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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

In Search of Optimum Fresh-Cut Raw Material: Using Computer Vision Systems as a Sensory Screening Tool for Browning-Resistant Romaine Lettuce Accessions

The popularity of ready-to-eat (RTE) salads has prompted novel technology to prolong the shelf life of their ingredients. Fresh-cut romaine lettuce is widely used in RTE salads; however, its tendency to quickly discolor continues to be a challenge for the industry. Selecting the ideal lettuce accessions for use in RTE salads is essential to ensure maximum shelf life, and it is critical to have a practical way to assess and compare the quality of multiple lettuce accessions that are being considered for use in fresh-cut applications. Thus, in this work we aimed to determine whether a computer vision system (CVS) composed of image acquisition, processing, and analysis could be effective to detect visual quality differences among 16 accessions of fresh-cut romaine lettuce during postharvest storage. The CVS involved a post-capturing color correction, effective image segmentation, and calculation of a browning index, which was tested as a predictor of quality and shelf life of fresh-cut romaine lettuce. The results demonstrated that machine vision software can be implemented to replace or supplement the scoring of a trained panel and instrumental quality measurements. Overall visual quality, a key sensory parameter that determines food preferences and consumer behavior, was highly correlated with the browning index, with a Pearson correlation coefficient of −0.85. Other important sensory decision parameters were also strongly or moderately correlated with the browning index, with Pearson correlation coefficients of −0.84 for freshness, 0.79 for off odor, and 0.57 for browning. The ranking of the accessions according to quality acceptability from the sensory evaluation produced a similar pattern to those obtained with the CVS. This study revealed that multiple lettuce accessions can be effectively benchmarked for their performance as fresh-cut sources via a CVS-based method. Future opportunities and challenges in using machine vision image processing to predict consumer preferences for RTE salad greens is also discussed.

Agriculture↗
NASA NTRS2005

Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery

The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Evaluation Studies↗
DOE OSTI2019

Imaging findings of hemorrhagic hepatic cysts with enhancing mural nodules

Purpose: This study aimed to evaluate the clinical and radiological findings of hemorrhagic hepatic cysts with enhancing mural nodules. Methods: The radiology databases of five facilities were retrospectively searched for reports indicating hemorrhagic hepatic cysts or hepatic cystic tumors. Cases of hemorrhagic hepatic cysts with enhancing mural nodules based on pathological or radiological findings were identified and reviewed. Results: We included 14 cases (11 female and 3 male) with a mean patient age of 72.6 years. Up until the enhancing mural nodules were detected, the cysts had decreased in size in all ten cases for which radiological imaging was available for a period of > 3 years previous to detection. Dynamic contrast-enhanced CT or MRI showed focal enhancement in the early phase and progressive centrifugal enhancement in the delayed phase in all 16 mural nodules ≥ 10 mm in diameter. Thirteen of 14 MRI assessable enhancing mural nodules ≥ 10 mm in diameter showed a hypointense rim with central hyperintensity on T2-weighted imaging. All cases showed calcification of the cyst wall. In the three referred cases, {sup 18}F-fluorodeoxyglucose (FDG) positron emission tomography/CT demonstrated no intense FDG uptake in the enhancing mural nodules. In the four resected cases, histopathology of the enhancing mural nodules revealed neovascularization within an organized hematoma, including extensive dilated vessels and hemangioma-like lesions. Conclusions: Features including a decrease in cyst size, a progressive centrifugal enhancing pattern on dynamic contrast-enhanced CT or MRI, a hypointense rim with central hyperintensity on T2-weighted MRI, and cyst wall calcification may indicate a hemorrhagic hepatic cyst.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

OPEN CLUSTERS IN THE MILKY WAY OUTER DISK: NEWLY DISCOVERED AND UNSTUDIED CLUSTERS IN THE SPITZER GLIMPSE-360, CYG-X, AND SMOG SURVEYS

Open stellar clusters are extremely valuable probes of Galactic structure, star formation, kinematics, and chemical abundance patterns. Near-infrared (NIR) data have enabled the detection of hundreds of clusters hidden from optical surveys, and mid-infrared (MIR) data are poised to offer an even clearer view into the most heavily obscured parts of the Milky Way. We use new MIR images from the Spitzer GLIMPSE-360, Cyg-X, and SMOG surveys to visually identify a large number of open cluster candidates in the outer disk of the Milky Way (65 Degree-Sign < l < 265 Degree-Sign ). Using NIR color-magnitude diagrams, stellar isochrones, and stellar reddening estimates, we derive cluster parameters (metallicity, distance, reddening) for those objects without previous identification and/or parameters in the literature. In total, we present coordinates and sizes of 20 previously unknown open cluster candidates; for 7 of these we also present metallicity, distance, and reddening values. In addition, we provide the first estimates of these values for nine clusters that had been previously cataloged. We compare our cluster sizes and other derived parameters to those in the open cluster catalog of Dias et al. and find strong similarities except for a higher mean reddening for our objects, which signifies our increased detection sensitivity in regions of high extinction. The results of this cluster search and analysis demonstrate the ability of MIR imaging and photometry to augment significantly the current census of open clusters in the Galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Panels of HIV-1 Subtype C Env Reference Strains for Standardized Neutralization Assessments

In the search for effective immunologic interventions to prevent and treat HIV-1 infection, standardized reference reagents are a cost-effective way to maintain robustness and reproducibility among immunological assays. To support planned and ongoing studies where clade C predominates, here we describe three virus panels, chosen from 200 well-characterized clade C envelope (Env)-pseudotyped viruses from early infection. All 200 Envs were expressed as a single round of replication pseudoviruses and were tested to quantify neutralization titers by 16 broadly neutralizing antibodies (bnAbs) and sera from 30 subjects with chronic clade C infections. We selected large panels of 50 and 100 Envs either to characterize cross-reactive breadth for sera identified as having potent neutralization activity based on initial screening or to evaluate neutralization magnitude-breadth distributions of newly isolated antibodies. We identified these panels by downselection after hierarchical clustering of bnAb neutralization titers. The resulting panels represent the diversity of neutralization profiles throughout the range of virus sensitivities identified in the original panel of 200 viruses. A small 12-Env panel was chosen to screen sera from vaccine trials or natural-infection studies for neutralization responses. We considered panels selected by previously described methods but favored a computationally informed method that enabled selection of viruses representing diverse neutralization sensitivity patterns, given that we do not a priori know what the neutralization-response profile of vaccine sera will be relative to that of sera from infected individuals. The resulting 12-Env panel complements existing panels. Use of standardized panels enables direct comparisons of data from different trials and study sites testing HIV-1 clade C-specific products. HIV-1 group M includes nine clades and many recombinants. Clade C is the most common lineage, responsible for roughly half of current HIV-1 infections, and is a focus for vaccine design and testing. Standard reference reagents, particularly virus panels to study neutralization by antibodies, are crucial for developing cost-effective and yet rigorous and reproducible assays against diverse examples of this variable virus. We developed clade C-specific panels for use as standardized reagents to monitor complex polyclonal sera for neutralization activity and to characterize the potency and breadth of cross-reactive neutralization by monoclonal antibodies, whether engineered or isolated from infected individuals. We chose from 200 southern African, clade C envelope-pseudotyped viruses with neutralization titers against 16 broadly neutralizing antibodies and 30 sera from chronic clade C infections. We selected panels to represent the diversity of bnAb neutralization profiles and Env neutralization sensitivities. Finally, use of standard virus panels can facilitate comparison of results across studies and sites.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2001

The Mountains of Io: Global and Geological Perspectives from Voyager and Galileo

To search for local and global scale geologic associations that may be related to the internal dynamics of Io, we have completed a global catalog of all mountains and volcanic centers. We have identified 115 mountain structures (covering approx. 3% of the surface) and 541 volcanic centers, including paterae (calderas and dark spots) and shield volcanoes. The average length of an Ionian mountain is 157 km, with the longest being 570 km. The mean height of Ionian mountains is 6.3 km, and the highest known mountain is Boosaule Montes (17.5 +/- 3 km). Five basic morphologic types of mountains have been identified; mesa, plateau peak, ridge, and massif. Very few mountains bear any physical similarity. to classic volcanic landforms, but many resemble flatiron mountains on Earth and are interpreted as tilted crustal blocks. This would be consistent with the hypothesis that most mountains are thrust blocks formed as a result of compressive stresses built up in the lower crust due to the global subsidence of volcanic layers as they are buried over time. More than one mechanism may be responsible for all Ionian mountains, however. The proximity of some mountains to paterae may indicate a direct link between some mountains and volcanism, although it is not always clear which came first. In contrast to earlier studies, a pronounced bimodal pattern is observed in the global distribution of both mountains and volcanic centers. The regions of highest areal densities of volcanic centers are near the sub- and anti-Jovian regions, but are offset roughly 90deg in longitude from the two, regions of greatest concentration of mountains. This anticorrelation may indicate the overprinting of a second stress field on the global compressive stresses due to subsidence. The bimodal distribution of volcanic centers and mountains is consistent with models of asthenospheric tidal heating and internal convection developed by Tackley et al.Over regions of mantle upwelling, compressive stresses in the lower crust induced by global subsidence might be reduced, encouraging volcanism and discouraging mountain building. In regions of mantle downwelling, these compressive stresses in the lower crust might be increased, discouraging volcanism and encouraging mountain building. Alternatively, the global pattern may be related to possible (but undocumented) nonsynchronous rotation of lo, which would produce two regions each of compression and extension in the crust. Evidence of layering and of mass wasting, including landslides, block sliding, debris aprons and downslope creep, on Ionian mountains suggests that the crust of Io is essentially a layered stack of partially consolidated volcanic lavas and plume deposits, becoming more consolidated with depth. The lower crust especially may also be ductily deformed, punctuated by volcanic intrusions and faulting at paterae, and broken into blocks, some of which have been uplifted to form mountains.

Schenk, Paul↗
DOE OSTI2024

From phase decomposition to evaporation: A multi-modal evaluation of thermally degraded model lightweight high-entropy alloy

Lightweight high-entropy alloys (LHEAs) have the potential to replace conventional lightweight materials due to their superior mechanical properties and thermal stability. However, the thermal degradation pattern of LHEAs from phase decomposition to evaporation is not clear. We develop a new Al-based dual phase (FCC + HCP) LHEA—AlTi 0.45 CuZn, and further investigate its thermal degradation behavior for potential high-temperature structural applications. Using multimodal advanced characterization techniques such as differential scanning calorimetry/thermogravimetric analysis, scanning/transmission electron microscopy, and synchrotron X-ray diffraction/pair distribution function (XRD/PDF), a sequence of thermal degradation events beyond the thermal phase stability limit—between 250 and 360 °C—is observed. These include phase decomposition at ~360 °C, Zn evaporation at ~750 °C, and LHEA melting at 880 °C which results in ~25% cumulative weight loss. The formation of Al-Ti phase off the AlTi 0.45 CuZn matrix is due to the largest negative mixing enthalpy for Al-Ti than other binary pairs. Similarly, Zn evaporation from AlTi 0.45 CuZn LHEA is due to its faster evaporation rate than other constituent elements. The high-resolution synchrotron XRD and PDF results support the aforementioned observations; in addition, they reveal local atomic arrangements, local strain, and sluggish grain growth in the LHEA. Among other LHEAs of close density range (5.55 ≤ ρ ≤ 5.85 g/cc), the investigated LHEA exhibits outstanding nano-indentation hardness values due to the coupled grain size effect and HCP phase strengthening of the FCC matrix. As the search for LHEAs for lightweight applications grows, this study shows the potential use of AlTi 0.45 CuZn LHEA for structural applications even at elevated temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Comparative genomics reveals phylogenetic distribution patterns of secondary metabolites in Amycolatopsis species

Background: Genome mining tools have enabled us to predict biosynthetic gene clusters that might encode compounds with valuable functions for industrial and medical applications. With the continuously increasing number of genomes sequenced, we are confronted with an overwhelming number of predicted clusters. In order to guide the effective prioritization of biosynthetic gene clusters towards finding the most promising compounds, knowledge about diversity, phylogenetic relationships and distribution patterns of biosynthetic gene clusters is necessary. Results: Here, we provide a comprehensive analysis of the model actinobacterial genus Amycolatopsis and its potential for the production of secondary metabolites. A phylogenetic characterization, together with a pan-genome analysis showed that within this highly diverse genus, four major lineages could be distinguished which differed in their potential to produce secondary metabolites. Furthermore, we were able to distinguish gene cluster families whose distribution correlated with phylogeny, indicating that vertical gene transfer plays a major role in the evolution of secondary metabolite gene clusters. Still, the vast majority of the diverse biosynthetic gene clusters were derived from clusters unique to the genus, and also unique in comparison to a database of known compounds. Our study on the locations of biosynthetic gene clusters in the genomes of Amycolatopsis’ strains showed that clusters acquired by horizontal gene transfer tend to be incorporated into non-conserved regions of the genome thereby allowing us to distinguish core and hypervariable regions in Amycolatopsis genomes. Conclusions: Using a comparative genomics approach, it was possible to determine the potential of the genus Amycolatopsis to produce a huge diversity of secondary metabolites. Furthermore, the analysis demonstrates that horizontal and vertical gene transfer play an important role in the acquisition and maintenance of valuable secondary metabolites. Our results cast light on the interconnections between secondary metabolite gene clusters and provide a way to prioritize biosynthetic pathways in the search and discovery of novel compounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Reproductive and leaf litterfall fluxes in forest ecosystem sites globally (1950-2022)

Forest allocation of net primary productivity (NPP) to reproduction is poorly quantified globally, despite its critical role in forest regeneration and a well-supported trade-off with allocation to growth. Although field measurements of total NPP are rare, our work finds that a proxy for reproductive carbon allocation constructed from leaf (L) and reproductive (R) litterfall fluxes, R/(R+L), is strongly correlated with R/NPP, facilitating analysis across a wide range of sites where biometric estimates of NPP are not available (R² = 0.85; Hanbury-Brown et al., 2022, Ward et al., in prep). To investigate relationships between ecosystem-scale reproductive allocation (RA) and climate, soil fertility, and stand age gradients, we conducted a literature search and synthesized 824 observations of annual average leaf and reproductive litterfall fluxes across forest sites globally. The zip file includes 1) a folder Data/ containing the litterfall data ("GlobalForestRA_data.csv") and metadata ("GlobalForestRA_metadata.doc") files. The data file includes geographic coordinates, long-term mean annual temperature and precipitation (1970-2000, extracted from WorldClim2.1), leaf and reproductive litterfall fluxes, sampling interval and protocols, forest characteristics (dominant leaf morphology, information pertaining to forest age and successional stage, and disturbance history) and soil properties (% sand, %silt, %clay, total phosphorus (P), nitrogen (N), cation exchange capacity (CEC) and pH) extracted from SoilGrids250 and from on-site measurements, where available. The metadata file contains information about each variable reported in the data file, including data sources, processing methods, and all references. The Data folder contains two additional files used to create Figure 1; these are described in greater detail in the README.2) R scripts GloalForestRA_analysis.r and GlobalForestRA_SI.r and a folder /Functions used to produce results, figures, and tables in the manuscript Ward et al. (in press)3) a README file describing how the data and R scripts can be used to reproduce statistical results, figures, and tables found in the manuscript. Ward et al. (in press)This repository can also be found at: https://github.com/r-ward/Global_Analysis_ForestRA.Ward, R.E., Zhang-Zheng, H. Aernethy, K., Adu-Bredu, S., Arroyo, L., Bailey, A. et al. (in press). Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally. Ecology Letters. Hanbury-Brown, A.R., Ward, R.E. & Kueppers, L.M. (2022). Forest regeneration within Earth system models: current process representations and ways forward. New Phytol., 235, 20–40.Ward et al. (2025), Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally, in prep.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Discovering Mercury Protein Modifications in Whole Proteomes Using Natural Isotope Distributions Observed in Liquid Chromatography-Tandem Mass Spectrometry

The identification of peptides that result from post-translational modifications is critical for understanding normal pathways of cellular regulation as well as identifying damage from, or exposures to xenobiotics, i.e. the exposome. However, because of their low abundance in proteomes, effective detection of modified peptides by mass spectrometry (MS) typically requires enrichment to eliminate false identifications. We present a new method for confidently identifying peptides with mercury (Hg)-containing adducts that is based on the influence of mercury's seven stable isotopes on peptide isotope distributions detected by high-resolution MS. Using a pure protein and E. coli cultures exposed to phenyl mercuric acetate, we show the pattern of peak heights in isotope distributions from primary MS single scans efficiently identified Hg adducts in data from chromatographic separation coupled with tandem mass spectrometry with sensitivity and specificity greater than 90%. Isotope distributions are independent of peptide identifications based on peptide fragmentation (e.g. by SEQUEST), so both methods can be combined to eliminate false positives. Summing peptide isotope distributions across multiple scans improved specificity to 99.4% and sensitivity above 95%, affording identification of an unexpected Hg modification. We also illustrate the theoretical applicability of the method for detection of several less common elements including the essential element, selenium, as selenocysteine in peptides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

The Octavius1500 2D ion chamber array and its associated phantoms: Dosimetric characterization of a new prototype

Purpose: The purpose of the study is to characterize the prototype of the new Octavius1500 (PTW, Freiburg, Germany) 2D ion chamber array, covering its use in different phantom setups, from the most basic solid water sandwich setup to the more complex cylindrical Octavius{sup ®} 4D (Oct4D) (PTW) phantom/detector combination. The new detector houses nearly twice the amount of ion chambers as its predecessors (Seven29 and Octavius729), thereby tackling one of the most important limitations of ion chamber (or diode) arrays, namely the limited detector density. The 0.06 cm{sup 3} cubic ion chambers are now arranged in a checkerboard pattern, leaving no lines (neither longitudinally nor laterally) without detectors. Methods: All measurements were performed on a dual energy (6 MV and 18 MV) iX Clinac (Varian Medical Systems, Palo Alto, CA) and all calculations were done in the Eclipse treatment planning system (Varian) with the Anisotropic Analytical Algorithm. First, the basic characteristics of the 2D array, such as measurement stability, dose rate dependence and dose linearity were investigated in the solid water sandwich setup. Second, the directional dependence was assessed to allow the evaluation of the new Octavius2D phantom (Oct2D{sup 1500}) for planar verification measurements of composite plans. Third, measurements were performed in the Oct4D phantom to evaluate the impact of the increased detector density on the accuracy of the volumetric dose reconstruction. Results: While showing equally good dose linearity and dose rate independence, the Octavius1500 outperforms the previous models because of its instantaneous measurement stability and its twofold active area coverage. Orthogonal field-by-field measurements immediately benefit from the increased detector density. The 3.9 cm wide compensation cavity in the new Oct2D{sup 1500} phantom prototype adequately corrects for directional dependence from the rear, resulting in good agreement within the target dose. Discrepancies may arise towards the sides of the array because of uncompensated lateral beam incidence. The beneficial impact of the detector density is most prominent in the Oct4D system, for which the average pass rate (PR) is now nearly 100% (99.31 ± 0.37) when using gamma criteria of 2%G,2 mm (10% dose threshold). In search of gamma analysis criteria that are not too lenient to detect possibly relevant deviations, the authors conclude that for our radiotherapy environment, the authors choose to adopt 3%L,3 mm PR97% (threshold 10%) criteria for the Oct2D{sup 1500}/Octavius1500 system and 2%L,3 mm PR97% (threshold 10%) for the Oct4D/Octavius1500 system. These are first line pass/check criteria and plans that fail are not necessarily rejected, but submitted to a more detailed investigation. Conclusions: When irradiated from the front, the Octavius1500 array has two main advantages over its 729 predecessors: its instantaneous measurement stability and-–most importantly—its twofold detector density. In the Oct2D1500 phantom, these advantages are counterbalanced by the more pronounced directional dependence. The measurement-based 3D dose reconstruction in the Oct4D system, however, benefits considerably from the higher detector density in the checkerboard panel design.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Eye-tracking of nodule detection in lung CT volumetric data

Purpose: Signal detection on 3D medical images depends on many factors, such as foveal and peripheral vision, the type of signal, and background complexity, and the speed at which the frames are displayed. In this paper, the authors focus on the speed with which radiologists and naïve observers search through medical images. Prior to the study, the authors asked the radiologists to estimate the speed at which they scrolled through CT sets. They gave a subjective estimate of 5 frames per second (fps). The aim of this paper is to measure and analyze the speed with which humans scroll through image stacks, showing a method to visually display the behavior of observers as the search is made as well as measuring the accuracy of the decisions. This information will be useful in the development of model observers, mathematical algorithms that can be used to evaluate diagnostic imaging systems. Methods: The authors performed a series of 3D 4-alternative forced-choice lung nodule detection tasks on volumetric stacks of chest CT images iteratively reconstructed in lung algorithm. The strategy used by three radiologists and three naïve observers was assessed using an eye-tracker in order to establish where their gaze was fixed during the experiment and to verify that when a decision was made, a correct answer was not due only to chance. In a first set of experiments, the observers were restricted to read the images at three fixed speeds of image scrolling and were allowed to see each alternative once. In the second set of experiments, the subjects were allowed to scroll through the image stacks at will with no time or gaze limits. In both static-speed and free-scrolling conditions, the four image stacks were displayed simultaneously. All trials were shown at two different image contrasts. Results: The authors were able to determine a histogram of scrolling speeds in frames per second. The scrolling speed of the naïve observers and the radiologists at the moment the signal was detected was measured at 25–30 fps. For the task chosen, the performance of the observers was not affected by the contrast or experience of the observer. However, the naïve observers exhibited a different pattern of scrolling than the radiologists, which included a tendency toward higher number of direction changes and number of slices viewed. Conclusions: The authors have determined a distribution of speeds for volumetric detection tasks. The speed at detection was higher than that subjectively estimated by the radiologists before the experiment. The speed information that was measured will be useful in the development of 3D model observers, especially anthropomorphic model observers which try to mimic human behavior.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Improved molecular level identification of organic compounds using comprehensive two-dimensional chromatography, dual ionization energies and high resolution mass spectrometry

A new analytical methodology combining comprehensive two-dimensional gas chromatography (GC×GC), dual ionization energies and high resolution time of flight mass spectrometry has been developed that improves molecular level identification of organic compounds in complex environmental samples. GC×GC maximizes compound separation providing cleaner mass spectra by minimizing erroneous fragments from interferences and co-eluting peaks. Traditional electron ionization (EI, 70 eV) provides MS fragmentation patterns that can be matched to published EI MS libraries while vacuum ultraviolet photoionization (VUV, 10.5 eV) yields MS with reduced fragmentation enhancing the abundance of the molecular ion providing molecular formulas when combined with high resolution mass spectrometry. We demonstrate this new approach by applying it to a sample of organic aerosol. In this sample, 238 peaks were matched to EI MS library data with FM ≥ 800 but a fifth (42 compounds) were determined to be incorrectly identified because the molecular formula was not confirmed by the VUV MS data. This highlights the importance of using a complementary technique to confirm compound identifications even for peaks with very good matching statistics. In total, 171 compounds were identified by EI MS matching to library spectra with confirmation of the molecular formula from the high resolution VUV MS data and were not dependent on the matching statistics being above a threshold value. A large number of unidentified peaks were still observed with FM < 800, which in routine analysis would typically be neglected. Where possible, these peaks were assigned molecular formulas from the VUV MS data (211 in total). In total, the combination of EI and VUV MS data provides more than twice as much molecular level peak information than traditional approaches and improves confidence in the identification of individual organic compounds. The molecular formula data from the VUV MS data was used, in conjunction with GC×GC retention times and the observed EI MS, to generate a new, searchable EI MS library compatible with the standard NIST MS search program. This library is deliberately dynamic and editable so that other end users can add new entries and update existing entries as new information becomes available.A new analytical methodology has been developed to improve molecular level identification of organic compounds in complex samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Mapping Organic-Mineral Associations in Jezero crater

The search for potential signs of life on Mars, a primary aim of the Mars 2020 mission, is greatly informed by the detection of organic matter1. The presence of organic matter also provides key information about the habitability and biological potential of the planet throughout its history. The Perseverance rover was designed for in situ science with the ability to collect a suite of promising samples for eventual return to Earth. One of its instruments, Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC), is a deep ultraviolet (DUV) Raman and fluorescence spectrometer designed to map the distribution of organic molecules and minerals on rock surfaces at a resolution of 100 μm2. With its unique spectral mapping capabilities, SHERLOC enables a novel understanding of organic-mineral relationships on Mars to better determine their formation, deposition, and preservation mechanisms. The rover’s landing site within Jezero crater combines a high potential for past habitability as the site of an ancient lake basin with a diverse set of minerals, including carbonates and clays, that may preserve organic materials and potential biosignatures. The Jezero crater floor includes three formations (fm); two of these, Máaz and Séítah, were explored as part of the mission’s first campaign. Here, we report the detection of multiple species of aromatic organic molecules using Raman and fluorescence spectroscopy across ten targets in the two formations. This is the first evidence of organic molecules in Martian materials obtained using Raman spectroscopy, and among the first using fluorescence spectroscopy, beyond Earth3. We report specific spatial patterns and classes of organic molecules in these compositionally distinct formations, potentially indicating different fates of carbon in these environments. Our findings indicate that there is a diversity of aromatic molecules prevalent on the Martian surface and these materials persist despite exposure to surface conditions. These organic molecules are largely found within minerals linked to aqueous processes, suggesting that these processes may have had a key role in organic synthesis, transport from their point of origin, or preservation.

Sunanda Sharma↗
DOE OSTI2012

Detection and Characterization of Underground Facilities by Stochastic Inversion and Modeling of Data from the New Generation of Synthetic Aperture Satellites (Final Report)

Many clandestine development and production activities can be conducted underground to evade surveillance. The purpose of the study reported here was to develop a technique to detect underground facilities by broad-area search and then to characterize the facilities by inversion of the collected data. This would enable constraints to be placed on the types of activities that would be feasible at each underground site, providing a basis the design of targeted surveillance and analysis for more complete characterization. Excavation of underground cavities causes deformation in the host material and overburden that produces displacements at the ground surface. Such displacements are often measurable by a variety of surveying or geodetic techniques. One measurement technique, Interferometric Synthetic Aperture Radar (InSAR), uses data from satellite-borne (or airborne) synthetic aperture radars (SARs) and so is ideal for detecting and measuring surface displacements in denied access regions. Depending on the radar frequency and the acquisition mode and the surface conditions, displacement maps derived from SAR interferograms can provide millimeter- to centimeter-level measurement accuracy on regional and local scales at spatial resolution of {approx}1-10 m. Relatively low-resolution ({approx}20 m, say) maps covering large regions can be used for broad-area detection, while finer resolutions ({approx}1 m) can be used to image details of displacement fields over targeted small areas. Surface displacements are generally expected to be largest during or a relatively short time after active excavation, but, depending on the material properties, measurable displacement may continue at a decreasing rate for a considerable time after completion. For a given excavated volume in a given geological setting, the amplitude of the surface displacements decreases as the depth of excavation increases, while the area of the discernable displacement pattern increases. Therefore, the ability to detect evidence for an underground facility using InSAR depends on the displacement sensitivity and spatial resolution of the interferogram, as well as on the size and depth of the facility and the time since its completion. The methodology development described in this report focuses on the exploitation of synthetic aperture radar data that are available commercially from a number of satellite missions. Development of the method involves three components: (1) Evaluation of the capability of InSAR to detect and characterize underground facilities ; (2) inversion of InSAR data to infer the location, depth, shape and volume of a subsurface facility; and (3) evaluation and selection of suitable geomechanical forward models to use in the inversion. We adapted LLNL's general-purpose Bayesian Markov Chain-Monte Carlo procedure, the 'Stochastic Engine' (SE), to carry out inversions to characterize subsurface void geometries. The SE performs forward simulations for a large number of trial source models to identify the set of models that are consistent with the observations and prior constraints. The inverse solution produced by this kind of stochastic method is a posterior probability density function (pdf) over alternative models, which forms an appropriate input to risk-based decision analyses to evaluate subsequent response strategies. One major advantage of a stochastic inversion approach is its ability to deal with complex, non-linear forward models employing empirical, analytical or numerical methods. However, while a geomechanical model must incorporate adequate physics to enable sufficiently accurate prediction of surface displacements, it must also be computationally fast enough to render the large number of forward realizations needed in stochastic inversion feasible. This latter requirement prompted us first to investigate computationally efficient empirical relations and closed-form analytical solutions. However, our evaluation revealed severe limitations in the ability of existing empirical and analytical forms to predict deformations from underground cavities with an accuracy consistent with the potential resolution and precision of InSAR data. We followed two approaches to overcoming these limitations. The first was to develop a new analytical solution for a 3D cavity excavated in an elastic half-space. The second was to adapt a fast parallelized finite element method to the SE and evaluate the feasibility of using in the stochastic inversion. To date we have demonstrated the ability of InSAR to detect underground facilities and measure the associated surface displacements by mapping surface deformations that track the excavation of the Los Angeles Metro system. The Stochastic Engine implementation has been completed and undergone functional testing.

58 GEOSCIENCES↗
NASA NTRS2013

Characterizing the Phyllosilicates and Amorphous Phases Found by MSL Using Laboratory XRD and EGA Measurements of Natural and Synthetic Materials

The Curiosity Rover landed on the Peace Vallis alluvial fan in Gale crater on August 5, 2012. A primary mission science objective is to search for past habitable environments, and, in particular, to assess the role of past water. Identifying the minerals and mineraloids that result from aqueous alteration at Gale crater is essential for understanding past aqueous processes at the MSL landing site and hence for interpreting the site's potential habitability. X-ray diffraction (XRD) data from the CheMin instrument and evolved gas analyses (EGA) from the SAM instrument have helped the MSL science team identify phases that resulted from aqueous processes: phyllosilicates and amorphous phases were measure in two drill samples (John Klein and Cumberland) obtained from the Sheepbed Member, Yellowknife Bay Fm., which is believed to represent a fluvial-lacustrine environment. A third set of analyses was obtained from scoop samples from the Rocknest sand shadow. Chemical data from the APXS instrument have helped constrain the chemical compositions of these secondary phases and suggest that the phyllosilicate component is Mg-enriched and the amorphous component is Fe-enriched, relatively Si-poor, and S- and H-bearing. To refine the phyllosilicate and amorphous components in the samples measured by MSL, we measured XRD and EGA data for a variety of relevant natural terrestrial phyllosilicates and synthetic mineraloids in laboratory testbeds of the CheMin and SAM instruments. Specifically, Mg-saturated smectites and vermiculites were measured with XRD at low relative humidity to understand the behavior of the 001 reflections under Mars-like conditions. Our laboratory XRD measurements suggest that interlayer cation composition affects the hydration state of swelling clays at low RH and, thus, the 001 peak positions. XRD patterns of synthetic amorphous materials, including allophane, ferrihydrite, and hisingerite were used in full-pattern fitting (FULLPAT) models to help determine the types and abundances of amorphous phases in the martian rocks and sand shadow. These models suggest that the rocks and sand shadow are composed of approx 30% amorphous phases. Sulfate-adsorbed allophane and ferrihydrite were measured by EGA to further understand the speciation of the sulfur present in the amorphous component. These data indicate that sulfate adsorbed onto the surfaces of amorphous phases could explain a portion of the SO2 evolution in the Rocknest SAM data. The additional constraints placed on the mineralogy and chemistry of the aqueous alteration phases through our laboratory measurements can help us better understand the nature of the fluids that affected the different samples and devise a history of aqueous alteration for the Sheepbed Member of the Yellowknife Bay Fm. at Gale crater.

Rampe, Elizabeth B.↗
DOE OSTI2021

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Runway Configuration Management with Offline Reinforcement Learning

Runway configuration management (RCM) is a challenging task, and it affects the efficiency of the National Airspace System (NAS) and airport surface operations significantly. Each airport, depending on the geometry, capacity, local climate patterns, etc. has multiple configurations for the runway usage for arriving and departing flights. Many factors such as the incoming/outgoing traffic load, wind direction and speed, convective weather, cloud ceiling and other environmental factors might affect the choice of a runway configuration at any point in time. However, other factors such as safety measures and regulations, noise abatement, capacity of each configuration, and preference of the air traffic controllers (ATCs) can also play a significant role in selecting the configuration. A sub-optimal selection of the runway configuration, or delay in making configuration changes might result in significant increase in taxi times for aircraft on the surface of the airport, fuel and energy use of the aircraft, and maintenance costs. It can also lead to safety concerns, such as an aircraft performing one or more go-arounds before being able to land. All these factors make RCM an extremely important and challenging decision-making process for the ATCs. The current state of practice sets the runway configuration by the ATCs based on relevant information available at the time including weather, traffic, noise abatement, safety bounds, etc. This makes the decision-making process subjective based on the accuracy of the available information and the bias in human decision making. Unfortunately, this approach yields poor results (e.g., significant delays) if the predicted outcomes are uncertain and their relative impact is not well understood. This is especially evident when the uncertainty increases the size of possible predicted outcomes (combinatorial explosion in possible scenarios) that cannot be handled by human reasoning. On the other hand, an automated approach based on machine intelligence can make use of historical data and search through all (or significant amount of) possible scenarios under uncertainty and make well-informed decisions.

Milad Memarzadeh↗