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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Activity in F stars

Measurements of He I 5876 A and IUE measurements of chromospheric and transition region lines in a large sample of F-type stars are presented. The data show that activity is detectable in nearly all early F-type stars and differs in several of its characteristics from that typically seen in cooler stars with slow rotation and fully developed convective zones. The onset of activity occurs near B-V = 0.28, which corresponds approximately to spectral type F0 and T(eff) = 7300 K. There is no correlation between the level of activity and the abundances of lithium and beryllium in F stars hotter than T(eff) = 6600 K. All but one of the stars in the 6600-7300 K temperature interval are active. The levels of activity in these stars are independent of Rossby number.

Wolff, Sidney C.↗
DOE OSTI2023

Seasonal activities of the phyllosphere microbiome of perennial crops

Understanding the interactions between plants and microorganisms can inform microbiome management to enhance crop productivity and resilience to stress. Here, we apply a genome-centric approach to identify ecologically important leaf microbiome members on replicated plots of field-grown switchgrass and miscanthus, and to quantify their activities over two growing seasons for switchgrass. We use metagenome and metatranscriptome sequencing and curate 40 medium- and high-quality metagenome-assembled-genomes (MAGs). We find that classes represented by these MAGs (Actinomycetia, Alpha- and Gamma- Proteobacteria, and Bacteroidota) are active in the late season, and upregulate transcripts for short-chain dehydrogenase, molybdopterin oxidoreductase, and polyketide cyclase. Stress-associated pathways are expressed for most MAGs, suggesting engagement with the host environment. We also detect seasonally activated biosynthetic pathways for terpenes and various non-ribosomal peptide pathways that are poorly annotated. Our findings support that leaf-associated bacterial populations are seasonally dynamic and responsive to host cues.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

High-resolution crystal structure of a polyextreme GH43 glycosidase from Halothermothrix orenii with α-l-arabinofuranosidase activity

The crystal structure of the H. orenii glycosidase was determined by molecular replacement and refined at 1.10 Å resolution. A gene from the heterotrophic, halothermophilic marine bacterium Halothermothrix orenii has been cloned and overexpressed in Escherichia coli. This gene encodes the only glycoside hydrolase of family 43 (GH43) produced by H. orenii. The crystal structure of the H. orenii glycosidase was determined by molecular replacement and refined at 1.10 Å resolution. As for other GH43 members, the enzyme folds as a five-bladed β-propeller. The structure features a metal-binding site on the propeller axis, near the active site. Based on thermal denaturation data, the H. orenii glycosidase depends on divalent cations in combination with high salt for optimal thermal stability against unfolding. A maximum melting temperature of 76°C was observed in the presence of 4 M NaCl and Mn{sup 2+} at pH 6.5. The gene encoding the H. orenii GH43 enzyme has previously been annotated as a putative α-l-arabinofuranosidase. Activity was detected with p-nitrophenyl-α-l-arabinofuranoside as a substrate, and therefore the name HoAraf43 was suggested for the enzyme. In agreement with the conditions for optimal thermal stability against unfolding, the highest arabinofuranosidase activity was obtained in the presence of 4 M NaCl and Mn{sup 2+} at pH 6.5, giving a specific activity of 20–36 µmol min{sup −1} mg{sup −1}. The active site is structurally distinct from those of other GH43 members, including arabinanases, arabinofuranosidases and xylanases. This probably reflects the special requirements for degrading the unique biomass available in highly saline aqueous ecosystems, such as halophilic algae and halophytes. The amino-acid distribution of HoAraf43 has similarities to those of mesophiles, thermophiles and halophiles, but also has unique features, for example more hydrophobic amino acids on the surface and fewer buried charged residues.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1977

Possible Jovian methane emission at 76 GHz in coincidence with decameter activity

The tentative detection of a methane line in emission at 76.2 GHz in the atmosphere of Jupiter is reported. The observed feature is well-correlated with the presence and absence of Jovian decameter-emission activity on successive days. The present results may represent the first detection of extraterrestrial methane microwave emission.

Fox, K.↗
DOE OSTI2019

Radio VLBA polarization and multiband monitoring of the high-redshift quasar S5 0836 + 710 during a high-activity period

ABSTRACT We report on results of a multiband monitoring campaign from radio to γ-rays of the high-redshift flat spectrum radio quasar S5 0836 + 710 during a high-activity period detected by the Large Area Telescope on board the Fermi Gamma-ray Space Telescope. Two major flares were detected, in 2015 August and November. In both episodes, the apparent isotropic γ-ray luminosity exceeds 1050 erg s−1, with a doubling time-scale of about 3 h. The high γ-ray activity may be related to a superluminal knot that emerged from the core in 2015 April at the peak of the radio activity and is moving downstream along the jet. The low variability observed in X-rays may indicate that X-ray emission is produced by the low-energy tail of the same electron population that produces the γ-ray emission. The analysis of full-polarization pc-scale radio observations suggests the presence of a limb-brightened polarization structure at about 1 mas from the core in which a rotation measure gradient with a sign change is observed transverse to the jet direction. These characteristics are consistent with a scenario in which Faraday rotation is produced by a sheath of thermal electrons with a toroidal magnetic field surrounding the emitting jet.

Orienti, M.↗
DOE OSTI2018

Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection

Automated analysis methods are crucial aids for monitoring and defending a network to protect the sensitive or confidential data it hosts. This work introduces a flexible, powerful, and unsupervised approach to detecting anomalous behavior in computer and network logs; one that largely eliminates domain-dependent feature engineering employed by existing methods. By treating system logs as threads of interleaved ``sentences'' (event log lines) to train online unsupervised neural network language models, our approach provides an adaptive model of normal network behavior. We compare the effectiveness of both standard and bidirectional recurrent neural network language models at detecting malicious activity within network log data. Extending these models, we introduce a tiered recurrent architecture, which provides context by modeling sequences of users' actions over time. Compared to isolation forests and Principal Components Analysis (PCA), two popular anomaly detection algorithms, we observe superior performance on the Los Alamos National Laboratory Cyber Security dataset. For log-line-level predictions, our best performing character-based model provides test set anomaly scores ranking red team events in the 98th percentile on average, and yields 0.97 area under the receiver operator characteristic curve, demonstrating the strong fine-grained anomaly detection performance of this approach on open vocabulary logging sources.

Cyber Analysis, Deep Learning, language analysis, ↗
DOE OSTI2014

Improved Fission Neutron Data Base for Active Interrogation of Actinides

This project will develop an innovative neutron detection system for active interrogation measurements. Many active interrogation methods to detect fissionable material are based on the detection of neutrons from fission induced by fast neutrons or high-energy gamma rays. The energy spectrum of the fission neutrons provides data to identify the fissionable isotopes and materials such as shielding between the fissionable material and the detector. The proposed path for the project is as follows. First, the team will develop new neutron detection systems and algorithms by Monte Carlo simulations and bench-top experiments. Next, they will characterize and calibrate detection systems both with monoenergetic and white neutron sources. Finally, high-fidelity measurements of neutron emission from fissions induced by fast neutrons will be performed. Several existing fission chambers containing U-235, Pu-239, U-238, or Th-232 will be used to measure the neutron-induced fission neutron emission spectra. The challenge for making confident measurements is the detection of neutrons in the energy ranges of 0.01 – 1 MeV and above 8 MeV, regions where the basic data on the neutron energy spectrum emitted from fission is least well known. In addition, improvements in the specificity of neutron detectors are required throughout the complete energy range: they must be able to clearly distinguish neutrons from other radiations, in particular gamma rays and cosmic rays. The team believes that all of these challenges can be addressed successfully with emerging technologies under development by this collaboration. In particular, the collaboration will address the area of fission neutron emission spectra for isotopes of interest in the advanced fuel cycle initiative (AFCI).

Pozzi, Sara A.↗
DOE OSTI2021

Self-Supervised Anomaly Detection via Neural Autoregressive Flows with Active Learning

Many self-supervised methods have been proposed with the target of image anomaly detection. These methods often rely on the paradigm of data augmentation with predefined transformations such as flipping, cropping, and rotations. However, it is not straightforward to apply these techniques for non-image data, such as time series or tabular data, while the performance of the existing deep approaches has been under our expectation on tasks beyond images. In this work, we propose a novel active learning (AL) scheme that relied on neural autoregressive flows (NAF) for self-supervised anomaly detection, specifically on small-scale data. Unlike other generative models such as GANs or VAEs, flow-based models allow to explicitly learn the probability density and thus can assign accurate likelihoods to normal data which makes it usable to detect anomalies. The proposed NAF-AL method is achieved by efficiently generating random samples from latent space and transforming them into feature space along with likelihoods via invertible mapping. The samples with lower likelihoods are selected and further checked by outlier detection using Mahalanobis distance. The augmented samples incorporating with normal samples are used for training a better detector so as to approach decision boundaries. Compared with random transformations, NAF-AL can be interpreted as a likelihood-oriented data augmentation that is more efficient and robust. Extensive experiments show that our approach outperforms existing baselines on multiple time series and tabular datasets, and a real-world application in advanced manufacturing, with significant improvement on anomaly detection accuracy and robustness over the state-of-the-art.

Zhang, Jiaxin↗
DOE OSTI2021

A Sample of Massive Black Holes in Dwarf Galaxies Detected via [Fe x] Coronal Line Emission: Active Galactic Nuclei and/or Tidal Disruption Events

The massive black hole (BH) population in dwarf galaxies ( M BH ≲ 10 5 M ⊙ ) can provide strong constraints on the origin of BH seeds. However, traditional optical searches for active galactic nuclei (AGNs) only reliably detect high-accretion, relatively high-mass BHs in dwarf galaxies with low amounts of star formation, leaving a large portion of the overall BH population in dwarf galaxies relatively unexplored. Here, we present a sample of 81 dwarf galaxies ( M $\star$ ≤ 3 × 10 9 M ⊙ ) with detectable [Fe x]λ6374 coronal line emission indicative of accretion onto massive BHs, only two of which were previously identified as optical AGNs. Here, we analyze optical spectroscopy from the Sloan Digital Sky Survey and find [Fe x]λ6374 luminosities in the range L [Fe x] ≈ 10 36 –10 39 erg s –1 , with a median value of 1.6 × 10 38 erg s –1 . The [Fe x]λ6374 luminosities are generally much too high to be produced by stellar sources, including luminous Type IIn supernovae (SNe). Moreover, based on known SNe rates, we expect at most eight Type IIn SNe in our sample. That said, the [Fe x]λ6374 luminosities are consistent with accretion onto massive BHs from AGNs or tidal disruption events (TDEs). We find additional indicators of BH accretion in some cases using other emission line diagnostics, optical variability, and X-ray and radio emission (or some combination of these). However, many of the galaxies in our sample only have evidence for a massive BH based on their [Fe x]λ6374 luminosities. This work highlights the power of coronal line emission to find BHs in dwarf galaxies missed by other selection techniques and to probe the BH population in bluer, lower-mass dwarf galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Structure and activity of DmmA, a marine haloalkane dehalogenase

DmmA is a haloalkane dehalogenase (HLD) identified and characterized from the metagenomic DNA of a marine microbial consortium. Dehalogenase activity was detected with 1,3-dibromopropane as substrate, with steady-state kinetic parameters typical of HLDs (K{sub m} = 0.24 {+-} 0.05 mM, k{sub cat} = 2.4 {+-} 0.1 s{sup -1}). The 2.2-{angstrom} crystal structure of DmmA revealed a fold and active site similar to other HLDs, but with a substantially larger active site binding pocket, suggestive of an ability to act on bulky substrates. This enhanced cavity was shown to accept a range of linear and cyclic substrates, suggesting that DmmA will contribute to the expanding applications of HLDs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Identifying Abandoned Well Sites Using Database Records and Aeromagnetic Surveys

Oil and natural gas are primary sources of energy in the United States. Improved drilling and extracting techniques have led to a renewed interest in historic oil and gas fields, but limited records of legacy wells make new drilling efforts more difficult, as abandoned wells may provide conduits for liquids and gases to migrate into groundwater reservoirs or the atmosphere. Well finding using aeromagnetic surveys pinpoints the location of steel-cased wells, detecting both active and abandoned wells, including buried casings lacking aboveground markers. Here, we present six aeromagnetic surveys conducted in Pennsylvania and Wyoming as case studies, comparing the magnetic points to locations known in databases. In all study sites, more magnetic points were detected than recorded in databases. Based on differences between theoretical database well counts and the actual number of wells detected in surveys, we estimated the total number of wells in Pennsylvania to be 395 000–466 000 and 181 000–182 000 in Wyoming. Extrapolating to the national level, in this work, we estimate the average number of wells in the continental United States is 6.04 ± 19.97 million wells with 1.16 ± 3.84 million of those designated as abandoned wells, within the range of previous abandoned well count estimations. Although aeromagnetic surveys are limited to detecting steel-cased wells and do not differentiate sites based on well status, this study nevertheless demonstrates the utility of aeromagnetic surveys in well finding efforts across the country and shows limitations in database records of oil and natural gas wells.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Practical reconstruction protocol for quantitative {sup 90}Y bremsstrahlung SPECT/CT

Purpose: To develop a practical background compensation (BC) technique to improve quantitative {sup 90}Y-bremsstrahlung single-photon emission computed tomography (SPECT)/computed tomography (CT) using a commercially available imaging system. Methods: All images were acquired using medium-energy collimation in six energy windows (EWs), ranging from 70 to 410 keV. The EWs were determined based on the signal-to-background ratio in planar images of an acrylic phantom of different thicknesses (2–16 cm) positioned below a {sup 90}Y source and set at different distances (15–35 cm) from a gamma camera. The authors adapted the widely used EW-based scatter-correction technique by modeling the BC as scaled images. The BC EW was determined empirically in SPECT/CT studies using an IEC phantom based on the sphere activity recovery and residual activity in the cold lung insert. The scaling factor was calculated from 20 clinical planar {sup 90}Y images. Reconstruction parameters were optimized in the same SPECT images for improved image quantification and contrast. A count-to-activity calibration factor was calculated from 30 clinical {sup 90}Y images. Results: The authors found that the most appropriate imaging EW range was 90–125 keV. BC was modeled as 0.53× images in the EW of 310–410 keV. The background-compensated clinical images had higher image contrast than uncompensated images. The maximum deviation of their SPECT calibration in clinical studies was lowest (<10%) for SPECT with attenuation correction (AC) and SPECT with AC + BC. Using the proposed SPECT-with-AC + BC reconstruction protocol, the authors found that the recovery coefficient of a 37-mm sphere (in a 10-mm volume of interest) increased from 39% to 90% and that the residual activity in the lung insert decreased from 44% to 14% over that of SPECT images with AC alone. Conclusions: The proposed EW-based BC model was developed for {sup 90}Y bremsstrahlung imaging. SPECT with AC + BC gave improved lesion detectability and activity quantification compared to SPECT with AC only. The proposed methodology can readily be used to tailor {sup 90}Y SPECT/CT acquisition and reconstruction protocols with different SPECT/CT systems for quantification and improved image quality in clinical settings.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Long none coding RNA HOTTIP/HOXA13 act as synergistic role by decreasing cell migration and proliferation in Hirschsprung disease

Long noncoding RNAs (lncRNAs) have been confirmed to be associated with various human diseases. However, whether they are associated with Hirschsprung disease (HSCR) progression remains unclear. In this study, we designed the experiment to explore the relationship between lncRNA HOTTIP and HOXA13, and their pathogenicity to HSCR. Quantitative real-time PCR and Western blot were performed to detect the levels of lncRNA, mRNAs, and proteins in colon tissues from 79 patients with HSCR and 79 controls. Small RNA interference transfection was used to study the function experiments in human 293T and SK-N-BE cell lines. The cell viability and activities were detected by the transwell assays, CCK8 assay, and flow cytometry, respectively. LncRNA HOTTIP and HOXA13 were significantly down-regulated in HSCR compared to the controls. Meanwhile, the declined extent of their expression levels makes sense between two main phenotype of HSCR. SiRNA-mediated knock-down of HOTTIP or HOXA13 correlated with decreased levels of each other and both reduced the cell migration and proliferation without affecting cell apoptosis or cell cycle. Our study demonstrates that aberrant reduction of HOTTIP and HOXA13, which have a bidirectional regulatory loop, may play an important role in the pathogenesis of HSCR. - Highlights: • LncRNA HOTTIP and HOXA13 are both down-regulated in HSCR. • HOTTIP and HOXA13 can regulate each other in 293T and SK-N-BE(2) cell lines. • Both HOTTIP and HOXA13 can decrease cell migration and proliferation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Project report for year 1

In the first year of the project, we developed a fire event tracking system using active fire detections recorded by the Visible Infrared Imaging Radiometer Suite (VIIRS). We employed this algorithm to track all large fires that occurred in California from 2013 to 2020, and created a retrospective Fire Event Data Suite (FEDS) that contains the vector shapes of fire perimeters, active fire fronts, and the locations and fire radiative powers for each fire pixel at 12-hour temporal resolution for each fire event. Using the 2020 Creek Fire as a test bed, we also delineated hourly fire perimeters by combining the FEDS data with the hourly rates of spread derived from Geostationary Operational Environmental Satellite (GOES) Advanced Baseline Imager (ABI) fire data. This dataset will form the basis of the near-real-time hourly fire emissions product that we plan to develop at years 2 and 3 of the project.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Plasma wave measurements in the magnetosphere of Uranus

As Voyager 2 traversed the magnetosphere of Uranus, the plasma-wave instrument detected very significant phenomena related to local wave-particle interactions, radio emissions, and dust impacts. Here the region between the inbound and outbound bow shock traversals (covering a distance of more than 250 Uranus radii) is considered, and it is demonstrated that intense plasma-wave activity developed only in the inner magnetosphere (r less than 12 Uranus radii); this result is similar to that found at Saturn, but it is in marked contrast with the Jupiter case, where very strong wave activity was detected out to distances of 250 Jupiter radii. The Uranus plasma-wave observations in the inner magnetosphere are compared with corresponding results from the Jupiter and Saturn encounters, and it is shown that the Uranus wave measurements are unique in several significant ways. These new aspects include: (1) the detection of a marked inbound-outbound asymmetry and (2) the detection of whistler-mode waves that yield the strongest wave-particle interactions found in outer planet magnetospheres.

Scarf, F. L.↗
DOE OSTI2024

Analyzing Risks of Virtual Private Network Connections

The use of Splunk for analyzing VPN logs is an effective approach for identifying vulnerabilities in network endpoints. Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data, enables organizations to aggregate VPN logs in real-time, providing insights into network activity, user behavior, and potential security risks. By indexing VPN traffic and authentication logs, security teams can track abnormal patterns such as multiple failed login attempts, unusual IP addresses, or unexpected changes in bandwidth usage, all of which could indicate potential vulnerabilities or breaches. With Splunk’s advanced search and reporting capabilities, users can create custom dashboards and alerts to detect suspicious activities. Automated searches can flag endpoints exhibiting unusual behavior, while correlation analysis can identify links between compromised devices and broader network vulnerabilities. In particular, Splunk's machine learning capabilities can be leveraged to predict and prevent threats by identifying trends that might otherwise be missed in traditional log analysis. This proactive approach to monitoring VPN logs allows for the early detection of security weaknesses, enabling rapid response and minimizing potential damage to network integrity. By enhancing endpoint visibility, Splunk plays a crucial role in securing remote connections and safeguarding sensitive information. Additionally, Splunk’s automation and alerting features allow teams to create custom workflows that notify them of vulnerable or misconfigured endpoints identified through Shodan. This synergy between Splunk’s log analysis and Shodan’s device intelligence enhances an organization’s ability to proactively identify and mitigate security risks, improving the overall resilience of their VPN infrastructure.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1988

Sample selection and preservation techniques for the Mars sample return mission

It is proposed that a miniaturized electron spin resonance (ESR) spectrometer be developed as an effective, nondestructivew sample selection and characterization instrument for the Mars Rover Sample Return mission. The ESR instrument can meet rover science payload requirements and yet has the capability and versatility to perform the following in situ Martian sample analyses: (1) detection of active oxygen species, and characterization of Martian surface chemistry and photocatalytic oxidation processes; (2) determination of paramagnetic Fe(3+) in clay silicate minerals, Mn(2+) in carbonates, and ferromagnetic centers of magnetite, maghemite and hematite; (3) search for organic compounds in the form of free radicals in subsoil, and detection of Martian fossil organic matter likely to be associated with carbonate and other sedimentary deposits. The proposed instrument is further detailed.

Tsay, Fun-Dow↗