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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

environmental monitoring↗
NASA NTRS1989

Properties of grains derived from IRAS observations of dust

The authors used the results of Infrared Astronomy Satellite (IRAS) observations of diffuse medium dust to develop a theoretical model of the infrared properties of grains. Recent models based entirely on traditional observations of extinction and polarization include only particles whose equilibrium temperatures do not exceed 20 K in the diffuse interstellar medium. These classical grains, for which the authors have adopted the multipopulation model developed by Hong and Greenberg (1980), can explain only the emission in the IRAS 100 micron band. The measurements at shorter wavelengths (12, 25 and 60 microns) require two new particle populations. Vibrational fluorescence from aromatic molecules provides the most likely explanation for the emission observed at 12 microns, with polycyclic aeromatic hydrocarbons (PAHs) containing about 10 percent of cosmic carbon. A simplified model of the emission process shows that PAH molecules can also explain most of the emission measured by IRAS at 25 microns. The authors identified the warm particles responsible for the excess 60 microns emission with small (a approx. equals 0.01 microns) iron grains. A compilation of the available data on the optical properties of iron indicates that the diffuse medium temperature of small iron particles should be close to 50 K and implies that a large, possibly dominant, fraction of cosmic iron must be locked up in metallic particles in order to match the observed 60 microns intensities. The model matches the infrared fluxes typically observed by IRAS in the diffuse medium and can also reproduce the infrared surface brightness distribution in individual clouds. In particular, the combination of iron and classical cool grains can explain the surprising observations of the 60/100 microns flux ratio in clouds, which is either constant or increases slightly towards higher opacities. The presence of metallic grains has significant implications for the physics of the interstellar medium, including catalytic H2 formation, for which iron grains could be the main site; differences in depletion patterns between iron and other refractory elements (Mg, Si); and superparamagnetic behavior of large grains with embedded iron clusters giving rise to the observed high degree of alignment by the galactic magnetic field.

Wesselius, P. R.↗
NASA NTRS1991

Void statistics of the CfA redshift survey

Clustering properties of two samples from the CfA redshift survey, each containing about 2500 galaxies, are studied. A comparison of the velocity distributions via a K-S test reveals structure on scales comparable with the extent of the survey. The void probability function (VPF) is employed for these samples to examine the structure and to test for scaling relations in the galaxy distribution. The galaxy correlation function is calculated via moments of galaxy counts. The shape and amplitude of the correlation function roughly agree with previous determinations. The VPFs for distance-limited samples of the CfA survey do not match the scaling relation predicted by the hierarchical clustering models. On scales not greater than 10/h Mpc, the VPFs for these samples roughly follow the hierarchical pattern. A variant of the VPF which uses nearly all the data in magnitude-limited samples is introduced; it accounts for the variation of the sampling density with velocity in a magnitude-limited survey.

Vogeley, Michael S.↗
NASA NTRS2006

Comparison of Orbital Parameters for GEO Debris Predicted by LEGEND and Observed by MODEST: Can Sources of Orbital Debris be Identified?

Since 2002 the National Aeronautics and Space Administration (NASA) has carried out an optical survey of the debris environment in the geosynchronous Earth-orbit (GEO) region with the Michigan Orbital Debris Survey Telescope (MODEST) in Chile. The survey coverage has been similar for 4 of the 5 years allowing us to follow the orbital evolution of Correlated Targets (CTs), both controlled and un-controlled objects, and Un-Correlated Targets (UCTs). Under gravitational perturbations the distributions of uncontrolled objects, both CTs and UCTs, in GEO orbits will evolve in predictable patterns, particularly evident in the inclination and right ascension of the ascending node (RAAN) distributions. There are several clusters (others have used a "cloud" nomenclature) in observed distributions that show evolution from year to year in their inclination and ascending node elements. However, when MODEST is in survey mode (field-of-view approx.1.3deg) it provides only short 5-8 minute orbital arcs which can only be fit under the assumption of a circular orbit approximation (ACO) to determine the orbital parameters. These ACO elements are useful only in a statistical sense as dedicated observing runs would be required to obtain sufficient orbital coverage to determine a set of accurate orbital elements and then to follow their evolution. Identification of the source(s) for these "clusters of UCTs" would be advantageous to the overall definition of the GEO orbital debris environment. This paper will set out to determine if the ACO elements can be used to in a statistical sense to identify the source of the "clustering of UCTs" roughly centered on an inclination of 12deg and a RAAN of 345deg. The breakup of the Titan 3C-4 transtage on February 21, 1992 has been modeled using NASA s LEGEND (LEO-to-GEO Environment Debris) code to generate a GEO debris cloud. Breakup fragments are created based on the NASA Standard Breakup Model (including fragment size, area-to-mass (A/M), and delta-V distributions). Once fragments are created, they are propagated forward in time with a subroutine GEOPROP. Perturbations included in GEOPROP are those due to solar/lunar gravity, radiation pressure, and major geopotential terms. The question to be addressed: are the UCTs detected by MODEST in this inclination/RAAN region related to the Titan 3C-4 breakup? Discussion will include the observational biases in attempting to detect a specific, uncontrolled target during given observing session. These restrictions include: (1) the length of the observing session which is 8 hours or less at any given date or declination; (2) the assumption of ACO elements for detected object when the breakup model predicts debris with non-zero eccentricities; (3) the size and illumination or brightness of the debris predicted by the model and the telescope/sky limiting magnitude.

Barker, Edwin S.↗
DOE OSTI2021

An Integrated View of Hydraulic Induced Fracture Geometry in Hydraulic Fracture Test Site 2

Until relatively recently, most of our understanding about the geometry of hydraulically induced fractures in unconventional reservoirs has been inferred by patterns observed via microseismic monitoring. Important information, such as fracture-azimuth, fracture-length, height-growth and other geometric data has been determined from microseismic “event clouds”, which in turn has been used to interpret a stimulated reservoir volume (SRV). It is important to note that relatively limited microseismic results have been acquired in conjunction with other diagnostics and validated in a consistent manner. The Hydraulic Fracture Test Site 2 (HFTS2) in the Permian Delaware Basin provides a unique opportunity to compare the frac geometry interpretations derived from multiple frac diagnostic tools and at multiple scales. The integrated view that emerges from all the frac diagnostic tools is that in HFTS2 the geometries of hydraulically induced fractures are not random and with a highly complex branching architecture. In fact, the fracs are mostly vertical, parallel plana domains, and both vertically and horizontally asymmetrical. The hydraulically induced fractures have a very consistent azimuth with a strike that matches SHmax. At the distance corresponding to the spacing between nearby wells in HFTS2, ~ 660 ft, the pattern of strain interceptions observed from Low Frequency Distributed Acoustic Sensing (LF-DAS) shows far-field dimensions that are consistent with the stage length dimensions at the stimulated well. In general, larger stages with higher number of clusters create larger number of interceptions and wider stimulated intervals than that of shorter stages with the same cluster to cluster spacing and fewer clusters. The hydraulically induced fractures also show a clear tendency to preferentially grow upwards as shown by the microseismic data, by the relative lower number of LF-DAS interceptions in nearby deeper wells and finally by the observed LF-DAS strain patterns in the vertical observation well. In the near field, the geometries of the fracture domains are also consistent. As shown by the distributed strain measurements obtained during production via the monitoring of Rayleigh Frequency Shift (RFS), each cluster has a separate, non-overlapping, frac-zone-domain that are generally centered around the locations of each perforation cluster. Overall, the hydraulically induced fractures in HFTS2 are interpreted as occurring in swarms associated with individual clusters, each with its own unique geometry but with similar predictable geometric and propagation tendencies. The comprehensive frac diagnostic program in HFTS2, the well-pad layout that permits the investigation of the Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S018R003/2477511/urtec-2021-5396-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5396 2 impact that nearby producing wells has on frac geometry, together with an innovative Design of Experiment (DofE) that includes sequential-fracing, consistent cluster-to-cluster distances and few single-perforation cluster stages, has allowed us to gain a unique perspective about the geometry of the induced hydraulic fractures on this pad. Finally, the HFTS2 dataset has also provided us with a better understanding of the applicability and limitations of the different diagnostic tools.

58 GEOSCIENCES↗
DOE OSTI2017

Observations of the Ultraviolet-bright Star Y453 in the Globular Cluster M4 (NGC 6121)

We present a spectral analysis of the UV-bright star Y453 in M4. Model fits to the star’s optical spectrum yield T{sub eff} ∼ 56,000 K. Fits to the star’s FUV spectrum, obtained with the Cosmic Origins Spectrograph on board the Hubble Space Telescope, reveal it to be considerably hotter, with T{sub eff} ∼ 72,000 K. We adopt T{sub eff} = 72,000 ± 2000 K and logg = 5.7 ± 0.2 as our best-fit parameters. Scaling the model spectrum to match the star’s optical and near-infrared magnitudes, we derive a mass M{sub ∗}=0.53±0.24 M{sub ⊙} and luminosity logL/L{sub ⊙}=2.84±0.05, consistent with the values expected of an evolved star in a globular cluster. Comparing the star with post-horizontal-branch evolutionary tracks, we conclude that it most likely evolved from the blue horizontal branch, departing the asymptotic giant branch before third dredge-up. It should thus exhibit the abundance pattern (O-poor and Na-rich) characteristic of the second-generation (SG) stars in M4. We derive the star’s photospheric abundances of He, C, N, O, Si, S, Ti, Cr, Fe, and Ni. CNO abundances are roughly 0.25 dex greater than those of the cluster’s SG stars, while the Si and S abundances match the cluster values. Abundances of the iron-peak elements (except for iron itself) are enhanced by 1–3 dex. Rather than revealing the star’s origin and evolution, this pattern reflects the combined effects of diffusive and mechanical processes in the stellar atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Characterizing Signatures of Geothermal Exploration Data with Machine Learning Techniques: An Application to the Nevada Play Fairway Analysis

We are introducing machine learning methods to the play fairway analysis to generate geothermal potential maps to support the evaluation of geothermal resource potential and the exploration for undiscovered blind geothermal systems in the Nevada Great Basin region. Our project aims to identify new ways to combine the play fairway data and empirically organize relationships between feature weights and labels in an improved workflow. As a means of doing this, we introduce machine learning methods to evaluate the influence of certain geological and geophysical features/feature sets in predicting geothermal favorability. This report highlights promising approaches based on supervised and unsupervised learning methods. First, we demonstrate a filter method applied to supervised classification modeling. The supervised filter method is based on permutation analysis to evaluate every possible feature combination/drop out scenario and rank feature influence based on the performance variance of supervised classification models. Additionally, we present an unsupervised factor analysis based on principal component analysis coupled with a semi-supervised kmeans clustering algorithm. This analysis allows us to identify the optimal number of groups/clusters for training sites and structural settings to identify feature patterns including correlation, variance, and latent and dominant feature relationships. The results from these methods offer a promising avenue for identifying favorable sources of predictive information to identify the locations of blind geothermal systems and furthering our understanding of complex geothermal feature and label relationships in the Great Basin region and beyond.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

Abstract Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

A redshift survey toward a proposed void of galaxies suggested by the distribution of Abell clusters

A program of redshift measurements was carried out in a region of the sky in which a relative under-density of Abell clusters had been used to infer the presence of a large (diameter about 40/h Mpc) void in the general galaxy distribution. The purpose of this study was to investigate whether the large-scale distribution of galaxies is traced by the distribution of rich clusters. Redshifts are presented for 308 galaxies in the Zwicky Catalog in a 234 square degree region centered on R.A. about 2h, Decl. about 12 deg of which 229 have been newly measured. These data reveal a pattern of filamentary structure alternating with voids of characteristic diameter about 25-30/h Mpc, throughout the volume sampled. While the redshift data reveal an underdensity in the distribution of galaxies in the general region suggested by the Abell cluster distribution, they do not support the existence there of a 40/h Mpc diameter void.

Willick, Jeffrey A.↗
DOE OSTI2016

Metal mixtures in urban and rural populations in the US: The Multi-Ethnic Study of Atherosclerosis and the Strong Heart Study

Background: Natural and anthropogenic sources of metal exposure differ for urban and rural residents. We searched to identify patterns of metal mixtures which could suggest common environmental sources and/or metabolic pathways of different urinary metals, and compared metal-mixtures in two population-based studies from urban/sub-urban and rural/town areas in the US: the Multi-Ethnic Study of Atherosclerosis (MESA) and the Strong Heart Study (SHS). Methods: We studied a random sample of 308 White, Black, Chinese-American, and Hispanic participants in MESA (2000–2002) and 277 American Indian participants in SHS (1998–2003). We used principal component analysis (PCA), cluster analysis (CA), and linear discriminant analysis (LDA) to evaluate nine urinary metals (antimony [Sb], arsenic [As], cadmium [Cd], lead [Pb], molybdenum [Mo], selenium [Se], tungsten [W], uranium [U] and zinc [Zn]). For arsenic, we used the sum of inorganic and methylated species (∑As). Results: All nine urinary metals were higher in SHS compared to MESA participants. PCA and CA revealed the same patterns in SHS, suggesting 4 distinct principal components (PC) or clusters (∑As-U-W, Pb-Sb, Cd-Zn, Mo-Se). In MESA, CA showed 2 large clusters (∑As-Mo-Sb-U-W, Cd-Pb-Se-Zn), while PCA showed 4 PCs (Sb-U-W, Pb-Se-Zn, Cd-Mo, ∑As). LDA indicated that ∑As, U, W, and Zn were the most discriminant variables distinguishing MESA and SHS participants. Conclusions: In SHS, the ∑As-U-W cluster and PC might reflect groundwater contamination in rural areas, and the Cd-Zn cluster and PC could reflect common sources from meat products or metabolic interactions. Among the metals assayed, ∑As, U, W and Zn differed the most between MESA and SHS, possibly reflecting disproportionate exposure from drinking water and perhaps food in rural Native communities compared to urban communities around the US. - Highlights: • We identified and compared environmental sources of urinary metals in MESA and SHS. • ∑As-U-W in SHS may reflect groundwater contamination in rural areas. • Cd-Zn in SHS may reflect common sources from meat products or metabolic interaction. • ∑As, U, W, and Zn differed the most between MESA and SHS participants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Structural investigation of the temperature-stable relaxor dielectric Ba 0.8 Ca 0.2 TiO 3 -Bi(Mg 0.5 Ti 0.5 )O 3

Aberration corrected scanning transmission electron microscopy (STEM) and electron diffraction have been used to disclose local structure and nano-chemistry in a Ca modified BaTiO 3 -Bi(Mg 0.5 Ti 0.5 )O 3 relax or dielectric ceramic which exhibits high and near-invariant relative permittivity over a wide temperature range. High resolution, synchrotron X-ray diffraction indicated a globally cubic structure ($Pm$$\overline{3}$$m$), but direct atomic-scale imaging by STEM revealed local tetragonal distortions. Nanopolar clusters were identified from B-site atomic displacement vectors measured relative to oxygen ion positions along < 100 > and < 110 > zone axes of integrated differential phase contrast (iDPC) STEM images, highlighting cluster sizes of 2–5 nm. Chemical analysis by STEM-energy dispersive X-ray spectroscopy and full pattern refinements of X-ray powder diffraction data each implied high levels of Bi vacancies within the matrix. The possibility that these A-site vacancies modulate the nanopolar structure and promote flattening of the permittivity-temperature response in this class of dielectric is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The Reconstruction Software for the Muon Ionization Cooling Experiment Trackers

The international Muon Ionisation Cooling Experiment (MICE) is designed to demonstrate the principle of muon ionization cooling, for application to a future Neutrino Factory or Muon Collider. In order to measure the change in emittance, MICE is equipped with a pair of high precision scintillating fibre trackers. The trackers are required to measure a 10% change in emittance to 1% accuracy (giving an overall precision of 0.1%). This paper describes the tracker reconstruction software, as a part of the overall MICE software framework, MAUS. Channel clustering is described, proceeding to the formation of space-points, which are then associated with particle tracks using pattern recognition algorithms. Finally a full custom Kalman track fit is performed, to account for energy loss and multiple scattering. Exemplar results are shown for Monte Carlo data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Solvent minimization induces preferential orientation and crystal clustering in serial micro-crystallography on micro-meshes, in situ plates and on a movable crystal conveyor belt

X-ray diffraction data were obtained at the National Synchrotron Light Source from insulin and lysozyme crystals that were densely deposited on three types of surfaces suitable for serial micro-crystallography: MiTeGen MicroMeshes™, Greiner Bio-One Ltd in situ micro-plates, and a moving kapton crystal conveyor belt that is used to deliver crystals directly into the X-ray beam. 6° wedges of data were taken from ~100 crystals mounted on each material, and these individual data sets were merged to form nine complete data sets (six from insulin crystals and three from lysozyme crystals). Insulin crystals have a parallelepiped habit with an extended flat face that preferentially aligned with the mounting surfaces, impacting the data collection strategy and the design of the serial crystallography apparatus. Lysozyme crystals had a cuboidal habit and showed no preferential orientation. Preferential orientation occluded regions of reciprocal space when the X-ray beam was incident normal to the data-collection medium surface, requiring a second pass of data collection with the apparatus inclined away from the orthogonal. In addition, crystals measuring less than 20 µm were observed to clump together into clusters of crystals. Clustering required that the X-ray beam be adjusted to match the crystal size to prevent overlapping diffraction patterns. No additional problems were encountered with the serial crystallography strategy of combining small randomly oriented wedges of data from a large number of specimens. Lastly, high-quality data able to support a realistic molecular replacement solution were readily obtained from both crystal types using all three serial crystallography strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2016

WE-FG-202-10: Assessing Hepatocellular Carcinoma (HCC) Response to SBRT Using DCE-MRI

Purpose: To investigate the feasibility of using DCE-MRI to assess treatment response of HCC to SBRT. Methods: For seven liver HCC patients treated by photon SBRT with radiation dose ranging from 35 to 50 Gy in 5 fractions, T1-weighted DCE-MRI was performed before and at 1–3 months after the treatment. Each study included one pre-contrast and five post Gd-EOB-DTPA-enhanced imaging series. The target tumor and the liver were manually outlined on the arterial phase images. Then, a regional deformable image registration was applied to align liver volumes at different phases in order to compensate respiratory and cardiac motions. An unsupervised fuzzy c-means clustering technique was carried out to partition the tumor voxels into a number of groups based on their enhancement patterns over time. The representative kinetic curve of the tumor was selected as the one with the maximum enhancement. Six semi-quantitative features were extracted to depict the maximum contrast enhancement, uptake rate, washout rate, time to peak, the area under the kinetic curve (AUKC), as well as the ratio of the most enhanced area in each tumor. The change of these feature values after SBRT was compared using Wann-Whiteney test to characterize the tumor response to RT. Results: Eight HCCs from these seven patients were included in this retrospective study, in which four were identified to respond well to SBRT. The responding tumors showed reduced enhancement after SBRT while the non-responding tumors had steady or even enhanced kinetic dynamics. The median AUKC change after SBRT was −0.65 for responding tumors and 1.0165 for non-responding tumors (p=0.029) Conclusion: The preliminary results demonstrate that DCE-MRI has the potential to monitor the effects of SBRT in patients with HCC. We are expanding our database and developing more quantitative imaging biomarkers in the future study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Analysis of Superconducting Magnet Quench Antenna Data

Quenching poses a serious problem for superconducting magnets operating at high currents. It occurs when the material transitions from the superconducting to the normal state, which leads to heating and potential damage to the magnet. To understand and mitigate quenching, the Magnet Department at Fermilab is developing and testing superconducting magnet quench antenna arrays. This study delves into the anomalous events preceding the quench during magnet training by analyzing the collected data. With the moving average and Fast Fourier Transform techniques, we investigate the trends and frequency patterns of the data. Moreover, we introduce an unsupervised anomaly detection algorithm based on Principal Component Analysis and DBSCAN clustering. It can autonomously identify events within background noise, without relying on any predefined event features. Our analysis reveals that the spatio-temporal distribution of these anomalous events has little connection to the quench location, indicating that a majority of them bear no relation to the quenching process.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Chemical Abundance Analysis of Tucana III, the Second r -process Enhanced Ultra-faint Dwarf Galaxy

Here, we introduce a chemical abundance analysis of four additional confirmed member stars of Tucana III, a Milky Way satellite galaxy candidate in the process of being tidally disrupted as it is accreted by the Galaxy. Two of these stars are centrally located in the core of the galaxy while the other two stars are located in the eastern and western tidal tails. The four stars have chemical abundance patterns consistent with the one previously studied star in Tucana III: they are moderately enhanced in r-process elements, i.e., they have $\langle$[Eu/Fe]$\rangle$ ≈ +0.4 dex. The non-neutron-capture elements generally follow trends seen in other dwarf galaxies, including a metallicity spread of 0.44 dex and the expected trend in α-elements, i.e., the lower metallicity stars have higher Ca and Ti abundance. In general, the chemical abundance patterns of these stars suggest that Tucana III was an ultra-faint dwarf galaxy, and not a globular cluster, before being tidally disturbed. As is the case for the one other galaxy dominated by r-pr ocess enhanced stars, Reticulum II, Tucana III’s stellar chemical abundances are consistent with pollution from ejecta produced by a binary neutron star merger, although a different r-process element or dilution gas mass is required to explain the abundances in these two galaxies if a neutron star merger is the sole source of r-process enhancement.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2013

A Periglacial Analog for Landforms in Gale Crater, Mars

Several features in a high thermal inertia (TI) unit at Gale crater can be interpreted within a periglacial framework. These features include polygonally fractured terrain (cf. ice-wedge polygons), circumferential patterns of polygonal fractures (cf. relict pingos with ice-wedge polygons on their surfaces), irregularly-shaped and clustered depressions (cf. remnants of collapsed pingos and ephemeral lakes), and a general hummocky topography (cf. thermokarst). This interpretation would imply a major history of water and ice in Gale crater, involving permafrost, freeze-thaw cycles, and perhaps ponded surface water.

Oehler, Dorothy Z.↗
NASA NTRS2019

Cluster Analysis of IRIS Spectroscopic Line Profiles and SDO/AIA EUV Emission in Observations and RMHD Simulations of the Solar Atmosphere

Spatially-resolved observations from the IRIS and SDO/AIA satellites, especially when coupled with realistic 3D RMHD simulations, are a powerful tool for analysis of processes in the solar chromosphere, transition region, and corona. However, the complexity of the data makes understanding the observations and modeling results difficult. In this work, we apply unsupervised clustering algorithms for analysis of observational and synthetic chromospheric Mg II h&k 2796Å&2803Å and transition region C II 1334Å&1335Å line profiles observed by IRIS, and extreme ultraviolet (EUV) emission observed by SDO/AIA, for various types of problems. The synthetic line profiles are computed for simulations of the quiescent solar atmosphere (using the StellarBox and RH1.5 codes). The K-Means clustering algorithm is applied, and the selection of an optimal number of clusters is supported by the average silhouette width technique. We discuss applications of the line profile clustering method to 1) visualization of computational and observational spectroscopic imaging data; 2) understanding of evolutionary trends and behavior patterns of quiet Sun emission and during solar flares; and 3) recognition of heating events and shock waves.

Sadykov, Viacheslav↗