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At least 523 records · Page 29

Terahertz Landau level spectroscopy of Dirac fermions in millimeter-scale twisted bilayer graphene

Exotic electronic physics including correlated insulating states and fractional Chern insulators have been observed in twisted bilayer graphene in a magnetic field when the Fermi velocity vanishes, however a question remains as to the stability of these states which is controlled by the gap to the first excited state. Free-space terahertz magneto-optics can directly probe the gap to charge excitations which bounds the stability of electronic states, but this measurement has thus-far been inaccessible due to the micron size of twisted bilayer graphene samples, while the wavelength of terahertz light is up to a millimeter. Here we leverage advances in fabrication to create twisted bilayer graphene samples over 5 mm x 5 mm in size with a uniform twist angle and study the magnetic field dependence of the cyclotron resonance by a complex Faraday rotation experiment in p-doped large angle twisted bilayer graphene. These measurements directly probe charge excitations in inter-Landau level transitions and determine the Fermi velocity as a function of twist angle.

36 MATERIALS SCIENCE↗

Nb3Ge as a potential candidate material for 15- to 25-T magnets

The critical temperature, upper critical field and structure of Nb3Ge materials produced by sputtering onto sapphire or by chemical vapor deposition on sapphire or Hastelloy were determined. In the case of the samples formed by deposition, several dopants, including Nb5Ge3, NbN and NbC were used. A variety of deposition temperatures were studied. Highest upper critical field values were obtained in samples deposited in the 750 to 850 C range. The degree of flux pinning exhibited a correlation with grain size. The presence of an impurity dopant had a depressant effect on the critical temperature and upper critical field.

Daniel, M. R.↗

Liquid drop stability for protein crystal growth in microgravity

It is possible to grow protein crystals for biomedical research in microgravity by deploying a protein-rich solution from a syringe, forming a drop in which crystallization can occur with the proper degree of supersaturation. Drop stability is critical to the success of this research, due to the large drop sizes which can be achieved in space. In order to determine the type of syringe tips most suitable to support these large drops, tests were performed during brief periods of weightlessness onboard the NASA KC-135 low-gravity simulation aircraft. The drops were analyzed using three simple models in which the samples were approximated by modified pendulum and spring systems. It was concluded that the higher frequency systems were the most stable, indicating that of the syringes utilized, a disk-shaped configuration provided the most stable environment of low-gravity protein crystal growth.

Owen, Robert B.↗

Atomic oxygen effects on SiO(x) coated Kapton for photovoltaic arrays in low earth orbit

Commercially applied SiOx was evaluated as a protective coating for the polyimide Kapton solar array blankets for Space Station Freedom. Three different rolls of coated material were tested in a plasma asher to determine their durability to attack by atomic oxygen. Mass loss data indicated that all of the coatings tested would structurally survive for 15 years in LEO (low earth orbit), except for one which had several uncoated lines across the sample which were caused by ridgelanes in the Kapton. It appears that the size rather than number of defects alone effects the mass loss the most. Careful handling of the material after coating and during processing may be critical for array survival.

Rutledge, Sharon K.↗

Field Evaluations of Sampling, Interviewing, and Flight Tracking of NASA's Low Boom Flight Demonstrator Aircraft

The first year’s effort identified sampling and interviewing as the principal risks to assessment of prompt reactions to overflights producing low-amplitude sonic booms. It also 1) established the utility of geo-information system-based route planning for LBFD flight missions, 2) developed and demonstrated a prototype of a geographically-distributed, Internet-enabled instrumentation system capable of wide-area tracking of LBFD aircraft in near-real time. The latter system permits synchronizing the conduct of interviews in multiple overflown communities with arrival times of shock waves at interviewing sites; and of measuring, archiving, and processing their acoustic signatures. Means were also recommended for constructing representative, telephone-based samples of eligible respondents living in households within carpet boom corridors adjacent to LBFD flight tracks, and for conducting interviews with cross-sectional (independent) samples of such respondents about their prompt reactions to exposure to low-amplitude sonic booms. A detailed study design was prepared and accepted by NASA for a set of single-contact attempt telephone interviews with a nationally representative sample of households. The study design focused on testing automated and live agent interview completion rates obtainable without callbacks. A minimal (two monitoring station) version of the aircraft tracking system was built and installed near a civil airport in a successful demonstration of the system’s ability to detect and track aircraft movements. The field exercise also demonstrated the ability of the system to capture the acoustic emissions of departing aircraft, and to serve aircraft position and sound level information to remote, geographically-distributed analysts in near-real time. Upon approval of OMB and IRB of the detailed study plan, a stratified, nationally representative sample of landline and wireless telephone-subscribing households was constructed. A total of 12,734 telephone interview contact attempts of the sort required by a straightforward cross-sectional study design were then made. These contact attempts demonstrated the impracticality of conducting a time-critical, cross-sectional study of prompt community response to low-amplitude sonic booms by means of “independent” (single contact attempt per respondent for each LBFD flight mission) telephone samples of respondents. The observed interview completion rates for these single telephone contact attempts were so low (~ 1% to 3% for automated and live agent interviews, respectively) that: 1) the representativeness of collected opinions would be susceptible to intuitive challenge as inadequate, even absent conclusive evidence of non-representativeness. Refuting challenges to representativeness would have to demonstrate that the composition of the actual sample did not differ from that of the target population, a task that is tantamount to proving a negative; 2) the information required to refute allegations of non-representativeness would require a questionnaire considerably lengthier than that required simply to determine the prevalence of boom-induced startle and annoyance. Such a questionnaire would have to inquire about potentially sensitive and intrusive matters, including respondents’ age, gender, education, employment, home ownership, income, ethnicity, family size, and other demographic factors; and 3) unreasonable numbers of attempts would be required to re-contact households with unsuccessful initial contact attempts, given the limited time available for doing so. For example, if about 500 completed interviews were desired in a supersonically overflown community, approximately 50,000 automated interview attempts would have to be made within ten to fifteen minutes of each LBFD overflight. Such large numbers of contact attempts could well exceed the numbers of households available for interview in areas of similar boom exposure levels in some communities near LBFD flight tracks. Such large numbers of interviews could be cost-effectively undertaken only by means of automated (i.e., outgoing interactive voice response) interviewing, a data collection method ill-suited for complex and sensitive questionnaire items. The infeasibility of independent sampling for evaluating prompt responses to LBFD overflights in a cross-sectional study is due in large part to simple non-response: that is, potential respondents – particularly those contacted on wireless telephones – refusing to answer calls with unfamiliar caller IDs. It is also due in part, however, to 1) the lack of time to attempt to contact the same respondent more than once within a few minutes after the arrival of a shock wave at the respondent’s location; and 2) the need to place calls during weekday/daytime hours, when response rates are notably lower than during evenings and weekends. Despite the poor interview completion rates achieved under the above constraints, cross sectional assessments of delayed reactions to LBFD overflights could still be feasible, if multiple attempts could be made to contact respondents during evening and weekend time periods, over extended time periods. Detailed plans for a longitudinal (panel) sample were developed as an alternative to a cross sectional sample design.

Fidell, Sanford↗

Petrology, Geochemistry, and Pairing of Lunar Meteorites from the Dominion Range

Introduction: During the 2018-2019 Antarctic Search for Meteorites (ANSMET) field season in the Dominion Range (DOM), 7 lunar meteorite stones were collected: DOM 18242 (15.1 g), DOM 18244 (25.1 g), DOM 18262 (6.8 g), DOM 18509 (16.5 g), DOM 18543 (13.6 g), DOM 18666 (45.9 g), and DOM 18678 (11.6 g). Here we present the initial results of electron microprobe and X-ray computed tomography (XCT) studies of these stones and look at the details of their petrography and mineral chemistry, as well as investigate possible pairing relationships, both with each other and with previously described lunar meteorites. Most of the work presented here is on the DOM 18509, 18543, and 18678 stones; subsamples of the other stones are in hand and similar measurements will be made on them by the time of the meeting. Methods: Textures in DOM 18509, DOM 18543, and DOM 18678 were characterized in 2D by optical microscopy, backscattered electron (BSE) imaging and elemental X-ray images on thin sections, as well as in 3D by X-ray computed tomography (XCT) on sample chips. Mineral compositions were assessed through a combination of wavelength dispersive spectroscopy EPMA (electron probe microanalysis) and x-ray mapping on the JEOL 8530 at NASA JSC. The bulk composition of all three meteorites was determined based on analyses of the fusion crust glass. XCT analyses were done on the Nikon XTH 320 at NASA JSC. ICP-MS data on bulk rock subsamples for each meteorite will be carried out in the near future. Results: The stones are all similar in macroscopic appearance with a dark aphanitic matrix hosting a variety of small- to medium-sized angular mineral and lithic fragments (often light colored in nature) [1,2]. Based on EPMA and XCT results, the three meteorites are polymict regolith breccias comprised of mineral, glass, and lithic clasts ranging up to several mm in length. Melt veins run through all three meteorite samples. Mineral clasts in all 3 stones are dominated by pyroxene and plagioclase (An82-96), with minor amounts of SiO2, olivine (Fo1-52), and FeTi-oxides. Pyroxene grains are mostly Fe-rich pigeonite and augite, and larger clasts are normally zoned and have fine exsolution lamellae. The lithic clasts in all stones consists of: (1) basalt clasts that contain zoned pyroxene, plagioclase laths, and ilmenite, with minor silica and Fe-rich olivine; (2) granulitic clasts; (3) anorthosite clasts; (4) Si-rich clasts that also contain ilmenite, troilite, high-Ca pyroxene, fayalite, and K-feldspar likely mesostasis from late stage basalts). All three meteorites contain glassy fusion crust that is highly vesicular, high in FeO and Al2O3 (15-17 wt% each), ferroan (Mg# of 23-24), and moderately rich in TiO2 (1.4-1.8 wt%). The composition of the fusion crust can serve as a proxy for the bulk meteorite composition and is identical within error for all three meteorites. Implications: The lithic and mineral clasts in all three stones are similar in clast population and assemblages as well as mineral chemistry. In addition, the fusion crust composition, a proxy for bulk composition, is within error of each other for all three stones. Thus DOM 18509, DOM 18543, and DOM 18678 are almost certainly paired. Based on similarities in macroscopic description as well as preliminary classification data [1,2], all 7 lunar stones from DOM are likely paired, though additional quantitative analyses are needed to confirm this. The presence of spherules and vesicular fusion crusts indicates that the DOM pairing group is a regolith breccia. The presence of basaltic and gabbroic clasts as well as more feldspathic materials, suggest that the regolith from which these meteorites formed contained a mixture of feldspathic highland material and mare material, suggesting a possible provenance near a marehighlands boundary. No evidence of KREEPy lithologies have been observed so far in these meteorites, however, future ICP-MS data on bulk rock chips for the stones will reveal any KREEP component if present. The DOM pairing group has many similarities to previously described lunar breccia meteorite MET 01210, however more detailed compositional data will be needed to make a definitive comparison.

R.A. Zeigler↗

Equibiaxial flexural strength determination of UO 2 using a ball-on-ring test

To increase nuclear fuel performance and reliability, their mechanical properties require an accurate and statistically relevant assessment. Biaxial flexural strength tests provide an alternative to bend bar techniques for assessing mechanical behavior; namely, the transverse rupture strength (TRS) of ceramic samples. Biaxial test samples require simple geometries and minimal surface preparation, reducing fabrication costs and handling hazards. This study investigated the TRS of polycrystalline UO 2 fuel forms at room temperature using a ball-on-ring test fixture. Here, pellets were fabricated from UO 2 powder using conventional powder processing and sintering techniques. The TRS and Weibull parameters were obtained through Weibull statistics on over 60 UO 2 samples tested under equibiaxial flexure. The larger sample size in this study enabled a more robust Weibull statistical analysis than alternative test methods, which may not capture the stochastic failure of typical ceramics. Furthermore, two different loading ball diameters were employed to assess the impact of contact damage on fracture strength. While Hertzian contact damage was observed with the smaller loading ball, the fracture strength remained unaffected. A fracture analysis of the tested UO 2 samples indicated a mixture of intergranular and transgranular fracture that transitions to transgranular fracture with increasing distance from the fracture origin. The characteristic strength of the combined data sets was determined to be 148 MPa, and the Weibull modulus was determined to be 9.1. The TRS values and Weibull parameters were close to values found in the literature for alternative testing techniques using samples with similar microstructure and density. The findings in this study validate the ball-on-ring method used to obtain the TRS of UO 2 with a sample geometry more representative of nuclear fuels. Additionally, experimental TRS results from this study can be implemented in modeling codes to predict fuel performance, which is critical to fuel burnup extension and advanced nuclear fuel technologies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dynamic properties of 316l stainless steel repaired using electron beam additive manufacturing

Additive manufacturing has the potential to be used for repair of high-value parts, but the strength and integrity of such repaired parts, especially under dynamic loading, in still unknown. This work presents the results of high strain-rate dynamic testing of additively repaired stainless steel samples. The 316L samples were intentionally damaged and subsequently repaired with 308L stainless steel wire using electron beam additive manufacturing. The repaired samples were subjected to gas-gun impact testing to induce incipient damage and determine the role played by the repaired region in dictating damage and failure. The results show the following: 1) the equation of state of the repaired region is comparable to the original material as shown by the unchanged spall plane location, 2) the deformation behavior is similar to the original material as shown by the similar Hugoniot Elastic limit, 3) the spall strength of the repaired region is slightly higher than the original material due to varying grain size, and 4) the damage morphology in the repaired region is different and involves a high rate of void coalescence. In conclusion, despite these minor differences in the spall strength and the damage morphology, the overall dynamic response of the original material and repaired samples is similar suggesting that AM is a promising approach for repairing high-value components.

36 MATERIALS SCIENCE↗

A bootstrapping approach to social media quantification

Abstract This work considers the use of classifiers in a downstream aggregation task estimating class proportions, such as estimating the percentage of reviews for a movie with positive sentiment. We derive the bias and variance of the class proportion estimator when taking classification error into account to determine how to best trade off different error types when tuning a classifier for these tasks. Additionally, we propose a method for constructing confidence intervals that correctly adjusts for classification error when estimating these statistics. We conduct experiments on four document classification tasks comparing our methods to prior approaches across classifier thresholds, sample sizes, and label distributions. Prior approaches have focused on providing the most accurate point estimate while this work focuses on the creation of correct confidence intervals that appropriately account for classifier error. Compared to the prior approaches, our methods provide lower error and more accurate confidence intervals.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Additional Analysis of the 2H-Evaporator Wall Scale Sample HTF-17-57

Savannah River National Laboratory previously analyzed scale samples from both the wall and cone sections of the 242-16H Evaporator prior to chemical cleaning. The samples were analyzed for uranium and plutonium isotopes required for a Nuclear Criticality Safety Assessment of the scale removal process. The analysis of the scale samples found the material to contain crystalline nitrated cancrinite and clarkeite and significant amounts of mercury. Savannah River Remediation subsequently requested additional analyses on the samples. Inspection of the sample bottles revealed that no sample remained of the cone scale (HTF-17-56) while approximately 4 g of the wall scale sample (HTF-17-57) remained. The wall sample was subsequently ground with a mortar and pestle, at which time it was discovered that the sample contained a significant amount of liquid, metallic mercury. The portion of the sample that was not mercury was approximately 3 g. This portion of the sample was analyzed to determine the concentrations of selected radionuclides. The following radionuclide concentrations were measured: <9.6E+02 dpm/g H-3, 2.9E+02 dpm/g C-14, 5.6E+03 dpm/g Tc-99, and 1.6E+02 dpm/g I-129. Blank samples were also analyzed to evaluate sample contamination from the Shielded Cells environment. All blank sample results were below detectable limits. Due to the limited sample size and the anticipated low levels of the target radionuclides, no replicate sample analysis was conducted.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

IER-501 CED-3b: Experiment Execution Summary for the Pulsed-Neutron Die-Away Experimental Testbed for Thermal Scattering Law Benchmarks (PNDA)

This report summarizes the experiments done for IER-501, a testbed for pulsed-neutron die-away (PNDA) experiments at Lawrence Livermore National Laboratory (LLNL). The PNDA experiments were conducted in two separate two-day campaigns: one campaign for high-density polyethylene and another for Lucite. All experiments were performed at Lawrence Livermore Laboratory. They will become high-quality benchmarks that serve to optimize and validate thermal neutron scattering laws (TSLs), which are high priority nuclear data for the Department of Energy’s Nuclear Criticality Safety Program (NCSP). The report presents the PNDA design and its equipment, and it documents the experimental die-away curves. It presents the characterization measurements that have been performed to-date. Importantly, mass spectrometry measurements to determine sample impurities were not yet completed. These will be included in the final benchmark. The report gives the fitted decay constants for the die-away curves of each target sample. It also provides the data for the die-away curves in the appendices. The HDPE experiments examined twelve targets of varying size. The Lucite measurements included ten targets of varying size. Experimenters in the campaign were Daniel Siefman, William Zywiec, and Ruby Araj.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

IER-501 CED-3b: Experiment Execution Summary for the Pulsed-Neutron Die-Away Experimental Testbed for Thermal Scattering Law Benchmarks (PNDA)

This report summarizes the experiments performed for IER-501, a testbed for pulsed-neutron die-away (PNDA) experiments at Lawrence Livermore National Laboratory (LLNL). The PNDA experiments were conducted in two separate two-day campaigns: one campaign for high-density polyethylene and another for Lucite. All experiments were performed at LLNL. They will become high-quality benchmarks that serve to optimize and validate thermal neutron scattering laws (TSLs), which are high-priority nuclear data for the Department of Energy’s Nuclear Criticality Safety Program (NCSP). The report presents the PNDA design and its equipment, and it documents the experimental die-away curves. It presents the characterization measurements that have been performed to-date. Importantly, mass spectrometry measurements to determine sample impurities were not yet completed. These will be included in the final benchmark. The report gives the fitted decay constants for the die-away curves of each target sample. It also provides the data for the die-away curves in the appendices. The HDPE experiments examined twelve targets of varying size. The Lucite measurements included ten targets of varying size.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Spacecraft mass trade-offs versus radio-frequency power and antenna size at 8 GHz and 32 GHz

The purpose of this analysis is to help determine the relative merits of 32 GHz over 8 GHz for future deep space communications. This analysis is only a piece of the overall analysis and only considers the downlink communication mass, power, and size comparisons for 8 and 32 GHz. Both parabolic antennas and flat-plate arrays are considered. The Mars Sample Return mission is considered in some detail as an example of the tradeoffs involved; for this mission the mass, power, and size show a definite advantage of roughly 2:1 in using the 32 GHz over 8 GHz.

Gilchriest, C. E.↗

Sintering time and atmosphere influences on the microstructure and mechanical properties of tungsten heavy alloys

The present paper traces the microstructure and mechanical property variations vs sintering time under conditions where the atmosphere was adjusted to suppress pore generation. Attention is given to tracing the mechanical property links to the grain size under optimized sintering conditions. The optimal cycle is used to sinter two heavy alloy compositions (88 and 95 wt pct W) for times up to 600 minutes at 1480 C. The 88-pct-W samples slumped, but the 95-pct-W samples were fully densified and suitable for tensile testing. At long sintering times, the tungsten grains flattened and the tungsten contiguity decreased, indicating a transition to low-energy configurations for the solid-liquid interfaces. The cube of the mean grain size varied linearly with the isothermal sintering time. This allowed the determination of grain size effects on mechanical properties, showing a decreasing yield strength with increasing time in agreement with the Hall-Petch behavior. The tensile strength and elongation were highest for sintering times from 30 to 90 min, reflecting a minimum in the residual porosity.

German, R. M.↗

Particle Morphology and Size Results from the Smoke Aerosol Measurement Experiment-2

Results are presented from the Reflight of the Smoke Aerosol Measurement Experiment (SAME-2) which was conducted during Expedition 24 (July-September 2010). The reflight experiment built upon the results of the original flight during Expedition 15 by adding diagnostic measurements and expanding the test matrix. Five different materials representative of those found in spacecraft (Teflon, Kapton, cotton, silicone rubber and Pyrell) were heated to temperatures below the ignition point with conditions controlled to provide repeatable sample surface temperatures and air flow. The air flow past the sample during the heating period ranged from quiescent to 8 cm/s. The smoke was initially collected in an aging chamber to simulate the transport time from the smoke source to the detector. This effective transport time was varied by holding the smoke in the aging chamber for times ranging from 11 to 1800 s. Smoke particle samples were collected on Transmission Electron Microscope (TEM) grids for post-flight analysis. The TEM grids were analyzed to observe the particle morphology and size parameters. The diagnostics included a prototype two-moment smoke detector and three different measures of moments of the particle size distribution. These moment diagnostics were used to determine the particle number concentration (zeroth moment), the diameter concentration (first moment), and the mass concentration (third moment). These statistics were combined to determine the diameter of average mass and the count mean diameter and, by assuming a log-normal distribution, the geometric mean diameter and the geometric standard deviations can also be calculated. Overall the majority of the average smoke particle sizes were found to be in the 200 nm to 400 nm range with the quiescent cases producing some cases with substantially larger particles.

Urban, David L.↗

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

Transcriptomics-based Machine Learning (ML) Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗