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

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

X-ray detected active galactic nuclei in dwarf galaxies at 0 < z < 1

We present a sample of accreting supermassive black holes (SMBHs) in dwarf galaxies at z<1. We identify dwarf galaxies in the NEWFIRM Medium Band Survey with stellar masses of M{sub ⋆}<3×10{sup 9} M{sub ⊙} that have spectroscopic redshifts from the DEEP2 survey and lie within the region covered by deep (flux limit of ∼5×10{sup −17}--6×10{sup −16} erg cm{sup −2} s{sup −1}) archival Chandra X-ray data. From our sample of 605 dwarf galaxies, 10 exhibit X-ray emission consistent with that arising from active galactic nucleus (AGN) activity. If black-hole mass scales roughly with stellar mass, then we expect that these AGNs are powered by SMBHs with masses of ∼10{sup 5}--10{sup 6} M{sub ⊙} and typical Eddington ratios of ∼5%. Furthermore, we find an AGN fraction consistent with extrapolations of other searches of ∼0.6%--3% for 10{sup 9} M{sub ⊙}⩽M{sub ⋆}⩽3×10{sup 9} M{sub ⊙} and 0.1<z<0.6. Our AGN fraction is in good agreement with a semi-analytic model, suggesting that, as we search larger volumes, we may use comparisons between observed AGN fractions and models to understand seeding mechanisms in the early universe.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2017

Enzymatic Activity Detection via Electrochemistry for Enceladus

Electrochemical detection of biological molecules is a pertinent topic and application in many fields such as medicine, environmental spills, and life detection in space. Proteases, a class of molecules of interest in the search for life, catalyze the hydrolysis of peptides. Trypsin, a specific protease, was chosen to investigate an optimized enzyme detection system using electrochemistry. This study aims at providing the ideal functionalization of an electrode that can reliably detect a signal indicative of an enzymatic reaction from an Enceladus sample.

astrobiolog↗
DOE OSTI2021

Malicious activity detection in a memory

A method and apparatus for monitoring a volatile memory in a computer system. Samples of compressed data from locations in the volatile memory in the computer system are read. Data in the volatile memory is reconstructed using the samples of compressed data. The data is an image of the volatile memory. The image enables determining whether an undesired process is present in the volatile memory.

Wheeler, Jason W.↗
DOE OSTI2024

A cell-based Papain-like Protease (PLpro) activity assay for rapid detection of active SARS-CoV-2 infections and antivirals

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants are a continuous threat to human life. An urgent need remains for simple and fast tests that reliably detect active infections with SARS-CoV-2 and its variants in the early stage of infection. Here we introduce a simple and rapid activity-based diagnostic (ABDx) test that identifies SARS-CoV-2 infections by measuring the activity of a viral enzyme, Papain-Like protease (PLpro). The test system consists of a peptide that fluoresces when cleaved by SARS PLpro that is active in crude, unprocessed lysates from human tongue scrapes and saliva. Test results are obtained in 30 minutes or less using widely available fluorescence plate readers, or a battery-operated portable instrument for on-site testing. Proof-of-concept was obtained in a study on clinical specimens collected from patients with COVID-19 like symptoms who tested positive (n = 10) or negative (n = 10) with LIAT RT-PCR using nasal mid turbinate swabs. When saliva from these patients was tested with in-house endpoint RT-PCR, 17 were positive and only 5 specimens were negative, of which 2 became positive when tested 5 days later. PLpro activity correlated in 17 of these cases (3 out of 3 negatives and 14 out of 16 positives, with one invalid specimen). Despite the small number of samples, the agreement was significant (p value = 0.01). Two false negatives were detected, one from a sample with a late Ct value of 35 in diagnostic RT-PCR, indicating that an active infection was no longer present. The PLpro assay is easily scalable and expected to detect all viable SARS-CoV-2 variants, making it attractive as a screening and surveillance tool. Additionally, we show feasibility of the platform as a new homogeneous phenotypic assay for rapid screening of SARS-CoV-2 antiviral drugs and neutralizing antibodies.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1967

Compilation of detection sensitivities in thermal-neutron activation

Detection sensitivities of the chemical elements following thermal-neutron activation have been compiled from the available experimental cross sections and nuclear properties and presented in a concise and usable form. The report also includes the equations and nuclear parameters used in the calculations.

Wahlgren, M. A.↗
DOE OSTI2018

Special Nuclear Material Detection and Monitoring by Environmental Activation Products Detection

Through a series of measurements with a high purity germanium detector, we have established that the past presence of neutron emitting material can be detected by the decay of activation products in aluminum containers, tungsten shielding, and concrete floors even several days after last exposure. The time since last exposure can also be estimated by the gamma-ray detection rate. These findings may lead to interesting new CONOPS in the detection of illicit SNM or the verification of the absence (or presence) of SNM containing objects in facilities and/or transit even after the material has been removed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Exploring the Capabilities of a Machine Learning Algorithm to Detect Space Weather-Significant Emerging Active Regions

Active regions are a source of various phenomena responsible for Space Weather disturbances; therefore, developing a technology for early warning about upcoming magnetic activity is crucial to mitigate its impact. However, observational limitations and the high nonlinearity of processes associated with the accumulation of magnetic flux and its interaction with the surrounding plasma during the emergence through the convection zone make early activity detection a challenging problem. To address these challenges, we developed a physics-driven machine learning model that allows us to detect active regions (ARs) before they become visible on the solar surface by analyzing the power spectra of acoustic oscillations observed by the SDO/HMI instrument. This study is based on a time series of Doppler shift maps of 31x31-degree areas tracked with the Carrington rotation rate for four days before and after the emergence. The Doppler shift time series are processed into the oscillation power maps for four frequency ranges and accompanied by line-of-sight magnetograms and the continuum intensity maps from SDO/HMI. The resulting data are converted into a 1D time series representing the mean temporal variations of these quantities. The redacted time series are used as input to predict AR emergence using the Long Short Term Memory (LSTM) method. The training of the LSTM model is based on 40 ARs, which includes an independent analysis for each sub region that exhibits AR emergence or remains quiet. The emergence of magnetic flux (defined as a decrease of the continuum intensity) was detected with the developed LSTM algorithm from 5 to 48 hours before the reported time by NOAA. The developed model is capable of pointing to the time and location of active region formation. In this presentation, we discuss reasons that impact how early in advance the model can identify the upcoming activity and the possibility of improving the current predictive skills and steps to transition to the operational forecast.

Heliophysics↗
DOE OSTI2025

Nanopore Activity Assays for Detection of Biomarker Protease Activity: Design and Testing of Substrates for Both Nanopore Sequencing and PCR-Based Detection Methods

The work performed in this project has demonstrated the ability to construct proteolytic enzyme substrates that are PCR and sequencing-readable reporter molecules. Specifically, the goal was to detect those reporter molecules via PCR and Oxford Nanopore Technologies MinION sequencing methods following exposure to the biomarker protease thrombin. The assay development focused on binding the constructed peptide-oligonucleotide chimera to immobilized streptavidin. The action of thrombin on the peptide portion of the molecule released the oligonucleotide for detection. Detection of protease activity was demonstrated in a concentration-dependent manner using MALDI-MS, RT-PCR and DNA sequencing. Additional steps to remove background release of reporter molecules during the assay was used to improve the difference in detected oligonucleotide reporter following protease activity. Additional steps in assay development will be to (1) test the assay in an appropriate matrix, (2) investigate detection using additional DNA sequencing platforms and (3) demonstrate multiplexed detection of multiple protease markers in a single reaction.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

A Machine Learning Ready Dataset of Acoustic Power Maps for Detection of Active Region Emergence

The development of an accurate forecast for solar eruptive activity has become increasingly important in order to prevent any potential impact on activities in space and the Earth's environment. It is therefore crucial to detect active regions before they appear on the solar surface and create early warning capabilities for upcoming Space Weather disturbances. In this work, 9TB of solar data (SDO/HMI dopplergrams, magnetograms and continuum intensity maps) involving the emergence of 61 NOAA solar active regions since 2010 were processed using the NASA HECC capabilities. An acoustic power maps time-series dataset was created (for four different frequency ranges and processed to take into account the solar sphere geometric effect ) which can be used for understanding the dynamics of the solar surface and train a variety of ML models. The calculated acoustic power maps carry precursor information associated with the decrease in continuum intensity on the solar surface, verifying older helioseismology research. Our results show that a Long Short-Term Memory (LSTMs) model, with a modest layer depth and the right hyperparameters tuned, when trained on this solar acoustic power maps dataset can predict without false negatives a drop in intensity (associated with the emergence of the active region), up to 18 hours in advance.

SMD↗
DOE OSTI2012

PARAMETER-FREE AUTOMATIC SOLAR ACTIVE REGION DETECTION BY HERMITE FUNCTION DECOMPOSITION

We present a new method for the automated detection of sunspots and active regions (ARs) from full-disk observations of the photospheric Stokes vector. The algorithm relies on a Hermite function decomposition of observed Stokes polarization profiles as a function of position on the solar disk. This approach is unique in that it requires no user-defined tunable parameters, like intensity or magnetic field thresholds, and utilizes no information traditionally exploited by other detection schemes to signal the presence of an AR. It is truly a black-box approach, utilizing a self-consistent statistical analysis of the Hermite coefficients. We present the method and show the results of its application to Synoptic Optical Long-term Investigations of the Sun Vector Spectromagnetograph full-disk observations. Detection efficiency is presented for a one-month time series of daily photospheric observations, and we derive a skill-score for the method during this time period.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Evolution of archaeal Rib7 and eubacterial RibG reductases in riboflavin biosynthesis: Substrate specificity and cofactor preference

Highlights: • The first archaeal dimeric structures of Methanosarcina mazei Rib7 are reported. • Our studies show the divergences between archaeal and eubacterial Rib7 reductases. • Asp33 together with Arg36, had been evolved to ensure the substrate specificity. • Unexpectedly, an endogenous NADPH cofactor is observed in M. mazei Rib7. • The endogenous NADPH greatly enhances the structural stability of archaeal Rib7. Archaeal/fungal Rib7 and eubacterial RibG possess a reductase domain for ribosyl reduction in the second and third steps, respectively, of riboflavin biosynthesis. These enzymes are specific for an amino and a carbonyl group of the pyrimidine ring, respectively. Here, several crystal structures of Methanosarcina mazei Rib7 are reported at 2.27–1.95 Å resolution, which are the first archaeal dimeric Rib7 structures. Mutational analysis displayed that no detectable activity was observed for the Bacillus subtilis RibG K151A, K151D, and K151E mutants, and the M. mazei Rib7 D33N, D33K, and E156Q variants, while 0.1–0.6% of the activity was detected for the M. mazei Rib7 N9A, S29A, D33A, and D57N variants. Our results suggest that Lys151 in B. subtilis RibG, while Asp33 together with Arg36 in M. mazei Rib7, ensure the specific substrate recognition. Unexpectedly, an endogenous NADPH cofactor is observed in M. mazei Rib7, in which the 2′-phosphate group interacts with Ser88, and Arg91. Replacement of Ser88 with glutamate eliminates the endogenous NADPH binding and switches preference to NADH. The lower melting temperature of ∼10 °C for the S88E and R91A mutants suggests that nature had evolved a tightly bound NADPH to greatly enhance the structural stability of archaeal Rib7.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Nucleic Acid-Based Detection Protease Activity

Proteases include clinically relevant markers for clotting disorders, certain cancers as well as toxins. Assays for protease activity often use designed peptides mimicking natural substrates and detection with colorometric and fluorescence-based detection that is difficult to multiplex without expensive and resource demanding instruments. This work demonstrates detection of proteolytic activity using PCR and sequencing-readable reporter molecules. The assay development focused on binding the constructed peptide-oligonucleotide chimera to immobilized streptavidin. Thrombin, an essential component of the clotting cascade, was used as a model system for testing peptide substrate recognition and release of a designed oligonucleotide for detection. Detection of protease activity was demonstrated in a concentration-dependent manner using MALDI-MS, RT-PCR and DNA sequencing.

Wunschel, David S [Pacific Northwest National Labo↗
DOE OSTI2016

Information flow for security in control systems

This paper considers the development of information flow analyses to support resilient design and active detection of adversaries in cyber physical systems (CPS). CPS security, though well studied, suffers from fragmentation. In this paper, we consider control systems as an abstraction of CPS. Here, we use information flow analysis, a well established set of methods developed in software security, to obtain a unified framework that captures and extends results in control system security. Specifically, we propose the Kullback Liebler (KL) divergence as a causal measure of information flow, which quantifies the effect of adversarial inputs on sensor outputs. We show that the proposed measure characterizes the resilience of control systems to specific attack strategies by relating the KL divergence to optimal detection. We then relate information flows to stealthy attack scenarios where an adversary can bypass detection. Finally, this article examines active detection mechanisms where a defender intelligently manipulates control inputs or the system itself to elicit information flows from an attacker's malicious behavior. In all previous cases, we demonstrate an ability to investigate and extend existing results through the proposed information flow analyses.

Weerakkody, Sean↗
NASA NTRS2023

Quantifying Burned Area of Wildfires in the Western United States From Polar-Orbiting and Geostationary Satellite Active-Fire Detections

Background : Accurately estimating burned area from satellites is key to improving biomass burning emission models, studying fire evolution and assessing environmental impact. Previous studies have found that current methods for estimating burned area of fires from satellite active-fire data do not always provide an accurate estimate. Aims and Methods : In this work, we develop a novel algorithm to estimate hourly accumulated burned area based on the area from boundaries of non-convex polygons containing the accumulated Visible Infrared Imaging Radiometer Suite (VIIRS)active-fire detections. Hourly time series are created by combining VIIRS estimates with fire radiative power (FRP) estimates from GOES-17 data. Conclusions, Key Results and Implication : We evaluate the performance of the algorithm for both accumulated and change in burned area between airborne observations, and specifically examine sensitivity to the choice of the parameter controlling how much the boundary can shrink towards the interior of the area polygon. Results of the hourly accumulation of burned area for multiple fires from 2019 and 2020 generally correlate strongly with airborne infrared (IR) observations collected by the United States Forest Service National Infrared Operations (NIROPS), exhibiting correlation coefficient values usually greater than 0.95 and errors <20%.

burned area↗