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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Morphological and Genomic Features of the New Klosneuvirinae Isolate Fadolivirus IHUMI-VV54

Since the discovery of Mimivirus, viruses with large genomes encoding components of the translation machinery and other cellular processes have been described as belonging to the nucleocytoplasmic large DNA viruses. Recently, genome-resolved metagenomics led to the discovery of more than 40 viruses that have been grouped together in a proposed viral subfamily named Klosneuvirinae. Members of this group had genomes of up to 2.4Mb in size and featured an expanded array of translation system genes. Yet, despite the large diversity of the Klosneuvirinae in metagenomic data, there are currently only two isolates available. Here, we report the isolation of a novel giant virus known as Fadolivirus from an Algerian sewage site and provide morphological data throughout its replication cycle in amoeba and a detailed genomic characterization. The Fadolivirus genome, which is more than 1.5Mb in size, encodes 1,452 predicted proteins and phylogenetic analyses place this viral isolate as a near relative of the metagenome assembled Klosneuvirus and Indivirus. The genome encodes for 66 tRNAs, 23 aminoacyl-tRNA synthetases and a wide range of transcription factors, surpassing Klosneuvirus and other giant viruses. The Fadolivirus genome also encodes putative vacuolar-type proton pumps with the domains D and A, potentially constituting a virus-derived system for energy generation. The successful isolation of Fadolivirus will enable future hypothesis-driven experimental studies providing deeper insights into the biology of the Klosneuvirinae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Latent Tracks in Ion-Irradiated LiTaO 3 Crystals: Damage Morphology Characterization and Thermal Spike Analysis

Systematic research on the response of crystal materials to the deposition of irradiation energy to electrons and atomic nuclei has attracted considerable attention since it is fundamental to understanding the behavior of various materials in natural and manmade radiation environments. This work examines and compares track formation in LiTaO3 induced by separate and combined effects of electronic excitation and nuclear collision. Under 0.71–6.17 MeV/u ion irradiation with electronic energy loss ranging from 6.0 to 13.8 keV/nm, the track damage morphologies evolve from discontinuous to continuous cylindrical zone. Based on the irradiation energy deposited via electronic energy loss, the subsequently induced energy exchange and temperature evolution processes in electron and lattice subsystems are calculated through the inelastic thermal spike model, demonstrating the formation of track damage and relevant thresholds of lattice energy and temperature. Combined with a disorder accumulation model, the damage accumulation in LiTaO3 produced by nuclear energy loss is also experimentally determined. The damage characterizations and inelastic thermal spike calculations further demonstrate that compared to damage-free LiTaO3, nuclear-collision-damaged LiTaO3 presents a more intense thermal spike response to electronic energy loss owing to the decrease in thermal conductivity and increase in electron–phonon coupling, which further enhance track damage.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of Standard Image Processing of 3D X-ray Microscopy on Morphology, Topology and Effective Properties

Estimating porous media properties is a vital component of geosciences and the physics of porous media. Until now, imaging techniques have focused on methodologies to match image-derived flows or geomechanical parameters with experimentally identified values. Less emphasis has been placed on the compromise between image processing techniques and the consequences on topological and morphological characteristics and on computed properties such as permeability. The effects of some of the most popular image processing techniques (filtering and segmentation) available in open source on 3D X-ray Microscopy (micro-XRM) images are qualitatively and quantitatively discussed. We observe the impacts of various filters such as erosion-dilation and compare the efficiency of Otsu’s method of thresholding and the machine-learning-based software Ilastik for segmentation.

58 GEOSCIENCES↗
DOE OSTI2025

Influence of Supplementary Blue and Far-Red Light on the Morphology and Texture of Ocimum basilicum L. Grown in Controlled Environments

Basil (Ocimum basilicum L.) is highly sensitive to environmental conditions and is an ideal candidate for cultivation in controlled environment agriculture (CEA). Light-emitting diode technology has become essential in CEA, offering precise control over light intensity, spectrum, and duration. This study investigated how supplemental blue light, far-red light, or their combination influences basil biomass, morphology, texture, and color when added to a white + red light spectrum. Basil ’Prospera’ and ’Amethyst’ were exposed to five light treatments for 14–28 days: white + red at 180 µmol∙m−2∙s−1 (W) as the control, and four treatments with an additional 60 µmol∙m−2∙s−1 of either white + red (+W60), blue (+B60), far-red (+FR60), or a combination of B and FR (+B30+FR30), for a total photon flux density of 240 µmol∙m−2∙s−1. The results demonstrated that +B60 and +W60 light treatments increased leaf thickness by 17–20% compared to the +FR60 treatment. Conversely, texture analysis revealed that +FR60-treated leaves had higher puncture resistance, with ’Amethyst’ and ’Prospera’ requiring 1.57 ± 0.43 N and 1.45 ± 0.35 N of force, respectively, compared to 1.19 ± 0.32 N and 1.1 ± 0.21 N under +B60. These findings suggest that tailored light recipes in CEA can optimize basil quality, allowing growers to modify traits like leaf color, thickness, and toughness.

Oehler, Madison A. (ORCID:0000000297919667)↗
DOE OSTI2020

Characterization of the Nucleus, Morphology, and Activity of Interstellar Comet 2I/Borisov by Optical and Near-infrared GROWTH, Apache Point, IRTF, ZTF, and Keck Observations

We present visible and near-infrared (NIR) photometric and spectroscopic observations of interstellar object (ISO) 2I/Borisov taken from 2019 September 10 to 2019 December 20 using the GROWTH, the Apache Point Observatory Astrophysical Research Consortium 3.5 m, and the NASA Infrared Telescope Facility 3.0 m combined with pre- and postdiscovery observations of 2I obtained by the Zwicky Transient Facility from 2019 March 17 to 2019 May 5. Comparison with imaging of distant solar system comets shows an object very similar to mildly active solar system comets with an outgassing rate of ∼10{sup 27} mol s{sup −1}. The photometry, taken in filters spanning the visible and NIR range, shows a gradual brightening trend of ∼0.03 mag day{sup −1} since 2019 September 10 UTC for a reddish object becoming neutral in the NIR. The light curve from recent and prediscovery data reveals a brightness trend suggesting the recent onset of significant H{sub 2}O sublimation with the comet being active with super volatiles such as CO at heliocentric distances >6 au consistent with its extended morphology. Using the advanced capability to significantly reduce the scattered light from the coma enabled by high-resolution NIR images from Keck adaptive optics taken on 2019 October 4, we estimate a diameter for 2I’s nucleus of ≲1.4 km. We use the size estimates of 1I/’Oumuamua and 2I/Borisov to roughly estimate the slope of the ISO size distribution, resulting in a slope of ∼3.4 ± 1.2, similar to solar system comets and bodies produced from collisional equilibrium.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Monitoring the Morphology of M87* in 2009-2017 with the Event Horizon Telescope

The Event Horizon Telescope (EHT) has recently delivered the first resolved images of M87*, the supermassive black hole in the center of the M87 galaxy. These images were produced using 230 GHz observations performed in 2017 April. Additional observations are required to investigate the persistence of the primary image feature—a ring with azimuthal brightness asymmetry—and to quantify the image variability on event horizon scales. To address this need, we analyze M87* data collected with prototype EHT arrays in 2009, 2011, 2012, and 2013. While these observations do not contain enough information to produce images, they are sufficient to constrain simple geometric models. We develop a modeling approach based on the framework utilized for the 2017 EHT data analysis and validate our procedures using synthetic data. Applying the same approach to the observational data sets, we find the M87* morphology in 2009–2017 to be consistent with a persistent asymmetric ring of ∼40 μas diameter. The position angle of the peak intensity varies in time. In particular, we find a significant difference between the position angle measured in 2013 and 2017. These variations are in broad agreement with predictions of a subset of general relativistic magnetohydrodynamic simulations. We show that quantifying the variability across multiple observational epochs has the potential to constrain the physical properties of the source, such as the accretion state or the black hole spin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

What is Important? Morphological Asymmetries are Useful Predictors of Star Formation Rates of Star-forming Galaxies in SDSS Stripe 82

The morphology and structure of galaxies reflect their star formation and assembly histories. We use the framework of mutual information (MI) to quantify the interdependence among several structural variables and to rank them according to their relevance for predicting the specific star formation rate (SSFR) by comparing the MI of the predictor variables with the SSFR and penalizing variables that are redundant. We apply this framework to study ~3700 face-on star-forming galaxies (SFGs) with varying degrees of bulge dominance and central concentration and with stellar mass $M$ * ≈ 10 9 $M$ ⊙ at redshift $z$ = 0.02–0.12. We use the Sloan Digital Sky Survey (SDSS) Stripe 82 deep $i$-band imaging data, which improve measurements of asymmetry and bulge dominance indicators. We find that star-forming galaxies are a multiparameter family. In addition to $M$ * , asymmetry emerges as the most powerful predictor of SSFR residuals of SFGs, followed by bulge prominence/concentration. Star-forming galaxies with higher asymmetry and stronger bulges have higher SSFR at a given $M$ * . In conclusion, the asymmetry reflects both irregular spiral arms and lopsidedness in seemingly isolated SFGs and structural perturbations by galaxy interactions or mergers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Beyond Galaxy Bimodality: The Complex Interplay between Kinematic Morphology and Star Formation in the Local Universe

It is generally assumed that galaxies are a bimodal population in both star formation and structure; star-forming galaxies are disks, while passive galaxies host large bulges or are entirely spheroidal. Here we test this scenario by presenting a full census of the kinematic morphologies of a volume-limited sample of galaxies in the local universe extracted from the MaNGA galaxy survey. We measure the integrated stellar line-of-sight velocity to velocity dispersion ratio (V/σ) for 4574 galaxies in the stellar mass range 9.75 < logM $\star$ [M ⊙ ] < 11.75. We show that at fixed stellar mass, the distribution of V/σ is not bimodal, and that a simple separation between fast and slow rotators is oversimplistic. Fast rotators are a mixture of at least two populations, referred to here as dynamically cold disks and intermediate systems, with disks dominating in both total stellar mass and number. When considering star-forming and passive galaxies separately, the star-forming population is almost entirely made up of disks, while the passive population is mixed, implying an array of quenching mechanisms. Passive disks represent ~30% (both in number and mass) of passive galaxies, nearly a factor of two higher than that of slow rotators, reiterating that these are an important population for understanding galaxy quenching. These results paint a picture of a local universe dominated by disky galaxies, most of which become somewhat less rotation-supported upon or after quenching. While spheroids are present to a degree, they are certainly not the evolutionary end point for the majority of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Phase and Morphology of Water-ice Grains Formed in a Cryogenic Laboratory Plasma

Abstract Grains of ice are formed spontaneously when water vapor is injected into a weakly ionized laboratory plasma in which the background gas has been cooled to cryogenic temperatures comparable to those of deep space. These ice grains are levitated indefinitely within the plasma so that their time evolution can be observed under free-floating conditions. Using microscope imaging, ice grains are shown to have a spindle-like fractal structure and grow over time. Both crystalline and amorphous phases of ice are observed using Fourier transform infrared spectroscopy. A mix of crystalline and amorphous grains coexists under certain thermal conditions, and a linear mixing model is used on the ice absorption band surrounding 3.2 μ m to examine the ice phase composition and its temporal stability. The extinction spectrum is also affected by inelastic scattering as grains grow, and characteristic grain radii are obtained from Mie scattering theory and compared to size measurements from direct imaging. Observations are used to compare possible ice nucleation mechanisms, and it is concluded that nucleation is likely catalyzed by ions, as ice does not nucleate in the absence of plasma and impurities are not detected. Ice grain properties and infrared extinction spectra show similarity to observations of some astrophysical ices observed in protoplanetary disks, implying that the fractal morphology of the ice and observed processes of homogeneous ice nucleation could occur as well in such astrophysical environments with weakly ionized conditions.

Astronomy & Astrophysics↗
DOE OSTI2023

An Extensive Catalog of Early-type Dwarf Galaxies in the Local Universe: Morphology and Environment

We present an extensive catalog of 5405 early-type dwarf (dE) galaxies located in the various environments, i.e., clusters, groups, and fields, of the local universe (z < 0.01). The dEs are selected through visual inspection of the Legacy survey's g–r–z combined tricolor images. The inspected area, covering a total sky area of 7643 deg 2 , encompasses two local clusters (Virgo and Fornax), 265 groups, and the regions around 586 field galaxies of M K < -21 mag. The catalog aims to be one of the most extensive and publicly accessible collections of data on dEs, despite its complex completeness limits, which may not accurately represent its statistical completeness. The strength of the catalog lies in the morphological characteristics, including nucleated, tidal, and ultradiffuse dEs. The two clusters contribute nearly half (2437 out of 5405) of the dEs, and the 265 groups contribute 2103 dEs. There are 864 dEs in 586 fields, i.e., ~1.47 dEs per field. Using a standard definition commonly used in literature, we identify 100 ultradiffuse galaxies (UDGs), which compose ~2% of the dE population. We find that 40% of our sample dEs harbor a central nucleus, and among the UDG population, a majority (79%) are nonnucleated. About 1.3% of dEs suffer from ongoing tidal disturbance by nearby massive galaxies, and only 0.03% show a sign of recent dwarf–dwarf mergers. The association between dEs and their nearest bright neighbor galaxies suggests that dEs are more likely created where their neighbors are non-star-forming ones.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Ring Morphology with Dust Coagulation in Protoplanetary Disks

Tidal interactions between the embedded planets and their surrounding protoplanetary disks are often postulated to produce the observed complex dust substructures, including rings, gaps, and asymmetries. In this Letter, we explore the consequences of dust coagulation on the dust dynamics and ring morphology. Coagulation of dust grains leads to dust size growth that, under typical disk conditions, produces faster radial drifts, potentially threatening the dust ring formation. Utilizing 2D hydrodynamical simulations of protoplanetary disks that include a full treatment of dust coagulation, we find that if the planet does not open a gap quickly enough, the formation of an inner ring is impeded due to dust coagulation and subsequent radial drift. Furthermore, we find that a "buildup" of submillimeter-sized grains often appears in the dust emission at the outer edge of the dust disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A Wind-driven Origin for the Firework Morphology of the Supernova Remnant Pa 30

Pa 30—the likely remnant of the Galactic Type Iax supernova of 1181 AD—displays an unusual, firework-like morphology, consisting of radial filaments extending from a common center, where a white dwarf (WD) currently drives a very fast wind (speed ≳10 4 km s −1 ). We propose the filaments arose from the Rayleigh–Taylor-unstable nature of the interface between the circumstellar medium (CSM) and the shocked wind launched by the natal WD; the filaments then elongated intact due to the Kelvin–Helmholtz-stable nature of the large initial density contrast between the wind and CSM, supplemented by the slowly declining wind density profile (relative to homologously expanding ejecta). To support this interpretation, we present two-dimensional hydrodynamical simulations and derive the filament properties, including their speed, density, and temperature, all of which are consistent with observations. We suggest the filaments elongate until the wind and CSM densities become comparable at the contact discontinuity, which occurs within 1–10 yr, and then truncate because the Rayleigh–Taylor instability (RTI) halts. The subsequent Kelvin–Helmholtz instability growth timescale across the current width of the filaments is longer than the age of Pa 30, so they remain intact. The filament-less central region in Pa 30 is therefore more likely a consequence of the finite timescale over which the RTI operates, rather than a wind termination shock. In general, firework-like filaments may form in other systems, provided there is a sufficiently large density contrast between the ejecta and its surroundings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Computing water flow through complex landscapes – Part 2: Finding hierarchies in depressions and morphological segmentations

Depressions – inwardly draining regions of digital elevation models – present difficulties for terrain analysis and hydrological modeling. Analogous “depressions” also arise in image processing and morphological segmentation, where they may represent noise, features of interest, or both. Here we provide a new data structure – the depression hierarchy – that captures the full topologic and topographic complexity of depressions in a region. We treat depressions as networks in a way that is analogous to surface-water flow paths, in which individual sub-depressions merge together to form meta-depressions in a process that continues until they begin to drain externally. This hierarchy can be used to selectively fill or breach depressions or to accelerate dynamic models of hydrological flow. Complete, well-commented, open-source code and correctness tests are available on GitHub and Zenodo.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Determining flow directions in river channel networks using planform morphology and topology

Abstract. The abundance of global, remotely sensed surface water observations has accelerated efforts toward characterizing and modeling how water moves across the Earth's surface through complex channel networks. In particular, deltas and braided river channel networks may contain thousands of links that route water, sediment, and nutrients across landscapes. In order to model flows through channel networks and characterize network structure, the direction of flow for each link within the network must be known. In this work, we propose a rapid, automatic, and objective method to identify flow directions for all links of a channel network using only remotely sensed imagery and knowledge of the network's inlet and outlet locations. We designed a suite of direction-predicting algorithms (DPAs), each of which exploits a particular morphologic characteristic of the channel network to provide a prediction of a link's flow direction. DPAs were chained together to create “recipes”, or algorithms that set all the flow directions of a channel network. Separate recipes were built for deltas and braided rivers and applied to seven delta and two braided river channel networks. Across all nine channel networks, the recipe-predicted flow directions agreed with expert judgement for 97 % of all tested links, and most disagreements were attributed to unusual channel network topologies that can easily be accounted for by pre-seeding critical links with known flow directions. Our results highlight the (non)universality of process–form relationships across deltas and braided rivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Urban morphology and urban water demand evolution in the Los Angeles region

Detailed description of the dataset sources used in this study, the experimental workflow, and plotting for the paper figures provided at the associated GitHub Meta Repo: https://github.com/IMMM-SFA/Ferencz_et_al_2024_ERL The future water demand projections from this study are hypothetical future water demands that reflect the population and urban land cover changes represented by the scenarios considered. The intent and emphasis of this work is investigating the interactions between population change, evolution of urban morphology, and water demand. These projections are not meant to be likely future demands for specific water providers or the LA region and should not be interpreted as such. The folders contain input and output data for each step of the "Recreate my Experiment" workflow described in the associated GitHub meta-repository as well as data used for plotting Figures for the paper that this dataset supports. Description of each folder's contents and use: Step_1a: All necessary inputs to the associated python script provided on the GitHub repo. Step_1b: All necessary inputs (downscaled population rasters) used by the associated python script provided on the GitHub repo. Original 1-km squared rasters that were downscaled also provided. Step_1c: Urban growth projection rasters corresponding to SSP3 and SSP5 population scenarios are provided in separate subfolders as well as the water provider boundaries used for analysis. Outputs of data processing also provided. Associated python script provided on GitHub. Step_1d: Description of Inputs used by the QGIS Model Builder GUI that automates geospatial processing and clipping the of the high resolution land cover data for each urban land class footprint within a defined polygon boundary. The Model Builder is provided on the GitHub repo and can be used by QGIS. The outputs of this step are in "Clipped Provider Hi Res Landcover". If the user wants to use The Model Builder for different regions of LA or two test our outputs, they will need to download the hi resolution landcover raster listed in the Readme and in Ref [2] of the GitHub Page. Step_1e: All necessary inputs to generate average monthly demand for each water provider. Associated python script on GitHub. Step 2: Output data about land cover metrics (areas and fractions) for each urban land class for each water provider. Associated python script on GitHub. Uses outputs from Step 1d "Clipped Provider Hi Res Landcover" Step 3: Inputs for and Outputs from the urban projection raster analysis Python script on GitHub. The outputs are rasters of urban pixels that were converted to a higher land class and the number of land class units that changed (Values of 1, 2, or 3). For example, a value of 2 could be LC 21 -> 23 or LC 22 -> 24. These maps are label "intensification." The other outputs are "urban growth" rasters showing the conversion of non urban to urban land, which are indicated by pixel values of 1. Step 4: Output projections of indoor and outdoor annual and monthly demands for each water provider. These are used for Figures 4 - 7 of the paper. Figures: This folder has data used for plotting Figures 1 through 5. Data for Figures 6 and 7 are sourced directly from folders associated with the Processing and Analysis Steps 1 - 4 and the plotting scripts for Figures 6 and 7 are commented with what folder paths are needed to generate the figures. The GitHub page provides descriptions of how each figure was made and the associated plotting scripts used.

Los Angeles↗
DOE OSTI2024

Urban morphology and urban water demand evolution in the Los Angeles region

Detailed description of the dataset sources used in this study, the experimental workflow, and plotting for the paper figures provided at the associated GitHub Meta Repo: https://github.com/IMMM-SFA/Ferencz_et_al_2024_ERL The future water demand projections from this study are hypothetical future water demands that reflect the population and urban land cover changes represented by the scenarios considered. The intent and emphasis of this work is investigating the interactions between population change, evolution of urban morphology, and water demand. These projections are not meant to be likely future demands for specific water providers or the LA region and should not be interpreted as such. The folders contain input and output data for each step of the "Recreate my Experiment" workflow described in the associated GitHub meta-repository as well as data used for plotting Figures for the paper that this dataset supports. Description of each folder's contents and use: Step_1a: Inputs to the associated python script provided on the GitHub repo. Step_1b: Inputs (downscaled population rasters) used by the associated python script provided on the GitHub repo. Original 1-km squared rasters that were downscaled also provided. Step_1c: Urban growth projection rasters corresponding to SSP3 and SSP5 population scenarios are provided in separate subfolders as well as the water provider boundaries used for analysis. Outputs of data processing also provided. Associated python script provided on GitHub. Step_1d: Description of Inputs used by the QGIS Model Builder GUI that automates geospatial processing and clipping the of the high-resolution 60 cm land cover data for each urban land class footprint within a defined polygon boundary. The Model Builder is provided on the GitHub repo and can be used by QGIS. The outputs of this step are in "Clipped Provider Hi Res Landcover". If the user wants to use The Model Builder for different regions of LA or to test our outputs, they will need to download the hi resolution landcover raster listed in the Readme and in Ref [2] of the GitHub Page. Step_1e: All necessary inputs to generate average monthly demand over the 2017-2021 period and the minimum and maximum demands over the 2014-2021 for each water provider. Associated python scripts are on GitHub. Step 2: Output data about land cover metrics (areas and fractions) for each urban land class for each water provider. Associated python script on GitHub. Uses outputs from Step 1d "Clipped Provider Hi Res Landcover" Step 3: Both the Inputs for and Outputs from the urban projection raster analysis Python script on GitHub. The inputs are urban land class rasters for specific SSP and zoning scenarios (low, medium, high) from Step 1c. The outputs are rasters of urban pixels that were converted to a higher land class and the number of land class units that changed (Values of 1, 2, or 3). For example, a value of 2 could be LC 21 -> 23 or LC 22 -> 24. These maps are label "intensification." The other outputs are "urban growth" rasters showing the conversion of non urban to urban land, which are indicated by pixel values of 1. These are used for the urban growth change maps in Figure 3. Step 4: Output projections of indoor and outdoor annual and monthly demands for each water provider for the average, minimum, and maximum monthly demand scenarios for each of the four urban growth scenarios (SSP3 med, SSP5 low, SSP5 med, and SSP5 high). The outputs also include metrics on each water provider used for the demand sensitivity analysis presented in Figure 8. Outputs from Step 4 are used for Figures 4 - 8 of the paper. Figures: This folder has data used for plotting Figures 1 through 5, and 8. Data for Figures 6 and 7 are sourced directly from folders associated with the Processing and Analysis Steps 1 - 4. The GitHub meta repository provides descriptions of how each figure was made and the associated plotting scripts used.

Los Angeles↗