Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “community detection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Spatial turnover of soil viral populations and genotypes overlain by cohesive responses to moisture in grasslands

Viruses shape microbial communities, food web dynamics, and carbon and nutrient cycling in diverse ecosystems. However, little is known about the patterns and drivers of viral community composition, particularly in soil, precluding a predictive understanding of viral impacts on terrestrial habitats. To investigate soil viral community assembly processes, here we analyzed 43 soil viromes from a rainfall manipulation experiment in a Mediterranean grassland in California. We identified 5,315 viral populations (viral operational taxonomic units [vOTUs] with a representative sequence ≥10 kbp) and found that viral community composition exhibited a highly significant distance–decay relationship within the 200-m 2 field site. This pattern was recapitulated by the intrapopulation microheterogeneity trends of prevalent vOTUs (detected in ≥90% of the viromes), which tended to exhibit negative correlations between spatial distance and the genomic similarity of their predominant allelic variants. Although significant spatial structuring was also observed in the bacterial and archaeal communities, the signal was dampened relative to the viromes, suggesting differences in local assembly drivers for viruses and prokaryotes and/or differences in the temporal scales captured by viromes and total DNA. Despite the overwhelming spatial signal, evidence for environmental filtering was revealed in a protein-sharing network analysis, wherein a group of related vOTUs predicted to infect actinobacteria was shown to be significantly enriched in low-moisture samples distributed throughout the field. Overall, our results indicate a highly diverse, dynamic, active, and spatially structured soil virosphere capable of rapid responses to changing environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Resource availability governs polyhydroxyalkanoate (PHA) accumulation and diversity of methanotrophic enrichments from wetlands

Aquatic environments account for half of global CH 4 emissions, with freshwater wetlands being the most significant contributors. These CH 4 fluxes can be partially offset by aerobic CH 4 oxidation driven by methanotrophs. Additionally, some methanotrophs can convert CH 4 into polyhydroxyalkanoate (PHA), an energy storage molecule as well as a promising bioplastic polymer. In this study, we investigate how PHA-accumulating methanotrophic communities enriched from wetlands were shaped by varying resource availability (i.e., C and N concentrations) at a fixed C/N ratio. Cell yields, PHA accumulation, and community composition were evaluated in high (20% CH 4 and 10 mM NH 4 + ) and low resource (0.2% CH 4 and 0.1 mM NH 4 + ) conditions simulating engineered and environmental settings, respectively. High resource availability decreased C-based cell yields, while N-based cell yields remained stable, suggesting nutrient exchange patterns differed between methanotrophic communities at different resource concentrations. PHA accumulation was only observed in high resource enrichments, producing approximately 12.6% ± 2.4% (m/m) PHA, while PHA in low resource enrichments remained below detection. High resource enrichments were dominated by Methylocystis methanotrophs, while low resource enrichments remained significantly more diverse and contained only a minor population of methanotrophs. This study demonstrates that resource concentration shapes PHA-accumulating methanotrophic communities. Together, this provides useful information to leverage such communities in engineering settings as well as to begin understanding their role in the environment.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2025

Laminae as Structural Biosignatures in NASA’s Life Detection Knowledge Base

Laminae are millimeter-scale features in rocks created by physiochemical processes that can be influenced by the presence and activities of communities of organisms that occur as biofilms and microbial mats. The structure and composition of laminae reflect the processes involved in their formation and can be preserved in the rock record over geologic time, however diagenetic and metamorphic alteration can lead to the loss of primary information and confusion over the interpretation of their origins. As potential records of ancient life, laminae can preserve evidence of microbial activity over billions of years of Earth’s history. On planetary bodies beyond Earth, laminae in sedimentary rocks are the most common sedimentary structure and represent significant features of interest that can record habitable conditions (e.g., the presence of liquid water) at the time of their formation. Here we review the significance of laminae as targets for astrobiological exploration. We discuss common mechanisms by which laminae form in natural environments on Earth, present arguments and evidence for laminae as biosignatures, and describe how such information is incorporated into the NASA Life Detection Knowledge Base.

Astrobiology↗
DOE OSTI2023

Effects of error, chimera, bias, and GC content on the accuracy of amplicon sequencing

ABSTRACT Targeted amplicon sequencing is widely used in microbial ecology studies. However, sequencing artifacts and amplification biases are of great concern. To identify sources of these artifacts, a systematic analysis was performed using mock communities comprised of 16S rRNA genes from 33 bacterial strains. Our results indicated that while sequencing errors were generally isolated to low-abundance operational taxonomic units, chimeric sequences were a major source of artifacts. Singleton and doubleton sequences were primarily chimeras. Formation of chimeric sequences was significantly correlated with the GC content of the targeted sequences. Low-GC-content mock community members exhibited lower rates of chimeric sequence formation. GC content also had a large impact on sequence recovery. The quantitative capacity was notably limited, with substantial recovery variations and weak correlation between anticipated and observed strain abundances. The mock community strains with higher GC content had higher recovery rates than strains with lower GC content. Amplification bias was also observed due to the differences in primer affinity. A two-step PCR strategy reduced the number of chimeric sequences by half. In addition, comparative analyses based on the mock communities showed that several widely used sequence processing pipelines/methods, including DADA2, Deblur, UCLUST, UNOISE, and UPARSE, had different advantages and disadvantages in artifact removal and rare species detection. These results are important for improving sequencing quality and reliability and developing new algorithms to process targeted amplicon sequences. IMPORTANCE Amplicon sequencing of targeted genes is the predominant approach to estimate the membership and structure of microbial communities. However, accurate reconstruction of community composition is difficult due to sequencing errors, and other methodological biases and effective approaches to overcome these challenges are essential. Using a mock community of 33 phylogenetically diverse strains, this study evaluated the effect of GC content on sequencing results and tested different approaches to improve overall sequencing accuracy while characterizing the pros and cons of popular amplicon sequence data processing approaches. The sequencing results from this study can serve as a benchmarking data set for future algorithmic improvements. Furthermore, the new insights on sequencing error, chimera formation, and GC bias from this study will help enhance the quality of amplicon sequencing studies and support the development of new data analysis approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Characterization of SimulCam, a standoff Raman system for scientific support of SuperCam operations on Mars

During the development activities of SuperCam Calibration Target, target intended for one of the two first Raman instruments to be deployed on another planetary body, our group developed a laboratory instrument that could simulate to some extent the Raman capabilities of one of such instruments and could provide data with similar quality. The use of this kind of laboratory instruments has demonstrated its utility in the evaluation of potential calibration targets or anticipating the science outcome that an instrument could provide. The present work describes our laboratory setup to support SuperCam, evaluating similarities between both instruments, despite of differences in the hardware. Evaluation of data gathered by SuperCam on Mars and the availability of one replica of SuperCam’s Calibration Target allowed the comparison on the same set of targets, demonstrating how similar Signal-to-Noise Ratio (SNR) could be achieved from both instruments. The higher energy per pulse on SimulCam is compensated by a greater analytical footprint and the use of smaller collection optics. The results show how spectra obtained at representative distances of SuperCam are comparable. Operational principles are also comparable in terms of time resolution, and close in terms of spectral resolution. This similarity has allowed different science support works using SimulCam data, as well as the support to Mars detections using our setup. We provide examples of this support that will be shared with the community in different papers, as well as examples of possible operations activities that could benefit from experiments performed with SimulCam. We show how this setup can complement the two laboratory replicas in Los Alamos and Toulouse in providing support data to different experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Feasibility of Metal Oxide Glasses and Polymer Membranes as Sorbents for Gaseous Oxidized Mercury

Mass spectrometry methods are currently under development by the atmospheric mercury (Hg) research community to elucidate the identity of atmospheric oxidized mercury (Hg II ) compounds. Due to high instrument detection limits, materials that can quantitatively preconcentrate atmospheric Hg II without facilitating compound-altering chemical reactions are needed to support these methods. Cation exchange membranes (CEM) and nylon membranes are currently used to preconcentrate ambient Hg II for concentration measurements and Hg II compound estimation, respectively. However, CEM and nylon membranes are poor candidates for observations by mass spectrometry methods due to release of interfering compounds upon heating; glasses do not have this problem. Here, three metal oxide glasses were explored as potential alternatives for Hg II preconcentration for future use with mass spectrometry methods: calcium phosphate (CaP), iron phosphate (FeP), and calcium aluminate (CaAl). The glasses demonstrated quantitative selective capture of HgBr 2 without capture of Hg 0 . Under ambient conditions, the CaP, FeP, and CaAl sorbed 36.4 ± 12.6% of the total HgII as the CEM. However, when Hg concentrations were normalized to surface area, CaP, FeP, and CaAl sorbed more HgBr 2 in the laboratory and ambient HgII compared to CEM. The CEM and CaP retained similar concentrations of HgBr 2 when preloaded samples were deployed in the field. Additionally, a permeation tube-based calibrator was used to load sorbents with HgBr 2 for investigation of HgII retention on CEM and thermal desorption profile changes on nylon membranes during active sampling. Nylon membranes were purchased from three vendors and used to compare HgBr 2 retention; a different HgBr 2 thermal desorption profile was achieved for each vendor’s nylon membrane.

Amides↗
DOE OSTI2024

The S-PLUS Fornax Project (S+FP): A first 12-band glimpse of the Fornax galaxy cluster

ABSTRACT The Fornax galaxy cluster is the richest nearby (D ∼ 20 Mpc) galaxy association in the southern sky. As such, it provides a wealth of opportunities to elucidate on the processes where environment holds a key role in transforming galaxies. Although it has been the focus of many studies, Fornax has never been explored with contiguous homogeneous wide-field imaging in 12 photometric narrow and broad bands like those provided by the Southern Photometric Local Universe Survey (S-PLUS). In this paper, we present the S-PLUS Fornax Project (S+FP) that aims to comprehensively analyse the galaxy content of the Fornax cluster using S-PLUS. Our data set consists of 106 S-PLUS wide-field frames (FoV∼1.4 × 1.4 deg2) observed in five Sloan Digital Sky Survey-like ugriz broad bands and seven narrow bands covering specific spectroscopic features like [O ii], Ca ii H+K, Hδ, G band, Mg b triplet, Hα, and the Ca ii triplet. Based on S-PLUS specific automated photometry, aimed at correctly detecting Fornax galaxies and globular clusters in S-PLUS images, our data set provides the community with catalogues containing homogeneous 12-band photometry for ∼3 × 106 resolved and unresolved objects within a region extending over ∼208 deg2 (∼5 Rvir in RA) around Fornax’ central galaxy, NGC 1399. We further explore the eagle and IllustrisTNG cosmological simulations to identify 45 Fornax-like clusters and generate mock images on all 12 S-PLUS bands of these structures down to galaxies with M⋆ ≥ 108 M⊙. The S+FP data set we put forward in this first paper of a series will enable a variety of studies some of which are briefly presented.

Astronomy & Astrophysics↗
DOE OSTI2025

Aerosol biome of a cafeteria and medical facility in Los Alamos, New Mexico, USA

Aerosol sampling with next-generation sequencing was used to characterize microbial communities in a cafeteria and medical facility waiting room in Los Alamos, New Mexico, USA. We detected sequences from human, bacteria, archaea, fungi, other eukaryotes, and viruses, providing insights into the diversity of the aerosol microbiome.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Terabase-Scale Coassembly of a Tropical Soil Microbiome

Petabases of reads are being produced by environmental metagenome sequencing. An essential step in analyzing these data is metagenome assembly, the computational reconstruction of genome sequences from microbial communities. “Coassembly” of metagenomic sequence data, in which multiple samples are assembled together, enables more complete detection of microbial genomes in an environment than “multiassembly,” in which samples are assembled individually.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

D2U: Data Driven User Emulation for the Enhancement of Cyber Testing, Training, and Data Set Generation

Whether testing intrusion detection systems, conducting training exercises, or creating data sets to be used by the broader cybersecurity community, realistic user behavior is a critical component of a cyber range. Existing methods either rely on network level data or replay recorded user actions to approximate real users in a network. Our work is the first to produce generative models trained on actual user data (sequences of application usage) collected on endpoints. Once trained to the user's behavioral data, these models can generate novel sequences of actions %that appear to come from the same distribution as the training data. These sequences of actions are then fed to our custom software via configuration files, which replicate those behaviors on end devices. Notably, our models are platform agnostic and could generate behavior data for any emulation software package. In this paper we present our model generation process, software architecture, and an initial evaluation of the fidelity of our models. Our software is currently deployed in a cyber range to help evaluate the efficacy of defensive cyber technologies. We suggest additional ways that the cyber community as a whole can benefit from more realistic user behavior emulation. The data used to train our model, as well as sample configuration files produced by the model, are available at [redacted].

Oesch, T↗
DOE OSTI2025

Radio Afterglow Detection and AI-driven Response (RADAR): A Federated Framework for Gravitational-wave Event Follow-up

The landmark detection of both gravitational waves (GWs) and electromagnetic (EM) radiation from the binary neutron star merger GW170817 has spurred efforts to streamline the follow-up of GW alerts in current and future observing runs of ground-based GW detectors. Within this context, the radio band of the EM spectrum presents unique challenges. Sensitive radio facilities capable of detecting the faint radio afterglow seen in GW170817, and with sufficient angular resolution, have small fields of view compared to typical GW localization areas. Additionally, theoretical models predict that the radio emission from binary neutron star mergers can evolve over weeks to years, necessitating long-term monitoring to probe the physics of the various postmerger ejecta components. These constraints, combined with limited radio observing resources, make the development of more coordinated follow-up strategies essential—especially as the next generation of GW detectors promises a dramatic increase in detection rates. Here, we present RADAR, a framework designed to address these challenges by promoting community-driven information sharing, federated data analysis, and system resilience, while integrating AI methods for both GW signal identification and radio data aggregation. We show that it is possible to preserve data rights while sharing models that can help design and/or update follow-up strategies. We demonstrate our approach through a case study of GW170817, and discuss future directions for refinement and broader application.

Gravitational waves↗
NASA NTRS2016

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

anomaly detection↗
NASA NTRS2018

Flash Optical Energy from the Geostationary Lightning Mapper

The Geostationary Operational Environmental Satellite -16 (GOES-16) Geostationary Lightning Mapper (GLM) is evaluated for many months during the Post Launch Product Test (PLPT) phase in order to ensure that optimal products are available for both the operational forecasting and broader scientific research communities. The emphasis of the PLPT phase is to validate the GLM performance (i.e., lightning flash detection efficiency, geolocation and time-stamp accuracy) using an extensive network of independent ground-based, in-situ, and space-based reference lightning detection systems. However, another essential aspect of the PLPT phase is to obtain benchmarks of the GLM lightning optical amplitude, so that any long-term degradation in the nadir-staring GLM camera system can be realized and quantitatively assessed. This is accomplished in a straight-forward manner by collecting a very large sample of lightning flashes across many geographical regions in the GLM field-of-view so that statistically meaningful benchmarks of lightning optical amplitude (i.e., optical energy in units of femto-joules per flash) are obtained. The benchmarking is particularly important to follow-on studies that will attempt to incorporate the flash optical energy product into new derived products (e.g., energy-weighted lightning "jump" warning algorithms, and lightning nitrogen oxides production estimates).

Lightning↗
NASA NTRSDate not supplied

Why Near Real-time/Low Latency is Important to Monitor the Changing World

An essential factor for remote sensing data products in impacting decision making is latency, or the time between earth observation and data are available to users. In many applications areas, latency plays an important or even decisive role where low latency earth observations help people to make timely, data-based decisions. Within the open and free NASA resources, NASA’s Land, Atmosphere Near real-time Capability for Earth Observing System (EOS) (LANCE) supports users interested in monitoring a wide variety of natural and man-made phenomena using near real-time (NRT) data products that are made available much quicker than routine processing allows. The combination of all available LANCE satellite products provides global coverage at multiple times per day, which makes it possible to meet user needs in various areas of applications including water resources, agriculture, air quality, wildland fire and many other disasters monitoring and management. As one of the prime users of LANCE, NASA’s Earth Science Applied Sciences Program promotes the use of LANCE data products to demonstrate applications in decision making and facilitates the end-user feedback to the science team to improve data products. One of the most critical applications that we expect data to be processed as close to the user as possible is wildland file response and management. User feedback indicates that LANCE NRT fire data products within 3 hours latency would meet the needs of the wildland fire community. Other examples of earth science application areas for which low latency is particularly important include detecting volcanic eruptions, early warning of disasters, tracking extreme weather events, and monitoring air quality.

Tian Yao↗
NASA NTRS2024

ENLIGHTEN: Electrical Network Line Inspection Guided by High-Speed Technology & Electromagnetic Navigation

Natural disasters are a major cause of power outages, primarily due to their damage to power line infrastructure. As a result, the current state of power maintenance, with a heavy reliance on manual labor, is in trouble. Its lack of speed and autonomy must be addressed to ensure power security for households and institutions worldwide. This innovative approach explores how High-Speed Unmanned Aerial Vehicle (HSUAV) technology can inspect power line infrastructure rapidly in response to natural disaster scenarios. The HSUAV technology will be accompanied by enhanced sensory equipment including light detection and ranging (LiDAR), thermal imaging, and electromagnetic field (EMF) navigation. It would also be supplemented by innovative forms of machine learning models and recharging systems to efficiently detect anomalies in power line infrastructure. The proposed system, ENLIGHTEN, can help restore power in affected communities after a devastating natural disaster, greatly improving relief efforts. In the future, ENLIGHTEN can be expanded beyond the United States and shared worldwide, effectively mitigating the consequences on a larger scale.

UAV systems, Power line management, Natural disast↗
DOE OSTI2022

Dryocosmus kuriphilus Yasumatsu (Hymenoptera: Cynipidae) in Minho (Northern Portugal): Bioecology, Native Parasitoid Communities and Biological Control with Torymus sinensis Kamijo (Hymenoptera: Torymidae)

The Asian chestnut gall wasp Dryocosmus kuriphilus Yasumatsu, native to China, was first detected in Europe in Italy in 2002. In Portugal it was declared in 2014, and it has since affected the Portuguese chestnut production. The introduction of its natural parasitoid Torymus sinensis Kamijo started through inoculative releases according to the National Action Plan for the Control of Dryocosmus kuriphilus, established by the Direção Geral de Alimentação e Veterinária (DGAV), in 2015. This research was carried out during 2018 and 2019, in five chestnut orchards in the Minho region (Northern Portugal). Between January and March 2018, at each location, three monthly harvests of 100 buds were carried out to determine the infestation level. Between April and June 2018, 240 galls were harvested every two weeks, with the purpose of studying the bioecology of D. kuriphilus. In each sampling site, 160 galls were placed in emergence boxes to follow adults of the D. kuriphilus population, and 80 galls were dissected with a binocular magnifying glass, to count and record the evolution of the larval stages of D. kuriphilus and of the parasitoids. The identification of T. sinensis and native parasitoids was carried out. The parasitism rates and Simpson diversity indices were determined. The percentage of buds infested by D. kuriphilus was high in all studied places, varying between 67% and 80%, regardless of the number of T. sinensis releases made and of the chestnut cultivars present in each orchard. The highest rate of parasitism by T. sinensis was 0.5044% and it was recorded in an orchard where there were two releases of T. sinensis in 2016 and 2017 (Arcos de Valdevez—Rio Cabrão—P1). Considering that the exotic parasitoid has already been released in the region since 2016, its establishment in all the chestnut orchards studied was confirmed, although with very low parasitism rates. The natural parasitism associated with the native parasitoid species of D. kuriphilus was confirmed in this work, recording values between 34% and 51% of the parasitized chestnut galls, with 11 species of native parasitoids having been identified: Eupelmus azureos, Eupelmus uruzonus, Eurytoma brunnivientris, Eurytoma pistaciae, Megastigmus dorsalis, Mesopolobus sp., Ormyrus pomaceus, Sycophila biguttata, Sycophila iracemae, Sycophila variegatta and Torymus flavipes.

Amorim, Amaro↗
NASA NTRS2017

PandExo: A Community Tool for Transiting Exoplanet Science with JWST and HST

As we approach the James Webb Space Telescope (JWST) era, several studies have emerged that aim to (1) characterize how the instruments will perform and (2) determine what atmospheric spectral features could theoretically be detected using transmission and emission spectroscopy. To some degree, all these studies have relied on modeling of JWST's theoretical instrument noise. With under two years left until launch, it is imperative that the exoplanet community begins to digest and integrate these studies into their observing plans, as well as think about how to leverage the Hubble Space Telescope (HST) to optimize JWST observations. To encourage this and to allow all members of the community access to JWST & HST noise simulations, we present here an open-source Python package and online interface for creating observation simulations of all observatory-supported timeseries spectroscopy modes. This noise simulator, called PandExo, relies on some aspects of Space Telescope Science Institute's Exposure Time Calculator, Pandeia. We describe PandExo and the formalism for computing noise sources for JWST. Then we benchmark PandExoʼs performance against each instrument team's independently written noise simulator for JWST, and previous observations for HST. We find that PandExo is within 10% agreement for HST/WFC3 and for all JWST instruments.

Batalha, Natasha E.↗
DOE OSTI2021

Viromes outperform total metagenomes in revealing the spatiotemporal patterns of agricultural soil viral communities

Abstract Viruses are abundant yet understudied members of soil environments that influence terrestrial biogeochemical cycles. Here, we characterized the dsDNA viral diversity in biochar-amended agricultural soils at the preplanting and harvesting stages of a tomato growing season via paired total metagenomes and viral size fraction metagenomes (viromes). Size fractionation prior to DNA extraction reduced sources of nonviral DNA in viromes, enabling the recovery of a vaster richness of viral populations (vOTUs), greater viral taxonomic diversity, broader range of predicted hosts, and better access to the rare virosphere, relative to total metagenomes, which tended to recover only the most persistent and abundant vOTUs. Of 2961 detected vOTUs, 2684 were recovered exclusively from viromes, while only three were recovered from total metagenomes alone. Both viral and microbial communities differed significantly over time, suggesting a coupled response to rhizosphere recruitment processes and/or nitrogen amendments. Viral communities alone were also structured along an 18 m spatial gradient. Overall, our results highlight the utility of soil viromics and reveal similarities between viral and microbial community dynamics throughout the tomato growing season yet suggest a partial decoupling of the processes driving their spatial distributions, potentially due to differences in dispersal, decay rates, and/or sensitivities to soil heterogeneity.

59 BASIC BIOLOGICAL SCIENCES↗