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NASA NTRSDate not supplied

Does Collection Time Bias the Ecology of Cleanroom Air Samples?

Microbial monitoring of astromaterials collections has taken on increased importance with the return of biologically sensitive samples from the asteroids Ryugu and Bennu and the initiation of the Mars Sample Return Program. Terrestrial bacteria and fungi can alter the mineralogy and organic composition of our collections causing irreversible contamination of pristine samples and increasing the risk of false positives for life detection measurements. NASA has conducted routine microbial monitoring of its existing collections since 20181. Initial monitoring focused on surface samples collected with foam swabs. Although, airborne microbiology is often decoupled from surface microbiology in the built environment2 culture-based air sampling techniques like impactors were not compliant with existing contamination control requirements. Bringing organic rich media, gelatin or liquids into curation cleanrooms presents an unacceptable risk to pristine samples. In 2022 NASA purchased a materials complaint air sampler and began collecting air samples from the cleanrooms in addition to surface samples3. The new instrument uses an electret filter to collect samples that are suitable for cultivating organisms or for direct DNA sequencing. Preliminary DNA sequencing results appeared to indicate that longer sampling times biased the microbial community in favor of hearty, spore-forming bacteria3. We present the results of a study comparing overnight sampling (17 hours) to short (1 hour) sampling of unoccupied curation cleanrooms. The results will help us optimize our monitoring protocols and develop a more detailed inventory of the ecology of astromaterials curation cleanrooms. Methods: We analyzed 72 paired air samples from six different cleanrooms including the meteorite processing lab (ISO 7 equivalent, 16 samples), the lunar lab (ISO 6 equivalent, 10 samples), the stardust lab (ISO 5 equivalent 14 samples), the OSIRIS-REx lab (ISO 5 equivalent, 12 samples), the Hayabusa2 lab (ISO 5 equivalent, 14 samples), and the Genesis lab (ISO 4 equivalent, 6 samples). All the samples were collected with an InnovaPrep Bobcat air sampler operating at a sampling rate of 200 L/min. The sampler operates for 5 minutes out of every 20 minute period. Half of the samples were collected by filtering 3,000L (15 min. of active sampling) of air across an electret filter for one hour. The rest of the samples were collected by filtering approximately 51,000 L air across the filter overnight (~17 hours, 255 min. of active sampling). Cells were eluted from the filter using 6-7 ml of pressurized 0.15% tween 20 in PBS (phosphate buffered saline). This liquid was used to cultivate bacteria according to previously published methods1,4,5 and for DNA extraction and next generation sequencing. DNA was extracted with a Qiagen MagAttract PowerMicrobiome kit6. To identify bacteria and archaea, the 16S rRNA gene was amplified using Earth Microbiome primers for the V4 region 7. The amplified DNA was sequenced on an Illumina MiSeq using a V3 reagent kit. The resulting sequences were processed using DADA2 and QIIME2 as implemented on the EDGE bioinformatics platform8–10. Results: Only two of the 72 samples had no amplifiable DNA. Amplified DNA concentrations ranged from 2.67 – 0.272 ng/µl. The median concentration of amplified DNA for the 1 hour samples was 0.770 ± 0.368 ng/µl. The median concentration of amplified DNA for the overnight samples was 0.877 ± 0.434 ng/µl. On average the overnight samples had slightly more sequences (58,960 vs. 59,456) and ASV’s (amplicon sequence variants) (60 vs 64.5) than the one hour samples, but these differences are not statistically significant. The most abundant ASV in every sample mapped to the genus Cupravidus. ASV’s mapping to the genuses Bacillus, Schlegelella, Thermus, and Staphylococcus were also common. Discussion and Future Work: Alpha diversity statistics like Shannon Entropy and Faith Phylogenetic Diversity are used to describe the diversity of organisms in a single sample. If a longer sampling time was biasing the data, we would expect to see a change in these diversity statistics vs. sample time. However, we did not observe this in our data. The median Shannon entropy was slightly higher for the overnight samples (3.773 vs 3.611) as was the Faith Phylogenetic Diversity (4.042 vs 3.596), but both values were within a standard deviation of each other for the two sampling times (Fig. 1). It is unlikely, that the longer sampling time is introducing bias into our data. We do observe a significant decrease in diversity when comparing the air samples by lab. The Genesis lab (ISO 4 equivalent) has a lower median number of ASV’s (45.5) than the other labs (62). Median values for Shannon Entropy (3.717 vs. 3.430) and Faith Phylogenetic Diversity (3.796 vs. 3.548) are also lower for Genesis, but those values are with one standard deviation of each other for the different sampling times. This is consistent with previous culture-based results suggesting that the environment in cleanrooms tends to select for a core group of organisms capable of surviving under dry, low nutrient, conditions. The presence of the ASV’s mapping to Cupravidus and Thermus in our sequencing blanks and controls suggests that several of the most common organisms in our samples represent contaminants from the reagents used to perform the DNA extractions and sequencing. Further work is needed to identify these contaminants, remove them from our data and recalculate the diversity statistics. This is a systematic error. Therefore, we do not expect removing the sequencing contaminants to change our conclusions. Longer air sample collection times appear to result in slightly higher diversity and do not bias the results towards “hardy” bacteria like spore-formers. Based on these preliminary results we conclude that sampling at least 3,000 liters of air is sufficient to capture the microbial diversity of cleanrooms, and that air samples can also be collected overnight without negatively impacting diversity. These results allow us to be flexible when designing microbial monitoring plans so that they do not interfere with routine lab activity. References: 1. Regberg, A. B. et al. 49th Lunar and Planetary Science Conference (2018). 2. The United States Pharmacopeial Convention. USP General Chapter <1116> (2013). 3. Regberg, A. B., et al. 54th Lunar and Planetary Science Conference (2023). 4. Regberg, A. B. et al. 53rd Lunar and Planetary Science Conference ( 2022). 5. Davis, R. E.,et al. 50th Lunar and Planetary Science Conference (2019). 6. Qiagen. MagAttract® PowerMicrobiome® DNA/RNA EP Kit Handbook. (2018). 7. Walters, W. et al. mSystems 1, (2015). 8. Callahan, B. J. et al. Nat. Methods 13, 581–583 (2016). 9. Hall, M. & Beiko, R. G. Microbiome Analysis: Methods and Protocols113–129 (Springer, 2018). 10. Philipson, C. et al. Bio-Protoc. 7, e2622 (2017).

A. B. Regberg↗
NASA NTRS1999

ACTS Ka-band Propagation Research in a Spatially Diversified Network with Two USAT Ground Stations

Congestion in the radio spectrum below 18 GHz is stimulating greater interest in the Ka (20/30 GHz) frequency band. Transmission at these shorter wavelengths is greatly influenced by rain resulting in signal attenuation and decreased link availability. The size and projected cost of Ultra Small Aperture Terminals (USATS) make site diversity methodology attractive for rain fade compensation. Separation distances between terminals must be small to be of interest commercially. This study measures diversity gain at a separation distance <5 km and investigates utilization of S-band weather radar reflectivity in predicting diversity gain. Two USAT ground stations, separated by 2.43 km for spatial diversity, received a continuous Ka-band tone sent from NASA Glenn Research Center via the Advanced Communications Technology Satellite (ACTS) steerable antenna beam. Received signal power and rainfall were measured, and Weather Surveillance Radar-1998 Doppler (WSR-88D) data were obtained as a measure of precipitation along the USAT-to-ACTS slant path. Signal attenuation was compared for the two sites, and diversity gain was calculated for fades measured on eleven days. Correlation of WSR-88D S-band reflectivity with measured Ka-band attenuation consisted of locating radar volume elements along each slant path, converting reflectivity to Ka-band attenuation with rain rate calculation as an intermediate step. Specific attenuation for each associated path segment was summed, resulting in total attenuation along the slant path. Derived Ka-band attenuation did not correlate closely with empirical data (r = 0.239), but a measured signal fade could be matched with an increase in radar reflectivity in all fade events. Applying a low pass filter to radar reflectivity prior to deriving Ka-band attenuation improved the correlation between measured and derived signal attenuation (r = 0.733). Results indicate that site diversity at small separation distances is a viable means of rain fade compensation, and that existing models underestimate diversity gain for a subtropical climate such as Florida. Also, filtered WSR-88D reflectivity can be used for optimizing diversity terminal placement by comparing derived Ka- band attenuation between the diversity sites.

Kalu, Alex↗
NASA NTRS1989

Conceptual modeling of coincident failures in multiversion software

Recent work by Eckhardt and Lee (1985) shows that independently developed program versions fail dependently (specifically, simultaneous failure of several is greater than would be the case under true independence). The present authors show there is a precise duality between input choice and program choice in this model and consider a generalization in which different versions can be developed using diverse methodologies. The use of diverse methodologies is shown to decrease the probability of the simultaneous failure of several versions. Indeed, it is theoretically possible to obtain versions which exhibit better than independent failure behavior. The authors try to formalize the notion of methodological diversity by considering the sequence of decision outcomes that constitute a methodology. They show that diversity of decision implies likely diversity of behavior for the different verions developed under such forced diversity. For certain one-out-of-n systems the authors obtain an optimal method for allocating diversity between versions. For two-out-of-three systems there seem to be no simple optimality results which do not depend on constraints which cannot be verified in practice.

Littlewood, Bev↗
NASA NTRS1995

Overview of techniques for mitigation of fading and shadowing in the direct broadcast satellite radio environment

The DBS radio propagation environment is divided into three sub-environments, indoor, rural-suburban mobile and urban mobile. Indoor propagation effects are in a large part determined by construction material. Non-metallic materials afford direct, albeit attenuated penetration of the satellite signal with a minimum of multipath signal scattering. Signal penetration into structures using significant metallic materials is often indirect, through openings such as doors and windows and propagation will involve significant multipath components. Even so, delay spread in many situations is on the order of 10's of nanoseconds resulting in relatively flat fading. Thus frequency diversity techniques such as Orthogonal Frequency Division Multiplex (OFDM) and Code Division Multiple Access (CDMA) or equalization techniques do not realize their intended performance enhancement. Antenna diversity, directivity and placement are key mitigation techniques for the indoor environment. In the Rural-Suburban mobile environment with elevation angles greater than 20 deg, multipath components from the satellite signal are 15-20 dB below the line-of-sight signal level and often originate from nearby reflectors. Thus shadowing is the dominant signal impairment and fading effects are again found to be relatively flat for a large fading margin. Because receiver motion induces rapid variations in the signal level, temporal diversity techniques such as interleaving, channel coding and retransmission can be used to combat short intermittent fading events. Antenna diversity and directivity techniques are again useful in this environment. Finally, in the Urban mobile environment, slower vehicle speeds and blockage by buildings causes signal fades that are too long and too deep to combat with signal margin or time diversity. Land-based signal boosters are needed to fill in the coverage gaps of the satellite only broadcast scheme. On frequency boosters are suggested to conserve bandwidth yet these produce long delay multipath and create a frequency selective fading environment. Enter now OFDM, spread spectrum, equalization and other techniques that are capable of deconvolving the channel effects and effecting significant performance improvements by extracting the frequency diversity or time diversity components comprising the received signal.

Bell, David↗
NASA NTRS2011

Towards a Regolith Maturity Index for Howardites

The Dawn spacecraft has just arrived at asteroid 4 Vesta, parent of the howardite, eucrite and diogenite (HED) meteorites [1], to begin a yearlong surface study from orbit [2]. As Dawn will view a debris-covered surface, understanding the formation and mixing processes for the debris layer will strongly aid surface data interpretations. Howardites are polymict breccias mainly composed of clasts derived from basaltic (eucritic) and orthopy-roxenitic (diogenitic) parent materials [3]. Some howardites are poorly reworked (fragmental howardites) whilst others have been extensively gardened in an active regolith (regolithic howardites) [4]. The latter may represent an ancient, well-mixed regolith, whilst the former may be from more recent ejecta deposits [4]. Due to environmental differences, regolith development on Vesta differs in detail from that on the Moon [4-6]. We have been developing petrological criteria to apply to howardite thin sections to determine their relative regolithic maturity, which we are fine-tuning with comparison to noble gas data [7, 8]. Whilst we previously emphasized the abundance of reworked clasts (fragmental and impact-melt breccia clasts), this is an imperfect criterion: one howardite with abundant re-worked clasts (EET 99408) shows no evidence of solar wind Ne (SW-Ne), yet, two of our alleged fragmental howardites have clear SW-Ne signatures (LEW 85313, MET 00423) [7, 8]. We are now investigating the diversity in minor and trace element contents of low-Ca pyroxene clasts in howardites as a measure of regolith grade, and will begin analyses of such grains within reworked clasts. Our hypothesis is that regolithic howardites (and the breccia clasts they contain) will show greater diversity because they sampled more diverse diogenitic plutons than fragmental howardites, which formed from ejecta from only a few impacts [e.g. 4]. Our initial LA-ICP-MS work showed ranges in trace element diversity in low-Ca pyroxenes (estimated from the standard error of the mean of analyses), where those howardites considered of medium to high regolithic grade showed greater diversity [9]. Our EMPA results (from a larger howardite suite) show an overall greater diversity in our putative medium to high regolithic grade howardites, though there are exceptions. The greatest diversity is found for paired howardites GRO 95574 and GRO 95581, which were not considered regolithic in our initial study. We will continue investigating avenues to determine regolith maturity in thin section, factoring in bulk rock compositional data, and will coordinate these studies with noble gas results.

Mittlefehldt, David W.↗
NASA NTRSDate not supplied

Categorization of planets and exoplanets for Astrobiology.

Introduction: The number of exoplanets detected is astounding –and was not predicted. Note that Bo-rucki’s foundational paper for the Kepler mission in 1984 predicted:“...a detection rate of one planet per year of observation appears possible.”[1]. Even more astounding is the enormous diversity of exoplanets [2,3]. It is already clear from the data, that our Solar System does not bound the diversity and the range of processes seen in the exoplanets [2,3,4]. As telescopes improve it is certain that the number of exoplanets will become astronomical and the diversity will increase apace. The search for habitable locations and for evidence of life is a central part of the approach and excitement of exoplanet research [5,6]. Based on our experience to date we can expect that there will be enormous diversity in the types of habitability and life on exoplanets and that the Earth and our Solar System do not bound the possibilities for either habitability and life, and may not even provide a definite guide to selecting c and i-dates for detailed study from the enormous lists of exoplanets that will emerge. How can we develop a system for categorizing exoplanets in a way that allows for selection and prioritization in the search for diverse habitats and for diverse lifeforms?The short answer is we have no idea. In this short abstract I will venture some suggested approach-es. (see also[7]). To date, our solar system provides three classes for a habitable world:1) Earth. Water worlds, represented, of course, by Earth, and Earth-like worlds Venus and Mars. 2) Europa. Ice-covered worlds represented by Europa and including Enceladus and others, and 3) Titan. Cryogenic liquid covered worlds, represented by Titan. Earth and Europa world simply life made from carbon compounds in a water medium. Interest in these“ water worlds” is rooted in our understanding of life on Earth–the only example of life we have. The primary difference between Earth and Europa worlds is access to sunlight as an energy source on Earth. Titan represents the concept of carbon-based life in a cryogenic liquid such as CH4or C2H6 [8-13]. It is unlikely that Earth, Europa, and Titan represent the full range of possible classes of habitability for the many exoplanets that have been, or will be, discovered. It is also unlikely that life as we know it on Earth represents the full range of possible life on exoplanets. I am suggesting here that we start with these three classes (Earth, Europa, Titan) for exoplanet characterization and add others based on predicted types, such as “Hycean” worlds, a hypothetical type of planet with a hot, water-covered surface with a hydrogen dominated atmosphere [14] and the many examples considered in [15,16] and even imagined habitability and life forms [7] such as Sarr -a small, hot (500°C) rocky planet with an atmosphere over liquid sulfur. And that hosts only sulfur-based life. We are probably safe in the assumption that the richness and diversity of the exoplanets will exceed that of our collective imaginations.

Christopher P Mckay↗
NASA NTRS2001

Multifunctional Collaborative Modeling and Analysis Methods in Engineering Science

Engineers are challenged to produce better designs in less time and for less cost. Hence, to investigate novel and revolutionary design concepts, accurate, high-fidelity results must be assimilated rapidly into the design, analysis, and simulation process. This assimilation should consider diverse mathematical modeling and multi-discipline interactions necessitated by concepts exploiting advanced materials and structures. Integrated high-fidelity methods with diverse engineering applications provide the enabling technologies to assimilate these high-fidelity, multi-disciplinary results rapidly at an early stage in the design. These integrated methods must be multifunctional, collaborative, and applicable to the general field of engineering science and mechanics. Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple-method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized. The multifunctional methodology presented provides an effective mechanism by which domains with diverse idealizations are interfaced. This capability rapidly provides the high-fidelity results needed in the early design phase. Moreover, the capability is applicable to the general field of engineering science and mechanics. Hence, it provides a collaborative capability that accounts for interactions among engineering analysis methods.

Ransom, Jonathan B.↗
NASA NTRS2010

Algorithms for Learning Preferences for Sets of Objects

A method is being developed that provides for an artificial-intelligence system to learn a user's preferences for sets of objects and to thereafter automatically select subsets of objects according to those preferences. The method was originally intended to enable automated selection, from among large sets of images acquired by instruments aboard spacecraft, of image subsets considered to be scientifically valuable enough to justify use of limited communication resources for transmission to Earth. The method is also applicable to other sets of objects: examples of sets of objects considered in the development of the method include food menus, radio-station music playlists, and assortments of colored blocks for creating mosaics. The method does not require the user to perform the often-difficult task of quantitatively specifying preferences; instead, the user provides examples of preferred sets of objects. This method goes beyond related prior artificial-intelligence methods for learning which individual items are preferred by the user: this method supports a concept of setbased preferences, which include not only preferences for individual items but also preferences regarding types and degrees of diversity of items in a set. Consideration of diversity in this method involves recognition that members of a set may interact with each other in the sense that when considered together, they may be regarded as being complementary, redundant, or incompatible to various degrees. The effects of such interactions are loosely summarized in the term portfolio effect. The learning method relies on a preference representation language, denoted DD-PREF, to express set-based preferences. In DD-PREF, a preference is represented by a tuple that includes quality (depth) functions to estimate how desired a specific value is, weights for each feature preference, the desired diversity of feature values, and the relative importance of diversity versus depth. The system applies statistical concepts to estimate quantitative measures of the user s preferences from training examples (preferred subsets) specified by the user. Once preferences have been learned, the system uses those preferences to select preferred subsets from new sets. The method was found to be viable when tested in computational experiments on menus, music playlists, and rover images. Contemplated future development efforts include further tests on more diverse sets and development of a sub-method for (a) estimating the parameter that represents the relative importance of diversity versus depth, and (b) incorporating background knowledge about the nature of quality functions, which are special functions that specify depth preferences for features.

Wagstaff, Kiri L.↗
NASA NTRS1974

Methods of alleviation of ionospheric scintillation effects on digital communications

The degradation of the performance of digital communication systems because of ionospheric scintillation effects can be reduced either by diversity techniques or by coding. The effectiveness of traditional space-diversity, frequency-diversity and time-diversity techniques is reviewed and design considerations isolated. Time-diversity signaling is then treated as an extremely simple form of coding. More advanced coding methods, such as diffuse threshold decoding and burst-trapping decoding, which appear attractive in combatting scintillation effects are discussed and design considerations noted. Finally, adaptive coding techniques appropriate when the general state of the channel is known are discussed.

Massey, J. L.↗