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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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Unmanned Aircraft Systems (UAS) and Light Detection and Ranging (LiDAR)/Camera Technologies to Detect Avian Events and Other Environmental Measures at Utility- Scale Power Plants (Final Report)
The goal of this project was to develop and validate two complementary, cost-effective remote sensing technologies to monitor avian fatalities at utility-scale solar facilities: fixed platform (Animal Activity Monitoring-AAM) and aerial-based (Uncrewed Aircraft Systems-UAS). This project used these features with machine learning to automate the detection of avian carcasses and nests at solar facilities.
Identification of Serine-Containing Microcystins by UHPLC-MS/MS Using Thiol and Sulfoxide Derivatizations and Detection of Novel Neutral Losses
Microcystins (MCs) are hepatotoxic cyclic heptapeptides produced by cyanobacteria, and their structural diversity has led to the discovery of more than 300 congeners to date. However, with known amino acid combinations, many more MC congeners are theoretically possible, suggesting many remain unidentified. Herein, two novel serine (Ser)-containing MCs were putatively identified in a Lake Erie cyanobacterial harmful algal bloom (cyanoHAB), using high-resolution UHPLC-MS as well as thiol and sulfoxide derivatization procedures. These MCs contain an α,β-unsaturated carbonyl on methyl dehydroalanine (Mdha) residue that undergoes Michael addition to produce a thiol-derivatized MC. Derivatization reactions using various thiolation reagents were followed by MS/MS, and two Python codes were used for data analysis and structural elucidation of MCs. Two novel MCs containing Ser at position 1 (i.e., next to Mdha) were putatively identified as [Ser 1 ]MC-RR and [Ser 1 ]MC-YR. Using thiol- and sulfoxide-modified [Ser 1 ]MCs, identifications were confirmed by the observation of specific neutral losses of the oxidized thiols or sulfoxides in CID-MS/MS spectra in both positive and negative electrospray ionization (ESI) modes. These novel neutral losses are unique for MCs with Mdha and an adjacent Ser residue. In conclusion, data suggest that a gas-phase reaction occurs between oxygen from adjacent Ser residue and sulfur of the Mdha-bonded thiol or sulfoxide, which leads to the formation and detection of stable cyclic MC ions in MS/MS spectra at m/z values corresponding to the loss of oxidized thiols or oxidized sulfoxides from Ser 1 -containing MCs.
Detection of hydrogen isotopes in Zircaloy-4 via femtosecond LIBS
Spatio-temporal mapping of species in a femtosecond laser induced Zircaloy-4 plasma identified conditions well-suited for the detection and analysis of deuterium across a wide range of concentrations.
Detection of hot electrons originating from an upper valley at ∼1.7eV above the Γ valley in wurtzite GaN using electron emission spectroscopy
Using electron emission spectroscopy, measurement and analysis were conducted on the energy distribution of vacuum emitted electrons from electrically driven InGaN/GaN green (peak wavelengths 𝜆 ≈ 515nm) light-emitting diodes (LEDs) with and without a prewell superlattice (SL). Here, we report on the detection of a high-energy upper valley at ∼ 1.7eV above the Γ valley from samples with no prewell SL. We propose that these upper valley electrons originate predominantly from trap-assisted Auger recombination (TAAR) in green LEDs, as the intensity of these peaks is found to have quadratic dependence on the carrier density 𝑛 [see Espenlaub et al., J. Appl. Phys. 126, 184502 (2019)]. The high-energy upper valley peak was not observed in the sample with a prewell SL which is attributed to gettering by the prewell SL of still unidentified impurities that act as TAAR centers.
BOS Gas Detection Pipeline (Integrated System for Optical Hydrogen Detection Using Background Oriented Schlieren and Machine Learning) [SWR-26-007]
This software is the world's first integrated background oriented schlieren and machine learning-based leak detection system. The system provides real time visualization of gas leaks and machine learning interpenetration of leak severity. The software is supplemented by SWR-25-177, "gpu_piv (Graphics Processing Unit Accelerated Background Oriented Schlieren Algorithm", also developed by the National Laboratory of the Rockies. SEE DOECODE ID 182832.
Detectability of Varied Hybridization Scenarios Using Genome-Scale Hybrid Detection Methods
Hybridization events complicate the accurate reconstruction of phylogenies, as they lead to patterns of genetic heritability that are unexpected under traditional, bifurcating models of species trees. This phenomenon has led to the development of methods to infer these varied hybridization events, both methods that reconstruct networks directly, as well as summary methods that predict individual hybridization events from a subset of taxa. However, a lack of empirical comparisons between methods – especially those pertaining to large networks with varied hybridization scenarios – hinders their practical use. Here, we provide a comprehensive review of popular summary methods: TICR, MSCquartets, HyDe, Patterson’s D-Statistic (ABBA-BABA), D3, and Dp. TICR and MSCquartets are based on quartet concordance factors gathered from gene tree topologies and HyDe, Patterson’s D-Statistic, D3, and Dp use site pattern frequencies to identify hybridization events between sets of three taxa. We then use simulated data to address questions of method accuracy and ideal use scenarios by testing methods against complex networks which depict gene flow events that differ in depth (timing), quantity (single vs. multiple, overlapping hybridizations), and rate of gene flow (γ). We find that deeper or multiple hybridization events may introduce noise and weaken the signal of hybridization, leading to higher relative false negative rates across all methods. Despite some forms of hybridization eluding quartet-based detection methods, MSCquartets displays high precision in most scenarios. While HyDe results in high false negative rates when tested on hybridizations involving extinct or unsampled ghost lineages, HyDe is the only method able to identify the direction of hybridization, distinguishing the source parental lineages from recipient hybrid lineages. Lastly, we test the methods on a dataset of ultraconserved elements from the bee subfamily Nomiinae, finding possible hybridization events between clades which correspond to regions of poor support in the species tree estimated in a previous study.
Low Energy LArTPC Signal Detection Using Anomaly Detection
Extracting low-energy signals from LArTPC detectors is useful, for example, for detecting supernova events or calibrating the energy scale with argon-39. However, it is difficult to efficiently extract the signals because of noise. We propose using a 1DCNN to select wire traces that have a signal. This efficiently suppresses the background while still being efficient for the signal. This is then followed by a 1D autoencoder to denoise the wire traces. At that point the signal waveform can be cleanly extracted. In order to make this processing efficient, we implement the two networks on an FPGA. In particular we use hls4ml to produce HLS from the Keras models for both the 1DCNN and the autoencoder. We deploy them on an AMD/Xilinx Alveo U55C using the Vitis software platform.
Passive Detection of Phosphorus in Agricultural Tile Waters Using Reactive Hybrid Anion Exchange Resins
Abstract not provided
Effects of payoff on detection in a symmetric auditory detection task
Signal detection payoff in symmetrical auditory task, studying effect on rates and error analysis
Near optimum delay-line detection filters for serial detection of MSK signals
A method for designing transversal delay-line filter approximations to the matched filter for the serial detection of minimum-shift keyed (MSK) modulated signals is given. Two configurations are characterized in terms of signal-to-noise ratio degradation at a bit error rate (BER) of 10 to the -6th. One is shown to depart less than 0.3 dB from the ideal matched filter performance when its parameter values are optimized. A lumped-element equivalent is also given and shown to provide a degradation of less than 0.4 dB at a BER of 10 to the -6th
Application of thermoluminescence for detection of cascade shower 2: Detection of cosmic ray cascade shower at Mount Fuji
The results of a thermoluminescence (TL) chamber exposed at Mt. Fuji during Aug. '83 - Aug. '84 are reported. The TL signal induced by cosmic ray shower is detected and compared with the spot darkness of X-ray film exposed at the same time.
A Feasibility Study for Perioperative Ventricular Tachycardia Prognosis and Detection and Noise Detection Using a Neural Network and Predictive Linear Operators
To locate the accessory pathway(s) in preexicitation syndromes, epicardial and endocardial ventricular mapping is performed during anterograde ventricular activation via accessory pathway(s) from data originally received in signal form. As the number of channels increases, it is pertinent that more automated detection of coherent/incoherent signals is achieved as well as the prediction and prognosis of ventricular tachywardia (VT). Today's computers and computer program algorithms are not good in simple perceptual tasks such as recognizing a pattern or identifying a sound. This discrepancy, among other things, has been a major motivating factor in developing brain-based, massively parallel computing architectures. Neural net paradigms have proven to be effective at pattern recognition tasks. In signal processing, the picking of coherent/incoherent signals represents a pattern recognition task for computer systems. The picking of signals representing the onset ot VT also represents such a computer task. We attacked this problem by defining four signal attributes for each potential first maximal arrival peak and one signal attribute over the entire signal as input to a back propagation neural network. One attribute was the predicted amplitude value after the maximum amplitude over a data window. Then, by using a set of known (user selected) coherent/incoherent signals, and signals representing the onset of VT, we trained the back propagation network to recognize coherent/incoherent signals, and signals indicating the onset of VT. Since our output scheme involves a true or false decision, and since the output unit computes values between 0 and 1, we used a Fuzzy Arithmetic approach to classify data as coherent/incoherent signals. Furthermore, a Mean-Square Error Analysis was used to determine system stability. The neural net based picking coherent/incoherent signal system achieved high accuracy on picking coherent/incoherent signals on different patients. The system also achieved a high accuracy of picking signals which represent the onset of VT, that is, VT immediately followed these signals. A special binary representation of the input and output data allowed the neural network to train very rapidly as compared to another standard decimal or normalized representations of the data.
TPF-I Planet Detection Testbed: progress in testing exo-planet signal detection
The Planet Detection Testbed is designed to simulate the architecture and operation of a space-borne four telescope nulling interferometer.
Kepler Planet Detection Metrics: Automatic Detection of Background Objects Using the Centroid Robovetter
We present an automated method of identifying background eclipsing binaries masquerading as planet candidates in the Kepler planet candidate catalogs. We codify the manual vetting process for Kepler Objects of Interest (KOIs) described in Bryson et al. (2013) with a series of measurements and tests that can be performed algorithmically. We compare our automated results with a sample of manually vetted KOIs from the catalog of Burke et al. (2014) and find excellent agreement. We test the performance on a set of simulated transits and find our algorithm correctly identifies simulated false positives approximately 50 of the time, and correctly identifies 99 of simulated planet candidates.
Rational design of a uranyl metal-organic framework for the capture and colorimetric detection of organic dyes
A new uranyl containing metal-organic framework, RPL-1: [(UO2)2(C28H18O8)] · H2O (RPL for Radiochemical Processing Laboratory), was prepared, structurally characterized, and the solid-state photoluminescence properties explored. The single crystal X-ray diffraction data reveal the structure of RPL-1 consists of two crystallographically unique three dimensional, interpenetrating nets with a 4,3-connected tbo topology. Each net contains large pores with an average width of 22.8 Å and is formed from monomeric, hexagonal bipyramidal uranyl nodes that are linked via 1,2,4,5-tetrakis(4-carboxyphenyl)benzene (TCPB) linkers. The thermal and photophysical properties of RPL-1 were investigated using thermogravimetric analysis and absorbance, fluorescence, and lifetime spectroscopies. The material displays excellent thermal stability and temperature dependent uranyl and TCBP luminescence. The framework is stable in aqueous media and due to the large void space (constituting 76% of the unit cell by volume) can sequester organic dyes, the uptake of which induces a visible change to the color of the material.
Physical anomaly detection and identification using Cerenkov radiation
Not provided.