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

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Distributed Direction-Optimizing Label Propagation for Community Detection

Designing a scalable algorithm for community detec-tion is challenging due to the tradeoff between the performance and the quality of the result. We propose a new distributed algorithm for community detection —Direction-Optimizing Label Propagation Algorithm, based on a novel Label Propagation Algorithm in community detection. The algorithm is inspired by the direction optimization technique for graph traversal algorithms and relies on the use of frontiers and alternates between label push and label pull operations. This organization creates ?exibility and affords opportunities for balancing the performance and the quality of the solution. We implement our algorithm in distributed memory with an active-message based asynchronous many-task runtime, AM++. We experiment with two seeding strategies for initial seeding stage, namely, random seeding and degree seeding. With the Graph Challenge datasets, our distributed implementation, in conjunction with the runtime support, achieves very good performance and reasonable quality of solution.

Liu, Xu↗
DOE OSTI2016

Comparative Community Proteomics Demonstrates the Unexpected Importance of Actinobacterial Glycoside Hydrolase Family 12 Protein for Crystalline Cellulose Hydrolysis

Glycoside hydrolases (GHs) are key enzymes in the depolymerization of plant-derived cellulose, a process central to the global carbon cycle and the conversion of plant biomass to fuels and chemicals. A limited number of GH families hydrolyze crystalline cellulose, often by a processive mechanism along the cellulose chain. During cultivation of thermophilic cellulolytic microbial communities, substantial differences were observed in the crystalline cellulose saccharification activities of supernatants recovered from divergent lineages. Comparative community proteomics identified a set of cellulases from a population closely related to actinobacterium Thermobispora bispora that were highly abundant in the most active consortium. Among the cellulases from T. bispora , the abundance of a GH family 12 (GH12) protein correlated most closely with the changes in crystalline cellulose hydrolysis activity. This result was surprising since GH12 proteins have been predominantly characterized as enzymes active on soluble polysaccharide substrates. Heterologous expression and biochemical characterization of the suite of T. bispora hydrolytic cellulases confirmed that the GH12 protein possessed the highest activity on multiple crystalline cellulose substrates and demonstrated that it hydrolyzes cellulose chains by a predominantly random mechanism. This work suggests that the role of GH12 proteins in crystalline cellulose hydrolysis by cellulolytic microbes should be reconsidered.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Data for Immediate Impacts of Soybean Cover Crop on Bacterial Community Composition and Diversity in Soil Under Long-Term Saccharum Monoculture

Saccharum yield decline results from long-term monoculture practices. Changes in cropping management can improve soil health and productivity. Below-ground bacterial community diversity and composition across soybean (Glycine max (L.) Merr) cover crop, Saccharum monoculture (30+ year) and fallowed soil were determined. Near full length (~1,400 base pairs) of 16S rRNA gene sequences were extracted from the rhizospheres of sugarcane and soybean and fallowed soil were compared. Higher soil bacterial diversity was observed in the soybean cover crop than sugarcane monoculture across all measured indices (observed operationational taxonomic units, Chao1, Shannon, reciprocal Simpson and Jackknife). Acidocateria, Proteobacteria, Bacteroidetes and Planctomycetes were the most abundant bacterial phyla across the treatments. Indicator species analysis identified nine indicator phyla. Planctomycetes, Armatimonadetes and candidate phylum FBP were associated with soybean; Proteobacteria and Firmicutes were linked with sugarcane and Gemmatimonadetes, Nitrospirae, Rokubacteria and unclassified bacteria were associated with fallowed soil. Non-metric multidimensional scaling analysis showed distinct groupings of bacterial operational taxonomic units (97% identity) according to management system (soybean, sugarcane or fallow) indicating compositional differences among treatments. This is confirmed by the results of the multi-response permutation procedures (A = 0.541, p = 0.00045716). No correlation between soil parameters and bacterial community structure was observed according to Mantel test (r = 211865, p = 0.14). Use of soybean cover-crop fostered bacterial diversity and altered community structure. This indicates cover crops could have a restorative effect and potentially promote sustainability in long-term Saccharum production systems.

Field Data↗
DOE OSTI2014

Toward Linking Aboveground Vegetation Properties and Soil Microbial Communities Using Remote Sensing

Despite their vital role in terrestrial ecosystem function, the distributions and dynamics of soil microbial communities (SMCs) are poorly understood. Vegetation and soil properties are the primary factors that influence SMCs. This paper discusses the potential effectiveness of remote sensing science and technologies for mapping SMC biogeography by characterizing surface biophysical properties (e.g., plant traits and community composition) strongly correlated with SMCs. Using remotely sensed biophysical properties to predict SMC distributions is extremely challenging because of the intricate interactions between biotic and abiotic factors and between above- and belowground ecosystems. However, the integration of biophysical and soil remote sensing with geospatial information about the e nvironment holds great promise for mapping SMC biogeography. Additional research needs invol ve microbial taxonomic definition, soil environmental complexity, and scaling strategies. The collaborative effort of experts from diverse disciplines is essential to linking terrestrial surface biosphere observations with subsurface microbial community distributions using remote sensing.

Hamada, Yuki↗
DOE OSTI2023

Report of the 2021 U.S. Community Study on the Future of Particle Physics (Snowmass 2021)

In 2019, with the construction of the projects supported by the 2014 P5 process well underway or in an advanced stage of planning, the Division of Particle and Fields (DPF) of the American Physical Society (APS) began to prepare a new community study of U.S. high energy physics (HEP) for the decade of 2025 – 2035, and beyond. This “Snowmass 2021” HEP Community Planning Exercise began formally with a kick-off meeting at the 2020 APS April Meeting and a Community-wide Planning Meeting in October of 2020. The exercise was to conclude in July of 2021 with a workshop in Seattle hosted by the University of Washington. The COVID-19 pandemic severely disrupted these plans. Work was paused from January to September of 2021 to lighten the burden on our younger scientists. We resumed work by September of 2021 and, despite the continuing challenges of COVID-19, our community was well prepared for the Seattle meeting, which had been rescheduled for July 17–26, 2022.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Assembly and Succession of Iron Oxide Microbial Mat Communities in Acidic Geothermal Springs

Biomineralized ferric oxide microbial mats are ubiquitous features on Earth, are common in hot springs of Yellowstone National Park (YNP, WY, USA), and form due to direct interaction between microbial and physicochemical processes. The overall goal of this study was to determine the contribution of different community members to the assembly and succession of acidic high-temperature Fe(III)-oxide mat ecosystems. Spatial and temporal changes in Fe(III)-oxide accretion and the abundance of relevant community members were monitored over 70 days using sterile glass microscope slides incubated in the outflow channels of two acidic geothermal springs (pH = 3-3.5; temperature = 68-75°C) in YNP. Hydrogenobaculum spp. were the most abundant taxon identified during early successional stages (4-40 days), and have been shown to oxidize arsenite, sulfide, and hydrogen coupled to oxygen reduction. Iron-oxidizing populations of Metallosphaera yellowstonensis were detected within 4 days, and reached steady-state levels within 14-30 days, corresponding to visible Fe(III)-oxide accretion. Heterotrophic archaea colonized near 30 days, and emerged as the dominant functional guild after 70 days and in mature Fe(III)-oxide mats (1-2 cm thick). First-order rate constants of Fe(III)-oxide accretion ranged from 0.046 to 0.05 day -1 , and in situ microelectrode measurements showed that the oxidation of Fe(II) is limited by the diffusion of O2 into the Fe(III)-oxide mat. The formation of microterracettes also implicated O2 as a major variable controlling microbial growth and subsequent mat morphology. The assembly and succession of Fe(III)-oxide mat communities follows a repeatable pattern of colonization by lithoautotrophic organisms, and the subsequent growth of diverse organoheterotrophs. The unique geochemical signatures and micromorphology of extant biomineralized Fe(III)-oxide mats are also useful for understanding other Fe(II)-oxidizing systems.

58 GEOSCIENCES↗
DOE OSTI2022

Community Planning for Solar: Conducting a Community Solar Survey

This guide is designed to assist community officials, volunteers, and regional planning agency staff in conducting a survey of residents to learn about attitudes and development preferences towards solar energy within the community. The guide will provide the key steps, timelines, distribution options, ethics, and considerations that should be made in developing a survey distribution strategy. The guide also contains an overview of various question types and response categories, with considerations for the type of data that are needed for the study. The guide concludes with recommendations for managing data and databases, data visualization, and reporting results. The appendix includes samples of materials used in a solar energy survey, from invitation letters to the survey. This document is intended to provide a practical guide for implementing a survey in communities that are proactively planning for solar development. The guide offers a practical “how-to” plan for conducting a survey. It may be advantageous to consult with an expert in survey development who will be familiar with any methods and techniques described in this guide, but this is not necessary. This guide offers basic considerations and examples of questions and analyses to help a community understand preferences of the community.

14 SOLAR ENERGY↗
DOE OSTI2017

Geographical Variation in Community Divergence: Insights from Tropical Forest Monodominance by Ectomycorrhizal Trees

Convergence occurs in both species traits and community structure, but how convergence at the two scales influences each other remains unclear. To address this question, we focus on tropical forest monodominance, in which a single, often ectomycorrhizal (EM) tree species occasionally dominates forest stands within a landscape otherwise characterized by diverse communities of arbuscular mycorrhizal (AM) trees. Such monodominance is a striking potential example of community divergence resulting in alternative stable states. However, it is observed only in some tropical regions. A diverse suite of AM and EM trees locally codominate forest stands elsewhere. We develop a hypothesis to explain this geographical difference using a simulation model of plant community assembly. Simulation results suggest that in a region with a few EM species (e.g., South America), EM trees experience strong selection for convergent traits that match the abiotic conditions of the environment. Consequently, EM species successfully compete against other species to form monodominant stands via positive plant-soil feedbacks. By contrast, in a region with many EM species (e.g., Southeast Asia), species maintain divergent traits because of complex plant-soil feedbacks, with no species having traits that enable monodominance. An analysis of plant trait data from Borneo and Peruvian Amazon was inconclusive. Furthermore, this work highlights the utility of geographical comparison in understanding the relationship between trait convergence and community convergence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Microbial Community Structure and Functional Potential Along a Hypersaline Gradient

© 2018 Kimbrel, Ballor, Wu, David, Hazen, Simmons, Singer and Jansson. Salinity is one of the strongest environmental drivers of microbial evolution and community composition. Here we aimed to determine the impact of salt concentrations (2.5, 7.5, and 33.2%) on the microbial community structure of reclaimed saltern ponds near San Francisco, California, and to discover prospective enzymes with potential biotechnological applications. Community compositions were determined by 16S rRNA amplicon sequencing revealing both higher richness and evenness in the pond sediments compared to the water columns. Co-occurrence network analysis additionally uncovered the presence of microbial seed bank communities, potentially primed to respond to rapid changes in salinity. In addition, functional annotation of shotgun metagenomic DNA showed different capabilities if the microbial communities at different salinities for methanogenesis, amino acid metabolism, and carbohydrate-active enzymes. There was an overall shift with increasing salinity in the functional potential for starch degradation, and a decrease in degradation of cellulose and other oligosaccharides. Further, many carbohydrate-active enzymes identified have acidic isoelectric points that have potential biotechnological applications, including deconstruction of biofuel feedstocks under high ionic conditions. Metagenome-assembled genomes (MAGs) of individual halotolerant and halophilic microbes were binned revealing a variety of carbohydrate-degrading potential of individual pond inhabitants.

Kimbrel, Jeffrey A.↗
DOE OSTI2022

A Case Study about Energy and Cost Impacts for Different Community Scenarios Using a Community-Scale Building Energy Modeling Tool

The United States building sector consumed approximately 75% of electricity in 2019. By implementing renewable energy technologies and control strategies into buildings, future buildings will serve as energy generators as well as consumers. To accommodate this transition, communications among buildings and between buildings and the grid could provide more possibilities to optimize the energy performance of buildings. This paper develops a community-scale building energy model tool and conducts a case study adopting behind-the-meter distributed energy resources, sharing energy in different buildings, and using different electricity tariff structures. Three scenarios are studied: (1) electricity only supplied by the grid, (2) photovoltaic (PV) panels installed on and available to some but not all buildings, and (3) a connected community. To consider the impacts of locations and energy tariffs, this paper selects four cities and three electricity tariffs to evaluate the energy and cost performances of these three scenarios. The results show that the PV panels in Scenario 2 reduce 25% to 33% of the community-level electricity consumption and 20% to 30% of the community-level electricity cost compared with Scenario 1 in all studied locations and energy tariffs. By considering power management in the connected community (Scenario 3), the electricity consumption and cost can be further reduced by 6% to 7% and 5% to 11%, respectively, compared with Scenario 2.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Pathways and Insights from Community Solar: A Guide to Community Energy Storage Success

Community energy assets bring the benefits of renewables to all energy system stakeholders, not just those with sufficient capital, land ownership, and resources. As the price of energy storage continues to decline and energy equity and justice principles are incorporated into policies and planning activities, Community Energy Storage (CES) is poised to follow in the footsteps of Community Solar’s (CS) success. Though CES is in its early stages and faces many unique challenges, it is an invaluable tool on the pathway to decarbonization, with the potential to increase renewable access, energy affordability, resilience, energy independence, wealth creation, and community empowerment. This paper provides a brief review of the history of CS, comparing the market and regulatory advances of CS to the current state of CES. The lessons learned from the rise of CS are then adapted to support those working to increase CES adoption in pursuit of a more equitable and sustainable energy system for all.

community energy planning, community solar, commun↗
DOE OSTI2017

Temporal effects of disturbance on community composition in simulated stage‐structured plant communities

Abstract In an era of global environmental change, understanding how disturbance affects the dynamics of ecological communities is crucial. However, few studies have theoretically explored the potential influence of disturbance including both intensity and frequency on compositional change over time in communities with stage structure. A spatially explicit, individual‐based model was constructed incorporating the various demographic responses to disturbance of plants at two different growth stages: seedlings and adults. In the model, we assumed that individuals within each stage were demographically equivalent (neutral) but differed between stages. We simulated a common phenomenon that seedlings suffered more from disturbance such as grazing and fire than adults. We showed how stage‐structured communities of seedlings and adults responded to disturbance with various levels of disturbance frequency and intensity. In “undisturbed” simulations, the relationship between average species abundance (defined here as the total number of individuals divided by species richness) and community composition turnover (measured by the Bray–Curtis similarity index) was asymptotic. However, in strongly “disturbed” simulations with the between‐disturbance intervals greater than one, this relationship became unimodal. Stage‐dependent response to disturbance underlay the above discrepancy between undisturbed and disturbed communities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Arbuscular Mycorrhizal Tree Communities Have Greater Soil Fungal Diversity and Relative Abundances of Saprotrophs and Pathogens than Ectomycorrhizal Tree Communities

Trees associating with different mycorrhizas often differ in their effects on litter decomposition, nutrient cycling, soil organic matter (SOM) dynamics, and plant-soil interactions. For example, due to differences between arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) tree leaf and root traits, ECM-associated soil has lower rates of C and N cycling and lower N availability than AM-associated soil. These observations suggest that many groups of nonmycorrhizal fungi should be affected by the mycorrhizal associations of dominant trees through controls on nutrient availability. To test this overarching hypothesis, we explored the influence of predominant forest mycorrhizal type and mineral N availability on soil fungal communities using next-generation amplicon sequencing. Soils from four temperate hardwood forests in southern Indiana, United States, were studied; three forests formed a natural gradient of mycorrhizal dominance (100% AM tree basal area to 100% ECM basal area), while the fourth forest contained a factorial experiment testing long-term N addition in both dominant mycorrhizal types. We found that overall fungal diversity, as well as the diversity and relative abundance of plant pathogenic and saprotrophic fungi, increased with greater AM tree dominance. Additionally, tree community mycorrhizal associations explained more variation in fungal community composition than abiotic variables, including soil depth, SOM content, nitrification rate, and mineral N availability. Our findings suggest that tree mycorrhizal associations may be good predictors of the diversity, composition, and functional potential of soil fungal communities in temperate hardwood forests. These observations help explain differing biogeochemistry and community dynamics found in forest stands dominated by differing mycorrhizal types.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO)

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Greater Toledo Community Foundation Sustainable Communities Educational Initiative (Final Technical Report)

The Greater Toledo Community Foundation’s (GTCF) Sustainable Communities Educational Initiative leveraged the two recently constructed Overland Solar Arrays to launch a diverse collection of educational activities designed to promote the intersection between workforce development, renewable energy and community activism to showcase emerging avenues for greater prosperity in communities that have experienced historic disinvestment. In addition to educational programming focused on employment in the clean energy and advanced manufacturing fields, the project also activated storytelling approaches to explain sustainable energy’s role in philanthropy, grantmaking and resident-led neighborhood enhancements.

14 SOLAR ENERGY↗
DOE OSTI2018

Dynamic graphs, community detection, and Riemannian geometry

A community is a subset of a wider network where the members of that subset are more strongly connected to each other than they are to the rest of the network. In this paper, we consider the problem of identifying and tracking communities in graphs that change over time {dynamic community detection} and present a framework based on Riemannian geometry to aid in this task. Our framework currently supports several important operations such as interpolating between and averaging over graph snapshots. We compare these Riemannian methods with entry-wise linear interpolation and that the Riemannian methods are generally better suited to dynamic community detection. Next steps with the Riemannian framework include developing higher-order interpolation methods (e.g. the analogues of polynomial and spline interpolation) and a Riemannian least-squares regression method for working with noisy data.

dynamic community detection↗