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A Comprehensive Characterization of Microorganisms and Allergens in Spacecraft Environment

The determination of risk from infectious disease during long-duration missions is composed of several factors including the concentration and the characteristics of the infectious agent. Thus, a thorough knowledge of the microorganisms aboard spacecraft is essential in mitigating infectious disease risk to the crew. While stringent steps are taken to minimize the transfer of potential pathogens to spacecraft, several medically significant organisms have been isolated from both the Mir and International Space Station (ISS). Historically, the method for isolation and identification of microorganisms from spacecraft environmental samples depended upon their growth on culture media. Unfortunately, only a fraction of the organisms may grow on a culture medium, potentially omitting those microorganisms whose nutritional and physical requirements for growth are not met. Thus, several pathogens may not have been detected, such as Legionella pneumophila, the etiological agent of Legionnaire s disease. We hypothesize that environmental analysis using non-culture-based technologies will reveal microorganisms, allergens, and microbial toxins not previously reported in spacecraft, allowing for a more complete health assessment. The development of techniques for this flight experiment, operationally named SWAB, has already provided advances in NASA laboratory processes and beneficial information toward human health risk assessment. The translation of 16S ribosomal DNA sequencing for the identification of bacteria from the SWAB experiment to nominal operations has increased bacterial speciation of environmental isolates from previous flights three fold compared to previous conventional methodology. The incorporation of molecular-based DNA fingerprinting using repetitive sequence-based polymerase chain reaction (rep-PCR) into the capabilities of the laboratory has provided a methodology to track microorganisms between crewmembers and their environment. Both 16S ribosomal DNA identification and bacterial fingerprinting have improved NASA s capability to better understand spacecraft environments and determine the source of contamination events. Preflight sampling has been completed for air, surface, and water samples. In-flight sample collection has been completed for a total of 8 air and surface sample collection sessions. In-flight hardware has performed well and the surface sampling device received positive feedback from the crew for its ease of use. While processing and analysis continue for these samples, early results have begun to provide information on the spacecraft environment. Using a method called Denaturing Gradient Gel Electrophoresis (DGGE), several air and samples were evaluated to determine the types of organisms that were present. Using only molecular techniques, DGGE does not depend on any microbial growth on culture media, allowing a more comprehensive assessment of the spacecraft interior. Preliminary results have identified several microorganisms that would not have been isolated using current technology, though none of these organisms would be considered medically significant. Interestingly, the isolation of Gram negative organisms is greater using DGGE than conventional media based isolation. The cause of this finding is unclear, though it may be the result of the technique s ability to isolate both viable and non-viable bacteria. The next phase of the SWAB sample analysis is the use of quantitative polymerase chain reaction (QPCR) to look for specific medically significant organisms. While not as broad as DGGE, QPCR is much more sensitive and may reveal findings that were not seen during the initial evaluation. Together, this information will lead toward an accurate microbial risk assessment to help set flight requirements to protect the safety, health, and performance of the crew.

Castro, V.A.↗

Near-UV Sources in the Hubble Ultra Deep Field: The Catalog

The catalog from the first high resolution U-band image of the Hubble Ultra Deep Field, taken with Hubble s Wide Field Planetary Camera 2 through the F300W filter, is presented. We detect 96 U-band objects and compare and combine this catalog with a Great Observatories Origins Deep Survey (GOODS) B-selected catalog that provides B, V, i, and z photometry, spectral types, and photometric redshifts. We have also obtained Far-Ultraviolet (FUV, 1614 Angstroms) data with Hubble s Advanced Camera for Surveys Solar Blind Channel (ACS/SBC) and with Galaxy Evolution Explorer (GALEX). We detected 31 sources with ACS/SBC, 28 with GALEX/FUV, and 45 with GALEX/NUV. The methods of observations, image processing, object identification, catalog preparation, and catalog matching are presented.

Gardner, Jonathan P.↗

Modulated High-Energy Gamma-Ray Emission from the Microquasar Cygnus X-3

Microquasars are accreting black holes or neutron stars in binary systems with associated relativistic jets. Despite their frequent outburst activity, they have never been unambiguously detected emitting high-energy gamma rays. The Fermi Large Area Telescope (LAT) has detected a variable high-energy source coinciding with the position of the x-ray binary and microquasar Cygnus X-3. Its identification with Cygnus X-3 is secured by the detection of its orbital period in gamma rays, as well as the correlation of the LAT flux with radio emission from the relativistic jets of Cygnus X-3. The gamma-ray emission probably originates from within the binary system, opening new areas in which to study the formation of relativistic jets.

Celik, O.↗

Microbial Diversity Aboard Spacecraft: Evaluation of the International Space Station

An evaluation of the microbial flora from air, water, and surface samples provided a baseline of microbial diversity onboard the International Space Station (ISS) to gain insight into bacterial and fungal contamination during the initial stages of construction and habitation. Using 16S genetic sequencing and rep-PeR, 63 bacterial strains were isolated for identification and fingerprinted for microbial tracking. The use of these molecular tools allowed for the identification of bacteria not previously identified using automated biochemical analysis and provided a clear indication of the source of several ISS contaminants. Fungal and bacterial data acquired during monitoring do not suggest there is a current microbial hazard to the spacecraft, nor does any trend indicate a potential health risk. Previous spacecraft environmental analysis indicated that microbial contamination will increase with time and require continued surveillance.

Castro, Victoria A.↗

Prognostics of Power Electronics, Methods and Validation Experiments

Abstract Failure of electronic devices is a concern for future electric aircrafts that will see an increase of electronics to drive and control safety-critical equipment throughout the aircraft. As a result, investigation of precursors to failure in electronics and prediction of remaining life of electronic components is of key importance. DC-DC power converters are power electronics systems employed typically as sourcing elements for avionics equipment. Current research efforts in prognostics for these power systems focuses on the identification of failure mechanisms and the development of accelerated aging methodologies and systems to accelerate the aging process of test devices, while continuously measuring key electrical and thermal parameters. Preliminary model-based prognostics algorithms have been developed making use of empirical degradation models and physics-inspired degradation model with focus on key components like electrolytic capacitors and power MOSFETs (metal-oxide-semiconductor-field-effect-transistor). This paper presents current results on the development of validation methods for prognostics algorithms of power electrolytic capacitors. Particularly, in the use of accelerated aging systems for algorithm validation. Validation of prognostics algorithms present difficulties in practice due to the lack of run-to-failure experiments in deployed systems. By using accelerated experiments, we circumvent this problem in order to define initial validation activities.

Kulkarni, Chetan S.↗

Knowledge Network Embedding of Transcriptomic Data From Spaceflown Mice Uncovers Signs and Symptoms Associated With Terrestrial Diseases

There has long been an interest in understanding how the hazards from spaceflight may trigger or exacerbate human diseases. With the goal of advancing our knowledge on physiological changes during space travel, NASA GeneLab provides an open-source repository of multi-omics data from real and simulated spaceflight studies. Alone, this data enables identification of biological changes during spaceflight, but cannot infer how that may impact an astronaut at the phenotypic level. To bridge this gap, SPOKE, a heterogeneous knowledge graph connecting biological and clinical data from over 30 databases, was used in combination with GeneLab transcriptomic data from six studies. This integration identified critical symptoms and physiological changes incurred during spaceflight.

spaceflight↗

European sources of halocarbons and nitrous oxide - Update 1986

New information on seasonal and secular trends in the releases of CFCl3, CF2Cl2, CCl4, CH3CCl3, and N20 from Europe was obtained as part of the Atmospheric Lifetime Experiment. Semicontinuous measurements of these pollutants were made at Adrigole, Ireland, using lean air from the Atlantic Ocean as a baseline. The results obtained include unambiguous evidence for elevated levels of N2O occurring concurrent with halocarbon pollution events; the detection of trends in the relative emission of different halocarbons; the discovery of seasonal variations in emission of CF2Cl2, CCl4, and CH3Cl3; the characterization of typical summer and winter pollution episodes; and the identification of weather patterns over Europe that are associated with high concentrations of chlorofluorocarbons at Adrigole. It was estimated that the European source of N2O represents 25 percent of the global emissions associated with combustion and 10 percent of the integrated stratospheric losses.

Prather, Michael↗

High Energy X-ray Applications for the Characterization of Metallic Uranium Alloys

Uranium-based metallic alloys are both candidates for fuels in high performance research and test reactors, as well as in fast spectrum reactors as nuclear transmutation fuels that can be utilized to burn long-lived minor actinides and fission products. Uranium-molybdenum (UMo) alloys are under development for the use in research and test reactors. Whereas, uranium-zirconium (U-Zr) alloys represent one of the types of fuels that are under consideration for use within the fast spectrum reactors. Both of these types of metallic fuels have been studied for over five decades in various types of reactors. Many of the previous studies had focused on performance-based aspects. However, recent advances in characterization tools and techniques, as well as short-term (low fluence) neutron irradiation facilities have contributed to a more in-depth understanding of nuclear fuel and material behavior following irradiation. This knowledge is crucial to the enhancement of current modeling and simulation techniques, particularly with respect to parameterization and validation. This paper focuses on the use of high energy x-rays to characterize metallic nuclear fuel. The specimens were composed of depleted uranium (DU) alloyed with either Zr or Mo, where DU-xZr (x = 10, 15, or 20 wt.%) and DU-yMo (y = 7 or 10 wt.%). The geometries of the specimens were 3 mm TEM disks that were ∼200 μm in thickness. The fuel alloys were initially prepared via an arc melting process. The samples were irradiated at the Advanced Test Reactor at Idaho National Laboratory (INL) using the hydraulic rabbit system. The hydraulic rabbit system allows for well-controlled, short term irradiations (less than one cycle), hence resulting in low fluences. The U-based alloys were irradiated to doses of 0.01 and 0.1 dpa. The irradiation temperature of the specimens ranged from 150 deg. C to 800 deg. C. Synchrotron characterization techniques can be used to provide insight into material microstructure ranging a multitude of spatial scales, from the atomic scale to the macroscale. High-energy x-rays at the National Synchrotron Light Source II (NSLS II) and the Advanced Photon Source (APS) have been utilized to understand the microstructural changes in these metallic alloys, specifically with respect to phase identification, phase fractions, chemical bonding, strain, and dislocation density through the use of diffraction and X-ray Absorption Spectroscopy (XAS). These experiments utilized a robot for specimen exchange during the diffraction measurements, allowing for remote handling of radioactive materials. This is an example of another recent advancement in characterization techniques that enables research with nuclear materials. Detailed results of the analyses of the microstructural changes are pending.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Automated Reconstruction, Signal Processing and Particle Identification in DUNE

Liquid Argon TPC (LArTPC) technology is increasingly prevalent in large-scale detectors designed to observe neutrino scattering events induced by accelerators or by natural sources. LArTPCs consist of a very high fraction of active detector material with spatial resolutions on the order of a few millimeters. Three-dimensional interactions are imaged in multiple two-dimensional views by the process of projection onto planes of wires. The goal of automated reconstruction is to correctly classify each neutrino scattering event by the flavor of the incoming neutrino, to separate charged-current events from neutral-current and other backgrounds, and to measure the energies of the incoming neutrinos. Detection of neutrinos from supernova bursts and also seaching for nucleon decay are important uses of automated reconstruction algorithms. Because the amount of spatial detail is high and the amount of scattering is high, this reconstruction presents many challenges that are now being investigated with sophisticated techniques.Signal processing, track and shower identification, particle identification, and event classification by a variety of innovative algorithms are reviewed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Assessing Single-Source Reproducibility of Human Head Hair Peptide Profiling from Different Regions of the Scalp

Neither microscopical hair comparisons nor mitochondrial DNA sequencing alone, or together, constitutes a basis for personal identification. Due to these limitations, a complementary technique to compare questioned and known hair shafts was investigated. Recently, scientists from Lawrence Livermore National Laboratory's Forensic Science Center and other collaborators developed a peptide profiling technique, which can infer non-synonymous single nucleotide polymorphisms (SNPs) preserved in hair shaft proteins as single amino acid polymorphisms (SAPs). In this study, peptide profiling was evaluated to determine if it can meet forensic expectations when samples are in limited quantities with the possibility that hair samples collected from different areas of a single donor’s scalp (i.e., single source) might not exhibit the same SAP profile. The average dissimilarity, percent differences in SAP profiles within each source, ranged from 0% difference to 29%. This pilot study suggests that more work is needed before peptide profiling of hair can be considered for forensic comparisons.

59 BASIC BIOLOGICAL SCIENCES↗

Common Column Identification for Table Similarity Detection in Electrified Transportation Data Lakes

Electrified transportation often requires researchers and operators to interact with datasets from a wide range of sources and disciplines, such as transportation, power systems, public health, policies, and regulations. These datasets vary in quality and format, making it difficult to understand, preprocess, and identify key columns representing real-world entities or values for indexing and joining, which can negatively impact downstream analysis and operation. Existing solutions are limited, requiring extensive manual customization or data expertise to utilize. In this article, we propose a multi-layered approach to automatically identify key columns to expedite preprocessing and aid in analysis of electrified transportation data. Our method leverages a dynamic ontology to identify common fields and an information theory-based strategy for edge cases that are difficult to generalize. Evaluations on a number of datasets from data.gov and kaggle.com show improved performance of our methods over several baseline techniques, and our ablation analyses illustrate the efficacy of individual components of our method. Our case studies also demonstrate that our methods have the potential to improve analysis of electrified transportation data and aid in automatic integration of such datasets.

33 ADVANCED PROPULSION SYSTEMS↗

The Highest L(sub X)/L(sub opt) Sources in the ROSAT All-Sky Survey

The purpose of our program was to identify new and interesting soft X-ray sources from the Bright Source Catalog of the ROSAT All-Sky Survey. Our intent was to use XMM to observe a sample of BSC objects that had been identified as less than 10% likely to be associated with any object in the USNO-A2.0 catalog (Rutledge et al. 2000). We requested a single 5-ks pointing for each of 32 sources in this category in order to make a systematic examination of the properties of these sources. Ultimately, we hoped to identify new isolated neutron stars from within this population. Our requested observations were scheduled for execution at the end of Cycle 2, for two of our targets only (selected by sky position). A two-target sample does not allow for the statistical investigation that we originally proposed; however, based on the identification of the BSC object in the XMM data, an improved position, and reevaluation of likely off-band counterparts, it does enable a source-by-source evaluation of whether the BSC object is an isolated neutron star (INS).

Kulkarni, Shrinivas R.↗

Identification of subsurface structures using electromagnetic data and shape priors

We consider the inverse problem of identifying large-scale subsurface structures using the controlled source electromagnetic method. To identify structures in the subsurface where the contrast in electric conductivity can be small, regularization is needed to bias the solution towards preserving structural information. We propose to combine two approaches for regularization of the inverse problem. In the first approach we utilize a model-based, reduced, composite representation of the electric conductivity that is highly flexible, even for a moderate number of degrees of freedom. With a low number of parameters, the inverse problem is efficiently solved using a standard, second-order gradient-based optimization algorithm. Further regularization is obtained using structural prior information, available, e.g., from interpreted seismic data. The reduced conductivity representation is suitable for incorporation of structural prior information. Such prior information cannot, however, be accurately modeled with a gaussian distribution. To alleviate this, we incorporate the structural information using shape priors. The shape prior technique requires the choice of kernel function, which is application dependent. We argue for using the conditionally positive definite kernel which is shown to have computational advantages over the commonly applied gaussian kernel for our problem. Numerical experiments on various test cases show that the methodology is able to identify fairly complex subsurface electric conductivity distributions while preserving structural prior information during the inversion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Automatic Identification of Solar X-Ray Bright Points in Hinode X-Ray Data

We have automated a method that is used to find point sources in Chandra X-ray telescope data, to identify solar bright points in Hinode X-ray data. This tool, called lextrct, first identifies candidate sources that are brighter than the surrounding background. The algorithm also allows selected pixels to be excluded from the source-finding, thus allowing saturated pixels (from flares and/or active regions) to be ignored. We then use lextrct to fit the sources to two-dimensional, elliptical Gaussians. The size and orientation give an approximation of the shape of the bright points. We are in the process of analyzing observations through the Al_poly filter with a four-second exposure time, to obtain a catalogue of bright points, which will include their sizes, lifetimes, intensities, and position on the solar disk

Adams, M. L.↗

Mid-Award Progress Report for Department of Energy Office of Science Graduate Student Research Program

The purpose of the work proposed for this study is to investigate the behavior and transport mechanisms for cesium-137 in soils collected from contaminated sites with distinct source release scenarios. More specifically, this study aims to determine with which elements and minerals cesium-137 associates in these various environments to more reliably predict its migration in the subsurface. This will be achieved using a state-of-the-art analysis technique available at Lawrence Livermore National Laboratory (LLNL) known as NanoSIMS. Nano-scale secondary ion mass spectrometry, or NanoSIMS, is a destructive surface analysis technique in which positive secondary ions are generated from the surface of a sample and then quantified based on their mass-to-charge ratio (m/z) using mass spectrometry. The data collected about the secondary ions can then be used to create isotope-specific spatial maps with a resolution of a few hundred nanometers and depth profiles that show the variation of the secondary ion intensity with sputtering time. This should be an ideal technique for locating cesium-137 in a sample, as cesium is an easily ionized element, meaning the yield of secondary cesium (Cs) ions produced should be high and making the identification of cesium-137 straight forward.

07 ISOTOPE AND RADIATION SOURCES↗

Comparison of Dynamic Stability Testing Techniques with Magnetic Suspension Wind Tunnel

Dynamic stability testing techniques currently utilized at NASA Langley Research Center (LaRC) are conducted in multiple facilities and consists of free flight, forced oscillation, and free-to-oscillate tests. The MIT/NASA/ODU Magnetic Suspension and Balance System (MSBS) has been recommissioned to explore its utility as an additional facility to expand the dynamic stability test capabilities currently available at NASA LaRC. Simulations were created to replicate each current test facility and method as closely as possible. Data collected from the simulated environments was corrupted with replicated noise sources of the different testing environments and then compared to real data collected during tests when such data was available. The corrupted data was then passed through data reduction and System Identification (SID) to estimate the accuracy of the results with the known aerodynamic model that was utilized within the simulation to generate the original data. Magnitudes of noise were varied utilizing Monte Carlo analysis to perform sensitivity analysis of each noise source on the extracted dynamic stability coefficients. Some preliminary results will be presented.

Otoniel Ramirez↗

Comparison of Dynamic Stability Testing Techniques with Magnetic Suspension Wind Tunnel

Dynamic stability testing techniques currently utilized at NASA Langley Research Center (LaRC) are conducted in multiple facilities and consists of free flight, forced oscillation, and free-to-oscillate tests. The MIT/NASA/ODU Magnetic Suspension and Balance System (MSBS) has been recommissioned to explore its utility as an additional facility to expand the dynamic stability test capabilities currently available at NASA LaRC. Simulations were created to replicate each current test facility and method as closely as possible. Data collected from the simulated environments was corrupted with replicated noise sources of the different testing environments and then compared to real data collected during tests when such data was available. The corrupted data was then passed through data reduction and System Identification (SID) to estimate the accuracy of the results with the known aerodynamic model that was utilized within the simulation to generate the original data. Magnitudes of noise were varied utilizing Monte Carlo analysis to perform sensitivity analysis of each noise source on the extracted dynamic stability coefficients. Some preliminary results will be presented.

Otoniel Ramirez↗