cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/89zf-pf7
title: Probabilistic cytoarchitectonic map of the area SFS1 of the human anterior dorsolateral prefrontal cortex (DLPFC) (v9.0)

description: This dataset contains the distinct cytoarchitectonic probability map of the area SFS1 of the human anterior dorsolateral prefrontal cortex (DLPFC) in the individual, single subject template of the MNI Colin 27 and the MNI ICBM 152 2009 nonlinear asymmetric reference space, as part of the Julich-Brain atlas. The area was identified using cytoarchitectonic analysis on cell-body-stained histological sections in both hemispheres of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The maps show the probability of belonging to the area SFS1 (anterior DLPFC) for each voxel of the reference spaces. Data is provided in the NifTi format. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create probabilistic brain maps. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.
DOI: 10.25493/prbe-dg
title: Probabilistic cytoarchitectonic map of the area SFS2 of the human anterior dorsolateral prefrontal cortex (DLPFC) (v9.0)

description: This dataset contains the distinct cytoarchitectonic probability map of the area SFS2 of the human anterior dorsolateral prefrontal cortex (DLPFC) in the individual, single subject template of the MNI Colin 27 and the MNI ICBM 152 2009 nonlinear asymmetric reference space, as part of the Julich-Brain atlas. The area was identified using cytoarchitectonic analysis on cell-body-stained histological sections in both hemispheres of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The maps show the probability of belonging to the area SFS2 (anterior DLPFC) for each voxel of the reference spaces. Data is provided in the NifTi format. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create probabilistic brain maps. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.
DOI: 10.25493/97g0-08a
title: Reference delineation of Area SFS1 of the anterior dorsolateral prefrontal cortex (DLPFC) in individual sections of the BigBrain (v1)

description: This dataset contains cytoarchitectonic maps of area SFS1 in the BigBrain. Delineations of area SFS1 resulted from the cytoarchitectonic analysis of the structure in coronal histological sections at 1-micron resolution of the BigBrain dataset. They have been transformed to sections of the 3D reconstructed BigBrain space using the transformations, which were provided by Claude Lepage (McGill).
DOI: 10.25493/6m5a-jj0
title: Ultrahigh-resolution 3D cytoarchitectonic map of Area SFS1 of the human anterior dorsolateral prefrontal cortex (DLPFC) created by a Deep-Learning assisted workflow (v1)

description: This dataset contains automatically created detailed map of the area SFS1 of the human anterior dorsolateral prefrontal cortex (DLPFC) in the BigBrain dataset. The mappings were created using Deep Convolutional Neural Networks based on Schiffer et al. 2021, which were trained on delineations on at least every 30th section created based on Bruno et al. 2022. Mappings are available on every section. Their quality was observed by a trained neuroscientist to exclude sections with low-quality results from further processing. Automatic mappings were transformed to the 3D reconstructed BigBrain space using transformations used in Amunts et al. 2013, which were provided by Claude Lepage (McGill). Mappings on individual sections were used to assemble 3D volumes of all areas. Low-quality results were replaced by interpolation between nearest neighboring sections. The volumes were then smoothed using a 3D median filter, and the largest connected components were identified to remove false positive results of the classification algorithm. The dataset consists of an HDF5 file containing the volume in RAS dimension ordering (20-micron isotropic resolution, dataset “volume”) and an affine transformation matrix (dataset “affine”). An additional dataset, “interpolation_info”, contains an integer vector with an integer value for each section which indicates if a section was replaced by interpolation due to low-quality results (value 2) or not (value 1). Due to the large size of the volume, it is recommended to view the data online using the provided viewer link.
DOI: 10.25493/shjb-np2
title: Reference delineation of Area SFS2 of the anterior dorsolateral prefrontal cortex (DLPFC) in individual sections of the BigBrain (v1)

description: This dataset contains cytoarchitectonic maps of area SFS2 in the BigBrain. Delineations of area SFS2 resulted from the cytoarchitectonic analysis of the structure in coronal histological sections at 1-micron resolution of the BigBrain dataset. They have been transformed to sections of the 3D reconstructed BigBrain space using the transformations, which were provided by Claude Lepage (McGill).
DOI: 10.25493/yh0a-sf6
title: Ultrahigh-resolution 3D cytoarchitectonic map of Area SFS2 of the human anterior dorsolateral prefrontal cortex (DLPFC) created by a Deep-Learning assisted workflow (v1)

description: This dataset contains automatically created detailed map of the area SFS2 of the human anterior dorsolateral prefrontal cortex (DLPFC) in the BigBrain dataset. The mappings were created using Deep Convolutional Neural Networks based on Schiffer et al. 2021, which were trained on delineations on at least every 30th section created based on Bruno et al. 2022. Mappings are available on every section. Their quality was observed by a trained neuroscientist to exclude sections with low-quality results from further processing. Automatic mappings were transformed to the 3D reconstructed BigBrain space using transformations used in Amunts et al. 2013, which were provided by Claude Lepage (McGill). Mappings on individual sections were used to assemble 3D volumes of all areas. Low-quality results were replaced by interpolation between nearest neighboring sections. The volumes were then smoothed using a 3D median filter, and the largest connected components were identified to remove false positive results of the classification algorithm. The dataset consists of an HDF5 file containing the volume in RAS dimension ordering (20-micron isotropic resolution, dataset “volume”) and an affine transformation matrix (dataset “affine”). An additional dataset, “interpolation_info”, contains an integer vector with an integer value for each section which indicates if a section was replaced by interpolation due to low-quality results (value 2) or not (value 1). Due to the large size of the volume, it is recommended to view the data online using the provided viewer link.
DOI: 10.25493/vqyx-1hs
title: Reference delineation of Area MFG1 of the anterior dorsolateral prefrontal cortex (DLPFC) in individual sections of the BigBrain (v1)

description: This dataset contains cytoarchitectonic maps of area MFG1 in the BigBrain. Delineations of area MFG1 resulted from the cytoarchitectonic analysis of the structure in coronal histological sections at 1-micron resolution of the BigBrain dataset. They have been transformed to sections of the 3D reconstructed BigBrain space using the transformations, which were provided by Claude Lepage (McGill).
DOI: 10.25493/jn40-ncg
title: Ultrahigh-resolution 3D cytoarchitectonic map of Area MFG1 of the human anterior dorsolateral prefrontal cortex (DLPFC) created by a Deep-Learning assisted workflow (v1)

description: This dataset contains automatically created detailed map of the area MFG1 of the human anterior dorsolateral prefrontal cortex (DLPFC) in the BigBrain dataset. The mappings were created using Deep Convolutional Neural Networks based on Schiffer et al. 2021, which were trained on delineations on at least every 30th section created based on Bruno et al. 2022. Mappings are available on every section. Their quality was observed by a trained neuroscientist to exclude sections with low-quality results from further processing. Automatic mappings were transformed to the 3D reconstructed BigBrain space using transformations used in Amunts et al. 2013, which were provided by Claude Lepage (McGill). Mappings on individual sections were used to assemble 3D volumes of all areas. Low-quality results were replaced by interpolation between nearest neighboring sections. The volumes were then smoothed using a 3D median filter, and the largest connected components were identified to remove false positive results of the classification algorithm. The dataset consists of an HDF5 file containing the volume in RAS dimension ordering (20-micron isotropic resolution, dataset “volume”) and an affine transformation matrix (dataset “affine”). An additional dataset, “interpolation_info”, contains an integer vector with an integer value for each section which indicates if a section was replaced by interpolation due to low-quality results (value 2) or not (value 1). Due to the large size of the volume, it is recommended to view the data online using the provided viewer link.
DOI: 10.25493/gqpv-yab
title: Reference delineation of Area MFG2 of the anterior dorsolateral prefrontal cortex (DLPFC) in individual sections of the BigBrain (v1)

description: This dataset contains cytoarchitectonic maps of area MFG2 in the BigBrain. Delineations of area MFG2 resulted from the cytoarchitectonic analysis of the structure in coronal histological sections at 1-micron resolution of the BigBrain dataset. They have been transformed to sections of the 3D reconstructed BigBrain space using the transformations, which were provided by Claude Lepage (McGill).
DOI: 10.25493/zr6f-v8p
title: Ultrahigh-resolution 3D cytoarchitectonic map of Area MFG2 of the human anterior dorsolateral prefrontal cortex (DLPFC) created by a Deep-Learning assisted workflow (v1)

description: This dataset contains automatically created detailed map of the area MFG2 of the human anterior dorsolateral prefrontal cortex (DLPFC) in the BigBrain dataset. The mappings were created using Deep Convolutional Neural Networks based on Schiffer et al. 2021, which were trained on delineations on at least every 30th section created based on Bruno et al. 2022. Mappings are available on every section. Their quality was observed by a trained neuroscientist to exclude sections with low-quality results from further processing. Automatic mappings were transformed to the 3D reconstructed BigBrain space using transformations used in Amunts et al. 2013, which were provided by Claude Lepage (McGill). Mappings on individual sections were used to assemble 3D volumes of all areas. Low-quality results were replaced by interpolation between nearest neighboring sections. The volumes were then smoothed using a 3D median filter, and the largest connected components were identified to remove false positive results of the classification algorithm. The dataset consists of an HDF5 file containing the volume in RAS dimension ordering (20-micron isotropic resolution, dataset “volume”) and an affine transformation matrix (dataset “affine”). An additional dataset, “interpolation_info”, contains an integer vector with an integer value for each section which indicates if a section was replaced by interpolation due to low-quality results (value 2) or not (value 1). Due to the large size of the volume, it is recommended to view the data online using the provided viewer link.
DOI: 10.5281/zenodo.7067588
title: Datasets for "A 2D Kaleidoscope of Electron Heat Fluxes Driven by Auroral Electron Precipitation"

description: These three datasets are supplemental material for the Geophysical Research Letters article, A 2D Kaleidoscope of Electron Heat Fluxes Driven by Auroral Electron Precipitation. Data Set DS1. Te data plotted in Figure S1. This is the 3-beam averaged Te data described in Text S1. The first row is the heading that, after Time, lists the altitudes in meters of the data in each column. The first column is time in the format: Year-Month-Day/Hour-Minute-Second. Data Set DS2. Te data errors plotted in Figure S1. This is the 3-beam averaged Te data propagated errors described in Text S1. The first row is the heading that, after Time, lists the altitudes in meters of the data in each column. The first column is time in the format: Year-Month-Day/Hour-Minute-Second. Data Set DS3. THEMIS ASI data at the PFISR location used to calculate the heat flux plotted in Figure S1. The first row is the header. Time, the first column, is in the format: Year-Month-Day/Hour-Minute-Second. The following columns are: geographic longitude, geographic latitude, energy flux for a Gaussian distribution, mean energy for a Gaussian distribution, energy flux for a Maxwellian distribution, mean energy for a Maxwellian distribution. Units are included in the header.
description: G. V. K. was partly supported by NASA HTMS program under award of 80NSSC20K1276, the MARBLE Project, funded by the NASA Living with a Star (LWS) Strategic Capabilities program, and NASA LWS awards 80NSSC19K0080 and 80NSSC21K1552. G.V.K and A.G. acknowledge the award 80NSSC20K1817. C. G. and Y.N. would like to acknowledge the NASA grant 80NSSC20K0725 and the AFOSR Grant FA9559‐16‐1‐0364. The THEMIS mission is supported by NASA contract NAS5‐02099, NSF Grant AGS‐1004736, and CSA contract 9F007‐046101.
DOI: 10.5281/zenodo.7067587
title: Datasets for "A 2D Kaleidoscope of Electron Heat Fluxes Driven by Auroral Electron Precipitation"

description: These three datasets are supplemental material for the Geophysical Research Letters article, A 2D Kaleidoscope of Electron Heat Fluxes Driven by Auroral Electron Precipitation. Data Set DS1. Te data plotted in Figure S1. This is the 3-beam averaged Te data described in Text S1. The first row is the heading that, after Time, lists the altitudes in meters of the data in each column. The first column is time in the format: Year-Month-Day/Hour-Minute-Second. Data Set DS2. Te data errors plotted in Figure S1. This is the 3-beam averaged Te data propagated errors described in Text S1. The first row is the heading that, after Time, lists the altitudes in meters of the data in each column. The first column is time in the format: Year-Month-Day/Hour-Minute-Second. Data Set DS3. THEMIS ASI data at the PFISR location used to calculate the heat flux plotted in Figure S1. The first row is the header. Time, the first column, is in the format: Year-Month-Day/Hour-Minute-Second. The following columns are: geographic longitude, geographic latitude, energy flux for a Gaussian distribution, mean energy for a Gaussian distribution, energy flux for a Maxwellian distribution, mean energy for a Maxwellian distribution. Units are included in the header.
description: G. V. K. was partly supported by NASA HTMS program under award of 80NSSC20K1276, the MARBLE Project, funded by the NASA Living with a Star (LWS) Strategic Capabilities program, and NASA LWS awards 80NSSC19K0080 and 80NSSC21K1552. G.V.K and A.G. acknowledge the award 80NSSC20K1817. C. G. and Y.N. would like to acknowledge the NASA grant 80NSSC20K0725 and the AFOSR Grant FA9559‐16‐1‐0364. The THEMIS mission is supported by NASA contract NAS5‐02099, NSF Grant AGS‐1004736, and CSA contract 9F007‐046101.
DOI: 10.34740/kaggle/dsv/4187055
title: OntoUML/UFO Catalog
DOI: 10.6084/m9.figshare.21077095
title: Vertical Ground Motions of a Saturated Soil Layer under the Freezing and Thawing Processes

description: <strong>Main dataset of Figures in a paper titled " Analytical and Numerical Studies on Vertical Ground Motions of a Saturated Soil Layer under the Freezing and Thawing Processes"</strong>
DOI: 10.6084/m9.figshare.21077095.v1
title: Vertical Ground Motions of a Saturated Soil Layer under the Freezing and Thawing Processes

description: <strong>Main dataset of Figures in a paper titled " Analytical and Numerical Studies on Vertical Ground Motions of a Saturated Soil Layer under the Freezing and Thawing Processes"</strong>
DOI: 10.34740/kaggle/dsv/4187128
title: BBC News
DOI: 10.5281/zenodo.7067625
title: Carbohydrate complexity limits microbial growth and reduces the sensitivity of synthetic human gut communities to perturbations

description: Illumina sequencing data for "Carbohydrate complexity limits microbial growth and reduces the sensitivity of synthetic human gut communities to perturbations". Nature Ecology and Evolution, 2022
DOI: 10.5281/zenodo.7067624
title: Carbohydrate complexity limits microbial growth and reduces the sensitivity of synthetic human gut communities to perturbations

description: Illumina sequencing data for "Carbohydrate complexity limits microbial growth and reduces the sensitivity of synthetic human gut communities to perturbations". Nature Ecology and Evolution, 2022
DOI: 10.15485/1463801
title: A Daily Hydroclimatological Data Set for the Continental U.S.

description: This hydro-meteorological data set for the continental United States was constructed for use in climate studies. The data were taken from USGS daily streamflow data and NOAA daily climatological data for precipitation, maximum and minimum temperature. The data set contains data from 1009 streamflow stations and 1036 precipitation/temperature stations distributed across the continental U.S. (see Wallis, et al. (1991) for station distribution).
DOI: 10.15485/1463817
title: ORNL FACE Weather Data

description: Weather data are available for 1999-2007. There is an hourly (*wh*) and a daily (*wd*) file for each of the six plots (rings) on the FACE site, giving a total of 12 files for each year. The 2007 files will be updated as data become available. Daily statistics were calculated only for those variables with at least 12 good hourly values, and the calculation of daily statistics for the variables, PAR2m, PAR22m, and PYRAN, required 12 good daylight hours. Otherwise, the daily values were set to missing.
DOI: 10.15485/1463818
title: Aspen FACE CO2 Data

description: File names follow this format: co21998r1-2.csv 1998 co2 data from ring 1.2
DOI: 10.15485/1463819
title: Nevada Desert Face Facility Larrea tridentata Shoot Growth
DOI: 10.15485/1463820
title: Aspen FACE Meteorological and Soil Data

description: File Content Indicator: 101 (201 data recorded at tower)Met Data Measurements Reported Every 30 Minutes (Missing Data Value = 6999)File Content Indicator: 124 (224 data recorded at tower)Met Data Daily Averages, Maximums, and Minimums w/ Times of Maximums and Minimums (Missing Data Value = 6999)File Content Indicator: 102 (202 data recorded at tower)Soil Moisture Measurements Reported Every 2 Hours (Missing Data Values = 6999)Each ring is divided into three areas: Birch: contains mixed Aspen/Birch Maple: contains mixed Aspen/Maple Aspen: contains pure Aspen
DOI: 10.15485/1463821
title: Duke FACE Stem Temperature

description: Raw, clean, and gap-filled data are available. Julian day #1 = Jan 1, 1990.
DOI: 10.15485/1463822
title: Scaling factors to improve the temporal and spatial distribution of CO2 emissions from global fossil fuel emission datasets

description: Details on the resulting scaling factors were published in a 2013 Nassar et al. paper in JGR - Atmospheres
DOI: 10.15485/1463842
title: ORNL FACE CO2 Concentration Data

description: CO2 concentration data are available for 1999-2006. There is an hourly file for each year which contains elevated and ambient CO2 concentrations. The 2007 file will be updated as data become available. These data files include FACE site measurements of CO2 concentrationsfor rings 1, 2, 4, and 5. Rings 1 and 2 are elevated CO2 concentrations, and rings 4 and 5 are ambient CO2 concentrations. CO2 is sampled continuously from the top of the canopy at the center of eachring and is measured with a LiCor 6252 infrared gas analyzer located in an instrument shed next to each ring. Wind speed and wind directionabove the canopy and solar angle also are recorded. In addition, ambientCO2 concentrations (ring 0) measured at Building 0813, approximately 0.5 km from the FACE site, are included in the files.
DOI: 10.15485/1463843
title: Nevada Desert Face Facility Micrometeorological Data

description: Micrometeorological Data taken at the Nevada Desert FACE FacilityData is logged every minute. Minute data for all rings are combined and averaged over one hour.
DOI: 10.15485/1463844
title: Global and Regional Land-Use Change Emissions

description: Regional carbon stocks, assumed NPP, and net land-use change emissions by ecosystem as estimated using historical land-use data and a simple carbon model. Net land-use change emissions are defined here as net emissions from the terrestrial system estimated without considering the effects of climate changes (e.g. temperature, precipitation).
DOI: 10.15485/1463845
title: ORNL FACE Nitrogen Concentrations (Leaves, Litter, Fine Roots, Wood)

description: This report documents the file, Nconc.dat, which contains the nitrogen concentration data for leaves, litter, fine roots, and wood for 1998-2006. These data were collected for rings 1 and 2 which are exposed to elevated CO2 and rings 3-5 which have ambient CO2.The 2005 and 2006 nitrogen concentrations for fine roots will be included when they become available. The N concentration in leaves could not bemeasured in ring 5 in 2006; an estimated value based on N concentration in litter and an average resorption efficiency is 1.073%.Additional information describing this dataset can be found in Norby, R.J. and C.M. Iversen (2006). Nitrogen uptake, distribution, turnover, and efficiency of use in a CO2-enriched sweetgum forest. Ecology 87:5-14.
DOI: 10.15485/1463846
title: ORNL FACE Soil Moisture Data

description: On the FACE site, soil moisture data are available for ring 1 through ring 5 from 1997-2007, and there are data for ring 6from 1997-1999. Ring 1 and ring 2 are exposed to elevated CO2, and the remaining rings have ambient CO2. Soil moisture was measured with a time-domain reflectometer(TRASE systems, Soil Moisture Equipment Corporation,Santa Barbara, CA) to a depth of 20cm. The missing-value indicator for the soil moisture data is -99.99.
DOI: 10.15485/1463847
title: Carbon-14 Measurements in Surface Water CO2 from the Atlantic, Indian and Pacific Oceans, 1965-1994.

description: In the 1960s, thermonuclear bomb tests released significant pulses of radioactive carbon-14 (14C) into the atmosphere. These major perturbations allowed scientists to study the dynamics of the global carbon cycle by calculating rates of isotopic exchange between the atmosphere and ocean waters. The Radiological Dating Laboratory at the Norwegian Institute of Technology performed 14C measurements of atmospheric CO2 from 1962 to 1993 at a network of ground stations in the northern and southern hemispheres; in addition it performed 14C measurements at high-altitude (between 9-12.6 km) during 1965 (Nydal and Lövseth, 1983, 1996). The Norwegian Radiological Dating Laboratory performed similar measurements on seawater samples collected at the ocean surface from 1965 through 1994. The resulting 14C ocean surface water database is documented here and is available from the Carbon Dioxide Information Analysis Center (CDIAC) as NDP-057A, free of charge. The data from NDP-057A, coupled with other 14C data sets, can lead to a greater understanding of the dynamic carbon reservoir and lead to a crude picture of anomalous sources and sinks at different geographical latitudes. The database is outstanding for its inclusion of early 14C measurements, broad spatial coverage of sampling, relative consistency of sampling methods, and Δ 14C calculation results corrected for isotopic fractionation and radioactive decay. This database replaces previous versions published by the author and the Radiological Dating Laboratory.