Results for “Community Detection” — Page 7

DOE OSTI2021

Community Fabric: Visualizing communities and structure in dynamic networks

We present Community Fabric, a novel visualization technique for simultaneously visualizing communities and structure within dynamic networks. In dynamic networks, the structure of the network is continuously evolving throughout time and these underlying topological shifts tend to lead to communal changes. Community Fabric helps the viewer more easily interpret and understand the interplay of structural change and community evolution in dynamic graphs. To achieve this, we take a new approach, hybridizing two popular network and community visualizations. Community Fabric combines the likes of the Biofabric static network visualization method with traditional community alluvial flow diagrams to visualize communities in a dynamic network while also displaying the underlying network structure. Our approach improves upon existing state-of-the-art techniques in several key areas. We describe the methodologies of Community Fabric, implement the visualization using modern web-based tools, and apply our approach to three example data sets.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

Decomposition of Nonlinear Dynamical Systems Using Koopman Gramians

In this paper we propose a new Koopman operator approach for nonlinear model decomposition using Koopman gramians. We introduce Koopman operators and discuss the notion of a input-Koopman operator. We show how input-Koopman operators can be used to cast a nonlinear system into the classical state-space form, as well as conditions under which input and state observable functions are well separated. We extend an existing method of dynamic mode decomposition for learning Koopman operators from data known as deep dynamic mode decomposition, for systems with control or disturbances. We illustrate the accuracy of the method on learning an input-state separable Koopman operator for an example system, even when the underlying system exhibits mixed state-input terms. Finally, we introduce a nonlinear decomposition algorithm, based on Koopman gramians, that maximizes internal subsystem observability and disturbance rejection from unwanted noise in other subsystems. To relieve the NP-hardness of the decomposition problem, we derive a relaxation based on Koopman gramians and multi-way partitioning. We illustrate our algorithm on a swing dynamics model for a IEEE 39 bus and discuss our findings.

Learning, Control, Distributed Control, koopman op↗

DOE OSTI2025

Inter-Kingdom Viral Interactions

Please cite as : Josué A. Rodríguez-Ramos, Amy E. Zimmerman, Ruonan Wu, Sheryl Bell, Trinidad Alfaro, Kirsten Hofmockel, William C. Nelson. 2025. Inter-Kingdom Viral Interactions. [Data Set] PNNL DataHub. This data is published under a CC0 license. The authors encourage data reuse and request attribution by referencing the above citations for the data package and associated manuscript. Deciphering viral ecology in soils is challenging due to their high physiochemical and community complexity. To enhance detection of sub-communities of DNA and RNA viruses, we applied fractionation approaches to soils collected across a moisture gradient from a grassland field experiment. Analyses included metagenomics and metatranscriptomics of size-fractionated extracellular viruses (i.e., DNA and RNA viromes), metagenomics of bacteria/archaea- or eukaryote-enriched samples, and whole soil metatranscriptomes with rRNA-depletion or polyadenylation enrichment. While RNA virome and whole soil RNA methods captured similar viral diversity, RNA viromes identified longer, higher-quality genomes. Further, we showed that significantly more DNA viruses were active in higher moisture than lower moisture samples, whereas responses by overall diversity vary by genome type (DNA versus RNA genomes). Finally, we demonstrate the power of fractionation approaches for identifying distinct viral communities that infect unique hosts, which has significant implications for ecological investigations, particularly related to interkingdom interactions.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1970

Detection and identification of benthic communities and shoreline features in Biscayne Bay

Progress made in the development of a technique for identifying and delinating benthic and shoreline communities using multispectral imagery is described. Images were collected with a multispectral scanner system mounted in a C-47 aircraft. Concurrent with the overflight, ecological ground- and sea-truth information was collected at 19 sites in the bay and on the shore. Preliminary processing of the scanner imagery with a CDC 1604 digital computer provided the optimum channels for discernment among different underwater and coastal objects. Automatic mapping of the benthic plants by multiband imagery and the mapping of isotherms and hydrodynamic parameters by digital model can become an effective predictive ecological tool when coupled together. Using the two systems, it appears possible to predict conditions that could adversely affect the benthic communities. With the advent of the ERTS satellites and space platforms, imagery data could be obtained which, when used in conjunction with water-level and meteorological data, would provide for continuous ecological monitoring.

Kolipinski, M. C.↗

NASA NTRS1975

Factors affecting the noise from small propeller driven aircraft

The factors affecting noise from small propeller driven airplanes are reviewed to quantify their affects where possible, and to indicate the potential for noise reduction. The main sources of external noise are noted to be the propellers and engines; the airframe being of less importance for both aural detection and community annoyance. Propeller noise is a strong function of tip speed and is affected adversely by nonuniform inflows. Reciprocating engine exhausts are noisier than those of comparably rated turboshaft engines, but their noise can be reduced by the use of flight certified exhaust mufflers. Presently, there are no generally accepted engineering methods for development of optimized propellers and exhaust muffler designs from weight and performance penalty standpoints. Flight demonstration results, however, suggest that required noise reductions for future certification should be possible with potentially small penalties.

Maglieri, D. J.↗

NASA NTRS1981

Sound measurements of the MOD-2 wind turbine generator

Sound measurements were made for the MOD-2 wind turbine generator for wind conditions of 7.6 to 13.4 m/sec and for output power ratings of about 1 to 2 NW. Both broad band and narrow band data wre obtained for a range of distances and azimuth angles from the machine. The rotor sound spectra are random in character and peak in the frequency ranges 30 to 50 Hz and 800 to 1300 Hz. Both peaks are predictable from experience with helicopter rotors and propellers. Results suggest that the lower frequency peak is due to the effects of inflow turbulence and the higher frequency peak is due to the interactions of the turbulent boundary layers with the trailing edges of the blades. The boundary layer related sound is the dominant component in the audible frequency range and determines the detectability of the machine. It could be detected at a distance of 1350 m in the upwind direction where the background noise was 30 dB (A) and at distances in excess of 2100 m in the downwind direction. Discrete frequency sound components associated with the power generation equipment are measurable in the direction normal to the axis of rotation but are not believed to be significant for detection or community response.

Hubbard, H. H.↗

NASA NTRSDate not supplied

ISS External Microorganisms: Collecting Planetary Protection Samples During Extravehicular Activity

Introduction: We have designed1, built, and tested a sampling kit (Fig. 1) to aseptically collect microbiological samples from exterior surfaces on the ISS (International Space Station). The kit was flown to ISS as part of the NG-19 commercial cargo mission in August of 2023. Astronauts will use the kit to collect samples from six exterior surfaces on ISS. These samples will be frozen at -80°C after collection and returned to the ground for next generation DNA sequencing. The results of this experiment will help inform planetary protection requirements for crewed missions. We hypothesize that there are detectable microbial communities outside ISS and that these communities originate from inside ISS. Current life support systems do not include any components for reducing microbial leakage. Gases are vented from inside ISS without filtration and there are currently no protocols in place to minimize bioburden on space suit exteriors prior to use. It is important to quantify the bioburden on current vehicles so that achievable limits can be set for crewed missions to astrobiologically relevant locations like Mars. Figure 1: The sampling kit contains eight swab canisters in total (six on the top and two on the bottom). A resuable end effector (1) is used to remove and reinstall the swabs. The kit also contains a handrail (2), tether loop (3), and, bayonet probes(4) to allow easy manipulation during EVA. Methods: We have designed a kit to carry 8 commercially available foam swabs into and out of vacuum without compromising the swabs’ sterility. The specially designed swab canisters contain a 0.2 µm Teflon filter that allows the canister to accommodate pressure changes without introducing unwanted contaminants. The kit meets existing EVA (Extravehicular Activity) safety requirements and has been used by human test subjects in the neutral buoyance lab and at vacuum in test chambers at the Johnson Space Center. In the early part of 2024, astronauts will use this sampling kit to swab six surfaces on the exterior of ISS. We will collect samples from: the airlock vestibule, the interior surface of the airlock thermal cover, an exterior handrail, a vent connected to the CO2 removal system, and a vent connected to the payload vacuum system inside ISS. Approximately 300 cm2 will be swabbed at each location. A seventh swab will be exposed to the vacuum of space without touching any surfaces as a blank. The eighth swab will remain sealed as a process control. After the EVA the swab kit will be frozen at -80°C and returned to earth at the earliest possible opportunity. The samples will remain frozen until they are thawed for next generation DNA sequencing on earth. We will use amplicon sequencing to identify any bacteria, archaea or fungi present in the samples. If there is enough DNA present, we will use shotgun metagenomic sequencing to further characterize the microbial ecology outside ISS. Preliminary Results: Results from ground-based testing demonstrate that the swab kit is capable of cycling in and out of vacuum without contaminating the swabs. Test subjects, wearing flight-like EVA gloves could remove swabs from the canister and sample discrete locations without inadvertently touching any other surfaces. Several types of bacteria and fungi were collected during these ground tests and survived up to 6 hours at vacuum. This includes non-spore forming bacterial like Staphyloccus capitis that are not traditionally considered extremophiles. Shotgun metagenomic sequencing of the ground-test samples revealed bacteria associated with human skin and airways on the exterior of space suits used during these tests 2 In addition to these results we will present preliminary results from our space-flight samples. We will also present lessons learned from attempting to collect microbiological samples during an EVA and describe how our results will affect planetary protection requirements for future crewed missions.

Aaron B. Regberg↗

NASA NTRSDate not supplied

ISS External Microorganisms: Tools and Techniques for Collecting Planetary Protection Samples During Extravehicular Activity

We have designed, built, and tested a sampling kit (Fig. 1) to aseptically collect microbiological samples from exterior surfaces on the ISS (International Space Station). The kit was flown to ISS as part of the NG-19 commercial cargo mission in August of 2023. Astronauts will use the kit to collect samples from six exterior surfaces on ISS. These samples will be frozen at -80°C after collection and returned to the ground for next generation DNA sequencing. The results of this experiment will help inform planetary protection requirements for crewed missions. We hypothesize that there are detectable microbial communities outside ISS and that these communities originate from inside ISS. Current life support systems do not include any components for reducing microbial leakage. Gases are vented from inside ISS without filtration and there are currently no protocols in place to minimize bioburden on space suit exteriors prior to use. It is important to quantify the bioburden on current vehicles so that achievable limits can be set for crewed missions to astrobiologically relevant locations like Mars.

Planetary Protection↗

NASA NTRSDate not supplied

ISS External Microorganisms: Collecting Planetary Protection Samples During Extravehicular Activity

Introduction: We have designed1, built, and tested a sampling kit (Fig. 1) to aseptically collect microbiological samples from exterior surfaces on the ISS (International Space Station). The kit was flown to ISS as part of the NG-19 commercial cargo mission in August of 2023. Astronauts will use the kit to collect samples from six exterior surfaces on ISS. These samples will be frozen at -80°C after collection and returned to the ground for next generation DNA sequencing. The results of this experiment will help inform planetary protection requirements for crewed missions. We hypothesize that there are detectable microbial communities outside ISS and that these communities originate from inside ISS. Current life support systems do not include any components for reducing microbial leakage. Gases are vented from inside ISS without filtration and there are currently no protocols in place to minimize bioburden on space suit exteriors prior to use. It is important to quantify the bioburden on current vehicles so that achievable limits can be set for crewed missions to astrobiologically relevant locations like Mars. Figure 1: The sampling kit contains eight swab canisters in total (six on the top and two on the bottom). A resuable end effector (1) is used to remove and reinstall the swabs. The kit also contains a handrail (2), tether loop (3), and, bayonet probes(4) to allow easy manipulation during EVA. Methods: We have designed a kit to carry 8 commercially available foam swabs into and out of vacuum without compromising the swabs’ sterility. The specially designed swab canisters contain a 0.2 µm Teflon filter that allows the canister to accommodate pressure changes without introducing unwanted contaminants. The kit meets existing EVA (Extravehicular Activity) safety requirements and has been used by human test subjects in the neutral buoyance lab and at vacuum in test chambers at the Johnson Space Center. In the early part of 2024, astronauts will use this sampling kit to swab six surfaces on the exterior of ISS. We will collect samples from: the airlock vestibule, the interior surface of the airlock thermal cover, an exterior handrail, a vent connected to the CO2 removal system, and a vent connected to the payload vacuum system inside ISS. Approximately 300 cm2 will be swabbed at each location. A seventh swab will be exposed to the vacuum of space without touching any surfaces as a blank. The eighth swab will remain sealed as a process control. After the EVA the swab kit will be frozen at -80°C and returned to earth at the earliest possible opportunity. The samples will remain frozen until they are thawed for next generation DNA sequencing on earth. We will use amplicon sequencing to identify any bacteria, archaea or fungi present in the samples. If there is enough DNA present, we will use shotgun metagenomic sequencing to further characterize the microbial ecology outside ISS. Preliminary Results: Results from ground-based testing demonstrate that the swab kit is capable of cycling in and out of vacuum without contaminating the swabs. Test subjects, wearing flight-like EVA gloves could remove swabs from the canister and sample discrete locations without inadvertently touching any other surfaces. Several types of bacteria and fungi were collected during these ground tests and survived up to 6 hours at vacuum. This includes non-spore forming bacterial like Staphyloccus capitis that are not traditionally considered extremophiles. Shotgun metagenomic sequencing of the ground-test samples revealed bacteria associated with human skin and airways on the exterior of space suits used during these tests 2 In addition to these results we will present preliminary results from our space-flight samples. We will also present lessons learned from attempting to collect microbiological samples during an EVA and describe how our results will affect planetary protection requirements for future crewed missions.

Aaron B. Regberg↗

DOE OSTI2020

TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure

Graph analytics has emerged as an important tool in the analysis of large scale data from diverse application domains such as social networks, cyber security and bioinformatics. Counting the number of triangles in a graph is a fundamental kernel with several applications such as detecting the community structure of a graph or in identifying important vertices in a graph. The ubiquity of massive datasets is driving the need to scale graph analytics on parallel systems. However, numerous challenges exist in efficiently parallelizing graph algorithms, especially on distributed-memory systems. Irregular memory accesses and communication patterns, low computation to communication ratios, and the need for frequent synchronization are some of the leading challenges. In this paper, we present TriC, our distributed-memory implementation of triangle counting in graphs using the Message Passing Interface (MPI), as a submission to the 2020 GraphChallenge competition. Using a set of synthetic and real-world inputs from the challenge, we demonstrate a speedup of up to 90x relative to previous work on 32 processor-cores of a NERSC Cori node. We also provide details from distributed runs with up to8192 processes along with strong scaling results. The observations presented in this work provide an understanding of the system-level bottlenecks at scale that specifically impact sparse-irregular workloads and will therefore benefit other efforts to parallelize graph algorithms.

Halappanavar, Mahantesh↗

DOE OSTI2019

Functional Gene Array-Based Ultrasensitive and Quantitative Detection of Microbial Populations in Complex Communities

ABSTRACT While functional gene arrays (FGAs) have greatly expanded our understanding of complex microbial systems, specificity, sensitivity, and quantitation challenges remain. We developed a new generation of FGA, GeoChip 5.0, using the Agilent platform. Two formats were created, a smaller format (GeoChip 5.0S), primarily covering carbon-, nitrogen-, sulfur-, and phosphorus-cycling genes and others providing ecological services, and a larger format (GeoChip 5.0M) containing the functional categories involved in biogeochemical cycling of C, N, S, and P and various metals, stress response, microbial defense, electron transport, plant growth promotion, virulence, gyrB , and fungus-, protozoan-, and virus-specific genes. GeoChip 5.0M contains 161,961 oligonucleotide probes covering >365,000 genes of 1,447 gene families from broad, functionally divergent taxonomic groups, including bacteria (2,721 genera), archaea (101 genera), fungi (297 genera), protists (219 genera), and viruses (167 genera), mainly phages. Computational and experimental evaluation indicated that designed probes were highly specific and could detect as little as 0.05 ng of pure culture DNAs within a background of 1 μg community DNA (equivalent to 0.005% of the population). Additionally, strong quantitative linear relationships were observed between signal intensity and amount of pure genomic (∼99% of probes detected; r > 0.9) or soil (∼97%; r > 0.9) DNAs. Application of the GeoChip to a contaminated groundwater microbial community indicated that environmental contaminants (primarily heavy metals) had significant impacts on the biodiversity of the communities. This is the most comprehensive FGA to date, capable of directly linking microbial genes/populations to ecosystem functions. IMPORTANCE The rapid development of metagenomic technologies, including microarrays, over the past decade has greatly expanded our understanding of complex microbial systems. However, because of the ever-expanding number of novel microbial sequences discovered each year, developing a microarray that is representative of real microbial communities, is specific and sensitive, and provides quantitative information remains a challenge. The newly developed GeoChip 5.0 is the most comprehensive microarray available to date for examining the functional capabilities of microbial communities important to biogeochemistry, ecology, environmental sciences, and human health. The GeoChip 5 is highly specific, sensitive, and quantitative based on both computational and experimental assays. Use of the array on a contaminated groundwater sample provided novel insights on the impacts of environmental contaminants on groundwater microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Leveraging Community and Author Context to Explain the Performance and Bias of Text-Based Deception Detection Models

Deceptive news posts shared in online communities can be detected with NLP models, and much recent research has focused on the development of such models. In this work, we use characteristics of online communities and authors --- the context of how and where content is posted --- to explain the performance of a neural network deception detection model and identify sub-populations who are disproportionately affected by model accuracy or failure. We examine who is posting the content, and where the content is posted to. We find that while author characteristics are better predictors of deceptive content than community characteristics, both characteristics are strongly correlated with model performance. Traditional performance metrics such as F1 score may fail to capture poor model performance on isolated sub-populations such as specific authors, and as such, more nuanced evaluation of deception detection models is critical.

machine learning (ML), machine learning explanatio↗

NASA NTRS2001

Impact of dilution on microbial community structure and functional potential: comparison of numerical simulations and batch culture experiments

A series of microcosm experiments was performed using serial dilutions of a sewage microbial community to inoculate a set of batch cultures in sterile sewage. After inoculation, the dilution-defined communities were allowed to regrow for several days and a number of community attributes were measured in the regrown assemblages. Based upon a set of numerical simulations, community structure was expected to differ along the dilution gradient; the greatest differences in structure were anticipated between the undiluted-low-dilution communities and the communities regrown from the very dilute (more than 10(-4)) inocula. Furthermore, some differences were expected among the lower-dilution treatments (e.g., between undiluted and 10(-1)) depending upon the evenness of the original community. In general, each of the procedures used to examine the experimental community structures separated the communities into at least two, often three, distinct groups. The groupings were consistent with the simulated dilution of a mixture of organisms with a very uneven distribution. Significant differences in community structure were detected with genetic (amplified fragment length polymorphism and terminal restriction fragment length polymorphism), physiological (community level physiological profiling), and culture-based (colony morphology on R2A agar) measurements. Along with differences in community structure, differences in community size (acridine orange direct counting), composition (ratio of sewage medium counts to R2A counts, monitoring of each colony morphology across the treatments), and metabolic redundancy (i.e., generalist versus specialist) were also observed, suggesting that the differences in structure and diversity of communities maintained in the same environment can be manifested as differences in community organization and function.

Non-NASA Center↗

DOE OSTI2017

BNLs Synchrotron-radiation Research Hub for Characterizing Detection Materials and Devices for the NA-22 Community

The goal of this project is to obtain and characterize scintillators, emerging- and commercial-compoundsemiconductor radiation- detection materials and devices provided by vendors and research organizations. The focus of our proposed research is to clarify the role of the deleterious defects and impurities responsible for the detectors' non-uniformity in scintillating crystals, commercial semiconductor radiation-detector materials, and in emerging R&D ones. Some benefits of this project addresses the need for fabricating high-performance scintillators and compound-semiconductor radiation-detectors with the proven potential for large-scale manufacturing. The findings help researchers to resolve the problems of non-uniformities in scintillating crystals, commercial semiconductor radiation-detector materials, and in emerging R&D ones.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Specialized protist communities on mycorrhizal fungal hyphae

Abstract Arbuscular mycorrhizal (AM) fungi not only play a crucial role in acquiring nutrients for plants but also serve as a habitat for soil microbes. Recent studies observed that AM fungal hyphae are colonized by specific bacterial communities. However, so far it has not been explored whether fungal hyphae and mycorrhizal networks also harbor specific communities of protists, a key group of microbes in the soil microbiome. Here, we characterized protist communities in soil in a compartment with plant roots and on hyphae collected from hyphal compartments without plant roots. We detected specific protist communities on fungal hyphae. Fourteen protistan amplicon sequences variants (ASVs) were significantly associated with fungal hyphae, half of which belonged to the Cercozoa group. This research, for the first-time detected specific protist ASVs directly associated with abundant AM fungus hyphae, highlighting the complexity of the hyphal food web.

Mycology↗

DOE OSTI2021

Viral community analysis in a marine oxygen minimum zone indicates increased potential for viral manipulation of microbial physiological state

Microbial communities in oxygen minimum zones (OMZs) are known to have significant impacts on global biogeochemical cycles, but viral influence on microbial processes in these regions are much less studied. Here we provide baseline ecological patterns using microscopy and viral metagenomics from the Eastern Tropical North Pacific (ETNP) OMZ region that enhance our understanding of viruses in these climate-critical systems. While extracellular viral abundance decreased below the oxycline, viral diversity and lytic infection frequency remained high within the OMZ, demonstrating that viral influences on microbial communities were still substantial without the detectable presence of oxygen. Viral community composition was strongly related to oxygen concentration, with viral populations in low-oxygen portions of the water column being distinct from their surface layer counterparts. However, this divergence was not accompanied by the expected differences in viral-encoded auxiliary metabolic genes (AMGs) relating to nitrogen and sulfur metabolisms that are known to be performed by microbial communities in these low-oxygen and anoxic regions. Instead, several abundant AMGs were identified in the oxycline and OMZ that may modulate host responses to low-oxygen stress. We hypothesize that this is due to selection for viral-encoded genes that influence host survivability rather than modulating host metabolic reactions within the ETNP OMZ. Together, this study shows that viruses are not only diverse throughout the water column in the ETNP, including the OMZ, but their infection of microorganisms has the potential to alter host physiological state within these biogeochemically important regions of the ocean.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2011

Probability of Detection (POD) Demonstration Transferability

NASA Special Level POD demonstration tests are typically performed on flat plates of a single material containing fatigue cracks with aspect rations between 0.3 and 0.5. Subsequent fracture mechanics analyses consider aspect ratios that range from 0.1 to 0.5. There is debate within the NDE community about the detectability of shallow cracks associated with NASA Special Level penetrant inspections that are routinely performed by propellant tank manufactures. The objective of the task is to investigate effect of crack aspect ratio on POD crack sizes for the penetrant inspection technique.

Parker, Bradford H.↗

DOE OSTI2021

The value of human data annotation for machine learning based anomaly detection in environmental systems

Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, which require a labelled dataset for their calibration, or unsupervised models, which do not require labels. While academic research has produced a vast array of tools and machine learning models for automated anomaly detection, the research community focused on environmental systems still lacks a comparative analysis that is simultaneously comprehensive, objective, and systematic. This knowledge gap is addressed for the first time in this study, where 15 different supervised and unsupervised anomaly detection models are evaluated on 5 different environmental datasets from engineered and natural aquatic systems. To this end, anomaly detection performance, labelling efforts, as well as the impact of model and algorithm tuning are taken into account. As a result, our analysis reveals the relative strengths and weaknesses of the different approaches in an objective manner without bias for any particular paradigm in machine learning. Most importantly, our results show that expert-based data annotation is extremely valuable for anomaly detection based on machine learning.

54 ENVIRONMENTAL SCIENCES↗