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At least 451 records · Page 25

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NASA NTRS2006

NASA Tech Briefs, June 2006

Topics covered include: Magnetic-Field-Response Measurement-Acquisition System; Platform for Testing Robotic Vehicles on Simulated Terrain; Interferometer for Low-Uncertainty Vector Metrology; Rayleigh Scattering for Measuring Flow in a Nozzle Testing Facility; "Virtual Feel" Capaciflectors; FETs Based on Doped Polyaniline/Polyethylene Oxide Fibers; Miniature Housings for Electronics With Standard Interfaces; Integrated Modeling Environment; Modified Recursive Hierarchical Segmentation of Data; Sizing Structures and Predicting Weight of a Spacecraft; Stress Testing of Data-Communication Networks; Framework for Flexible Security in Group Communications; Software for Collaborative Use of Large Interactive Displays; Microsphere Insulation Panels; Single-Wall Carbon Nanotube Anodes for Lithium Cells; Tantalum-Based Ceramics for Refractory Composites; Integral Flexure Mounts for Metal Mirrors for Cryogenic Use; Templates for Fabricating Nanowire/Nanoconduit- Based Devices; Measuring Vapors To Monitor the State of Cure of a Resin; Partial-Vacuum-Gasketed Electrochemical Corrosion Cell; Theodolite Ring Lights; Integrating Terrain Maps Into a Reactive Navigation Strategy; Reducing Centroid Error Through Model-Based Noise Reduction; Adaptive Modeling Language and Its Derivatives; Stable Satellite Orbits for Global Coverage of the Moon; and Low-Cost Propellant Launch From a Tethered Balloon

Source record↗

NASA NTRS2010

Oscillation of Angiogenesis with Vascular Dropout in Diabetic Retinopathy by VESsel GENeration Analysis (VESGEN)

PURPOSE. Vascular dropout and angiogenesis are hallmarks of the progression of diabetic retinopathy (DR). However, current evaluation of DR relies on grading of secondary vascular effects, such as microaneurysms and hemorrhages, by clinical examination instead of by evaluation of actual vascular changes. The purpose of this study was to map and quantify vascular changes during progression of DR by VESsel GENeration Analysis (VESGEN). METHODS. In this prospective cross-sectional study, 15 eyes with DR were evaluated with fluorescein angiography (FA) and color fundus photography, and were graded using modified Early Treatment Diabetic Retinopathy Study criteria. FA images were separated by semiautomatic image processing into arterial and venous trees. Vessel length density (L(sub v)), number density (N(sub v)), and diameter (D(sub v)) were analyzed in a masked fashion with VESGEN software. Each vascular tree was automatically segmented into branching generations (G(sub 1)...G(sub 8) or G(sub 9)) by vessel diameter and branching. Vascular remodeling status (VRS) for N(sub v) and L(sub v) was graded 1 to 4 for increasing severity of vascular change. RESULTS. By N(sub v) and L(sub v), VRS correlated significantly with the independent clinical diagnosis of mild to proliferative DR (13/15 eyes). N(sub v) and L(sub v) of smaller vessels (G(sub >=6) increased from VRS1 to VRS2 by 2.4 X and 1.6 X, decreased from VRS2 to VRS3 by 0.4 X and 0.6X, and increased from VRS3 to VRS4 by 1.7 X and 1.5 X (P < 0.01). Throughout DR progression, the density of larger vessels (G(sub 1-5)) remained essentially unchanged, and D(sub v1-5) increased slightly. CONCLUSIONS. Vessel density oscillated with the progression of DR. Alternating phases of angiogenesis/neovascularization and vascular dropout were dominated first by remodeling of arteries and subsequently by veins.

Parsons-Wingerter, Patricia↗

NASA NTRS1992

Zuotin, a putative Z-DNA binding protein in Saccharomyces cerevisiae

A putative Z-DNA binding protein, named zuotin, was purified from a yeast nuclear extract by means of a Z-DNA binding assay using [32P]poly(dG-m5dC) and [32P]oligo(dG-Br5dC)22 in the presence of B-DNA competitor. Poly(dG-Br5dC) in the Z-form competed well for the binding of a zuotin containing fraction, but salmon sperm DNA, poly(dG-dC) and poly(dA-dT) were not effective. Negatively supercoiled plasmid pUC19 did not compete, whereas an otherwise identical plasmid pUC19(CG), which contained a (dG-dC)7 segment in the Z-form was an excellent competitor. A Southwestern blot using [32P]poly(dG-m5dC) as a probe in the presence of MgCl2 identified a protein having a molecular weight of 51 kDa. The 51 kDa zuotin was partially sequenced at the N-terminal and the gene, ZUO1, was cloned, sequenced and expressed in Escherichia coli; the expressed zuotin showed similar Z-DNA binding activity, but with lower affinity than zuotin that had been partially purified from yeast. Zuotin was deduced to have a number of potential phosphorylation sites including two CDC28 (homologous to the human and Schizosaccharomyces pombe cdc2) phosphorylation sites. The hexapeptide motif KYHPDK was found in zuotin as well as in several yeast proteins, DnaJ of E.coli, csp29 and csp32 proteins of Drosophila and the small t and large T antigens of the polyoma virus. A 60 amino acid segment of zuotin has similarity to several histone H1 sequences. Disruption of ZUO1 in yeast resulted in a slow growth phenotype.

NASA Discipline Exobiology↗

DOE OSTI2026

FIB-ToF-SIMS characterization of irradiated U-10Zr

Post-irradiation examination (PIE) is critical for the performance assessment and qualification of nuclear fuels. Secondary ion mass spectrometry (SIMS) is a powerful materials characterization technique that allows for elemental and isotopic mapping with a depth resolution greater than EDS and EPMA. However, it has not yet been applied to PIE of metallic nuclear fuel. Here, in this work, we characterize an fast neutron spectrum irradiated U-10Zr fuel sample using a time-of-flight SIMS (ToF-SIMS) system connected to a FIB/SEM system, which allows for flexible sample analysis compared to a dedicated ToF-SIMS instrument. Analysis of the resulting hyperspectral micrograph data was aided by the development of an unsupervised machine learning (ML) algorithm that iterates on existing methods to segment the 3D micrographic datasets based on the similarity of mass spectra. The results showed that the FIB-ToF-SIMS instrument was potentially capable of spatially resolving closed fission gas bubbles in 3D by continued ion sputtering of the analyzed volume. Additionally, the ML algorithm proved useful in revealing the chemical segregation of light fission products (those with an atomic mass between approximately 85–105 amu, such as ruthenium and rhodium) plus matrix zirconium, heavy fission products (those with an atomic mass between approximately 135–150 amu, such as the lanthanides) and uranium. Future studies are planned to conduct FIB-ToF-SIMS analysis on more irradiated U-Zr samples to study the constituent redistribution.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

DOE OSTI2021

Ultra-Structural Imaging Provides 3D Organization of 46 Chromosomes of a Human Lymphocyte Prophase Nucleus

Three dimensional (3D) ultra-structural imaging is an important tool for unraveling the organizational structure of individual chromosomes at various stages of the cell cycle. Performing hitherto uninvestigated ultra-structural analysis of the human genome at prophase, we used serial block-face scanning electron microscopy (SBFSEM) to understand chromosomal architectural organization within 3D nuclear space. Acquired images allowed us to segment, reconstruct, and extract quantitative 3D structural information about the prophase nucleus and the preserved, intact individual chromosomes within it. Our data demonstrate that each chromosome can be identified with its homolog and classified into respective cytogenetic groups. Thereby, we present the first 3D karyotype built from the compact axial structure seen on the core of all prophase chromosomes. The chromosomes display parallel-aligned sister chromatids with familiar chromosome morphologies with no crossovers. Furthermore, the spatial positions of all 46 chromosomes revealed a pattern showing a gene density-based correlation and a neighborhood map of individual chromosomes based on their relative spatial positioning. A comprehensive picture of 3D chromosomal organization at the nanometer level in a single human lymphocyte cell is presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

NASA NTRS1993

Two generalizations of Kohonen clustering

The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.

Bezdek, James C.↗

NASA NTRS1976

On the computational cost of approximating and recognizing noise-perturbed straight lines and quadratic arcs in the plane

Recognition of underlying straight lines and quadratic arcs in line drawings, and approximation of very noisy data by such line/curve segments, is addressed as a subproblem of the more general problem of optimum recognition of complicated line/curve drawings. Some specific algorithms are presented with extensions and interpretations for more complicated applications, and a data generation model is developed for the problem. Data are generated as a perturbation of a single underlying straight line or an elliptic or hyperbolic arc. Recursive estimation techniques, minimization of central processing unit time, decision making with controlled error probabilities, and modeling and recognition of pictures consisting of noisy curves are dealt with. Applications envisaged include: picture data compression, contour line representation in maps, intelligent data searches, and ballistic missile decoy tracking.

Cooper, D. B.↗

NASA NTRS1984

Scarp development in the Valles Marineris

The scarps along the margins of the Vales Marineris display a complex assemblage of forms that have been related to a variety of mass wasting and sapping processes. These scarp segments display variations in the degree of development of spur and gully topography, the number and density of apparent sapping features and the frequency of large scale landslides which reflect the age, geology and processes of slope development throughout the Valles Marineris. This regional analysis should provide more information on the geologic evolution of the Valles Marineris as well as new insight into the relative importance of different processes in the development of the scarp forms. In order to evaluate the regional variation in scarp form and the influence of time and structure on scarp development geomorphic mapping and morphometric analysis of geologically distinct regions of Valles Marineris is being undertaken.

Patton, P. C.↗

NASA NTRSDate not supplied

The Wizard Staff: A Mobile Tool Supporting Human Exploration on The Lunar Surface

The Wizard Staff is a rechargeable, battery powered mobile tool with multiple uses for lunar surface exploration. It supports human activity as a surface survey tool, provides external illumination to enhance safety, delivers networking, communications, and navigation features to remote sites, and assists crew rescue with an emergency beacon and rigid splint structure. As a survey tool, it assists crewed geologic field site exploration with external lights, cameras, and LiDAR to illuminate, map, and record the sample collection process. As a relay station, it provides a surface intranet communications and navigation node for extended exploration far from the lander or habitation module. A separately developed Search-and-Rescue (SAR) handheld device can broadcast a signal to the Gandalf Staff containing crew position and biometric data. The staff then formats the message and sends it orbiting satellite(s) for emergency response via the LunaNET on a dedicated frequency similar to terrestrial applications using an Emergency Position-Indicating Radiobeacon (EPIRB). The staff is designed with an upper and lower segment. Components in the upper segment are the LiDAR, external lighting arrays, cameras, communications equipment, intelligence devices, and user interface for crew operations. The lower segment is a set of FeLiPO4 battery cells packed into the 2” diameter carbon fiber tube. When the battery pack is discharged, a spring connector (designed for the dusty lunar environment) easily disconnects the two segments for replacement with another fully charged battery pack. The lower segment can be used for Incapacitated Crew Rescue (ICR) as a rigid splint. As a stand-alone science platform, the Wizard Staff provides infrastructure for instruments and sensors to record the lunar environment over long periods of time. After a crew installs the components on the lunar surface, the platform delivers data to the lunar lander or base station for analysis. The stand-alone mode requires an auxiliary power source (e.g. solar array) and energy storage system (e.g. battery), so it could also be used as an electrical recharging station. A working prototype of Wizard Staff has been developed with collaboration between NASA (JSC, MSFC, and GSFC), Texas Space Technology Applications and Research (T STAR), and Texas A&M University (TAMU) using $300k of innovation funding in FY’21 and FY’22. The functional staff weights 36# on Earth (6# on the Moon), stands 2.1m tall and delivers external lighting with an array of 40 LED bulbs generating 1460 Lux at 2m range (near field), or 2 Lux at 50m (far field).

Gandalf Staff↗

DOE OSTI2025

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within 3m error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building > 12m . Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1972

Earthquake epicenters and fault intersections in central and southern California

The author has identifed the following significant results. ERTS-1 imagery provided evidence for the existence of short transverse fault segments lodged between faults of the San Andreas system in the Coast Ranges, California. They indicate that an early episode of transverse shear has affected the Coast Ranges prior to the establishment of the present San Andreas fault. The fault has been offset by transverse faults of the Transverse Ranges. It appears feasible to identify from ERTS-1 imagery geomorphic criteria of recent fault movements. Plots of historic earthquakes in the Coast Ranges and western Transverse Ranges show clusters in areas where structures are complicated by interaction of tow active fault systems. A fault lineament apparently not previously mapped was identified in the Uinta Mountains, Utah. Part of the lineament show evidence of recent faulting which corresponds to a moderate earthquake cluster.

Abdel-Gawad, M.↗

NASA NTRS1976

Distribution of small channels on the Martian surface

The distribution of small channels on Mars has been mapped from Mariner 9 images at the 1:5,000,000 scale. The small channels referred to here are small valleys ranging in width from the resolution limit of the Mariner 9 wide-angle images (about 1 km) to about 10 km. The greatest density of small channels occurs in dark cratered terrain. This dark zone forms a broad subequatorial band around the planet. The observed distribution may be the result of decreased small-channel visibility in bright areas due to obscuration by a high albedo dust or sediment mantle. Crater densities within two small-channel segments show crater size-frequency distributions consistent with those of the oldest of the heavily cratered plains units. Such crater densities coupled with the almost exclusive occurrence of small channels in old cratered terrain and the generally degraded appearance of small channels in the high-resolution images (about 100 m) imply a major episode of small-channel formation early in Martian geologic history.

Pieri, D.↗

NASA NTRSDate not supplied

VIPER: Systems Integration Status

NASA’s Artemis Program plans to return humans to the Moon for an extended stay. To do so will require substantial resources to sustain that continued human presence, including continuous supplies delivered from the Earth. Given the expense and complexity of resource deliveries from Earth, if some resources were indigenously available, substantial logistical savings could be available by “living off the land”, wherever possible. The LCROSS[1] , LRO and other missions have confirmed the presence of resources such as water-ice and other volatiles in lunar polar regions, so the next step is to understand the scientific nature and physical distribution of those candidate resources. Those local volatiles could be processed into propellants and human life-supporting needs, reducing risk of maintaining a permanent human presence on the Moon. The Volatiles Investigating Polar Exploration Resource (VIPER) is a surface mobility scientific platform, designed to spend ~100 days mapping and surveying four different Ice Stability Regions to understand the scientific nature and distribution of water and other volatiles. VIPER will also provide scientific mineralogical context of the lunar regolith, such as the presence of silicon and light metals in lunar regolith, providing a composite picture of resource availability and sustainment. This paper will discuss the latest systems-level integration activities by the VIPER team, following our initial introduction to this mission at IAC2021[2] . The VIPER team successfully passed its Systems Integration Review (SIR) in late-2022, and in early 2023, began system-level surface segment (rover) flight hardware assembly. VIPER is managed within NASA’s Science Mission Directorate (SMD), utilizing the Commercial Lunar Payload Services (CLPS) lunar delivery model with partner, Astrobotic, Inc.

VIPER↗

NASA NTRS1979

Low-level processing for real-time image analysis

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

Eskenazi, R.↗

NASA NTRS2012

An Overview of the Lightning - Atmospheric Chemistry Aspects of the Deep Convective Clouds and Chemistry (DC3) Experiment

Some of the major goals of the DC3 experiment are to determine the contribution of lightning to NO(x) in the anvils of observed thunderstorms, examine the relationship of lightning NO(x) production to flash rates and to lightning channel lengths, and estimate the relative production per flash for cloud-to-ground flashes and intracloud flashes. In addition, the effects of lightning NO(x) production on photochemistry downwind of thunderstorms is also being examined. The talk will survey the observation types that were conducted during DC3 relevant to these goals and provide an overview of the analysis and modeling techniques which are being used to achieve them. NO(x) was observed on three research aircraft during DC3 (the NCAR G-V, the NASA DC-8, and the DLR Falcon) in flights through storm anvils in three study regions (NE Colorado, Central Oklahoma to West Texas, and northern Alabama) where lightning mapping arrays (LMAs) and radar coverage were available. Initial comparisons of the aircraft NOx observations in storm anvils relative to flash rates have been conducted, which will be followed with calculations of the flux of NO(x) through the anvils, which when combined with observed flash rates can be used to estimate storm-average lightning NOx production per flash. The WRF-Chem model will be run for cloud-resolved simulations of selected observed storms during DC3. Detailed lightning information from the LMAs (flash rates and flash lengths as a function of time and vertical distributions of flash channel segments) will be input to the model along with assumptions concerning NO(x) production per CG flash and per IC flash. These assumptions will be tested through comparisons with the aircraft NOx data from anvil traverses. A specially designed retrieval method for lightning NO2 column amounts from the OMI instrument on NASA fs Aura satellite has been utilized to estimate NO2 over the region affected by selected DC3 storms. Combined with NO(x) to NO2 ratios from the aircraft data and WRF-Chem model and observed flash rates, average NO(x) production per flash can be estimated. Ozone production downwind of observed storms can be estimated from the WRF-Chem simulations and the specific downwind flights.

Pickering, K. E.↗

DOE OSTI2024

Unpaired image translation to mitigate domain shift in liquid argon time projection chamber detector responses

Deep learning algorithms often are developed and trained on a training dataset and deployed on test datasets. Any systematic difference between the training and a test dataset may severely degrade the final algorithm performance on the test dataset—what is known as the domain shift problem . This issue is prevalent in many scientific domains where algorithms are trained on simulated data but applied to real-world datasets. Typically, the domain shift problem is solved through various domain adaptation (DA) methods. However, these methods are often tailored for a specific downstream task, such as classification or semantic segmentation, and may not easily generalize to different tasks. This work explores the feasibility of using an alternative way to solve the domain shift problem that is not specific to any downstream algorithm. The proposed approach relies on modern Unpaired Image-to-Image (UI2I) translation techniques, designed to find translations between different image domains in a fully unsupervised fashion. In this study, the approach is applied to a domain shift problem commonly encountered in Liquid Argon Time Projection Chamber (LArTPC) detector research when seeking a way to translate samples between two differently distributed LArTPC detector datasets deterministically. This translation allows for mapping real-world data into the simulated data domain where the downstream algorithms can be run with much less domain-shift-related performance degradation. Conversely, using the translation from the simulated data to a real-world domain can increase the realism of the simulated dataset and reduce the magnitude of any systematic uncertainties. To evaluate the quality of the translations, we use both pixel-wise metrics and a downstream task to measure the effectiveness of UI2I methods for mitigating the domain shift problem. We adapted several popular UI2I translation algorithms to work on scientific data and demonstrated the viability of these techniques for solving the domain shift problem with LArTPC detector data. To facilitate further development of DA techniques for scientific datasets, the ‘Simple Liquid-Argon Track Samples’ dataset used in this study is also published.

97 MATHEMATICS AND COMPUTING↗