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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Searching for the 3.5 keV Line in the Stacked Suzaku Observations of Galaxy Clusters

We perform a detailed study of the stacked Suzaku observations of 47 galaxy clusters, spanning a redshift range of 0.01-0.45, to search for the unidentified 3.5 keV line. This sample provides an independent test for the previously detected line. We detect a 2sigma-significant spectral feature at 3.5 keV in the spectrum of the full sample. When the sample is divided into two subsamples (cool-core and non-cool core clusters), the cool-core subsample shows no statistically significant positive residuals at the line energy. A very weak (approx. 2sigma confidence) spectral feature at 3.5 keV is permitted by the data from the non-cool-core clusters sample. The upper limit on a neutrino decay mixing angle of sin(sup 2)(2theta) = 6.1 x 10(exp -11) from the full Suzaku sample is consistent with the previous detections in the stacked XMM-Newton sample of galaxy clusters (which had a higher statistical sensitivity to faint lines), M31, and Galactic center, at a 90% confidence level. However, the constraint from the present sample, which does not include the Perseus cluster, is in tension with previously reported line flux observed in the core of the Perseus cluster with XMM-Newton and Suzaku.

dark matter↗
NASA NTRS1986

Continuum radiation from active galactic nuclei: A statistical study

The physics of the continuum spectrum of active galactic nuclei (AGNs) was examined using a large data set and rigorous statistical methods. A data base was constructed for 469 objects which include radio selected quasars, optically selected quasars, X-ray selected AGNs, BL Lac objects, and optically unidentified compact radio sources. Each object has measurements of its radio, optical, X-ray core continuum luminosity, though many of them are upper limits. Since many radio sources have extended components, the core component were carefully selected out from the total radio luminosity. With survival analysis statistical methods, which can treat upper limits correctly, these data can yield better statistical results than those previously obtained. A variety of statistical tests are performed, such as the comparison of the luminosity functions in different subsamples, and linear regressions of luminosities in different bands. Interpretation of the results leads to the following tentative conclusions: the main emission mechanism of optically selected quasars and X-ray selected AGNs is thermal, while that of BL Lac objects is synchrotron; radio selected quasars may have two different emission mechanisms in the X-ray band; BL Lac objects appear to be special cases of the radio selected quasars; some compact radio sources show the possibility of synchrotron self-Compton (SSC) in the optical band; and the spectral index between the optical and the X-ray bands depends on the optical luminosity.

Isobe, T.↗
DOE OSTI2026

2013-2014 Greater Fairbanks, Alaska, Transportation Survey

The 2013-2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. The Alaska Department of Transportation and Public Facilities sponsored the survey, which was conducted by Westat. Data collection occurred in two phases: fall 2013 and winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey and a subsample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two.

1Hz data↗
DOE OSTI2024

Subsampling of Parametric Models with Bifidelity Boosting

Least squares regression is a ubiquitous tool for building emulators (a.k.a. surrogate models) of problems across science and engineering for purposes such as design space exploration and uncertainty quantification. When the regression data are generated using an experimental design process (e.g., a quadrature grid) involving computationally expensive models, or when the data size is large, sketching techniques have shown promise at reducing the cost of the construction of the regression model while ensuring accuracy comparable to that of the full data. However, random sketching strategies, such as those based on leverage scores, lead to regression errors that are random and may exhibit large variability. To mitigate this issue, we present a novel boosting approach that leverages cheaper, lower-fidelity data of the problem at hand to identify the best sketch among a set of candidate sketches. This in turn specifies the sketch of the intended high-fidelity model and the associated data. We provide theoretical analyses of this bifidelity boosting (BFB) approach and discuss the conditions the low- and high-fidelity data must satisfy for a successful boosting. In doing so, we derive a bound on the residual norm of the BFB sketched solution relating it to its ideal, but computationally expensive, high-fidelity boosted counterpart. Finally, empirical results on both manufactured and PDE data corroborate the theoretical analyses and illustrate the efficacy of the BFB solution in reducing the regression error, as compared to the nonboosted solution.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2015

Preserving the Science Legacy from the Apollo Missions to the Moon

Six Apollo missions landed on the Moon from 1969-72, returning to Earth 382 kg of lunar rock, soil, and core samples-among the best documented and preserved samples on Earth that have supported a robust research program for 45 years. From mission planning through sample collection, preliminary examination, and subsequent research, strict protocols and procedures are followed for handling and allocating Apollo subsamples. Even today, 100s of samples are allocated for research each year, building on the science foundation laid down by the early Apollo sample studies and combining new data from today's instrumentation, lunar remote sensing missions and lunar meteorites. Today's research includes advances in our understanding of lunar volatiles, lunar formation and evolution, and the origin of evolved lunar lithologies. Much sample information is available to researchers at curator.jsc.nasa.gov. Decades of analyses on lunar samples are published in LPSC proceedings volumes and other peer-reviewed journals, and tabulated in lunar sample compendia entries. However, for much of the 1969-1995 period, the processing documentation, individual and consortia analyses, and unpublished results exist only in analog forms or primitive digital formats that are either inaccessible or at risk of being lost forever because critical data from early investigators remain unpublished. We have initiated several new efforts to rescue some of the early Apollo data, including unpublished analytical data. We are scanning NASA documentation that is related to the Apollo missions and sample processing, and we are collaborating with IEDA to establish a geochemical database called Moon DB. To populate this database, we are working with prominent lunar PIs to organize and transcribe years of both published and unpublished data. Other initiatives include micro-CT scanning of complex lunar samples to document their interior structure (e.g. clasts, vesicles); linking high-resolution scans of Apollo film products to samples; and new procedures for systematic high resolution photography of samples before additional processing, enabling detailed 3D reconstructions of the samples. All of these efforts will provide comprehensive access to Apollo samples and support better curation of the samples for decades to come.

Evans, Cindy↗
DOE OSTI2020

Interpreting and reporting 40 Ar/ 39 Ar geochronologic data

The 40Ar/39Ar dating method is among the most versatile of geochronometers, having the potential to date a broad variety of K-bearing materials spanning from the time of Earth’s formation into the historical realm. Measurements using modern noble-gas mass spectrometers are now producing 40Ar/39Ar dates with analytical uncertainties of ~1%, thereby providing precise time constraints for a wide range of geologic and extraterrestrial processes. Analyses of increasingly smaller subsamples have revealed age dispersion in many materials, including some minerals used as neutron fluence monitors. Accordingly, interpretive strategies are evolving to address observed dispersion in dates from a single sample. Moreover, inferring a geologically meaningful “age” from a measured “date” or set of dates is dependent on the geological problem being addressed and the salient assumptions associated with each set of data. We highlight requirements for collateral information that will better constrain the interpretation of 40Ar/39Ar data sets, including those associated with single-crystal fusion analyses, incremental heating experiments, and in situ analyses of microsampled domains. To ensure the utility and viability of published results, we emphasize previous recommendations for reporting 40Ar/39Ar data and the related essential metadata, with the amendment that data conform to evolving standards of being findable, accessible, interoperable, and reusable (FAIR) by both humans and computers. Our examples provide guidance for the presentation and interpretation of 40 Ar/ 39 Ar dates to maximize their interdisciplinary usage, reproducibility, and longevity.

58 GEOSCIENCES↗
DOE OSTI2021

Probing the galaxy–halo connection with total satellite luminosity

ABSTRACT We demonstrate how the total luminosity in satellite galaxies is a powerful probe of dark matter haloes around central galaxies. The method cross-correlates central galaxies in spectroscopic galaxy samples with fainter galaxies detected in photometric surveys. Using models, we show that the total galaxy luminosity, Lsat, scales linearly with host halo mass, making Lsat an excellent proxy for Mh. Lsat is also sensitive to the formation time of the halo. We demonstrate that probes of galaxy large-scale environment can break this degeneracy. Although this is an indirect probe of the halo, it yields a high signal-to-noise ratio measurement for galaxies expected to occupy haloes at <1012 M⊙, where other methods suffer from larger errors. In this paper, we focus on observational and theoretical systematics in the Lsat method. We test the robustness of our method of finding central galaxies and our methods of estimating the number of background galaxies. We implement this method on galaxies in the Sloan Digital Sky Survey (SDSS) data, with satellites identified in fainter imaging data. We find excellent agreement between our theoretical predictions and the observational measurements. Finally, we compare our Lsat measurements to weak lensing estimates of Mh for red and blue subsamples. In the stellar mass range where the measurements overlap, we find consistent results, where red galaxies live in larger haloes. However, the Lsat approach allows us to probe significantly lower mass galaxies. At these masses, the Lsat values are equivalent. This example shows the potential of Lsat as a probe of dark haloes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A novel framework for increasing research transparency: Exploring the connection between diversity and innovation

A split sample/dual method research protocol is demonstrated to increase transparency while reducing the probability of false discovery. We apply the protocol to examine whether diversity in ownership teams increases or decreases the likelihood of a firm reporting a novel innovation using data from the 2018 United States Census Bureau’s Annual Business Survey. Transparency is increased in three ways: 1) all specification testing and identifying potentially productive models is done in an exploratory subsample that 2) preserves the validity of hypothesis test statistics fromde novoestimation in the holdout confirmatory sample with 3) all findings publicly documented in an earlier registered report and in this journal publication. Bayesian estimation procedures that leverage information from the exploratory stage included in the confirmatory stage estimation replace traditional frequentist null hypothesis significance testing. In addition to increasing statistical power by using information from the full sample, Bayesian methods directly estimate a probability distribution for the magnitude of an effect, allowing much richer inference. Estimated magnitudes of diversity along academic discipline, race, ethnicity, and foreign-born status dimensions are positively associated with innovation. A maximally diverse ownership team on these dimensions would be roughly six times more likely to report new-to-market innovation than a homophilic team.

Science & Technology - Other Topics↗
DOE OSTI2021

Constraining the baryon abundance with the kinematic Sunyaev-Zel’dovich effect: Projected-field detection using Planck , WMAP , and unWISE

The kinematic Sunyaev-Zel'dovich (kSZ) effect -- the Doppler boosting of cosmic microwave background (CMB) photons scattering off free electrons with non-zero line-of-sight velocity -- is an excellent probe of the distribution of baryons in the Universe. In this paper, we measure the kSZ effect due to ionized gas traced by infrared-selected galaxies from the \emph{unWISE} catalog. We employ the "projected-field" kSZ estimator, which does not require spectroscopic galaxy redshifts. To suppress non-kSZ foreground signals associated with the galaxies (e.g., dust emission and thermal SZ), this estimator requires cleaned CMB maps, which we obtain from \emph{Planck} and \emph{WMAP} data. Using a new "asymmetric" estimator that combines different foreground-cleaned CMB maps to maximize the signal-to-noise, we measure the kSZ$^2$-galaxy cross-power spectrum for three subsamples of the \emph{unWISE} galaxy catalog, which peak at mean redshifts $z \approx$ 0.6, 1.1, and 1.5, have average halo mass $\sim 1$-$5\times 10^{13}$ $h^{-1} M_{\odot}$, and in total contain over 500 million galaxies. After marginalizing over CMB lensing contributions, we measure the amplitude of the kSZ signal $A_{\rm kSZ^2} = 0.42 \pm 0.31$, $5.02 \pm 1.01$, and $8.23 \pm 3.23$, for the three subsamples, where $A_{\rm kSZ^2} = 1$ corresponds to our fiducial model. The combined kSZ detection S/N $>$ 5. We discuss possible explanations for the excess kSZ signal associated with the $z \approx 1.1$ sample, and show that foreground contamination in the CMB maps is very unlikely to be the cause. Our measurements illustrate clearly that no baryons are missing on large scales at low redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

Radio continuum observations of early- and late-type spiral galaxies

Two complete subsamples of early and late type spiral galaxies were mapped with the VLA in order to explore their radio and optical properties. The choice of the samples is explained, and the observational procedure and data reduction are described. The detection rate was 97 percent, with a detection limit of the order of 1-2 mJy. Total intensity data at 20 cm are presented for the whole sample, and 6 cm data for 11 galaxies. The results are presented in the form of tables and radio contour maps, and are discussed in comparison with previous work.

Gioia, Isabella M.↗
NASA NTRS2000

BOREAS TE-9 NSA Leaf Chlorophyll Density

The BOREAS TE-9 team collected several data sets related to chemical and photosynthetic properties of leaves in boreal forest tree species. These data were collected to help provide an explanation of potential seasonal and spatial changes of leaf pigment properties in boreal forest species at the NSA. At different dates (FFC-Winter, FFC-Thaw, IFC-1, IFC-2, and IMC-3), foliage samples were collected from the upper third of the canopy for five NSA sites (YJP, OJP, OBS, UBS, and OA) near Thompson, Manitoba. Subsamples of 100 needles for black spruce, 20 needles for jack pine, and single leaf for trembling aspen were cut into pieces and immersed in a 20-mL DMF aliquot in a Nalgene test tube. The extracted foliage materials were then oven-dried at 68 C for 48 hours and weighed. Extracted leaf dry weight was converted to a total leaf area basis to express the chlorophyll content in mg/sq cm of total leaf area. The data are provided in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
DOE OSTI2025

From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning

The 2024 Nobel Prize in Chemistry was awarded in part for de novo protein structure prediction using AlphaFold2, an artificial intelligence/machine learning (AI/ML) model trained on vast amounts of sequence and three-dimensional structure data. AlphaFold2 and related models, including RoseTTAFold and ESMFold, employ specialized neural network architectures driven by attention mechanisms to infer relationships between sequence and structure. At a fundamental level, these AI/ML models operate on the long-standing hypothesis that the structure of a protein is determined by its amino acid sequence. More recently, AlphaFold2 has been adapted for the prediction of multiple protein conformations by subsampling multiple sequence alignments. Herein, we provide an overview of the deterministic relationship between sequence and structure, which was hypothesized over half a century ago with profound implications for the biological sciences ever since. We postulate that protein conformational dynamics are also determined, at least in part, by amino acid sequence and that this relationship may be leveraged for construction of AI/ML models dedicated to predicting protein conformational ensembles. Accordingly, we describe a conceptual model architecture, which may be trained on sequence data in combination with conformationally sensitive structural information, coming primarily from nuclear magnetic resonance (NMR) spectroscopy. Notwithstanding certain limitations in this context, NMR offers abundant structural heterogeneity conducive to conformational ensemble prediction. As NMR and other data continue to accumulate, sequence-informed prediction of protein structural dynamics with AI/ML has the potential to emerge as a transformative capability across the biological sciences.

Artificial intelligence↗
NASA NTRSDate not supplied

Machine-Learning-Based Adaptive Thinning of CrIS Radiances to Improve Global Tropical Cyclone Analysis and Forecasts

This work is focused on optimizing the assimilation of hyperspectral infrared (IR) radiances from the Cross-track Infrared Sounder (CrIS) with the goal of improving the representation of tropical cyclones (TCs) in global analyses and forecasts. Current operational assimilation systems rely on subsampling IR radiances on a regular thinning grid. A new and improved adaptive methodology based on machine learning (ML) recognizes TCs from geostationary satellite imagery and is implemented in the Goddard Earth Observing System (GEOS) model and data assimilation framework. The ML methodology is extensively trained on existing TC data sets and creates for each TC a dynamic mask, based on the evolving shape and life cycle of that specific event. Once a TC mask is created, a switch is then activated in the data assimilation system to alter the thinning, ingesting more CrIS radiances within the moving mask, thus increasing the TC sampling. After the TC dissipates, the assimilation of CrIS radiances reverts to normal data density. Results of TC segmentation provided by a state-of-the-art generative machine learning model known as the Denoising Diffusion Probabilistic Model (DDPM) are compared to the previously used U-Net model. The new approach surpasses the performance of the previously developed one. The methodology is applied to both clear-sky and cloud-cleared radiances. Benefits from the latter methodology, particularly in improving the structure of TCs and the intensity forecasts, are presented.

Oreste Reale↗
DOE OSTI2024

SPRUCE Quantitative PCR (qPCR) of Microbial Gene Copy Numbers, 2021-2022

This dataset provides the results for quantitative polymerase chain reaction (qPCR) of peat samples collected from ambient and experimental plots in the Spruce and Peatland Responses Under Climatic and Environmental Change (SPRUCE) experiment site in June and August of 2021, and June of 2022. SPRUCE is located within the Marcell Experimental Forest in northern Minnesota, USA. The dataset includes bacterial, archaeal, fungal gene copy numbers, along with corresponding logarithmic values, at 11 depth increments of two-meter deep peat cores taken from 12 sampling sites locations inside SPRUCE plots (10 chambered and 2 ambient plots). The sampling, sample prep and analysis followed standard methods outlined in prior publications (Wilson et al. 2016; Kluber et al. 2020) except that a higher yielding Omega Bio-Tek Mag-Bind Environmental DNA 96 Kit was used for extractions and DNA was quantified using Qubit dsDNA High Sensitivity Assay Kit. qPCR subsamples of peat cores from the SPRUCE plots characterize changes in the abundance and composition of microbial communities of peat seasonally showing how composition varies under multiple levels of experimental peat warming and atmospheric CO2 concentrations. This dataset contains one data file in comma-separated values (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separated values (.csv) format and a user guide in PDF (*.pdf) format. On 2026-07-07 this dataset was updated to add three columns to the data file: ‘Fungal_copy_dry’, ‘Log_fungal_copy_dry’, ‘Fungal_copy_wet’. No previously released data values were altered. Additionally, the abstract, data dictionary, and user guide were updated, and a file-level metadata file was added.

Archaea↗
DOE OSTI2026

Brightest Cluster Galaxy ellipticity as proxy for halo shape: Orientation bias, assembly bias, and potential selection effects in SZ-selected clusters

The orientation of triaxial galaxy clusters with respect to the line-of-sight is expected to be one of the prime sources of scatter and potential bias in optical observables (e.g., richness and weak-lensing signal) of galaxy clusters. In this work, we use the observed shape of the central Brightest Cluster Galaxy (BCG) as proxy for the orientation along the line-of-sight for clusters selected via the Sunyaev-Zel'dovich (SZ) effect from the South Pole Telescope (SPT) and Atacama Cosmology Telescope (ACT) surveys, matched to optically selected clusters from the Dark Energy Survey Year 3 (DES). We construct two samples of clusters that are designed to be identical in SZ mass estimate and redshift but with the roundest vs. the most elliptical BCGs, which we expect to correspond to BCGs (and clusters) with major axes aligned along the line-of-sight vs. in the plane of the sky, respectively. We find that the optical richness of round-BCG clusters is $\sim 10$% larger than that of elliptical-BCG clusters, in agreement with the expectation from projection effects and presenting the first such detection in data. The density profiles, however, are not in agreement with the expectation from projection effects: the 1-halo term (below $6~h^{-1}\rm{Mpc}$) of both the weak-lensing and galaxy density profiles are the same for the subsamples, contrary to previous studies based on X-ray selected clusters. In the 2-halo regime (above $6~h^{-1}\rm{Mpc}$), we find a significant excess of the elliptical-BCG cluster profiles compared to the round-BCG cluster profiles, which is the opposite of the expectation from numerical simulations. We hypothesize that the intrinsic shape of the BCG reflects not just the orientation angle, but also intrinsic properties of the cluster which can affect both the SZ signal and the amplitude of the 2-halo term.

Srinivasan, Radhakrishnan [SUNY, Stony Brook] (ORC↗
DOE OSTI2021

Analysis of Previously Classified White Dwarf–Main-sequence Binaries Using Data from the APOGEE Survey

We present analyses of near-infrared spectroscopic data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey for 45 previously confirmed or candidate white dwarf–main-sequence (WDMS) binaries identified by the optical Sloan Digital Sky Survey (SDSS) and LAMOST surveys. Among these 45 systems, we classify three as having red giant primaries in the LAMOST sample and 14 as young stellar object contaminants in the photometrically identified SDSS sample. From among the subsample of 28 systems that we confirm to have MS primaries, we derive and place limits on orbital periods and velocity amplitudes for 14. Seven systems have significant velocity variations that warrant a post-common-envelope (PCE) binary classification, four of which are newly classified, three of which are newly confirmed, and five for which we can derive full orbital parameters. If confirmed, one of these newly discovered systems (2M14544500+4626456) will have the second-longest orbital period reported for a typical compact PCE WDMS binary (P = 15.1 days). In addition to the seven above, we also recover and characterize with APOGEE data the well-known PCE WDMS systems EG UMa and HZ 9. We also investigate the overall metallicity distribution of the WDMS sample, which is a parameter space not often explored for these systems. Of note, we find one system (2M14244053+4929580) to be extremely metal-poor ([Fe/H] = − 1.42) relative to the rest of the near-solar sample. Additionally, the PCE systems in our sample are found to be, on average, higher in metallicity than their wide-binary counterparts, though we caution that with this small number of systems, the sample may not be representative of the overall distribution of WDMS systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Comparison of venous and pooled capillary hemoglobin levels for the detection of anemia among adolescent girls

Introduction: Blood source is a known preanalytical factor affecting hemoglobin (Hb) concentrations, and there is evidence that capillary and venous blood may yield disparate Hb levels and anemia prevalence. However, data from adolescents are scarce. Objective: To compare Hb and anemia prevalence measured by venous and individual pooled capillary blood among a sample of girls aged 10–19 years from 232 schools in four regions of Ghana in 2022. Methods: Among girls who had venous blood draws, a random subsample was selected for capillary blood. Hb was measured using HemoCue® Hb-301. We used Lin’s concordance correlation coefficient (CCC) to quantify the strength of the bivariate relationship between venous and capillary Hb and a paired t-test for difference in means. We used McNemar’s test for discordance in anemia cases by blood source and weighted Kappa to quantify agreement by anemia severity. A multivariate generalized estimating equation was used to quantify adjusted population anemia prevalence and assess the association between blood source and predicted anemia risk. Results: We found strong concordance between Hb measures (CCC = 0.86). The difference between mean venous Hb (12.8 g/dL, ± 1.1) and capillary Hb (12.9 g/dL, ± 1.2) was not significant (p = 0.26). Crude anemia prevalence by venous and capillary blood was 20.6% and 19.5%, respectively. Adjusted population anemia prevalence was 23.5% for venous blood and 22.5% for capillary ( = 0.45). Blood source was not associated with predicted anemia risk (risk ratio: 0.99, 95% CI: 0.96, 1.02). Discordance in anemia cases by blood source was not significant (McNemar p = 0.46). Weighted Kappa demonstrated moderate agreement by severity (k =0.67). Among those with anemia by either blood source (n = 111), 59% were identified by both sources. Conclusion: In Ghanaian adolescent girls, there was no difference in mean Hb, anemia prevalence, or predicted anemia risk by blood source. However, only 59% of girls with anemia by either blood source were identified as having anemia by both sources. These findings suggest that pooled capillary blood may be useful for estimating Hb and anemia at the population level, but that caution is needed when interpreting individual-level data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Predicting Antimicrobial Resistance Using Partial Genome Alignments

Antimicrobial resistance (AMR) is an important global health threat that impacts millions of people worldwide each year. Developing methods that can detect and predict AMR phenotypes can help to mitigate the spread of AMR by informing clinical decision making and appropriate mitigation strategies. Many bioinformatic methods have been developed for predicting AMR phenotypes from whole-genome sequences and AMR genes, but recent studies have indicated that predictions can be made from incomplete genome sequence data. In order to more systematically understand this, we built random forest-based machine learning classifiers for predicting susceptible and resistant phenotypes for Klebsiella pneumoniae (1,640 strains), Mycobacterium tuberculosis (2,497 strains), and Salmonella enterica (1,981 strains). We started by building models from alignments that were based on a reference chromosome for each species. We then subsampled each chromosomal alignment and built models for the resulting subalignments, finding that very small regions, representing approximately 0.1 to 0.2% of the chromosome, are predictive. In K. pneumoniae, M. tuberculosis, and S. enterica, the subalignments are able to predict multiple AMR phenotypes with at least 70% accuracy, even though most do not encode an AMR-related function. We used these models to identify regions of the chromosome with high and low predictive signals. Finally, subalignments that retain high accuracy across larger phylogenetic distances were examined in greater detail, revealing genes and intergenic regions with potential links to AMR, virulence, transport, and survival under stress conditions. IMPORTANCE Antimicrobial resistance causes thousands of deaths annually worldwide. Understanding the regions of the genome that are involved in antimicrobial resistance is important for developing mitigation strategies and preventing transmission. Machine learning models are capable of predicting antimicrobial resistance phenotypes from bacterial genome sequence data by identifying resistance genes, mutations, and other correlated features. They are also capable of implicating regions of the genome that have not been previously characterized as being involved in resistance. In this study, we generated global chromosomal alignments for Klebsiella pneumoniae, Mycobacterium tuberculosis, and Salmonella enterica and systematically searched them for small conserved regions of the genome that enable the prediction of antimicrobial resistance phenotypes. In addition to known antimicrobial resistance genes, this analysis identified genes involved in virulence and transport functions, as well as many genes with no previous implication in antimicrobial resistance.

59 BASIC BIOLOGICAL SCIENCES↗