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20 results for “doe”
Lake Sediment Pollen and Charcoal from Doe Pond in Westfield MA from 13684 BP to Present
Aim We analyzed a dataset composed of multiple palaeoclimate and lake-sediment pollen and charcoal records from New England to explore how postglacial changes in forest composition and spatial patterns of vegetation and fire were controlled by regional-scale climate change, a subregional environmental gradient, and landscape-scale variations in soil characteristics. Location The 120,000-km2 study area includes parts of Vermont and New Hampshire in the north, where sites are 150-200 km from the Atlantic Ocean, and spans the coastline from southeastern New York to Cape Cod and the adjacent islands, including Block Island, the Elizabeth Islands, Nantucket, and Martha’s Vineyard. Results Boreal forest featuring Picea and Pinus banksiana was present across the region when conditions were cool and dry 14,000-12,000 calibrated 14C yrs before present (ybp). Pinus strobus became regionally dominant as temperatures increased between 12,000 and 10,000 ybp. The composition of forests in inland and coastal areas diverged in response to further warming after 10,000 ybp, when Quercus and Pinus rigida expanded across southern New England, while conditions remained cool enough in inland areas to maintain Pinus strobus. Fire severity was high during 10,000-8000 ybp. Increasing precipitation allowed Tsuga canadensis, Fagus grandifolia, and Betula to replace Pinus strobus in inland areas during 9000-8000 ybp, and also led to the expansion of Carya across the coastal part of the region beginning at 7000-6000 ybp. Abrupt cooling at 5500-5000 ybp caused sharp declines in Tsuga in inland areas and Quercus at some coastal sites, and the populations of those taxa remained low until they recovered around 3000 ybp in response to rising precipitation. Throughout most of the Holocene, sites underlain by sandy glacial deposits were occupied by Pinus rigida and Quercus. Main conclusions Postglacial changes in the composition and spatial pattern of New England forests were controlled by long-term t
Design of experiment (DOE) used in the study: Lightweight design of variable-stiffness imperfection-insensitive cylinders enabled by continuous tow shearing and machine learning
<p>There are five input variables that are changed for this design of experiment (DOE) within the following range:</p> <p><span class="math-tex">\(\begin{eqnarray} 0.05 \leq r_{CTS} \leq 0.20 \nonumber \\ 1 \leq n \leq 12 \nonumber \\ 0 \leq {c_2}_{ratio} \leq 1 \\ 0 \leq \theta_1 \leq 75 \nonumber \\ 0 \leq \theta_2 \leq 75 \nonumber \end{eqnarray}\)</span></p> <p>For the sake of simplicity, these variables are respectively called v1, v2, v3, v4, v5.</p> <p>The DOE consist of 2000 points created with Latin Hyper-cube Sampling, as available in the LHS toolbox (Carnell, R. lhs: Latin Hypercube Samples, 2021. R package version 1.1.3.).</p> <p>The outputs evaluated with this design of experiment (DOE) are the critical buckling load $P_{critical}$, $b_{factor}$ obtained with Koiter's asymptotic approach, and the mass.</p>
Archive of NASA-Unified WRF model daily forecasting simulations for DOE TRACER IOP
<pre># Copyright 2022 NASA GSFC All rights reserved. # Creative commons attribution 4.0 international license NASA-Unified WRF model daily simulations for DOE TRACER IOP Document updated: 22 June 2022 Point of contact: Takamichi Iguchi (ESSIC UMD, Code612 NASA GSFC), takamichi.iguchi@nasa.gov Toshi Matsui (ESSIC UMD, Code612 NASA GSFC), toshihisa.matsui-1@nasa.gov Contents: ./READMEtracer.txt # this file ./namelist.wps.tracer_iop_31.template # namelist.wps file to configure WRF Pre-Processing System (WPS) ./namelist.input.real.tracer_iop_31.template # namelist.input file for NU-WRF model real.exe ./namelist.input.wrf.tracer_iop_31.template # namelist.input file for NU-WRF model wrf.exe ./${YYYY}${MM}${DD} # these directories contain files produced from 48-hours NU-WRF forecasting from 00UTC on ${YYYY}${MM}${DD}: pyplot_${YYYY}-${MM}-${DD}_${HH}${MN}${SC}.png # Plot for Composite radar reflectivity (dBZ) # PBL height (m) + 10-m horizontal wind (850hPa-level wind in plots before 06/02/2022), # OLR TOA (W m-2), and 5-mins-accumulated IC+CG lighting flash extent density (flash km-2) # Note that this composite dBZ is calculated from NSSL 2-moment microphysics for S-band, # not from POLARRIS radar simulator pyplot.gif # Gif annimation file combining the png plot files for 1~48 hours in the forecasting accprecip_${YYYY}-${MM}-${DD}_${HH}${MN}${SC}.png # Plot for 1, 3, 6-hours, and total accumulated surface precipitation (mm) accprecip.gif # Gif annimation file combining the png plot files for 1~48 hours in the forecasting polarris_zh_zdr_rh_vr_${YYYY}_${MM}${DD}_${HH}${MN}${SC}.png # Plot from POLARRIS radar simulator in NU-WRF for QCed Reflectivity (dBZ), # differential reflectivity (dB), cross-polar correlation (-), and # radial velocity (m s-1) at 0.5 degree elevation angle polarris_zh_zdr_rh_vr.gif # Gif annimation file combining the png plot files roughly every hour # for 1~48 hours in the forecasting polarris_zh_4sweeps_${YYYY}_${MM}${DD}_${HH}${MN}${SC}.png # Plot from POLARRIS radar simulator in NU-WRF for QCed Reflectivity (dBZ) # at 0.5, 1.8, 4.0 and 8.0 degree elevation angles polarris_zh_4sweeps.gif # Gif annimation file combining the png plot files roughly every hour # for 1~48 hours in the forecasting # following files are produced 3 days late # day1 represent the first 0-24hr forecast, day2 represents the 24-48hr forecast. CFAD_con_day?.png # Convective part of Contoured Frequency of Altitude Diagrams CFAD_str_day?.png # Stratiform part of Contoured Frequency of Altitude Diagrams QVP_con_day?.png # Convective part of QVP-like domain-mean radar profiles QVP_str_day?.png # Stratiform part of QVP-like domain-mean radar profiles RadarFrac_day?.png # Composite Radar Horizontal Fraction (0-1) by different minimum reflectivity thresholds</pre>
Dataset obtained from DoE for the construction of lightweight concrete blocks using expanded polystyrene
<p>The dataset used in this study was generated through a Design of Experiments (DOE) approach to predict the material mixture proportions using machine learning techniques. It contains 36 experiments, where the independent variables include the proportions of cement, sand, gravel, and expanded polystyrene (Styrofoam). The dependent variables are the compressive strength values and water absorption rates, calculated across multiple components and used to classify the mixtures.</p> <p>The dataset columns include:</p> <ul> <li><strong>Cement:</strong> The proportion of cement used in the mixture.</li> <li><strong>Sand:</strong> The proportion of sand used.</li> <li><strong>Gravel:</strong> The proportion of gravel.</li> <li><strong>Styrofoam (Sty):</strong> The proportion of expanded polystyrene.</li> <li><strong>Comp. 1-6:</strong> Compressive strength values for different components.</li> <li><strong>Comp. Mean:</strong> The mean compressive strength value.</li> <li><strong>Abs. 1-3:</strong> Water absorption values for different components.</li> <li><strong>Abs. Mean:</strong> The mean water absorption rate.</li> <li><strong>Classification:</strong> The final classification of the mixture based on the obtained results, indicating if the mixture belongs to categories such as "B," "C," "D," or "No classification."</li> </ul> <p>This dataset was used to train and validate machine learning models, aiming to predict the mixture properties based on the material proportions.</p>
COMPASS-DOE/rf-synthesis: LOM accepted version
<p>This code and data for conducting analysis of parameter decision impacts on Random Forest model model performance and interpretation. Github associated with 10.1002/lom3.10523.</p>
Dataset DOE of non-ionic aqueous micellar extraction of trypsin inhibitors and isoflavones from soybean meal
<p>Design of Experiments data from the work "Non-ionic aqueous micellar extraction of trypsin inhibitors and isoflavones from soybean meal: process optimization"</p>
COMPASS-DOE/Rs-synthesis: JGR-BGS accepted version
<p>This code and data are for conducting a meta-analysis on the effect of precipitation changes on soil respiration using ecosystem type, manipulation strength and duration, as well as soil clay and organic carbon content as modifiers. Results and figures from the version here appear in the published manuscript.</p>
Ocean Dynamics in the DOE Energy, Exascale, Earth System Model (E3SM)
<p>Climate research at the U.S. Department of Energy (DOE) includes the development of ocean, sea-ice, atmosphere, land-vegetation and land-ice models. The ability to run high-resolution global simulations efficiently on the world’s largest computers is a priority for the DOE. This movie shows simulations from the variable-resolution ocean model, the Model for Prediction Across Scales (MPAS-Ocean), which is developed at Los Alamos National Laboratory. MPAS-Ocean is a component of the DOE’s newly released Energy, Exascale, Earth System Model (E3SM). Applications of E3SM include the simulation of 20th-century and future climate scenarios, as well as special configurations where model resolution is enhanced in regions of particular interest, like coastal areas, the Arctic, or below Antarctic ice shelves.</p> <p>Website: <a href="https://e3sm.org">https://e3sm.org</a>. </p>
NCEP/DOE Reanalysis II in HDF-EOS5, for GSSTF2c, 1x1 deg Monthly grid V2c (GSSTFM_NCEP) at GES DISC
These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-2c Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project. This is a Monthly product; data are projected to equidistant Grid that covers the globe at 1x1 degree cell size, resulting in data arrays of 360x180 size. A finer resolution, 0.25 deg, of this product has been released as Version 3. The input data sets used for this recent GSSTF production include the upgraded and improved datasets such as the Special Sensor Microwave Imager (SSM/I) Version-6 (V6) product of brightness temperature [Tb], total precipitable water [W], and wind speed [U] produced by the Wentz of Remote Sensing Systems (RSS), as well as the NCEP/DOE Reanalysis-2 (R2) product of sea skin temperature [SKT], 2-meter air temperature [Tair], and sea level pressure [SLP]. The short name for this product is GSSTFM_NCEP.
NCEP/DOE Reanalysis II, for GSSTF, 0.25x0.25 deg, Monthly grid V3 (GSSTFM_NCEP) at GES DISC
These data are the Goddard Satellite-based Surface Turbulent Fluxes Version 3 Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project. This is a Monthly product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size. The input data sets used for this recent GSSTF production include the upgraded and improved datasets such as the Special Sensor Microwave Imager (SSM/I) Version-6 (V6) product of brightness temperature [Tb], total precipitable water [W], and wind speed [U] produced by the Wentz of Remote Sensing Systems (RSS), as well as the NCEP/DOE Reanalysis-2 (R2) product of sea skin temperature [SKT], 2-meter air temperature [Tair], and sea level pressure [SLP]. The short name for this product is GSSTFM_NCEP.
NCEP/DOE Reanalysis II in HDF-EOS5, for GSSTF2c, 1x1 deg Daily grid V2c (GSSTF_NCEP) at GES DISC
These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-2c (GSSTF2c) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project. This is a Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 1x1 degree cell size, resulting in data arrays of 360x180 size. A finer resolution, 0.25 deg, of this product has been released as Version 3. The input data sets used for this recent GSSTF production include the upgraded and improved datasets such as the Special Sensor Microwave Imager (SSM/I) Version-6 (V6) product of brightness temperature [Tb], total precipitable water [W], and wind speed [U] produced by the Wentz of Remote Sensing Systems (RSS), as well as the NCEP/DOE Reanalysis-2 (R2) product of sea skin temperature [SKT], 2-meter air temperature [Tair], and sea level pressure [SLP]. The short name for this product is GSSTF_NCEP.
NARSTO ICARTT NEAX 2004 DOE G-1 Air Chemistry, Aerosol, and Met Data
NARSTO_ICARTT_NEAX_2004_DOE_G-1_DATA is the NARSTO_NE_MODEL is the North American Research Strategy for Tropospheric Ozone (NARSTO) ICARTT NEAX 2004 DOE G-1 Air Chemistry, Aerosol, and Met Data collected in July and August, 2004 during the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT), NorthEast Aerosol eXperiment (NEAX). The DOE Gulfstream G-1 aircraft operated within about 300 nautical miles from Latrobe, PA from about July 19 - August 15, 2004. There were 13 total flights on twelve different days. Data were reported for both 1 second and averaged 10 second sampling intervals.NARSTO, which has since disbanded, was a public/private partnership, whose membership spanned across government, utilities, industry, and academe throughout Mexico, the United States, and Canada. The primary mission was to coordinate and enhance policy-relevant scientific research and assessment of tropospheric pollution behavior; activities provide input for science-based decision-making and determination of workable, efficient, and effective strategies for local and regional air-pollution management. Data products from local, regional, and international monitoring and research programs are still available.
NCEP/DOE Reanalysis II, for GSSTF, 0.25 x 0.25 deg, Daily Grid V3 (GSSTF_NCEP) at GES DISC
These data are the Goddard Satellite-based Surface Turbulent Fluxes Version 3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. This HDF-EOS5 dataset is part of the MEaSUREs project. This is a Daily product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size. Data gap: Daily GSSTF_NCEP files are missing for October 21-22,26-28, in 1990.The input data sets used for this recent GSSTF production include the upgraded and improved datasets such as the Special Sensor Microwave Imager (SSM/I) Version-6 (V6) product of brightness temperature [Tb], total precipitable water [W], and wind speed [U] produced by the Wentz of Remote Sensing Systems (RSS), as well as the NCEP/DOE Reanalysis-2 (R2) product of sea skin temperature [SKT], 2-meter air temperature [Tair], and sea level pressure [SLP]. The short name for this product is GSSTF_NCEP.
NARSTO EPA Supersite (SS) Houston, Texas Air Quality Study 2000 (TexAQS2000) Department of Energy (DOE) G-1 Air Chemistry, Aerosol, and Met Data
NARSTO_EPA_SS_HOUSTON_TEXAQS2000_DOE_G-1_DATA is North American Research Strategy for Tropospheric Ozone (NARSTO) Environmental Protection Agency (EPA) Supersite (SS) Houston, Texas Air Quality Study 2000 (TexAQS2000) Department of Energy (DOE) G-1 Air Chemistry, Aerosol, and Met Data. Twenty research flights were made from August 18 to September 12, 2000.The Houston Supersite is one of several Supersites that was established in urban areas within the United States by the U.S. Environmental Protection Agency (EPA) to better understand the measurement, sources, and health effects of suspended particulate matter (PM). The overall goals were to characterize the composition and identify the sources of particulate matter in Southeastern Texas, to develop and test new methods for characterizing fine particulate matter, and to collect data on the physical and chemical characterization of fine particulate matter that can be used to support exposure and health effects studies.NARSTO, which has since disbanded, was a public/private partnership, whose membership spanned across government, utilities, industry, and academe throughout Mexico, the United States, and Canada. The primary mission was to coordinate and enhance policy-relevant scientific research and assessment of tropospheric pollution behavior; activities provide input for science-based decision-making and determination of workable, efficient, and effective strategies for local and regional air-pollution management. Data products from local, regional, and international monitoring and research programs are still available.
iPSc-to-thymic epithelial progenitor differentiation under multifactorial DoE optimization and transcriptomic profiling
GEO Series GSE302942. Homo sapiens. 96 samples. Type: Expression profiling by high throughput sequencing.
NARSTO SOS99NASH DOE G-1 Air Chemistry Data
NARSTO_SOS99NASH_G-1_AIR_CHEMISTRY_DATA is the North American Research Strategy for Tropospheric Ozone (NARSTO) SOS99 Nashville Department of Energy (DOE) G-1 Air Chemistry Data product. Data was collected via the G-1 aircraft deployed during the 1999 campaign to make measurements within the Nashville urban plume. These in situ, semi-Lagrangian measurements, in conjunction with surface-based observations independently made at the Polk Building and at the Cornelia Fort site, allowed quantification of the following:a) ozone production/loss rates, b) ozone production efficiency and c) NOx loss rates within this plume. Mechanical problems with the G-1 aircraft precluded making additional measurements. North American Research Strategy for Tropospheric Ozone (NARSTO), which has since disbanded, was a public/private partnership, whose membership spanned across government, utilities, industry, and academe throughout Mexico, the United States, and Canada. The primary mission was to coordinate and enhance policy-relevant scientific research and assessment of tropospheric pollution behavior; activities provide input for science-based decision-making and determination of workable, efficient, and effective strategies for local and regional air-pollution management. Data products from local, regional, and international monitoring and research programs are still available.
PBMC immune transcriptome analysis in kids fed on doe's milk(Control) versus kids fed on replacer milk (Test) post-PPR vaccination
GEO Series GSE223506. Capra hircus. 6 samples. Type: Expression profiling by high throughput sequencing.
PBMC immune transcriptome analysis in kids fed on doe's milk(Control) versus kids fed on replacer milk (Test)
GEO Series GSE223592. Capra hircus. 6 samples. Type: Expression profiling by high throughput sequencing.
Factorial Analysis -- DOE Apartment Building with Ideal Loads System (MAT files)
<p>This is a test upload of summarised simulation data as MAT files. The simulations were carried out with EnergyPlus. The original IDF files can be found on the USDOE website (http://energy.gov/eere/buildings/commercial-reference-buildings). I modified the files to have only ideal loads systems. The factorial analysis varies 5 factors at 3 levels each (243 files) -- U-value, Thermal Mass, Self-Shading (overhangs and fins), Window-to-Wall Ratio, and Ventilation Level.</p> <p>Upcoming related files, to be posted this summer, include:</p> <p>1. Original CSV outputs from Eplus.</p> <p>2. MATLAB scripts to make these summary files.</p> <p>3. MATLAB scripts to change the base IDF file for a factorial analysis.</p> <p>4. Other cool things?</p> <p> </p>
Eastern North Atlantic DOE Sampling site - E3SM outputs , code, and INP measurements
<p>This dataset provides the E3SM code and runscript for 6-hourly outputs using the MAM-4 aerosol module - E3SM_ENA_coderunscript_v2.tar.gz</p> <p>Here, we also include E3SM outputs in the file for the ENA DOE sampling site during the ExINP-ENA field campaign. 'ENA_E3SMoutput.tar.gz'</p> <p>We also archived the INP and other aerosol measurements that were conducted during the ExINP-ENA campaign - ENAsite_allmeasurements.tar.gz</p> <p>All analysis scripts to plot timeseries and aerosol-INP closure are archived in ENA_analysis_scriptspython.tar.gz</p> <p> </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.