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DOE OSTI2024

Metagenomic clustering links specific metabolic functions to globally relevant ecosystems

ABSTRACT Metagenomic sequencing has advanced our understanding of biogeochemical processes by providing an unprecedented view into the microbial composition of different ecosystems. While the amount of metagenomic data has grown rapidly, simple-to-use methods to analyze and compare across studies have lagged behind. Thus, tools expressing the metabolic traits of a community are needed to broaden the utility of existing data. Gene abundance profiles are a relatively low-dimensional embedding of a metagenome’s functional potential and are, thus, tractable for comparison across many samples. Here, we compare the abundance of KEGG Ortholog Groups (KOs) from 6,539 metagenomes from the Joint Genome Institute’s Integrated Microbial Genomes and Metagenomes (JGI IMG/M) database. We find that samples cluster into terrestrial, aquatic, and anaerobic ecosystems with marker KOs reflecting adaptations to these environments. For instance, functional clusters were differentiated by the metabolism of antibiotics, photosynthesis, methanogenesis, and surprisingly GC content. Using this functional gene approach, we reveal the broad-scale patterns shaping microbial communities and demonstrate the utility of ortholog abundance profiles for representing a rapidly expanding body of metagenomic data. IMPORTANCE Metagenomics, or the sequencing of DNA from complex microbiomes, provides a view into the microbial composition of different environments. Metagenome databases were created to compile sequencing data across studies, but it remains challenging to compare and gain insight from these large data sets. Consequently, there is a need to develop accessible approaches to extract knowledge across metagenomes. The abundance of different orthologs (i.e., genes that perform a similar function across species) provides a simplified representation of a metagenome’s metabolic potential that can easily be compared with others. In this study, we cluster the ortholog abundance profiles of thousands of metagenomes from diverse environments and uncover the traits that distinguish them. This work provides a simple to use framework for functional comparison and advances our understanding of how the environment shapes microbial communities.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2002

NASA Technology Investments in Electric Propulsion: New Directions in the New Millennium

The last decade was a period of unprecedented acceptance of NASA developed electric propulsion by the user community. The benefits of high performance electric propulsion systems are now widely recognized, and new technologies have been accepted across the commonly. NASA clearly recognizes the need for new, high performance, electric propulsion technologies for future solar system missions and is sponsoring aggressive efforts in this area. These efforts are mainly conducted under the Office of Aerospace Technology. Plans over the next six years include the development of next generation ion thrusters for end of decade missions. Additional efforts are planned for the development of very high power thrusters, including magnetoplasmadynamic, pulsed inductive, and VASIMR, and clusters of Hall thrusters. In addition to the in-house technology efforts, NASA continues to work closely with both supplier and user communities to maximize the acceptance of new technology in a timely and cost-effective manner. This paper provides an overview of NASA's activities in the area of electric propulsion with an emphasis on future program directions.

Sankovic, John M.↗

DOE OSTI2021

Reduction of the molecular hamiltonian matrix using quantum community detection

Abstract Quantum chemistry is interested in calculating ground and excited states of molecular systems by solving the electronic Schrödinger equation. The exact numerical solution of this equation, frequently represented as an eigenvalue problem, remains unfeasible for most molecules and requires approximate methods. In this paper we introduce the use of Quantum Community Detection performed using the D-Wave quantum annealer to reduce the molecular Hamiltonian matrix in Slater determinant basis without chemical knowledge. Given a molecule represented by a matrix of Slater determinants, the connectivity between Slater determinants (as off-diagonal elements) is viewed as a graph adjacency matrix for determining multiple communities based on modularity maximization. A gauge metric based on perturbation theory is used to determine the lowest energy cluster. This cluster or sub-matrix of Slater determinants is used to calculate approximate ground state and excited state energies within chemical accuracy. The details of this method are described along with demonstrating its performance across multiple molecules of interest and bond dissociation cases. These examples provide proof-of-principle results for approximate solution of the electronic structure problem using quantum computing. This approach is general and shows potential to reduce the computational complexity of post-Hartree–Fock methods as future advances in quantum hardware become available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1997

Summer Workshop on the Origins of Stars and Planets

The meeting had broad representation from both the national and international scientific communities. There were 38 oral lectures describing the latest research results pertaining to star and planet formation in young clusters presented at the workshop. In addition there were 65 poster papers describing research in this area also presented at the workshop. Because there was ample space made available by Wellesley College, all posters were up and available throughout the entire duration of the meeting. This insured more than adequate time for all participants to view the posters and interact with their authors. The oral talks were 15 minutes in duration with an additional 15 minutes reserved for questions and discussion. As a result there was considerable discussion and exchange of ideas which insured that the workshop nature of the conference was maintained despite the large attendance. In summary, the workshop was a great success scientifically while at the same time being extremely cost effective. The 1996 workshop exceeded the overall objectives originally set for it.

Lada, Charles J.↗

NASA NTRS2012

3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer

Determining the Z-R relationship (where Z is the radar reflectivity factor and R is rainfall rate) from disdrometer data has been and is a common goal of cloud physicists and radar meteorology researchers. The usefulness of this quantity has traditionally been limited since radar represents a volume measurement, while a disdrometer corresponds to a point measurement. To solve that problem, a 3D-DSD (drop-size distribution) method of determining an equivalent 3D Z-R was developed at the University of Central Florida and tested at the Kennedy Space Center, FL. Unfortunately, that method required a minimum of three disdrometers clustered together within a microscale network (.1-km separation). Since most commercial disdrometers used by the radar meteorology/cloud physics community are high-cost instruments, three disdrometers located within a microscale area is generally not a practical strategy due to the limitations of these kinds of research budgets. A relatively simple modification to the 3D-DSD algorithm provides an estimate of the 3D-DSD and therefore, a 3D Z-R measurement using a single disdrometer. The basis of the horizontal extrapolation is mass conservation of a drop size increment, employing the mass conservation equation. For vertical extrapolation, convolution of a drop size increment using raindrop terminal velocity is used. Together, these two independent extrapolation techniques provide a complete 3DDSD estimate in a volume around and above a single disdrometer. The estimation error is lowest along a vertical plane intersecting the disdrometer position in the direction of wind advection. This work demonstrates that multiple sensors are not required for successful implementation of the 3D interpolation/extrapolation algorithm. This is a great benefit since it is seldom that multiple sensors in the required spatial arrangement are available for this type of analysis. The original software (developed at the University of Central Florida, 1998.- 2000) has also been modified to read standardized disdrometer data format (Joss-Waldvogel format). Other modifications to the software involve accounting for vertical ambient wind motion, as well as evaporation of the raindrop during its flight time.

Lane, John↗

NASA NTRS2013

On the Performance of Global Magnetohydrodynamic Models in the Earth's Magnetosphere

We study the performance of four magnetohydrodynamic models (BATS-R-US, GUMICS, LFM, Open GGCM) in the Earths magnetosphere. Using the Community Coordinated Modeling Centers Run-on-Request system, we compare model predictions with magnetic field measurements of the Cluster, Geotail and Wind spacecraft during a multiple substorm event. We also compare model cross polar cap potential results to those obtained from the Super Dual Auroral Radar Network(SuperDARN) and the model magnetopause standoff distances to an empirical magnetopause model. The correlation coefficient (CC) and prediction efficiency (PE) metrics are used to objectively evaluate model performance quantitatively. For all four models, the best performance outside geosynchronous orbit is found on the dayside. Generally, the performance of models decreases steadily down stream from the Earth. On the dayside most CCs are above 0.5 with CCs for Bx and Bz close to 0.9 for three out of four models. In the magnetotail at a distance of about -130 Earth radii from Earth, the prediction efficiency of all models is below that of using an average value for the prediction with the exception of Bz. Bx is most often best predicted and correlated both on the dayside and the nightside close to the Earth whereas in the far tail the CC and PE for Bz are substantially higher than other components in all models. We also find that increasing the resolution or coupling an additional physics module does notautomatically increase the model performance in the magnetosphere.

geomagnetic tail↗

NASA NTRSDate not supplied

Visualizing Corridors in Terminal Airspace Using Trajectory Clustering

Context: Advances in battery and automation technology have made routine air taxi and cargo transport in urban areas a business model that can be attained by emerging aviation innovators. The community vision and work to enable these novel operations is discussed using the term ‘Urban Air Mobility’ or UAM. Small, piloted, airspace vehicles that fly with a few passengers do operate in urban areas today, and these vehicles can be studied as an early proxy for this future UAM traffic. Aim: We seek to identify corridors already in daily operation and their properties. Method: We applied DBSCAN and HDBSCAN to Dallas Forth-Worth TRACON flight data to identify corridors in use, their density, and devised a method to annotate landing sites used in these corridors with site metadata. Results: While DBSCAN was unable to group similar trajectories, we we were able to successfully identify corridors using HDBSCAN, measure their density and annotate them. Conclusion: The applied method can successfully identify corridors in daily operation with additional metadata to help domain expert understand the intent of UAM corridors.

UAM Trajectory, TRACON, Clustering, DBSCAN, HDBSCA↗

NASA NTRSDate not supplied

Visualizing Corridors in Terminal Airspace using Trajectory Clustering

UAM, Trajectory, TRACON, Clustering, DBSCAN, HDBSC↗

NASA NTRS2020

Cluster Analysis of Thermal Icequakes Using the Seismometer to Investigate Ice and Ocean Structure (SIIOS): Implications for Ocean World Seismology

Ocean Worlds are of high interest to the planetary community due to the potential habitability of their subsurface oceans. Over the next few decades several missions will be sent to ocean worlds including the Europa Clipper, Dragonfly, and possibly a Europa lander. The Dragonfly and Europa lander missions will carry seismic payloads tasked with detecting and locating seismic sources. The Seismometer to Investigate Ice and Ocean Structure (SIIOS) is a NASA PSTAR funded project that investigates ocean world seismology using terrestrial analogs. The goals of the SIIOS experiment include quantitatively comparing flight-candidate seismometers to traditional instruments, comparing single-station approaches to a small-aperture array, and characterizing the local seismic environment of our field sites. Here we present an analysis of detected local events at our field sites at Gulkana Glacier in Alaska and in Northwest Greenland approximately 80 km North of Qaanaaq, Greenland. Both field sites passively recorded data for about two weeks. We deployed our experiment on Gulkana Glacier in September 2017 and in Greenland in June 2018. At Gulkana there was a nearby USGS weather station which recorded wind data. Temperature data was collected using the MERRA satellite. In Greenland we deployed our own weather station to collect temperature and wind data. Gulkana represents a noisier and more active environment. Temperatures fluctuated around 0°C, allowing for surface runoff to occur during the day. The glacier had several moulins, and during deployment we heard several rockfalls from nearby mountains. In addition to the local environment, Gulkana is located close to an active plate boundary (relative to Greenland). This meant that there were more regional events recorded over two weeks, than in Greenland. Greenland’s local environment was also quieter, and less active. Temperatures remained below freezing. The Greenland ice was much thicker than Gulkana (~850 m versus ~100 m) and our stations were above a subglacial lake. Both conditions can reduce event detections from basal motion. Lastly, we encased our Greenland array in an aluminum vault and buried it beneath the surface unlike our array in Gulkana where the instruments were at the surface and covered with plastic bins. The vault further insulated the array from thermal and atmospheric events.

Marusiak, A. G.↗

DOE OSTI2025

Opening doors to physical sample tracking and attribution in Earth and environmental sciences

Physical samples and their associated data and metadata underpin scientific discoveries across disciplines and can enable new science when appropriately archived. However, there are significant gaps in current practices and infrastructure that prevent accurate provenance tracking, reproducibility, and attribution. For most samples, descriptive metadata are often sparse, inaccessible, or absent. Samples and associated data and metadata may also be scattered across numerous physical collections, data repositories, laboratories, data files, and papers with no clear linkage or provenance tracking as new information is generated over time. The Earth Science Information Partners (ESIP) Physical Samples Curation Cluster has therefore developed guidance for scientific authors on ‘Publishing Open Research Using Physical Samples.’ This involved synthesizing existing practices, gathering community feedback, and assessing real-world examples. We identified improvements needed to enable authors to efficiently cite and link Earth science samples and related data, and track their use. Our goal is to help improve discoverability, interoperability, and reuse of physical samples, and associated data and metadata. Though primarily focused on the needs of Earth and environmental sciences, these guidelines are broadly applicable.

58 GEOSCIENCES↗

DOE OSTI2020

Geology and climate influence rhizobiome composition of the phenotypically diverse tropical tree Tabebuia heterophylla

Plant-associated microbial communities have diverse phenotypic effects on their hosts that are only beginning to be revealed. We hypothesized that morpho-physiological variations in the tropical tree Tabebuia heterophylla, observed on different geological substrates, arise in part due to microbial processes in the rhizosphere. We characterized the microbiota of the rhizosphere and soil communities associated with T. heterophylla trees in high and low altitude sites (with varying temperature and precipitation) of volcanic, karst and serpentine geologies across Puerto Rico. We sampled 6 areas across the island in three geological materials including volcanic, serpentine and karst soils. Collection was done in 2 elevations (>450m and 0-300m high), that included 3 trees for each site and 4 replicate soil samples per tree of both bulk and rhizosphere. Genomic DNA was extracted from 144 samples, and 16S rRNA V4 sequencing was performed on the Illumina MiSeq platform. Proteobacteria, Actinobacteria, and Verrucomicrobia were the most dominant phyla, and microbiomes clustered by geological substrate and elevation. Volcanic samples were enriched in Verrucomicrobia; karst was dominated by nitrogen-fixing Proteobacteria, and serpentine sites harbored the most diverse communities, with dominant Cyanobacteria. Sites with similar climates but differing geologies showed significant differences on rhizobiota diversity and composition demonstrating the importance of geology in shaping the rhizosphere microbiota, with implications for the plant's phenotype. Our study sheds light on the combined role of geology and climate in the rhizosphere microbial consortia, likely contributing to the phenotypic plasticity of the trees.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Viral elements and their potential influence on microbial processes along the permanently stratified Cariaco Basin redoxcline

Little is known about viruses in oxygen-deficient water columns (ODWCs). In surface ocean waters, viruses are known to act as gene vectors among susceptible hosts. Some of these genes may have metabolic functions and are thus termed auxiliary metabolic genes (AMGs). AMGs introduced to new hosts by viruses can enhance viral replication and/or potentially affect biogeochemical cycles by modulating key microbial pathways. Here we identify 748 viral populations that cluster into 94 genera along a vertical geochemical gradient in the Cariaco Basin, a permanently stratified and euxinic ocean basin. The viral communities in this ODWC appear to be relatively novel as 80 of these viral genera contained no reference viral sequences, likely due to the isolation and unique features of this system. We identify viral elements that encode AMGs implicated in distinctive processes, such as sulfur cycling, acetate fermentation, signal transduction, [Fe–S] formation, and N-glycosylation. These AMG-encoding viruses include two putative Mu-like viruses, and viral-like regions that may constitute degraded prophages that have been modified by transposable elements. Our results provide an insight into the ecological and biogeochemical impact of viruses oxygen-depleted and euxinic habitats.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Identification of key bacterial populations affecting early embryonic development in cattle uterus

Abstract Superovulation is an important animal breeding biotechnology, while the quality of embryos obtained from superovulation is unstable in cattle. The relationship between the microorganisms in the cattle uterus and embryo qualities was determined to identify the key bacterial populations affecting early embryonic development. A total of 10 Xia Nan cows underwent superovulation, we collected cervical mucus and flush samples to investigated by 16S rDNA sequencing. Results showed that there were abundant microorganisms in cervical mucus, but no obvious relationship with the quality of embryos. The clustering results of flush samples were consistent with the grouping of embryo quality. Proteobacteria accounted for more than 95% of the total bacterial community in group A with the best embryo quality (qualified embryo ratio above 0.8), and as embryo quality decreased, the Proteobacteria proportion also decreased. In contrast to the proportion of Proteobacteria, the proportions of Firmicutes and Bacteroidetes significantly increased as embryo quality decreased. For group C with the worst embryo quality, the proportions of Firmicutes and Bacteroidetes increased to 4.7 times and 12.3 times of group A, respectively. These results showed that the quantities and proportions of Firmicutes and Bacteroidetes may be related to early embryonic development in cattle.

Lyu, Chenchen↗

NASA NTRS2018

Data Mining for Vortices on the Earth's Magnetosphere - Algorithm Application for Detection and Analysis

Unsteady processes in the solar wind– magnetosphere interaction, such as vortices developed at the magnetopause boundary by the Kelvin–Helmholtz instability, may contribute to the process of mass, momentum and energy transfer into the Earth’s magnetosphere. The research described in this paper validates an algorithm to automatically detect and characterize vortices based on velocity data from simulations. The vortex identification algorithm (VIA) systematically searches the 3-D velocity fields to identify critical points where the magnitude of the velocity vector vanishes. The velocity gradient tensor is computed and its invariants are used to assess vortex structure in the flow field. We use the Community Coordinated Modeling Center (CCMC) Runs on Request capability to create a series of model runs initialized from the conditions observed by the Cluster mission in the Hwang et al. (2011) analysis of Kelvin–Helmholtz vortices observed during southward interplanetary magnetic field (IMF) conditions. We analyze further the properties of the vortices found in the runs, including the velocity changes within their motion across the magnetosheath. We also demonstrate the potential of our tool to identify and characterize other transient features (e.g., flux transfer events, FTEs) with vortical internal structures. We find that the vortices are associated with flows on the magnetosheath side of the magnetopause that reach speeds greater than the solar wind speed at the bow shock.

Collado-Vega, Yaireska M.↗

DOE OSTI2022

Soil pH influences the structure of virus communities at local and global scales

The influence of biotic and abiotic factors on viral communities across environmental gradients in soil is relatively unknown. While soil pH strongly influences microbial community structure, it is unclear whether there is a similar influence on soil viruses. In this study, prokaryotic and viral communities were characterized in soils from a long-term pH-manipulated soil gradient (pH 4.5 and 7.5), and viral populations also compared to those of other soils ranging in pH (4.0–7.5). Viral communities were significantly influenced by pH at the local scale with 99% of viral operational taxonomic units restricted to pH 4.5 or 7.5 soil only. Analysis of viromes from six other European and North American soil systems demonstrated that a selection of viral clusters from acidic and neutral pH soils were more associated with those from the local gradient pH 4.5 or 7.5 soils, respectively. While direct pH effects on virion integrity and indirect selection via host composition were not distinguished, the results reveal that soil pH is a factor in structuring viral communities at local and global scales.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Distilling Knowledge from Ensembles of Cluster-Constrained-Attention Multiple-Instance Learners for Whole Slide Image Classification

The peculiar nature of whole slide imaging (WSI), digitizing conventional glass slides to obtain multiple high resolution images which capture microscopic details of a patient’s histopathological features, has garnered increased interest from the computer vision research community over the last two decades. Given the unique computational space and time complexity inherent to gigapixel-size whole slide image data, researchers have proposed novel machine learning algorithms to aid in the performance of diagnostic tasks in clinical pathology. One effective algorithm represents a Whole slide image as a bag of smaller image patches, which can be represented as low-dimension image patch embeddings. Weakly supervised deep-learning methods, such as cluster-constrained-attention multiple instance learning (CLAM), have shown promising results when combined with image patch embeddings. While traditional ensemble classifiers yield improved task performance, such methods come with a steep cost in model complexity. Through knowledge distillation, it is possible to retain some performance improvements from an ensemble, while minimizing costs to model complexity. In this work, we implement a weakly supervised ensemble using clustering-constrained-attention multiple-instance learners (CLAM), which uses attention and instance-level clustering to identify task salient regions and feature extraction in whole slides. By applying logit-based and attention-based knowledge distillation, we show it is possible to retain some performance improvements resulting from the ensemble at zero cost to model complexity.

Alamudun, Folami↗

DOE OSTI2025

dCache project status and update

The dCache project delivers an open-source, massively scalable, distributed storage system deployed internationally to satisfy today’s scientists’ ever-demanding storage requirements. Its multifaceted approach supports different use cases with the same storage, from high throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters, and longterm data persistence on tertiary storage. Even though dCache was initially developed for HEP experiments, today, it is used by various scientific communities, including astrophysics, biomed, and life science, each with their specific requirements. To match the needs of these new communities and keep up with the scaling demands of existing experiments, dCache is permanently evolving. With this contribution, we would like to highlight the recent developments in dCache regarding integration with CERN Tape Archive (CTA), advanced metadata handling, token-based authorization support, bulk API for QoS transitions, REST API to control interaction with the tape system, and future development directions.

Mkrtchyan, Tigran [DESY]↗

NASA NTRS2011

Identifying Geographic Areas at Risk of Soil-transmitted Helminthes Infection Using Remote Sensing and Geographical Information Systems: Boaco, Nicaragua as a Case Study

Several types of intestinal nematodes, that can infect humans and specially school-age children living in poverty, develop part of their life cycle in soil. Presence and survival of these parasites in the soil depend on given environmental characteristics like temperature and moisture that can be inferred with remote sensing (RS) technology. Prevalence of diseases caused by these parasitic worms can be controlled and even eradicated with anthelmintic drug treatments and sanitation improvement. Reliable and updated identification of geographic areas at risk is required to implement effective public health programs; to calculate amount of drug required and to distribute funding for sanitation projects. RS technology and geographical information systems (GIS) will be used to analyze for associations between in situ prevalence and remotely sensed data in order to establish RS proxies of environmental parameters that indicate the presence of these parasits. In situ data on helminthisasis will be overlaid over an ecological map derived from RS data using ARC Map 9.3 (ESRI). Temperature, vegetation, and distance to bodies of water will be inferred using data from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat TM and ETM+. Elevation will be estimated with data from The Shuttle Radar Topography Mission (SRTM). Prevalence and intensity of infections are determined by parasitological survey (Kato Katz) of children enrolled in rural schools in Boaco, Nicaragua, in the communities of El Roblar, Cumaica Norte, Malacatoya 1, and Malacatoya 2). This study will demonstrate the importance of an integrated GIS/RS approach to define clusters and areas at risk. Such information will help to the implementation of time and cost efficient control programs and sanitation efforts.

Moreno, Max J.↗