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DOE OSTI2022

Identification of new marker genes from plant single‐cell RNA‐seq data using interpretable machine learning methods

Summary An essential step in the analysis of single‐cell RNA sequencing data is to classify cells into specific cell types using marker genes. In this study, we have developed a machine learning pipeline called single‐cell predictive marker (SPmarker) to identify novel cell‐type marker genes in the Arabidopsis root. Unlike traditional approaches, our method uses interpretable machine learning models to select marker genes. We have demonstrated that our method can: assign cell types based on cells that were labelled using published methods; project cell types identified by trajectory analysis from one data set to other data sets; and assign cell types based on internal GFP markers. Using SPmarker, we have identified hundreds of new marker genes that were not identified before. As compared to known marker genes, the new marker genes have more orthologous genes identifiable in the corresponding rice single‐cell clusters. The new root hair marker genes also include 172 genes with orthologs expressed in root hair cells in five non‐ Arabidopsis species, which expands the number of marker genes for this cell type by 35–154%. Our results represent a new approach to identifying cell‐type marker genes from scRNA‐seq data and pave the way for cross‐species mapping of scRNA‐seq data in plants.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

A bootstrap approach to bump hunting

An important question in cluster analysis and pattern recognition is the determination of the number of clusters into which a given population should be divided. Frequently, particularly when certain specific clustering methods are being used, the number of clusters is taken to be equal to the number of modes, or local maxima, in the probability density function underlying the given data set. The use of kernal density estimates in mode estimation is discussed. The test statistic to be used is defined and a bootstrap technique for assessing significance is given. An illustrative application is followed by an examination of the asymptotic behavior of the test statistic.

Silverman, B. W.↗

NASA NTRS1988

Artificial intelligence applied to process signal analysis

Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

Corsberg, Dan↗

NASA NTRS1993

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Fayyad, Usama M.↗

NASA NTRS2004

Physics of Galaxy Clusters and How it Affects Cosmological Tests

The main activities in 2004 were focused on completion of the new 400 square degrees ROSAT PSPC survey for distant galaxy clusters. We observed and reduced optical spectra for all X-ray candidates and now we have complete identification for a statistically complete sample of distant 283 clusters. The papers describing the cluster catalog and first science results are in preparation and will be submitted in early 2005. We also completed a project to measure temperature and density profiles at large radii using Chandra observations of a 11 well exposed low-redshift clusters. We were able to demonstrate that the density, temperature, and total mass profiles are self-similar at large radii. This analysis has led to significant improvements in determination of the cluster baryon fraction as well as cosmologically important scaling relations, such as Mtot-T. The paper describing these results is submitted to ApJ in November, 2004. We continued to study evolution of the cluster scaling relations at high redshifts using Chandra and XMM data. We developed code for image and spectral deconvolution of the XMM observations. This code was used to reconstruct the distribution of baryons and total mass from observations of distant clusters which suffer from the finite size of the XMM PSF. This study allowed us to derive a high-redshift relation between cluster temperature and mass and compare it with the local relation obtained. The paper describing the first results is submitted to the ApJ. However, the project is still on-going as more distant cluster observations enter XMh4 and Chandra public data archives. We continued our work on improving techniques for accurate measurements of the cluster mass function and obtaining cosmological constraints from such observations. We published (ApJ, 601, 610) a study in which we derived the baryon mass function for a complete sample of low-redshift clusters. These papers argued that it was an excellent proxy for the total mass function. The baryon mass function can be used to constrain the amplitude and slope of the density fluctuation power spectrum on cluster scales. This method does not use observational determinations of the total mass and thus bypasses major uncertainties in the traditional analyses based on the X-ray temperature function. We derived the measurements for the amplitude of density perturbations, sigma8 = 0.72 +/- 0.04 and the shape parameter Omega*h = 0.l3 +/- 0.07, in good agreement with a number of independent methods.

Oliversen, Ronald J.↗

NASA NTRS2012

Engineering a Multimission Approach to Navigation Ground Data System Operations

The Mission Design and Navigation (MDNAV) Section at the Jet Propulsion Laboratory (JPL) supports many deep space and earth orbiting missions from formulation to end of mission operations. The requirements of these missions are met with a multimission approach to MDNAV ground data system (GDS) infrastructure capable of being shared and allocated in a seamless and consistent manner across missions. The MDNAV computing infrastructure consists of compute clusters, network attached storage, mission support area facilities, and desktop hardware. The multimission architecture allows these assets, and even personnel, to be leveraged effectively across the project lifecycle and across multiple missions simultaneously. It provides a more robust and capable infrastructure to each mission than might be possible if each constructed its own. It also enables a consistent interface and environment within which teams can conduct all mission analysis and navigation functions including: trajectory design; ephemeris generation; orbit determination; maneuver design; and entry, descent, and landing analysis. The savings of these efficiencies more than offset the costs of increased complexity and other challenges that had to be addressed: configuration management, scheduling conflicts, and competition for resources. This paper examines the benefits of the multimission MDNAV ground data system infrastructure, focusing on the hardware and software architecture. The result is an efficient, robust, scalable MDNAV ground data system capable of supporting more than a dozen active missions at once.

Mission Design and Navigation (MDNAV)↗

DOE OSTI2021

Charge radii in covariant density functional theory: A global view

A systematic global investigation of differential charge radii has been performed within the CDFT framework for the first time. Theoretical results obtained with conventional covariant energy density functionals and the separable pairing interaction of Tian et al. [Phys. Lett. B 676, 44 (2009)] are compared with experimental differential charge radii in the regions of the nuclear chart in which available experimental data crosses the neutron shell closures at N=28,50,82, and 126. The analysis of absolute differential radii of different isotopic chains and their relative properties indicate clearly that such properties are reasonably well described in model calculations in the cases when the mean-field approximation is justified. However, while the observed clusterization of differential charge radii of different isotopic chains is well described above the N=50 and N=126 shell closures, it is more difficult to reproduce it above the N=28 and N=82 shell closures because of possible deficiencies in the underlying single-particle structure. The impact of the latter has been evaluated for spherical shapes and it was shown that the relative energies of the single-particle states and the patterns of their occupation with increasing neutron number have an appreciable impact on the evolution of the δ$\langle$r2$\rangle$N,N' values. These factors also limit the predictive power of model calculations in the regions of high densities of the single-particle states of different origin. It is shown that the kinks in the charge radii at neutron shell closures are due to the underlying single-particle structure and due to weakening or collapse of pairing at these closures. The regions of the nuclear chart in which the correlations beyond mean field are expected to have an impact on charge radii are indicated; the analysis shows that the assignment of a calculated excited prolate minimum to the experimental ground state allows us to understand the trends of the evolution of differential charge radii with neutron number in many cases of shape coexistence even at the mean-field level. It is usually assumed that pairing is a dominant contributor to odd-even staggering (OES) in charge radii. Our analysis paints a more complicated picture. It suggests a new mechanism in which the fragmentation of the single-particle content of the ground state in odd-mass nuclei due to particle-vibration coupling provides a significant contribution to OES in charge radii.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

JIRIAF: JLAB Integrated Research Infrastructure Acros Facilities

The JIRIAF project aims to combine geographically diverse computing facilities into an integrated science infrastructure. This project starts by dynamically evaluating temporarily unallocated or idled compute resources from multiple providers. These resources are integrated to handle additional workloads without affecting local running jobs. This paper describes our approach to launch best-effort batch tasks which exploit these underutilized resources. Our system measures the real-time behavior of jobs running on a machine and learns to distinguish typical performance from outliers. Unsupervised ML techniques are used to analyze hardware-level performance measures, followed by a real-time cross-correlation analysis to determine which applications cause performance degradation. We then ameliorate bad behavior by throttling these processes. We demonstrate that problematic performance interference can be detected and acted on, which makes it possible to continue to share resources between applications and simultaneously maintain high utilization levels in a computing cluster. We relocate the CLAS12 data processing workflow to a remote data center for a case study, preventing file migration and temporal data persistency.

Lawrence, David↗

DOE OSTI2022

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

environmental monitoring↗

NASA NTRS1973

An objective technique to estimate percentage of an ERTS-1 water boundary resolution element covered by water

The author has identified the following significant results. An objective technique was developed to measure the surface area of water bodies. Nineteen water bodies in the Houston and Galveston, Texas area were selected as a basis for the technique development. The actual surface area of each body was determined from rectified and enlarged NASA aircraft photography. A clustering algorithm was used to produce classification maps of the region from ERTS-1 data. Certain classes were identified as being 100% water. Other classes were identified as being mixtures of water with land or vegetation. The number of picture elements falling on each water body and its boundary were counted. A linear regression analysis was performed to relate the total number of picture elements and boundary elements counted to the actual surface area. The standard error of the estimate was 6.7 acres. The absolute error was not a function of the actual surface area of the water body.

Erb, R. B.↗

NASA NTRS1978

Luna 24 - Lateral heterogeneity in the lunar crust

Results of petrological investigations of Luna 24 soil samples are compared with data from Apollo and other Luna missions in order to determine the large scale composition of the lunar surface and crust. Modal analysis of the 90 to 150 micron soil fraction and electron microprobe analysis of glass spheres and fragments of the Luna 24 core sample are presented. High and low MgO mare basalt compositional clusters are found, suggesting the derivation of southern Mare Crisium basalts from two magmas. A model of Luna 24 soils as being composed of a mixture of glass-poor mare material and glass-rich highland material is found to be consistent with glass and agglutinate modal abundances. Comparisons show that potassium, and by inference all lithophile trace elements, are depleted on the eastern limb of the moon relative to the central nearside. The observed depletion is interpreted to be characteristic of the underlying crust and mantle as well as the surface.

Warner, J. L.↗

NASA NTRS1990

Framework for a space shuttle main engine health monitoring system

A framework developed for a health management system (HMS) which is directed at improving the safety of operation of the Space Shuttle Main Engine (SSME) is summarized. An emphasis was placed on near term technology through requirements to use existing SSME instrumentation and to demonstrate the HMS during SSME ground tests within five years. The HMS framework was developed through an analysis of SSME failure modes, fault detection algorithms, sensor technologies, and hardware architectures. A key feature of the HMS framework design is that a clear path from the ground test system to a flight HMS was maintained. Fault detection techniques based on time series, nonlinear regression, and clustering algorithms were developed and demonstrated on data from SSME ground test failures. The fault detection algorithms exhibited 100 percent detection of faults, had an extremely low false alarm rate, and were robust to sensor loss. These algorithms were incorporated into a hierarchical decision making strategy for overall assessment of SSME health. A preliminary design for a hardware architecture capable of supporting real time operation of the HMS functions was developed. Utilizing modular, commercial off-the-shelf components produced a reliable low cost design with the flexibility to incorporate advances in algorithm and sensor technology as they become available.

Hawman, Michael W.↗

DOE OSTI2021

Scaling pair count to next galaxy surveys

ABSTRACT Counting pairs of galaxies or stars according to their distance is at the core of real-space correlation analyses performed in astrophysics and cosmology. Upcoming galaxy surveys (LSST, Euclid) will measure properties of billions of galaxies challenging our ability to perform such counting in a minute-scale time relevant for the usage of simulations. The problem is only limited by efficient access to the data, hence belongs to the big data category. We use the popular Apache Spark framework to address it and design an efficient high-throughput algorithm to deal with hundreds of millions to billions of input data. To optimize it, we revisit the question of non-hierarchical sphere pixelization based on cube symmetries and develop a new one dubbed the ‘Similar Radius Sphere Pixelization’ (SARSPix) with very close to square pixels. It provides the most adapted indexing over the sphere for all distance-related computations. Using LSST-like fast simulations, we compute autocorrelation functions on tomographic bins containing between a hundred million to one billion data points. In each case, we achieve the construction of a standard pair-distance histogram in about 2 min, using a simple algorithm that is shown to scale, over a moderate number of nodes (16–64). This illustrates the potential of this new techniques in the field of astronomy where data access is becoming the main bottleneck. They can be easily adapted to other use-cases as nearest-neighbours search, catalogue cross-match or cluster finding. The software is publicly available from https://github.com/astrolabsoftware/SparkCorr.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Organo‐Functionalized Lacunary Double Cubane‐Type Oxometallates: Synthesis, Structure, and Properties of [(M II Cl) 2 (V IV O) 2 {((HOCH 2 CH 2 )(H)N(CH 2 CH 2 O))(HN(CH 2 CH 2 O) 2 )} 2 ] (M=Co, Zn)

Abstract Organofunctionalized tetranuclear clusters [(M II Cl) 2 (V IV O) 2 {((HOCH 2 CH 2 )(H)N(CH 2 CH 2 O))(HN(CH 2 CH 2 O) 2 )} 2 ] (1, M=Co,2: M=Zn) containing an unprecedented oxometallacyclic {M 2 V 2 Cl 2 N 4 O 8 } (M=Co, Zn) framework have been prepared by solvothermal reactions. The new oxo‐alkoxide compounds were fully characterized by spectroscopic methods, magnetic susceptibility measurement, DFT and ab initio computational methods, and complete single‐crystal X‐ray diffraction structure analysis. The isostructural clusters are formed of edge‐sharing octahedral {VO 5 N} and trigonal bipyramidal {MO 3 NCl} units. Diethanolamine ligates the bimetallic lacunary double cubane core of1and2in an unusual two‐mode fashion, unobserved previously. In the crystalline state, the clusters of1and2are joined by hydrogen bonds to form a three‐dimensional network structure. Magnetic susceptibility data indicate weakly antiferromagnetic interactions between the vanadium centers [J iso (V IV −V IV )=−5.4(1); −3.9(2) cm −1 ], and inequivalent antiferromagnetic interactions between the cobalt and vanadium centers [J iso (V IV −Co II )=−12.6 and −7.5 cm −1 ] contained in1.

Chemistry↗

DOE OSTI2021

A Co-design Framework for Online Data Analysis and Reduction

Science applications preparing for the exascale era are increasingly exploring in situ computations comprising of simulation-analysis-reduction pipelines coupled in-memory. Efficient composition and execution of such complex pipelines for a target platform is a codesign process that evaluates the impact and tradeoffs of various application- and system-specific parameters. In this article, we describe a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for composing parametric studies on coupled applications, and Savanna, a runtime engine for orchestrating and executing campaigns of codesign experiments. Furthermore, this toolset facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage versus compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design of Cheetah and Savanna, and present application examples that use this framework to conduct codesign studies on small clusters as well as leadership class supercomputers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Cosmological analysis of three-dimensional BOSS galaxy clustering and Planck CMB lensing cross correlations via Lagrangian perturbation theory

In this work, we present a formalism for jointly fitting pre- and post-reconstruction redshift-space clustering (RSD) and baryon acoustic oscillations (BAO) plus gravitational lensing (of the CMB) that works directly with the observed 2-point statistics. The formalism is based upon (effective) Lagrangian perturbation theory and a Lagrangian bias expansion, which models RSD, BAO and galaxy-lensing cross correlations within a consistent dynamical framework. As an example we present an analysis of clustering measured by the Baryon Oscillation Spectroscopic Survey in combination with CMB lensing measured by Planck. The post-reconstruction BAO strongly constrains the distance-redshift relation, the full-shape redshift-space clustering constrains the matter density and growth rate, and CMB lensing constrains the clustering amplitude. Using only the redshift space data we obtain Ω m = 0.303 ± 0.008, $H_0$ = 69.21 ± 0.78 and $σ_8$ = 0.743 ± 0.043. The addition of lensing information, even when restricted to the Northern Galactic Cap, improves constraints to Ω m = 0.303 ± 0.008, $H_0$ = 69.21 ± 0.77 and $σ_8$ = 0.707 ± 0.035, in tension with CMB and cosmic shear constraints. The combination of Ω m and $H_0$ are consistent with Planck, though their constraints derive mostly from redshift-space clustering. The low $σ_8$ value are driven by cross correlations with CMB lensing in the low redshift bin ($\textit{z}$ ≃ 0.38) and at large angular scales, which show a 20% deficit compared to expectations from galaxy clustering alone. We conduct several systematics tests on the data and find none that could fully explain these tensions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Dark energy survey year 1 results: Constraining baryonic physics in the Universe

ABSTRACT Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3 × 2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modelling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude (Q1) generally reflects the strength of baryon feedback. With the upper limit of Q1 prior being bound by the Illustris feedback scenarios, we reach $\sim 20{{\ \rm per\ cent}}$ improvement in the constraint of $S_8=\sigma _8(\Omega _{\rm m}/0.3)^{0.5}=0.788^{+0.018}_{-0.021}$ compared to the original DES 3 × 2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 arcmin, which was excluded in previous DES analyses that did not model baryonic physics. We obtain $S_8=0.781^{+0.014}_{-0.015}$ for the combined DES Y1+Planck EE+BAO analysis with a non-informative Q1 prior. In terms of the baryon constraints, we measure $Q_1=1.14^{+2.20}_{-2.80}$ for DES Y1 only and $Q_1=1.42^{+1.63}_{-1.48}$ for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than 2σ.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Molecular and Epidemiological Investigation of Fluconazole-resistant Candida parapsilosis —Georgia, United States, 2021

Abstract Background Reports of fluconazole-resistant Candida parapsilosis bloodstream infections are increasing. We describe a cluster of fluconazole-resistant C parapsilosis bloodstream infections identified in 2021 on routine surveillance by the Georgia Emerging Infections Program in conjunction with the Centers for Disease Control and Prevention. Methods Whole-genome sequencing was used to analyze C parapsilosis bloodstream infections isolates. Epidemiological data were obtained from medical records. A social network analysis was conducted using Georgia Hospital Discharge Data. Results Twenty fluconazole-resistant isolates were identified in 2021, representing the largest proportion (34%) of fluconazole-resistant C parapsilosis bloodstream infections identified in Georgia since surveillance began in 2008. All resistant isolates were closely genetically related and contained the Y132F mutation in the ERG11 gene. Patients with fluconazole-resistant isolates were more likely to have resided at long-term acute care hospitals compared with patients with susceptible isolates (P = .01). There was a trend toward increased mechanical ventilation and prior azole use in patients with fluconazole-resistant isolates. Social network analysis revealed that patients with fluconazole-resistant isolates interfaced with a distinct set of healthcare facilities centered around 2 long-term acute care hospitals compared with patients with susceptible isolates. Conclusions Whole-genome sequencing results showing that fluconazole-resistant C parapsilosis isolates from Georgia surveillance demonstrated low genetic diversity compared with susceptible isolates and their association with a facility network centered around 2 long-term acute care hospitals suggests clonal spread of fluconazole-resistant C parapsilosis. Further studies are needed to better understand the sudden emergence and transmission of fluconazole-resistant C parapsilosis.

Misas, Elizabeth (ORCID:0000000162437716)↗