasets with limited attributes. Our approach does not explicitly use latitude and longitude during analysis. Locationbased information is only employed in the preprocessing stage to identify periods of movement (trips) and stops (dwelling). Beyond this step, all analysis is based on temporal patterns. In theory, if stops and dwell times could be detected through alternative means, our method could function entirely without location-based input. We demonstrate this methodology on the 2017 National Household Travel Survey (NHTS) data, because it includes a carefully designed and collected time use survey with representative sampling and labeled ground truth. The high-quality survey data allows us to test the accuracy of our methods because NHTS contains intended place labels and agent/user characteristics. We have also applied our validated AP identification algorithm on very large-scale GPS based trajectory data for Patterns-of-Life (PoL) assessment and other applications, but due to space limit that could not be presented here.

McBride, Liz [ORNL] (ORCID:0000000286925869)↗
NASA NTRS1992

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

Michaels, Anthony F.↗
DOE OSTI2022

Self-organized patterns at the plasma–liquid anode interface in a helium glow discharge: temporal development and mechanisms

Self-organization at the plasma–liquid anode interface is a commonly observed phenomenon for atmospheric pressure glow plasmas, resulting in patterns with distinctive shapes such as circular ring, star-shaped, and gear-like structures, depending primarily on the discharge current and solution conductivity. Recent studies have shown that the electrode gap distance, solute used for liquid anode solution, and gas composition can also significantly impact pattern formation. Nonetheless, an overarching model or explanation of the key underlying mechanisms consistent with all experimentally observed trends is not yet reported. We propose a key underlying mechanism enabling pattern formation motivated by a detailed parametric study of pattern formation complemented by the temporal development of patterns and consistent with all observed trends. Pattern formation was observed to be on a time scale of 100 μs, similar to the time scales of gas heating and evaporation. It was found that a minimum water evaporation rate of (3.5 ± 0.5) × 10 –6 kg s –1 and reduced electric field in the positive column of 16.6 ± 0.4 Td is required for pattern formation in the investigated cases irrespective of solution conductivity and gas composition for NaCl solutions. Nonetheless, the presence of cations for which the corresponding metal atom has a low ionization energy was identified as a necessary condition for pattern formation. Furthermore, the reported results suggest that the presence of a small amount of metal atoms in the gas phase with low ionization energy enhances the overall ionization rate in the near anode region which triggers pattern formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1982

Association of spectral development patterns with development stages of corn

Association is made between the development stages of corn as defined by Hanway and the temporal-spectral development pattern of corn in a transformed data space derived from Landsat-MSS band reflectance values, using field-collected reflectance and associated data. Results indicate that the spectral vegetation index used (a reflectance equivalent of Tasseled Cap Greenness) reaches a maximum well before the stage at which corn is expected to achieve its peak leaf area index. Possible physiological and canopy geometry related causes for this and other results are presented.

Crist, E. P.↗
DOE OSTI2020

Implanted satellite transmitters affect sea duck movement patterns at short and long timescales

Abstract Studies of the effects of transmitters on wildlife often focus on survival. However, sublethal behavioral changes resulting from radio-marking have the potential to affect inferences from telemetry data and may vary based on individual and environmental characteristics. We used a long-term, multi-species tracking study of sea ducks to assess behavioral patterns at multiple temporal scales following implantation of intracoelomic satellite transmitters. We applied state-space models to assess short-term behavioral patterns in 476 individuals with implanted satellite transmitters, as well as comparing breeding site attendance and migratory phenology across multiple years after capture. In the short term, our results suggest an increase in dispersive behavior immediately following capture and transmitter implantation; however, behavior returned to seasonally average patterns within ~5 days after release. Over multiple years, we found that breeding site attendance by both males and females was depressed during the first breeding season after radio-marking relative to subsequent years, with larger relative decreases in breeding site attendance among males than females. We also found that spring and breeding migrations occurred later in the first year after radio-marking than in subsequent years. Across all behavioral effects, the severity of behavioral change often varied by species, sex, age, and capture season. We conclude that, although individuals appear to adjust relatively quickly (i.e. within 1 week) to implanted satellite transmitters, changes in breeding phenology may occur over the longer term and should be considered when analyzing and reporting telemetry data.

Lamb, Juliet S.↗
DOE OSTI2025

Drosophila melanogaster pigmentation demonstrates adaptive phenotypic parallelism over multiple spatiotemporal scales

Abstract Populations are capable of responding to environmental change over ecological timescales via adaptive tracking. However, the translation from patterns of allele frequency change to rapid adaptation of complex traits remains unresolved. We used abdominal pigmentation in Drosophila melanogaster as a model phenotype to address the nature, genetic architecture, and repeatability of rapid adaptation in the field. We show that D. melanogaster pigmentation evolves as a highly parallel and deterministic response to shared environmental variation across latitude and season in natural North American populations. We then experimentally evolved replicate, genetically diverse fly populations in field mesocosms to remove any confounding effects of demography and/or cryptic structure that may drive patterns in wild populations; we show that pigmentation rapidly responds, in parallel, in fewer than 15 generations. Thus, pigmentation evolves concordantly in response to spatial and temporal climatic axes. We next examined whether phenotypic differentiation was associated with allele frequency change at loci with established links to genetic variance in pigmentation in natural populations. We found that across all spatial and temporal scales, phenotypic patterns were associated with variation at pigmentation-related loci, and the sets of genes we identified at each scale were largely nonoverlapping. Therefore, our findings suggest that parallel phenotypic evolution is associated with distinct components of the polygenic architecture shifting across each environmental axis to produce redundant adaptive patterns.

Evolutionary Biology↗
NASA NTRS2001

Use of Satellite-Derived Water Vapor Data to Investigate Northwestward Expansion of North Pacific Subtropical High During 1995 Summer: Westward Propagating Moisture Pattern

The spatial and temporal evolution of the moisture field over the subtropical northwest Pacific during the summer of 1995 is investigated using daily total precipitable water from combined SSM/I-TOVS data and pentad upper tropospheric humidity (UTH) data, in conjunction with NCEP reanalysis data. From analysis of the combined water vapor field, the westward movement of a dry airmass is observed along the 20-30 degrees N latitude zone from near the dateline to the south of Japan throughout the summer of 1995. Extended EOF analysis of total precipitable water reveals that the westward moving pattern takes place in conjunction with an expanding North Pacific subtropical high maintaining an oscillatory component exhibiting a period of some 15-25 days. A concomitant dipole-like oscillating anomalous circulation with approximately a 20-day period between the South China Sea and south of Japan appears to influence the westward expansion of the subtropical high. The analysis also suggests that the fluctuations of the North Pacific high are in response to a local Hadley-type circulation which is induced by westward-moving anomalous convection episodes along 10-20 degrees N.

Sohn, Byung-Ju↗
DOE OSTI2026

Global population structures and demographic history of Suillus luteus, a pine co‐introduced ectomycorrhizal fungus associated with exotic forestry and invasion

Human colonization since the 19th century has resulted in the global spread of pines beyond their original northern boreal distribution. Although the introduction history of pines is documented through historical records, little is known about the introduction history of their ectomycorrhizal (ECM) fungi, which are critical symbionts for the survival and invasion of pines. Using Suillus luteus as an example, whole genomes of 208 individuals collected across native and introduced ranges were sequenced to reveal the introduction history of pine co-introduced ECM fungi. Population genomics analyses showed that all introductions originated from Europe. With the exception of North America, introduced populations were genetically differentiated from the European population, with varying magnitudes of population expansion in different introduced regions. Genetic variation within the native European population followed isolation by distance, but not in the introduced range, highlighting the disparity in the spatial-genetic patterns of native vs exotic habitats. The spread of S. luteus is mediated by human activities accompanying pine introductions, with its demographic history linked to forestry practices. The spatial, temporal, and demographic patterns observed in S. luteus offer insight into the population genetics of a widely introduced ECM fungus and are likely applicable to other pine co-introduced ECM fungi.

Ke, Yi‐Hong↗
NASA NTRS2019

DSCOVR-EPIC MAIAC AOD - A Proxy for Understanding Aerosol Diurnal Patterns from Space

The Deep Space Climate Observatory (DSCOVR) spacecraft was launched on 11 February 2015 and in June 2015 achieved its orbit at the first Lagrange point (L1), 1.5 million km from Earth toward the sun. The Earth Polychromatic Imaging Camera (EPIC) onboard DSCOVR views the entire sunlit Earth from sunrise to sunset, every 1-2 hours, at scattering angles between 168.5° and 175.5° with 10 narrowband filters in the range of 317-779 nm. NASA Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm, originally developed for MODIS, has been applied to EPIC data with an Aerosol Optical Depth (AOD) product at 440nm with a 10km spatial resolution. This high temporal resolution product is a unique dataset for investigating diurnal patterns in aerosols from space. Our work analyzed the capability of the satellite-borne data to capture the aerosol diurnal variation by associating it with AERONET AOD at 440nm data over the contiguous US. We validated the DSCOVR MAIAC AOD data over 100 AERONET stations during 2015-2018, and examined the contribution of the surface reflectance and relevant acquisition angles, derived by the MAIAC algorithm, to the predicted error. We used over 180,000 hourly DSCOVR-EPIC MAIAC AOD observations with collocated with AERONET AOD observations averaged over +-30 minutes from the satellite overpass time. The AERONET and DSCOVR AOD temporal patterns show that the diurnal variation is different across US AERONET sites, with higher diurnal variation in the DSCOVR dataset in general.

Sorek-Hamer, Meytar↗
NASA NTRS2017

Large-Scale Circulation and Climate Variability

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Perlwitz, J.↗
DOE OSTI2021

Mining and Validating Social Media Data for COVID-19–Related Human Behaviors Between January and July 2020: Infodemiology Study

Background: Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging, is also important for minimizing long-term effects of an outbreak. Objective: We used social media data from Twitter to identify human behaviors relevant to COVID-19 transmission, as well as the perceived impacts of COVID-19 on individuals, as a first step toward real-time monitoring of public perceptions to inform public health communications. Methods: We developed a coding schema for 6 categories and 11 subcategories, which included both a wide number of behaviors as well codes focused on the impacts of the pandemic (eg, economic and mental health impacts). We used this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that performed adequately were applied to our remaining corpus, and temporal and geospatial trends were assessed. We compared the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. Results: We applied our labeling schema to approximately 7200 tweets. The worst-performing classifiers had F1 scores of only 0.18 to 0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, were much stronger, with F1 scores of 0.64 to 0.66. We applied the social distancing classifiers to over 228 million tweets. We showed temporal patterns consistent with real-world events, and we showed correlations of up to –0.5 between social distancing signals on Twitter and ground truth mobility throughout the United States. Conclusions: Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior, as well as for informing public health communication strategies by describing awareness of and compliance with suggested behaviors.

60 APPLIED LIFE SCIENCES↗