Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “persistent identifier”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Tree Growth Enhancement Drives a Persistent Biomass Gain in Unmanaged Temperate Forests

While enhanced tree growth over the last decades has been reported in forests across the globe, it remains unclear whether it drives persistent biomass increases of forest stands, particularly in mature forests. Enhanced tree growth and stand-level biomass are often linked with a simultaneous increase in density-driven mortality and a reduction in tree longevity. Identifying empirical evidence regarding the balance between these processes is challenging due to the confounding effects of stand history, management, and environmental changes. Here, we investigate the link between growth and biomass via the negative relationship between average tree size and stand density (tree number per area). We find increasing stand density for a given mean tree size in unmanaged closed-canopy forests in Switzerland over the past six decades and a positive relationship between tree growth and stand density across forest plots—qualitatively consistent with our simulations using a mechanistic, cohort-resolving ecosystem model (BiomeE). Model simulations show that, in the absence of other disturbances, enhanced tree growth persistently increases biomass stocks despite simultaneous decreases in carbon residence time and tree longevity. However, the magnitude of simulated biomass changes for a given growth enhancement critically depends on the shape of the mortality functions. Our analyses reconcile reports of growth-induced reductions of tree longevity with model predictions of persistent biomass increases, and with our finding of trends toward denser forests in response to growth—also in mature stands.

biomass stocks↗
DOE OSTI2020

A Causal Inference Model Based on Random Forests to Identify the Effect of Soil Moisture on Precipitation

Soil moisture influences precipitation mainly through its impact on land–atmosphere interactions. Understanding and correctly modeling soil moisture–precipitation (SM–P) coupling is crucial for improving weather forecasting and subseasonal to seasonal climate predictions, especially when predicting the persistence and magnitude of drought. However, the sign and spatial structure of SM–P feedback are still being debated in the climate research community, mainly due to the difficulty in establishing causal relationships and the high degree of nonlinearity in land–atmosphere processes. To this end, we developed a causal inference model based on the Granger causality analysis and a nonlinear machine learning model. This model includes three steps: nonlinear anomaly decomposition, nonlinear Granger causality analysis, and evaluation of the quality of SM–P feedback, which eliminates the nonlinear response of interannual and seasonal variability and the memory effects of climatic factors and isolates the causal relationship of local SM–P feedback. We applied this model by using National Climate Assessment–Land Data Assimilation System (NCA-LDAS) datasets over the United States. Here, the results highlight the importance of nonlinear atmosphere responses in land–atmosphere interactions. In addition, the strong feedback over the southwestern United States and the Great Plains both highlight the impacts of topographic factors rather than only the sensitivity of evapotranspiration to soil moisture. Furthermore, the SM–P index defined by our framework is used to benchmark Earth system models (ESMs), which provides a new metric for efficiently identifying potential model biases in modeling local land–atmosphere interactions and may help the development of ESMs in improving simulations of water cycle variability and extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Foundational insights into the mechanical and molecular evolution of porcine skin gelatin during gelation

Gelatin is a widely used material in biomedical fields, particularly in regenerative medicine and tissue engineering, due to its biocompatibility and versatile properties. While prior research has explored methods to enhance gelatin's mechanical strength and stability, fundamental studies on gelatin, specifically its curing process, mechanical stiffness, and chemical evolution during gelation, remain limited. This study uses ultrasonic testing and Fourier Transform Infrared Spectroscopy (FTIR) to examine gelatin's stiffness and molecular changes during gelation. Samples of 175 and 300 Porcine Skin Bloom Strength Gelatin at concentrations of 2% and 6% (w/v) were analyzed. Through transmission ultrasonic testing helped identify key transition points in gelation, with higher concentrations exhibiting delayed transitions. FTIR revealed that C-N bond formation peaks early while N-H bond deformation persists. A correlation emerged between sound speed and peak absorbance, suggesting that changes in molecular mobility may contribute to the observed sound speed behavior during periods of active bond formation. However, as gelation continues, fewer bonding components may be available, potentially decreasing molecular movement and contributing to the observed increase in sound speed. These findings provide insights into gelatin's mechanical and chemical evolution, offering a framework for improved control over its gelation kinetics. Swept-Frequency Acoustic Interferometry (SFAI) was performed at the end of the curing process to measure the sound speed, enabling the calculation of the bulk moduli of the gelatin samples. The combined use of ultrasonic and FTIR testing provides a non-destructive method for characterizing gelatin and other biomaterials. This approach advances understanding of gelatin curing behavior and supports the development of safer biomaterials with tailored mechanical properties for various applications such as tissue engineering and regenerative medicine.

Biomaterials↗
DOE OSTI2023

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ~ 0.94–0.99) for predicting single-component adsorption capacity in metal–organic frameworks (MOFs). Here, we consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Mechanisms of heat flux across the Southern Greenland continental shelf in 1/10° and 1/12° ocean/sea ice simulations

The increased presence of warm Atlantic water on the Greenland continental shelf has been connected to the accelerated melting of the Greenland Ice Sheet, particularly in the southwest and southeast shelf regions. Results from two high-resolution coupled ocean-sea ice simulations that utilized either the 1/10-degree Parallel Ocean Program (POP) or the 1/12-degree HYbrid Coordinate Ocean Model (HYCOM) are used to understand the flux of heat on and off the southern Greenland shelf. The analysis reveals that the region of greatest heat flux onto the shelf is southeast Greenland. On the southwestern shelf, heat is mainly exported from the shelf to the interior basins. We identify differences in the shelf break current structure and on-shelf heat content between the two simulations. Just south of the Denmark strait, there is a seasonally persistent pattern of multi-day variability in the cross-shelf heat flux in both simulations. In the POP simulation, this high-frequency signal results in net on-shore heat flux. In the HYCOM simulation, the signal is weaker and results in net off-shelf heat flux. This variability is consistent with Denmark Strait Overflow eddies traveling along the shelf break.

58 GEOSCIENCES↗
DOE OSTI2025

Nonideal stability analysis of differentially rotating plasmas with global curvature effects

The linear stability of global nonaxisymmetric modes in differentially rotating, magnetized, nonideal plasma is critical to classifying turbulence and transport phenomena. We investigate the competition between the local magneto-rotational instability (MRI) and the magneto-curvature instability (MCI)—a distinct nonaxisymmetric low-frequency curvature-driven global branch that appears alongside MRI. Here, to accomplish this, we developed a nonideal global spectral method, which is validated against NIMROD code simulations. This spectral approach allows for the direct derivation of an extended effective potential formalism and a resistive Alfvénic resonance condition, providing a framework for direct analysis of energy contributions and confinement mechanisms. Our study reveals that the global, low-frequency MCI persists at low magnetic Reynolds numbers (Rm), whereas the localized, high-frequency MRI is stabilized by diffusive broadening of its structure around its Alfvénic resonances. Consequently, we identify the global MCI branch as the primary onset mechanism for nonaxisymmetric magnetohydrodynamic instability in systems with finite curvature, e.g., astrophysical rotators. We establish distinct parameter regimes for mode dominance: MCI prevails in geometrically moderate-thickness disks with intermediate curvature and radial gaps, while MRI dominates in thin, low-curvature disks with large radial gaps. Mode competition is also highly sensitive to the flow profile, particularly vorticity and its gradient, with nonuniform shear profiles exhibiting more robust instability due to flow curvature (i.e., the second derivative of the flow profile) and shear contributions. A key outcome is the development of spectral diagrams derived from the global spectral method. These diagrams comprehensively map dominant instabilities and their characteristics, offering a predictive tool for critical onset parameters (i.e., flow curvature, magnetic field, and Rm) and facilitating the interpretation of experimental and simulation results. Notably, these diagrams demonstrate that the global MCI is generally the sole unstable mode at the initial onset of nonaxisymmetric instability.

Haywood, Alexander [Princeton Univ., NJ (United St↗
DOE OSTI2023

Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem

Background: Viruses impact nearly all organisms on Earth, including microbial communities and their associated biogeochemical processes. In soils, highly diverse viral communities have been identified, with a global distribution seemingly driven by multiple biotic and abiotic factors, especially soil temperature and moisture. However, our current understanding of the stability of soil viral communities across time and their response to strong seasonal changes in environmental parameters remains limited. Here, we investigated the diversity and activity of environmental soil DNA and RNA viruses, focusing especially on bacteriophages, across dynamics’ seasonal changes in a snow-dominated mountainous watershed by examining paired metagenomes and metatranscriptomes. Results: We identified a large number of DNA and RNA viruses taxonomically divergent from existing environmental viruses, including a significant proportion of fungal RNA viruses, and a large and unsuspected diversity of positive single-stranded RNA phages ( Leviviricetes ), highlighting the under-characterization of the global soil virosphere. Among these, we were able to distinguish subsets of active DNA and RNA phages that changed across seasons, consistent with a “seed-bank” viral community structure in which new phage activity, for example, replication and host lysis, is sequentially triggered by changes in environmental conditions. At the population level, we further identified virus-host dynamics matching two existing ecological models: “Kill-The-Winner” which proposes that lytic phages are actively infecting abundant bacteria, and “Piggyback-The-Persistent” which argues that when the host is growing slowly, it is more beneficial to remain in a dormant state. The former was associated with summer months of high and rapid microbial activity, and the latter with winter months of limited and slow host growth. Conclusion: Taken together, these results suggest that the high diversity of viruses in soils is likely associated with a broad range of host interaction types each adapted to specific host ecological strategies and environmental conditions. As our understanding of how environmental and host factors drive viral activity in soil ecosystems progresses, integrating these viral impacts in complex natural microbiome models will be key to accurately predict ecosystem biogeochemistry.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

A new technique for simultaneous monitoring of electrocardiogram and walking cadence

A new technique for simultaneously recording continuous electrocardiographic (ECG) data and walking step rate (cadence) is described. The ECG and gait signals are recorded on 2 channels of an ambulatory Holter monitor. Footfall is detected using ultrathin, force-sensitive foot switches and is frequency modulated. The footfall signal provides an indication of the subject's activity (walking or standing), as well as the instantaneous walking rate. Twenty-three young and elderly subjects were studied to demonstrate the use of this ECG and gait recorder. High-quality gait signals were obtained in all subjects, and the effects of walking on the electrocardiogram were assessed. Initial investigation revealed the following findings: (1) Although walking rates were similar in young and elderly subjects, the elderly had both decreased heart rate (HR) variability (p < 0.005) and increased cadence variability (p < 0.0001). (2) Overall, there was an inverse relation between HR and cadence variability (r = -0.73). Three elderly subjects with no known cardiac disease had HR and cadence variability similar to those of the young, whereas elderly subjects with history of congestive heart failure were among those with the lowest HR variability and the highest cadence variability. (3) Low-frequency (approximately equal to 0.1 Hz) HR oscillations (frequently observed during standing) persisted during walking in all young subjects. (4) In some subjects, both step rate and HR oscillated at the same low frequency (approximately equal to 0.1 Hz) previously identified with autonomic control of the baroreflex.(ABSTRACT TRUNCATED AT 250 WORDS).

NASA Discipline Cardiopulmonary↗
NASA NTRS2012

Review of Human Cognitive Performance in Spaceflight

Human space exploration is inherently hazardous, particularly for lon g duration (LD) missions (22 days or longer). Maintenance of cognitive functioning is essential, but flight environments pose numerous pote ntial risks to the brain and cognitive performance (eg, radiation, to xins, chronic stress, sleep deprivation, hypercarbia, fluid shifts, h ormone imbalances, and injury). There have been persistent anecdotal reports of cognitive deficits during missions, but an up?-to-date rev iew of the evidence for such changes has remained unavailable. Method s: We identified and reviewed English language publications found via electronic searches in PubMed, PsycInfo, Inspec, the NASA Technical Report Server, and the Defense Technical Information Center, plus rec ursive searches of publication bibliographies. Search terms included the word cognition, cognitive, or performance along with spaceflight, flight, mission, or closely related terms. Results: Inter?-study variability precluded meta?-analysis. Some 32 published studies involving cognitive assessment during spaceflight were identified, involving a total of 110 participants (mean: 3.4 participants per study). The lo ngest?-duration study spanned 438 days, with six additional studies i nvolving flight durations of 90 days, and 11 more studies involved fl ight durations exceeding 21 days. The available evidence failed to st rongly support or refute the existence of cognitive deficits in LD sp aceflight, in part due to inadequate power or control conditions. Evi dence of increased variability in cognitive performance during spacef light, both within and between individuals, was common. Discussion: T hese results represent a negative finding based on small numbers of s ubjects for any given cognitive function. The increased variability within and (particularly) between individuals highlights the potential danger of generalizing from case studies. A mismatch therefore remain s between anecdotal reports describing generalized cognitive slowing, attention and memory problems during missions and the experimental e vidence supporting such deficits. Since a major justification for man ned spaceflight rests with the cognitive flexibility of humans, addit ional studies and further analysis of existing operational data appea rs warranted.

Strangman, Gary↗
NASA NTRS2023

Microbial Adaptation to Spaceflight Is Correlated With Bacteriophage-Encoded Functions

Evidence from the International Space Station suggests microbial populations are rapidly adapting to the spacecraft environment; however, the mechanism of this adaptation is not understood. Bacteriophages are prolific mediators of bacterial adaptation on Earth. Here we survey 245 genomes sequenced from bacterial strains isolated on the International Space Station for dormant (lysogenic) bacteriophages. Our analysis indicates phage-associated genes are significantly different between spaceflight strains and their terrestrial counterparts. Additionally, we identify 283 complete prophages, those that could initiate bacterial lysis and infect additional hosts, of which 21% are novel. These prophage regions encode functions that correlate with increased persistence in extreme environments, such as spaceflight, to include antimicrobial resistance and virulence, DNA damage repair, and dormancy. Our results correlate microbial adaptation in spaceflight to bacteriophage-encoded functions that may impact human health in spaceflight.

Space Biology↗
DOE OSTI2022

Where does the dust deposited over the Sierra Nevada snow come from?

Abstract. Mineral dust contributes up to one-half of surface aerosol loading in spring over the southwestern United States, posing an environmental challenge that threatens human health and the ecosystem. Using self-organizing map (SOM) analysis with dust deposition and flux data from WRF-Chem and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), we identify four typical dust transport patterns across the Sierra Nevada, associated with the mesoscale winds, Sierra barrier jet (SBJ), North Pacific High (NPH), and long-range cross-Pacific westerlies, respectively. We find that dust emitted from the Central Valley is persistently transported eastward, while dust from the Mojave Desert and Great Basin influences the Sierra Nevada during mesoscale transport occurring mostly in winter and early spring. Asian dust reaching the mountain range comes either from the west through straight isobars (cross-Pacific transport) or from the north in the presence of the NPH. Extensive dust depositions are found on the west slope of the mountain, contributed by Central Valley emissions and cross-Pacific remote transport. In particular, the SBJ-related transport produces deposition through landfalling atmospheric rivers, whose frequency might increase in a warming climate.

Huang, Huilin (ORCID:0000000273286738)↗
DOE OSTI2025

Environmental life cycle of fentanyl: From the cradle to an unknown grave

The lack of available information on the presence and persistence of fentanyl in the environment is a significant gap in the technical literature. Although the origins of the opioid in the environment are well-known because they follow the same pathways of other drug-related environmental contaminants, the downstream effects of fentanyl in the water supply and its retention in soil are less understood. The characterization of fentanyl and its potential degradation products in complex environmental samples such as soil is severely understudied. Very few articles are available that work to identify fentanyl and its degradation products in complex samples or name the possible hazards that may result from environmental exposure and degradation. Therefore, the objectives were to identify available articles focused on environmental fentanyl and its pathways and highlight quantifiable research or results that included specific degradation products or downstream effects. Research articles focused on fentanyl between 2000 and 2024 were identified and reviewed and then filtered using Boolean search terms for environmental parameters. Various studies have determined that trace levels of fentanyl can be found in a variety of environments, and additional data suggest preferential partitioning into soils from water and long-term persistence. Despite this knowledge, very little data exists on the long-term downstream effects of fentanyl or its analogs. As the chronic effects from low-level fentanyl exposure are currently unknown, this lack of insight brings to the forefront the need for further research to improve our understanding of fentanyl persistence, degradation, and toxicity within the environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Building fault detection data to aid diagnostic algorithm creation and performance testing

It is estimated that approximately 4-5% of national energy consumption can be saved through corrections to existing commercial building controls infrastructure and resulting improvements to efficiency. Correspondingly, automated fault detection and diagnostics (FDD) algorithms are designed to identify the presence of operational faults and their root causes. A diversity of techniques is used for FDD spanning physical models, black box, and rule-based approaches. A persistent challenge has been the lack of common datasets and test methods to benchmark their performance accuracy. This article presents a first of its kind public dataset with ground-truth data on the presence and absence of building faults. This dataset spans a range of seasons and operational conditions and encompasses multiple building system types. It contains information on fault severity, as well as data points reflective of the measurements in building control systems that FDD algorithms typically have access to. The data were created using simulation models as well as experimental test facilities, and will be expanded over time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Viability, behavior, and color expression in the offspring of matings between common wall lizard Podarcis muralis color morphs

Abstract Color polymorphisms are widely studied to identify the mechanisms responsible for the origin and maintenance of phenotypic variability in nature. Two of the mechanisms of balancing selection currently thought to explain the long-term persistence of polymorphisms are the evolution of alternative phenotypic optima through correlational selection on suites of traits including color and heterosis. Both of these mechanisms can generate differences in offspring viability and fitness arising from different morph combinations. Here, we examined the effect of parental morph combination on fertilization success, embryonic viability, newborn quality, antipredator, and foraging behavior, as well as inter-annual survival by conducting controlled matings in a polymorphic lacertid Podarcis muralis, where color morphs are frequently assumed to reflect alternative phenotypic optima (e.g., alternative reproductive strategies). Juveniles were kept in outdoor tubs for a year in order to study inter-annual growth, survival, and morph inheritance. In agreement with a previous genome-wide association analysis, morph frequencies in the year-old juveniles matched the frequencies expected if orange and yellow expressions depended on recessive homozygosity at 2 separate loci. Our findings also agree with previous literature reporting higher reproductive output of heavy females and the higher overall viability of heavy newborn lizards, but we found no evidence for the existence of alternative breeding investment strategies in female morphs, or morph-combination effects on offspring viability and behavior. We conclude that inter-morph breeding remains entirely viable and genetic incompatibilities are of little significance for the maintenance of discrete color morphs in P. muralis from the Pyrenees.

Abalos, Javier↗
DOE OSTI2023

Leveraging Application Data Constraints to Optimize Database-Backed Web Applications

Exploiting the relationships among data is a classical query optimization technique. As persistent data is increasingly being created and maintained programmatically, prior work that infers data relationships from data statistics misses an important opportunity. We present Coco, the first tool that identifies data relationships by analyzing database-backed applications. Once identified, Coco leverages the constraints to optimize the application's physical design and query execution. Instead of developing a fixed set of predefined rewriting rules, Coco employs an enumerate-test-verify technique to automatically exploit the discovered data constraints to improve query execution. Each resulting rewrite is provably equivalent to the original query. Using 14 real-world web applications, our experiments show that Coco can discover numerous data constraints from code analysis and improve real-world application performance significantly.

Computer Science↗
NASA NTRS1988

Carbon monoxide over the Amazon Basin during the 1985 dry season

During the Amazon Boundary Layer Experiment, approximately 100 hours of in situ carbon monoxide measurements were obtained using a tunable diode laser sensor that provided continuous, fast-response (about 1 s) measurements. This data set, taken on board the NASA Electra between July 12 and August 12, 1985, characterizes the temporal and spatial changes in the CO distribution over the Amazon Basin as meteorological conditions progressed from the early to middle phases of the 1985 day season. Early dry-season CO values of 75-95 ppbv were generally observed in the PBL. As the dry season became well established, biomass burning and a persistent capping inversion at about 3 km profoundly altered the CO distribution, with PBL values typically reaching 150-275 ppbv. Concentrations as high as 800 ppbv were measured within identifiable haze layers. An analysis of satellite imagery shows that biomass burning was occurring along the Amazon River system and in savannah areas located more than 1000 km south of the region sampled.

Sachse, G. W.↗
DOE OSTI2020

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Characterization of Ionospheric Flow Patterns During Times of Unusual Auroral Activity Using DE and DMSP Data

This final report describes the work done by Dr. Marc Hairston and Dr. Rod Heelis on NASA SR&T grant NAGW-4411 studying the theta aurora using DE-1 ultraviolet imager data and DMSP particle data. This report covers the period from summer 1995 through summer 1996 along with a review of the previous work. Previous work on this grant looked at the time period from the launch of DMSP-F8 in June 1987 through the end of mission of DE-1 in summer 1991. Despite the sporadic and decreasing frequency of observations from DE-1 over this time period, we were able to identify six events for study where the DE-1 imager observed a theta aurora occurring during a period in which the DMSP-F8 satellite flew through the region of the aurora at an altitude of 800 km. We focused on the best two events where the theta aurora persisted for an extended period so that we could observe the DMSP particle signatures in both the hemisphere observed by DE-1 and in the other polar hemisphere immediately before or afterwards. These results were presented at the Fall 1994 meeting of the AGU. Initially we had hoped to expand on this work. However, further work showed that none of these events gave a clear enough signature in the DMSP data for us to identify a theta aurora in the hemisphere opposite to the hemisphere imaged by DE-1. Without that, there were no results from this work that were new enough to warrant publication. So instead we used the final year of the grant to work with our colleague, J. A. Cumnock on a similar project using DE data to study the evolution of theta auroras as a function of the IMF A paper from that work was published which acknowledged this grant and a copy of that paper is included with this final report.

Hairston, Marc↗