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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Powering the Blue Economy: Progress Exploring Marine Renewable Energy Integration With Ocean Observations

The blue economy is a dynamic and rapidly growing movement that captures the interplay between economic, social, and ecological sustainability of the ocean and encompasses numerous maritime sectors and activities (e.g., commerce and trade; living resources; renewable energy; minerals, materials, and freshwater; and ocean health and data). The demand for ocean data to inform scientific, risk reduction, and national security needs is leading to a large increase in the number of deployed ocean observation and monitoring systems, most of which require increased power. Because ocean observation systems are often placed in remote locations, they primarily rely on energy storage (or in some cases in situ energy generation) to power instruments and equipment, which imposes limits on sampling rates, deployment times, and spatiotemporal resolution of data. The U.S. Department of Energy Water Power Technologies Office is exploring the potential for marine renewable energy (MRE) devices (largely wave and tidal energy converters) to provide power to support multiple blue economy opportunities. A portion of these opportunities focus on power at sea markets for providing power in off-grid and offshore locations to support a variety of ocean-based activities, including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae farming, and seawater mining. Initially, research has focused on better understanding how and where MRE can provide a consistent source of reliable power to extend ocean observing missions, including operation of autonomous underwater vehicles. Online surveys as well as phone and inperson interviews were conducted with experts in the field of ocean observing systems and observatories to gather end-user requirements, determine energy needs, identify opportunities for codevelopment, and pinpoint constraints for MRE to meet those needs. The surveys and interviews provided feedback on the potential for powering devices and vehicles using MRE, including identifying common themes and challenges that will inform foundational research and development steps needed to advance the integration of MRE with ocean observing systems. In most cases, additional power generation on the order of watts was identified as significantly beneficial to enhancing ocean observations capabilities.

marine renewable energy, powering the blue economy↗
DOE OSTI2026

GridPIQ Reference Data

GridPIQ uses dozens of publicly available datasets to provide context for a user's grid project, as well as defaults for users to choose from. Users can choose to import their own data to better customize their analysis or use GridPIQ-supplied defaults. This allows users to get up and running with an analysis very quickly without having to spend significant time pulling together input data. To run an electric vehicle (EV) smart charging project, a user will need to provide or select from prepopulated values for the regional load profile shape and peak load, region of interest and closest weather station, EV charging profile, number of EVs to add for the analysis, maximum EV charging power, location of chargers relative to grid infrastructure, and allowable charging times (for coordinated charging mode). The outputs of the analysis are changes in air quality, EV energy consumption, EV peak demand, and EV hourly consumption profile—before and after project implementation." For a detailed description of the tool methodology, including all the publicly available datasets used by the tool, see the [GridPIQ documentation](https://gridpiq.pnnl.gov/v2-beta/doc/).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Data and scripts from: “Denoising autoencoder for reconstructing sensor observation data and predicting evapotranspiration: noisy and missing values repair and uncertainty quantification”

This data package includes data and scripts from the manuscript “Denoising autoencoder for reconstructing sensor observation data and predicting evapotranspiration: noisy and missing values repair and uncertainty quantification”.The study addressed common challenges faced in environmental sensing and modeling, including uncertain input data, missing sensor observations, and high-dimensional datasets with interrelated but redundant variables. Point-scaled meteorological and soil sensor observations were perturbed with noises and missing values, and denoising autoencoder (DAE) neural networks were developed to reconstruct the perturbed data and further predict evapotranspiration. This study concluded that (1) the reconstruction quality of each variable depends on its cross-correlation and alignment to the underlying data structure, (2) uncertainties from the models were overall stronger than those from the data corruption, and (3) there was a tradeoff between reducing bias and reducing variance when evaluating the uncertainty of the machine learning models.This package includes:(1) Four ipython scripts (.ipynb): “DAE_train.ipynb” trains and evaluates DAE neural networks, “DAE_predict.ipynb” makes predictions from the trained DAE models, “ET_train.ipynb” trains and evaluates ET prediction neural networks, and “ET_predict.ipynb” makes predictions from trained ET models.(2) One python file (.py): “methods.py” includes all user-defined functions and python codes used in the ipython scripts.(3) A “sub_models” folder that includes five trained DAE neural networks (in pytorch format, .pt), which could be used to ingest input data before being fed to the downstream ET models in ‘ET_train.ipynb” or ‘ET_predict.ipynb’.(4) Two data files (.csv). Daily meteorological, vegetation, and soil data is in “df_data.csv”, where “df_meta.csv” contains the location and time information of “df_data.csv”. Each row (index) in “df_meta.csv” corresponds to each row in “df_data.csv”. These data files are formatted to follow the data structure requirements and be directly used in the ipython scripts, and they have been shuffled chronologically to train machine learning models. The meteorological and soil data was collected using point sensors between 2019-2023 at(4.a) Three shrub-dominated field sites in East River, Colorado (named “ph1”, “ph2” and “sg5” in “df_meta.csv”, where “ph1” and “ph2” were located at PumpHouse Hillslopes, and “sg5” was at Snodgrass Mountain meadow) and(4.b) One outdoor, mesoscale, and herbaceous-dominated experiment in Berkeley, California (named “tb” in “df_meta.csv”, short for Smartsoils Testbed at Lawrence Berkeley National Lab).- See "df_data_dd.csv" and "df_meta_dd.csv" for variable descriptions and the Methods section for additional data processing steps. See "flmd.csv" and "README.txt" for brief file descriptions.- All ipython scripts and python files are written in and require PYTHON language software.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

AmeriFlux FLUXNET-1F US-CF1 CAF-LTAR Cook East

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CF1 CAF-LTAR Cook East. This is the FLUXNET version of the carbon flux data for the site US-CF1 CAF-LTAR Cook East produced by applying the standard ONEFlux (1F) software. Site Description - CF1 has operated since May 2017 at the R.J. Cook Agronomy Farm outside of Pullman, Washington, and monitors the no-till side of a paired-catchment study that is part of the Longterm Agroecosystem Research (LTAR) site common experiment. CF1 is located in “Cook East,” a field that has been in no-till management since 1998, and represents the Alternative treatment of the LTAR common experiment. It is paired with the CF2 tower location in “Cook West,” which has been in conventional tillage since prior to 1998 and represents the Prevalent treatments of the common experiment. Cook Agronomy Farm is in the high precipitation agroecological zone of the Columbia Plateau’s dryland cropping region. Crop rotations are wheat-based and include winter wheat, spring wheat, chickpea, spring canola, and winter peas. Wheat is the principal cash crop, with other crops grown in rotation for diversity, nutrient, and pest management. Soils are predominantly silt loam texture Mollisols in the Palouse, Thatuna, Naff soil series. The CF1 tower replaced US-RC1, which operated 2012-2016 in a neighboring field that was also in no-till management since 1998. CF1 and RC1 have distinct footprints, aspects, and soil series compositions.

Phillips, Claire L.↗
DOE OSTI2025

AmeriFlux US-UiF University of Illinois Miscanthus 2

This is the AmeriFlux version of the carbon flux data for the site US-UiF University of Illinois Miscanthus 2. Site Description - Agricultural field planted with miscanthus x giganteus perennial C4 bioenergy feedstock as a control site for Us-UiB when basalt began to be applied to Us-UiB in 2017. This field is typically harvested in Febraury or March. This site is located at an experimental farm approximately 2 miles south of the University of Illinois at Urbana Champaign and is colocated with (500-1000m distance) all other Us-Ui sites.

Bernacchi, Carl J [Department of Crop Sciences, Un↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-UiF University of Illinois Miscanthus 2

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UiF University of Illinois Miscanthus 2. This is the FLUXNET version of the carbon flux data for the site US-UiF University of Illinois Miscanthus 2 produced by applying the standard ONEFlux (1F) software. Site Description - Agricultural field planted with miscanthus x giganteus perennial C4 bioenergy feedstock as a control site for Us-UiB when basalt began to be applied to Us-UiB in 2017. This field is typically harvested in Febraury or March. This site is located at an experimental farm approximately 2 miles south of the University of Illinois at Urbana Champaign and is colocated with (500-1000m distance) all other Us-Ui sites.

Bernacchi, Carl J [Department of Crop Sciences, Un↗
DOE OSTI2024

Atmospheric Radiation Measurement (ARM) Management Plan

Mission and Vision Statements for the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Mission The ARM Climate Research Facility, a DOE scientific user facility, provides the climate research community with strategically located in situ and remote-sensing observatories designed to improve the understanding and representation, in climate and earth system models, of clouds and aerosols as well as their interactions and coupling with the Earth’s surface. Vision To provide a detailed and accurate description of the Earth atmosphere in diverse climate regimes to resolve the uncertainties in climate and Earth system models toward the development of sustainable solutions for the nation's energy and environmental challenges.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Marginal Soils Index Analysis & Geospatial Data

This data package contains output files associated with Mongird et al. (in prep) organized into four dataset directories. Each dataset is described in more detail below. 1. Marginal Soils Index Analysis Description: This folder contains a csv file with land needs and availability by state, power generating technology type, and scenario in 2050 when suitable siting areas are additionally constrained to areas with increasing levels of soil marginality. Files: msi_constrained_siting_availability_2050.csv Variables: Scenario - Projected 2050 scenario name State - US state abbreviation Technology - Generating technology type solar = solar photovoltaic gas_cc_re = natural gas combined cycle (recirculating cooling) wind = onshore wind gas_cc_ccs_re = natural gas combined cycle with carbon capture sequestration (recirculating cooling) gas_cc_dry = natural gas combined cycle with (dry cooling) gas_cc_pond = natural gas combined cycle with (pond cooling) coal_conv_ccs_re = conventional coal with carbon capture sequestration (recirculating cooling) Req_Capacity_MW - The amount of rated capacity required in 2050 of the given technology type in the given state and under the given scenario from the capacity expansion plan Req_Capacity_Factor - The assumed capacity factor (fraction between 0 and 1) for the given technology type in the given state and under the given scenario by the capacity expansion plan Req_Land_km2 - The amount of land required (in km-squared) to host the required generating capacity that is capable of meeting the specified capacity factor for the given technology type in the given state and under the given scenario Req_Energy_TWh - Product of Req_Capacity_MW, Req_Capacity_Factor, and 8760/1e6 for the given technology type in the given state and under the given scenario MSI_Case - The level of MSI that siting the given technology is additionally constrained to, where >0 means siting is additionally constrained to suitable land areas that have an MSI value greater than 0 >=1 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 1 >=2 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 2 >=3 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 3 Soil Attribute Rasters Description: This folder contains geospatial raster files for individual soil parameters upscaled to the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of non-missing 30m resolution values. All raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. Files: avg_cond_raster_ .tif - Average conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm max_cond_raster_ .tif - Maximum conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm min_ph_raster_ .tif- Min pH values across all soil horizons within a depth of 40 inches. avg_ph_raster_ .tif - Average pH value across all soil horizons within a depth of 40 inches. max_ph_raster_ .tif- Max pH value across all soil horizons within a depth of 40 inches. erosion_factor_raster_ .tif - Product of k-factor and percent slope flood_freq_raster_ .tif - Number of months of the year during which the area is commonly, frequently, or very frequently flooded. max_sar_raster_ .tif - Maximum sodium adsorption ratio across all horizons within a depth of 40 inches rock_frac_raster_ .tif - Fraction of the upper 6 inches of soil composed of rock fragments larger than 3 inches. temp_regime_raster_ .tif - Soil temperature regime with the following key: 0 = pergelic 1 = gelic 2 = cryic 3 = frigid 4 = isofrigid 5 = mesic 6 = isomesic 7 = thermic 8 = isothermic 9 = hyperthermic 10 =isohyperthermic Marginal Soils Index Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index at the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of 30m resolution. Both raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. A value of 0 indicates that there were no soil attributes present that indicate marginal soil. NA values indicate that data was unavailable or bodies of water. Files: marginal_soils_index_30m_raster.tif marginal_soils_index_1km_raster.tif Marginal Soils Index Resource Potential Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index + Resource Potential (MSI+RP) score at 1km resolution for geothermal, solar, and wind technologies. Raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. NA values indicate that the location is not suitable for siting the given technology due to policy, environmental, socioeconomic, topological, and other constraints regardless of soil marginality level. Areas with values greater than or equal to zero represent the product of the normalized MSI value and the normalized resource potential value. Files: geothermal_msi_ep_score_raster.tif solar_msi_ep_score_raster.tif wind_msi_ep_score_raster.tif Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Agriculture↗
DOE OSTI2021

A field guide for aging passerine nestlings using growth data and predictive modeling

Abstract Background Accurate nestling age is valuable for studies on nesting strategies, productivity, and impacts on reproductive success. Most aging guides consist of descriptions and photographs that are time consuming to read and subjective to interpret. The Western Bluebird ( Sialia mexicana ) is a secondary cavity-nesting passerine that nests in coniferous and open deciduous forests. Nest box programs for cavity-nesting species have provided suitable nesting locations and opportunities for data collection on nestling growth and development. Methods We developed models for predicting the age of Western Bluebird nestlings from morphometric measurements using model training and validation. These were developed for mass, tarsus, and two different culmen measurements. Results Our models were accurate to within less than a day, and each model worked best for a specific age range. The mass and tarsus models can be used to estimate the ages of Western Bluebird nestlings 0–10 days old and were accurate to within 0.5 days for mass and 0.7 days for tarsus. The culmen models can be used to estimate ages of nestlings 0–15 days old and were also accurate to within less than a day. The daily mean, minimum, and maximum values of each morphometric measurement are provided and can be used in the field for accurate nestling age estimations in real time. Conclusions The model training and validation procedures used here demonstrate that this method can create aging models that are highly accurate. The methods can be applied to any passerine species provided sufficient nestling morphometric data are available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Recent streamflow trends across permafrost basins of North America: Datasets

Climate change impacts, including changing temperatures, precipitation, and vegetation, are widely anticipated to cause major shifts to the permafrost with resulting impacts to hydro-ecosystems across the high latitudes of the globe. However, it is challenging to examine streamflow shifts in these regions owing to a paucity of data, discontinuity of records, and other issues related to data consistency and accuracy. We looked at recent changes in streamflow over 1976-2021 in watersheds affected by varying degrees of permafrost coverage to characterize trends and drivers for a range of watersheds across North America. Data sets are described in detail in the paper associated with this data set, Bennett et al. 2023, Front. Water - Water and Critical Zone, DOI: 10.3389/frwa.2023.1099660.These data contain CSV files of the streamflow, climate, and land surface characteristics for several sites located across the high latitude regions of North America. Both observed and reanalysis data products are provided. These files can be opened using Excel or a text editor, or they can be read, and analyzed in software tools such as Python or R. A brief description of the files is below, and more details can be found in the Methods section.rabpro_stats_north_select_74_55m.csv - This file describes the observed gages used in the analysis.GF31_23_metadat.csv - This file describes the 23 permafrost systems. Columns are as described in rabpro_stats_north_select_74_55m.csv above, with rabpro_id, the id used for the timeseries file mapping in GF31_23_time_series.csv.GF31_23_time_series.csv - This file contains the time series data for the stations described in GF31_23_metadat.csv.GF31_random_reaches_1583.csv - This file describes the 1583 randomly selected permafrost-dominant sites for machine learning analysis.era5_GF31_monthly_vars_random_reaches_1583.csv - This file contains the monthly ERA5 land data for the 1583 randomly selected permafrost-dominant sites.observed.zip: USGS and Hydat station data for the 74 gages analyzed in this study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1975-2022.streamflow_daily_GF31_infilled_1979_2022.csv - infilled daily streamflow data (infilled using GloFAS v 3.1) for 55 gages. Units are m3/sec. 1979-2022.glofas_23.zip - Glofas v3.1 file for the 23 permafrost-dominant gages in the study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1979-2021.glofas_1583.zip - Glofas v3.1 file for the 1583 randomly selected permafrost-dominant gages in the study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1979-2021.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Computational Aspects of Single-Molecule Kinetics for Coupled Catalytic Cycles: A Spectral Analysis

Catalysis from single active sites is analyzed using methods developed from single molecule kinetics. Using a stochastic Markov state description, the observable properties of general catalytic networks of reactions are expressed using an eigenvalue decomposition of the transition matrix for the Markov process. By the use of a sensitivity analysis, the necessary eigenvalues and eigenvectors are related to the energies of controlling barriers and wells located along the reaction routes. A generalization of the energetic span theory allows the eigenvalues to be computed from several activation energies corresponding to distinct barrier-well pairings. The formalism is demonstrated accurately for model problems for a physically realistic mechanism for an alkene hydrogenation reaction on a single atom catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Global root traits (GRooT) database

Motivation: Trait data are fundamental to the quantitative description of plant form and function. Although root traits capture key dimensions related to plant responses to changing environmental conditions and effects on ecosystem processes, they have rarely been included in large-scale comparative studies and global models. For instance, root traits remain absent from nearly all studies that define the global spectrum of plant form and function. Thus, to overcome conceptual and methodological roadblocks preventing a widespread integration of root trait data into large-scale analyses we created the Global Root Trait (GRooT) Database. GRooT provides readyto- use data by combining the expertise of root ecologists with data mobilization and curation. Specifically, we (a) determined a set of core root traits relevant to the description of plant form and function based on an assessment by experts, (b) maximized species coverage through data standardization within and among traits, and (c) implemented data quality checks. Main types of variables contained: GRooT contains 114,222 trait records on 38 continuous root traits. Spatial location and grain: Global coverage with data from arid, continental, polar, temperate and tropical biomes. Data on root traits were derived from experimental studies and field studies. Time period and grain: Data were recorded between 1911 and 2019. Major taxa and level of measurement: GRooT includes root trait data for which taxonomic information is available. Trait records vary in their taxonomic resolution, with subspecies or varieties being the highest and genera the lowest taxonomic resolution available. It contains information for 184 subspecies or varieties, 6,214 species, 1,967 genera and 254 families. Owing to variation in data sources, trait records in the database include both individual observations and mean values. Software format: GRooT includes two csv files. A GitHub repository contains the csv files and a script in R to query the database.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Occurrence Causal Analysis Report: Inadvertent Reaction During the Pressuring of Energetic Material

On June 30, 2020, an inadvertent reaction occurred during pressing of the energetic material pentaerythritol tetranitrate (PETN). The location of the event was the energetic component Rapid Prototype Facility (RPF), where similar operations performed on a variety of energetic materials are routinely provided for customers throughout Sandia National Laboratories (SNL). A background on pressing of energetic materials is provided to enhance clarity in the description of the event. This background includes a description of the equipment, materials, and tooling present during the event.

36 MATERIALS SCIENCE↗
DOE OSTI2023

KEBLM: Knowledge-Enhanced Biomedical Language Models

Pretrained language models (PLMs) have demonstrated strong performance on many natural language processing (NLP) tasks. Despite their great success, these PLMs are typically pretrained only on unstructured free texts without leveraging existing structured knowledge bases that are readily available for many domains, especially scientific domains. As a result, these PLMs may not achieve satisfactory performance on knowledge-intensive tasks such as biomedical NLP. Comprehending a complex biomedical document without domain-specific knowledge is challenging, even for humans. Inspired by this observation, we propose a general framework for incorporating various types of domain knowledge from multiple sources into biomedical PLMs. We encode domain knowledge using lightweight adapter modules, bottleneck feed-forward networks that are inserted into different locations of a backbone PLM. For each knowledge source of interest, we pretrain an adapter module to capture the knowledge in a self-supervised way. We design a wide range of self-supervised objectives to accommodate diverse types of knowledge, ranging from entity relations to description sentences. Once a set of pretrained adapters is available, we employ fusion layers to combine the knowledge encoded within these adapters for downstream tasks. Each fusion layer is a parameterized mixer of the available trained adapters that can identify and activate the most useful adapters for a given input. Our method diverges from prior work by including a knowledge consolidation phase, during which we teach the fusion layers to effectively combine knowledge from both the original PLM and newly-acquired external knowledge using a large collection of unannotated texts. After the consolidation phase, the complete knowledge-enhanced model can be fine-tuned for any downstream task of interest to achieve optimal performance. Extensive experiments on many biomedical NLP datasets show that our proposed framework consistently improves the performance of the underlying PLMs on various downstream tasks such as natural language inference, question answering, and entity linking. These results demonstrate the benefits of using multiple sources of external knowledge to enhance PLMs and the effectiveness of the framework for incorporating knowledge into PLMs. Finally, while primarily focused on the biomedical domain in this work, our framework is highly adaptable and can be easily applied to other domains, such as the bioenergy sector.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Cell Population–resolved Multiomics Atlas of the Developing Lung

The lung is a vital organ that undergoes extensive morphological and functional changes during postnatal development. To disambiguate how different cell populations contribute to organ development, we performed proteomic and transcriptomic analyses of four sorted cell populations from the lung of human subjects aged 0 to 8 years-old with a focus on early life. The cell populations analyzed included epithelial, endothelial, mesenchymal, and immune cells. Our results revealed distinct molecular signatures for each of the sorted cell populations that enable the description of molecular shifts occurring in these populations during post-natal development. Here, we confirmed that the proteome of the different cell populations was distinct regardless of age and identified functions specific to each population. We identified a series of cell population protein markers, including those located at the cell surface, that show differential expression and distribution on RNA in situ hybridization and immunofluorescence imaging. We validated the spatial distribution of AT1 and endothelial cell surface markers. Temporal analyses of the proteome of each of the four populations revealed processes modulated during postnatal development and disambiguating results obtained on whole tissue proteome. Finally, the proteome was compared to a transcriptomics survey performed on the same lung samples to evaluate processes under post-transcriptional control.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Utah FORGE: Seismic Velocity Models, February 2021

This dataset contains a map, showing the Utah FORGE seismic stations, and seismic velocity model data. There are 61 1-D velocity models which are in a compressed TAR file. A paper is referenced at the end of this description which discusses the use of these data in 3D modelling. The paper summary follows: We expand the application of spatial autocorrelation (SPAC) from typical 1-D Vs profiles to quasi-3-D imaging via Bayesian Monte Carlo inversion (BMCI) using a dense nodal array (49 nodes) located at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site. Combinations of 4 and 9 geophones in subarrays provide for 36 and 25 1-D Vs profiles, respectively. Profiles with error bars are determined by calculating coherency functions that fit observations in a frequency range of 0.2-5 Hz. Thus, a high-resolution quasi-3-D Vs model from the surface to 2.0 km depth is derived and shows that surface-parallel sedimentary strata deepen to the west, consistent with a 3-D seismic reflection survey. Moreover, the resulting Vs profile is consistent with a Vs profile derived from distributed acoustic sensing (DAS) data located in a borehole at the FORGE site. The quasi-3-D velocity model shows that the base of the basin dips ~22 degrees to the west and topography on the basement interface coincident with the Mag Lee Wash suggests that the bedrock interface is an unconformity. Reference: Zhang, H. and K. L. Pankow (2021). High-resolution Bayesian spatial auto-correlation (SPAC) pseudo-3D Vs model of Utah FORGE site with a dense geophone array, Geophys. Res. Int, https://doi.org/10.1093/gji/ggab049

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

AmeriFlux FLUXNET-1F CA-SF2 Saskatchewan - Western Boreal, forest burned in 1989

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-SF2 Saskatchewan - Western Boreal, forest burned in 1989. This is the FLUXNET version of the carbon flux data for the site CA-SF2 Saskatchewan - Western Boreal, forest burned in 1989 produced by applying the standard ONEFlux (1F) software. Site Description - Amiro_et_al_2006, AFM/136:...The 1989 burn site (F89) was northeast of Prince Albert National Park, Saskatchewan, with the humancaused fire covering 13,500 ha. Parts of the area had been logged prior to the fire, and slash residues would have been burned in some locations. Parts of the area were aerially seeded with jack pine seeds in the winter of 1990. The present tree canopy was composed of balsam poplar (Populus balsamifera L.), jack pine, trembling aspen, and birch (Betula papyrifera Marsh.) and prior to the fire, the stand consisted of these same species aswell asblack spruce.Deadsnags of black spruce and jack pinewere still standing, althoughmost had fallen over and formed a leaningmix of dry, dead tree boles. The understory vegetation consisted mostly of black spruce saplings, saplings of the tree overstory species, bearberry, blueberry (Vaccinium myrtilloides Michx.), raspberry (Rubus idaeus L.), rose (Rosa acicularis Lindl.), bunchberry (Cornus canadensis L.), and reed grass (Calamagrostis canadensis (Michx.) Nutt.).

Amiro, Brian↗
DOE OSTI2021

First report of Seville root-knot nematode, Meloidogyne hispanica (Nematoda: Meloidogynidae) in the USA and North America

A high number of second stage juveniles of the root-knot nematode were recovered from soil samples collected from a corn field, located in Pickens County, South Carolina, USA in 2019. Extracted nematodes were examined morphologically and molecularly for species identification which indicated that the specimens of root knot juveniles were Meloidogyne hispanica. The morphological examination and morphometric details from second-stage juveniles were consistent with the original description and redescriptions of this species. The ITS rRNA, D2-D3 expansion segments of 28S rRNA, intergenic COII-16S region, nad5 and COI gene sequences were obtained from the South Carolina population of M. hispanica. Phylogenetic analysis of the intergenic COII-16S region of mtDNA gene sequence alignment using statistical parsimony showed that the South Carolina population clustered with Meloidogyne hispanica from Portugal and Australia. To our best knowledge, this finding represents the first report of Meloidogyne hispanica in the USA and North America.

59 BASIC BIOLOGICAL SCIENCES↗