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At least 415 records · Page 23

Using Mask R-CNN to detect and mask ghosting and scattered-light artifacts in astronomical images

Wide-field astronomical surveys are often affected by the presence of undesirable reflections (often known as “ghosting artifacts” or “ghosts”) and scattered-light artifacts. The identification and mitigation of these artifacts is important for rigorous astronomical analyses of faint and low-surface-brightness systems. In this work, we use images from the Dark Energy Survey (DES) to train, validate, and test a deep neural network (Mask R-CNN) to detect and localize ghosts and scattered- light artifacts. We find that the ability of the Mask R-CNN model to identify affected regions is superior to that of conventional algorithms that model the physical processes that lead to such artifacts, thus providing a powerful technique for the automated detection of ghosting and scattered-light artifacts in current and near-future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Spatial top-down proteomics for the functional characterization of human kidney

Background: The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging. Results: Using healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions. Conclusions: We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) where discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

59 BASIC BIOLOGICAL SCIENCES↗

Soil Sampling Techniques For Alabama Grain Fields

Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.

Thompson, A. N.↗

Software for Simulating Remote Sensing Systems

The Application Research Toolbox (ART) is a collection of computer programs that implement algorithms and mathematical models for simulating remote sensing systems. The ART is intended to be especially useful for performing design-tradeoff studies and statistical analyses to support the rational development of design requirements for multispectral imaging systems. Among other things, the ART affords a capability to synthesize coarser-spatial-resolution image-data sets from finer-spatial-resolution data sets and multispectral-image-data products from hyperspectral-image-data products. The ART also provides for synthesis of image-degradation effects, including point-spread functions, misregistration of spectral images, and noise. The ART can utilize real or synthetic data sets, along with sensor specifications, to create simulated data sets. In one example of a typical application, simulated data pertaining to an existing multispectral sensor system are used to verify the data collected by the system in operation. In the case of a proposed sensor system, the simulated data can be used to conduct trade studies and statistical analyses to ensure that the sensor system will satisfy the requirements of potential scientific, academic, and commercial user communities.

Zanoni, Vicki↗

Software for Simulating Remote Sensing Systems

The Application Research Toolbox (ART) is a collection of computer programs that implement algorithms and mathematical models for simulating remote sensing systems. The ART is intended to be especially useful for performing design-tradeoff studies and statistical analyses to support the rational development of design requirements for multispectral imaging systems. Among other things, the ART affords a capability to synthesize coarser-spatial-resolution image-data sets from finer-spatial-resolution data sets and multispectral-image-data products from hyperspectral-image-data products. The ART also provides for synthesis of image-degradation effects, including point-spread functions, misregistration of spectral images, and noise. The ART can utilize real or synthetic data sets, along with sensor specifications, to create simulated data sets. In one example of a typical application, simulated data pertaining to an existing multispectral sensor system are used to verify the data collected by the system in operation. In the case of a proposed sensor system, the simulated data can be used to conduct trade studies and statistical analyses to ensure that the sensor system will satisfy the requirements of potential scientific, academic, and commercial user communities.

Vicki Zanoni↗

Simulating Remote Sensing Systems

The Application Research Toolbox (ART) is a collection of computer programs that implement algorithms and mathematical models for simulating remote sensing systems. The ART is intended to be especially useful for performing design-tradeoff studies and statistical analyses to support the rational development of design requirements for multispectral imaging systems. Among other things, the ART affords a capability to synthesize coarser-spatial-resolution image-data products. The ART also provides for simulations of image-degradation effects, including point-spread functions, misregistration of spectral images, and noise. The ART can utilize real or synthetic data sets, along with sensor specifications, to create simulated data sets. In one example of a particular application, simulated imagery of a coarse resolution system was created using high-resolution imagery from another system in order to perform a radiometric cross-comparison. In the case of a proposed sensor system, the simulated data can be used to conduct trade studies and statistical analyses to ensure that the sensor system will satisfy the requirements of potential scientific, academic, and commercial user communities.

Zanoni, Vicki↗

Preliminary analyses of SIB-B radar data for recent Hawaii lava flows

The Shuttle Imaging Radar (SIR-B) experiment acquired two L-band (23 cm wavelength) radar images (at about 28 and 48 deg incidence angles) over the Kilauea Volcano area of southeastern Hawaii. Geologic analysis of these data indicates that, although aa lava flows and pyroclastic deposits can be discriminated, pahoehoe lava flows are not readily distinguished from surrounding low return materials. Preliminary analysis of data extracted from isolated flows indicates that flow type (i.e., aa or pahoehoe) and relative age can be determined from their basic statistics and illumination angle.

Kaupp, V. H.↗

Confusion-limited galaxy fields. II - Classical analyses

Chokshi and Wright presented a detailed model for simulating angular distribution of galaxy images in fields that extended to very high redshifts. Standard tools are used to analyze these simulated galaxy fields for the Omega(O) = 0 and the Omega(O) = 1 cases in order to test the discriminatory power of these tools. Classical number-magnitude diagrams and surface brightness-color-color diagrams are employed to study crowded galaxy fields. An attempt is made to separate the effects due to stellar evolution in galaxies from those due to the space time geometry. The results show that this discrimination is maximized at near-infrared wavelengths where the stellar photospheres are still visible but stellar evolution effects are less severe than those observed at optical wavelenghts. Rapid evolution of the stars on the asymptotic giant branch is easily recognized in the simulated data for both cosmologies and serves to discriminate between the two extreme values of Omega(O). Measurements of total magnitudes of individual galaxies are not essential for studying light distribution in galaxies as a function of redshift. Calculations for the extragalactic background radiation are carried out using the simulated data, and compared to integrals over the evolutionary models used.

Chokshi, Arati↗

Coherent diffractive imaging with twisted X-rays: Principles, applications, and outlook

Recent technological breakthroughs in synchrotron and x-ray free electron laser facilities have revolutionized nanoscale structural and dynamic analyses in condensed matter systems. This review provides a comprehensive overview of the advancements in coherent scattering and diffractive imaging techniques, which are now at the forefront of exploring materials science complexities. These techniques, notably Bragg coherent diffractive imaging and x-ray photon correlation spectroscopy, x-ray magnetic dichroism, and x-ray correlation analysis leverage beam coherence to achieve volumetric three-dimensional imaging at unprecedented sub-nanometer resolutions and explore dynamic phenomena within sub-millisecond timeframes. Such capabilities are critical in understanding and developing advanced materials and technologies. Simultaneously, the emergence of chiral crystals—characterized by their unique absence of standard inversion, mirror, or other roto-inversion symmetries—presents both challenges and opportunities. These materials exhibit distinctive interactions with light, leading to phenomena such as molecular optical activity, chiral photonic waveguides, and valley-specific light emissions, which are pivotal in the burgeoning fields of photonic and spintronic devices. This review elucidates how novel x-ray probes can be leveraged to unravel these properties and their implications for future technological applications. A significant focus of this review is the exploration of new avenues in research, particularly the shift from conventional methods to more innovative approaches in studying these chiral materials. Inspired by structured optical beams, the potential of coherent scattering techniques utilizing twisted x-ray beams is examined. This promising direction not only offers higher spatial resolution but also opens the door to previously unattainable insights in materials science. By contextualizing these advancements within the broader scientific landscape and highlighting their practical applications, this review aims to chart a course for future research in this rapidly evolving field.

Physics↗

Nanoscale interfacial melting enables bonding during high velocity microparticle impacts

Melting during high-velocity particle impact has been understood to be typically detrimental to bonding by lowering the strength at the interface and promoting rebound before solidification can occur. Here we establish a possible remedy to this challenge: by dramatically restricting the volume of molten material, its resolidification is accelerated, effectively forming a nanoscale, braze-type joint during impact. In-situ single particle impact imaging is combined with post-mortem structural and chemical analyses to reveal a regime where adhesion is governed not by extensive plastic deformation, but by the kinetics of melt layer resolidification. Furthermore, these findings redefine the role of melting in impact-based processes, establishing transient melting and rapid solidification as a viable strategy for engineering successful adhesion events.

Additive manufacturing↗

Evidence of Reversible Oxidation at CuInSe2 Grain Boundaries

Effects related to alkali metal doping and grain boundaries have puzzled the chalcopyrite photovoltaics community for a long time. This study is the first to report reversible oxidation of grain boundaries in CuInSe2 thin films. The phenomenon is observed in sodium-doped films, but not in undoped ones. Cathodoluminescence imaging, secondary ion mass spectrometry and Kelvin probe force microscopy analyses are performed on CuInSe2 thin films before and after exposure to vacuum. The findings suggest the existence of yet unidentified solid-gas equilibria. Resolving the nature of such reactions will provide new insights into the mechanism of alkali metal doping and passivation in chalcopyrite solar cells.

14 SOLAR ENERGY↗

Apollo 16 far-ultraviolet imagery and spectra of the Large Magellanic Cloud

The Large Magellanic Cloud (LMC) was observed with a far-ultraviolet camera/spectrograph (Experiment S-201) from the lunar surface during the Apollo 16 mission. Images were obtained with about 3-arcmin resolution, in the 1050-1600- and 1250-1600-A wavelengths ranges, of nearly the entire LMC. Spectra were also obtained in the 1050-1600- and 900-1600-A ranges with 30-40-A resolution along a strip 0.25 deg wide passing across the LMC. The images and spectra have been scanned with a microdensitometer, and analyses of the data to date are discussed.

Page, T. L.↗

An interactive lake survey program

Consideration is given to the development and operation of the interactive lake survey program developed by the Jet Propulsion Laboratory and the Environmental Protection Agency. The program makes it possible to locate, isolate, and store any number of water bodies on the basis of a given digital image. The stored information may be used to generate statistical analyses of each body of water including the lake surface area and the shoreline perimeter. The hardware includes a 360/65 host computer, a Ramtek G100B display controller, and a trackball cursor. The system is illustrated by the LAKELOC operation as it would be applied to a Landsat scene, noting the FARINA and STATUS programs. The water detection algorithm, which increases the accuracy with which water and land data may be separated, is discussed.

Smith, A. Y.↗

X-ray spectra and the rotation-activity connection of RS Canum Venaticorum binaries

Results are presented from a survey of RS CVn binaries which were observed with the imaging proportional counter (IPC) on board the Einstein Observatory. Spectral analyses of the IPC pulse height spectra show that the coronae of RS CVn binaries always contain hot gas with temperatures in excess of 10 to the 7th K, similar to active late-type main-sequence stars, and that at least two temperature components are necessary to account for the higher quality IPC spectra (when absorption is unimportant). It is argued that these bimodal temperature distributions found by the IPC are indicative of true distributions of emission measure versus temperature that are continuous (just as is the case of magnetically confined coronal plasma loops observed on the sun). It is further shown that none of the derivable X-ray characteristics of RS CVn binaries depend on rotation period, implying that previous claims of period-activity relationships in RS CVn binaries were unfounded.

Majer, P.↗

Design and analysis of multilayer x ray/XUV microscope

The design and analysis of a large number of normal incidence multilayer x ray microscopes based on the spherical mirror Schwarzschild configuration is examined. Design equations for the spherical mirror Schwarzschild microscopes are summarized and used to evaluate mirror parameters for microscopes with magnifications ranging from 2 to 50x. Ray tracing and diffraction analyses are carried out for many microscope configurations to determine image resolution as a function of system parameters. The results are summarized in three publication included herein. A preliminary study of advanced reflecting microscope configurations, where aspherics are used in place of the spherical microscope mirror elements, has indicated that the aspherical elements will improve off-axis image resolution and increase the effective field of view.

Shealy, David L.↗

The great Chinese fire of 1987 - A view from space

One of the largest forest fires ever recorded burned in the People's Republic of China (PRC) and the Soviet Union in May 1987. The fire covered over 1.0 million hectares in the PRC and almost 4 million hectares in the Soviet Union. The progress and areal extent of the fire were measured using satellite images analyzed in the imaging facilities at NASA-Langley and Forestry Canada. The analyses show the utility and value of satellite measurements to assess the areal extent and geographical distribution of fires, and have important implications for future measurements to be obtained from space platforms, such as the Earth Observing System.

Cahoon, Donald R., Jr.↗

Improving Global Analysis and Short-Range Forecast Using Rainfall and Moisture Observations Derived from TRMM and SSM/I Passive Microwave Instruments

The Global Precipitation Mission, a satellite project under consideration as a follow-on to the Tropical Rainfall Measuring Mission (TRMM) by the National Aeronautics and Space Agency (NASA) in the United States, the National Space Development Agency (NASDA) in Japan, and other international partners, comprises an improved TRMM-like satellite and a constellation of 8 satellites carrying passive microwave radiometers to provide global rainfall measurements at 3-hour intervals. The success of this concept relies on the merits of rainfall estimates derived from passive microwave radiometers. This article offers a proof-of-concept demonstration of the benefits of using, rainfall and total precipitable water (TPW) information derived from such instruments in global data assimilation with observations from the TRMM Microwave Imager (TMI) and 2 Special Sensor Microwave/Imager (SSM/I) instruments. Global analyses that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data analyses contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. We show that assimilating the 6-h averaged TMI and SSM/I surface rainrate and TPW retrievals improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the upper tropospheric moisture in the analysis produced by the Goddard Earth Observing System (GEOS) Data Assimilation System, as verified against radiation measurements by the Clouds and the Earth's Radiant Energy System (CERES) instrument and brightness temperature observations by the TIROS Operational Vertical Sounder (TOVS) instruments. Typically, rainfall assimilation improves clouds and radiation in areas of active convection, as well as the latent heating and large-scale motions in the tropics, while TPW assimilation leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. Ensemble forecasts initialized with analyses that incorporate TMI and SSM/I rainfall and TPW data also yield better short-range predictions of geopotential heights, winds, and precipitation in the tropics. This study offers a compelling illustration of the potential of using rainfall and TPW information derived from passive microwave instruments to significantly improve the quality of 4-dimensional global datasets for climate analysis and weather forecasting applications.

Hou, Arthur Y.↗

Canopy Spectral Invariants: Application to Classification of Forest Types from Hyperspectral Data - Part 2

Many studies have been conducted to demonstrate the ability of hyperspectral data to discriminate plant dominant species. Most of them have employed the use of empirically based techniques, which are site specific, requires some initial training based on characteristics of known leaf and/or canopy spectra and therefore may not be extendable to operational use or adapted to changing or unknown land cover. In this paper we propose a physically based approach for separation of dominant forest type using hyperspectral data. The radiative transfer theory of canopy spectral invariants underlies the approach, which facilitates parameterization of the canopy reflectance in terms of the leaf spectral scattering and two spectrally invariant and structurally varying variables - recollision and directional escape probabilities. The methodology is based on the idea of retrieving spectrally invariant parameters from hyperspectral data first, and then relating their values to structural characteristics of three-dimensional canopy structure. Theoretical and empirical analyses of ground and airborne data acquired by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over two sites in New England, USA, suggest that the canopy spectral invariants convey information about canopy structure at both the macro- and micro-scales. The total escape probability (one minus recollision probability) varies as a power function with the exponent related to the number of nested hierarchical levels present in the pixel. Its base is a geometrical mean of the local total escape probabilities and accounts for the cumulative effect of canopy structure over a wide range of scales. The ratio of the directional to the total escape probability becomes independent of the number of hierarchical levels and is a function of the canopy structure at the macro-scale such as tree spatial distribution, crown shape and size, within-crown foliage density and ground cover. These properties allow for the natural separation of dominant forest classes based on the location of points on the total escape probability vs the ratio log-log plane.

Schull, M. A.↗