cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4031802
title: Root multiple ion uptake kinetics data for maize NAM founders, statistical code, and RhizoFlux hardware plans

description: This repository contains tabular data, R statistical code, protocols, and hardware plans associated with the following preprint: <strong>A multiple ion-uptake phenotyping platform reveals shared mechanisms that affect nutrient uptake by maize roots</strong> Marcus Griffiths, Sonali Roy, Haichao Guo, Anand Seethepalli, David Huhman, Yaxin Ge, Robert E. Sharp, Felix B. Fritschi, Larry M. York bioRxiv 2020.06.15.153601; doi: https://doi.org/10.1101/2020.06.15.153601 <strong>Equipment designs.zip</strong> - Contains the hardware plans, parts lists, and experimental protocol <strong>ImageJ_macro.zip</strong> - Contains scripts to use within ImageJ to segment images to calculate leaf area <strong>manuscript supplementary.zip</strong> - Contains the actual supplemental figures and tables for the manuscript as well as RNAseq data <strong>R code & raw data.zip</strong> - Contains a single .R text file containing all the R code to generate all the figures and and supplemental figures from the include raw data files E-mail mdgriffiths or lmyork at noble.org with any questions. Version 1 was used for the preprint. Version 2 was used for the final manuscript.
DOI: 10.6084/m9.figshare.12838124
title: corfiles_NS

description: Corrected segmentation data (.csv files) for immunofluorescence images (fixed samples, Nestor Saiz) for embryos analyzed in the paper by Morgani <i>et al.</i>, in <i>Developmental Biology </i>(2018) https://doi.org/10.1016/j.ydbio.2018.06.017
DOI: 10.6084/m9.figshare.12838136
title: corfiles_VG

description: Corrected segmentation data (.csv files) for immunofluorescence images (fixed samples, Vidur Garg) for embryos analyzed in the paper by Morgani <i>et al.</i>, in <i>Developmental Biology </i>(2018) https://doi.org/10.1016/j.ydbio.2018.06.017
DOI: 10.6084/m9.figshare.12838136.v2
title: corfiles_VG

description: Corrected segmentation data (.csv files) for immunofluorescence images (fixed samples, Vidur Garg) for embryos analyzed in the paper by Morgani <i>et al.</i>, in <i>Developmental Biology </i>(2018) https://doi.org/10.1016/j.ydbio.2018.06.017
DOI: 10.6084/m9.figshare.12838136.v1
title: corfiles_vg

description: Corrected segmentation data (.csv files) for immunofluorescence images (fixed samples, Vidur Garg) for embryos analyzed in the paper by Morgani <i>et al.</i>, in <i>Developmental Biology </i>(2018) https://doi.org/10.1016/j.ydbio.2018.06.017
DOI: 10.6084/m9.figshare.12960035
title: supplementary table 1.docx

description: supplementary table 1. The antibody sources and concentrations used for Western blotting and immunochemical staining.
DOI: 10.6084/m9.figshare.12960035.v1
title: supplementary table 1.docx

description: supplementary table 1. The antibody sources and concentrations used for Western blotting and immunochemical staining.
DOI: 10.6084/m9.figshare.12960095
title: supplementary table 2

description: supplementary table 2. Correlations between clinical parameters and results of quantification of Western blots.
DOI: 10.6084/m9.figshare.12960095.v1
title: supplementary table 2

description: supplementary table 2. Correlations between clinical parameters and results of quantification of Western blots.
DOI: 10.5281/zenodo.4031628
title: Supporting Data for Feldl et al. 2017: Coupled high-latitude climate feedbacks and their impact on atmospheric heat transport

description: This dataset includes GFDL AM2.1 model output used to create figures in the following papers: Feldl, N., S. Bordoni, and T. M. Merlis, 2017: Coupled high-latitude climate feedbacks and their Impact on atmospheric heat transport. <em>J. Climate</em>, 30, 189–201, https://doi.org/10.1175/JCLI-D-16-0324.1; and Feldl, N., B. T. Anderson, and S. Bordoni, 2017: Atmospheric eddies mediate lapse rate feedback and Arctic amplification. <em>J. Climate</em>, 30, 9213–9224, https://doi.org/10.1175/JCLI-D-16-0706.1. Here we provide monthly climatologies averaged over the last thirty years of each experiment.
DOI: 10.5281/zenodo.4031627
title: Supporting Data for Feldl et al. 2017: Coupled high-latitude climate feedbacks and their impact on atmospheric heat transport

description: This dataset includes GFDL AM2.1 model output used to create figures in the following papers: Feldl, N., S. Bordoni, and T. M. Merlis, 2017: Coupled high-latitude climate feedbacks and their Impact on atmospheric heat transport. <em>J. Climate</em>, 30, 189–201, https://doi.org/10.1175/JCLI-D-16-0324.1; and Feldl, N., B. T. Anderson, and S. Bordoni, 2017: Atmospheric eddies mediate lapse rate feedback and Arctic amplification. <em>J. Climate</em>, 30, 9213–9224, https://doi.org/10.1175/JCLI-D-16-0706.1. Here we provide monthly climatologies averaged over the last thirty years of each experiment.
DOI: 10.15468/bjnrwh
title: Two new species in Iris series Chinenses (Iridaceae) from south-central China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Wilson, Carol A. (2020): Two new species in Iris series Chinenses (Iridaceae) from south-central China. PhytoKeys 161: 41-60, DOI: http://dx.doi.org/10.3897/phytokeys.161.55483, URL: http://dx.doi.org/10.3897/phytokeys.161.55483
DOI: 10.15468/v2t45u
title: On the Leucanthemopsis alpina (L.) Heywood growing in the Illyrian region

description: This dataset contains the digitized treatments in Plazi based on the original journal article Tomasello, Salvatore, Konowalik, Kamil (2020): On the Leucanthemopsis alpina (L.) Heywood growing in the Illyrian region. PhytoKeys 161: 27-40, DOI: http://dx.doi.org/10.3897/phytokeys.161.53384, URL: http://dx.doi.org/10.3897/phytokeys.161.53384
DOI: 10.15468/284dtw
title: Rediscovery of Angiopteris tonkinensis (Marattiaceae) after 100 years, and its revision

description: This dataset contains the digitized treatments in Plazi based on the original journal article Wang, Ting, Xiao, Bo, Liu, En-De, Nguyen, Khang Sinh, Duan, Jie-Qiu, Wang, Kang-Lin, Yan, Yue-Hong, Xiang, Jian-Ying (2020): Rediscovery of Angiopteris tonkinensis (Marattiaceae) after 100 years, and its revision. PhytoKeys 161: 1-9, DOI: http://dx.doi.org/10.3897/phytokeys.161.54912, URL: http://dx.doi.org/10.3897/phytokeys.161.54912
DOI: 10.15468/296vky
title: Notes on the genus Ophryosporus (Asteraceae, Eupatorieae) in Chile

description: This dataset contains the digitized treatments in Plazi based on the original journal article Merklinger, Felix F., Luebert, Federico (2020): Notes on the genus Ophryosporus (Asteraceae, Eupatorieae) in Chile. PhytoKeys 161: 61-77, DOI: http://dx.doi.org/10.3897/phytokeys.161.53736, URL: http://dx.doi.org/10.3897/phytokeys.161.53736
DOI: 10.5281/zenodo.3525474
title: Aurora Subglacial Basin GlaDs inputs, outputs and geophysical data

description: The GlaDS_ASB_outputs.txt file includes the following: Glacier Drainage System (GlaDS) model inputs: node easting (m), node northing (m), bed elevation (m), ice thickness (m), basal velocity (m/year) and basal water production (m/year). GlaDS model results for water pressure as a fraction of overburden (Pw/Pi) and water depth (m):base line model, high conductivity, low conductivity, static water and static velocity model runs. Specularity content data for Aurora Subglacial Basin as an xyz file called: filtered.spec.asb.xyz with easting (m), northing (m) and specularity content. The ICECAP basal interface specularity content profiles can also be found at the U.S Antarctic Program (USAP) Data Center: https://doi.org/10.15784/601371
DOI: 10.5281/zenodo.3525473
title: Aurora Subglacial Basin GlaDs inputs, outputs and geophysical data

description: The GlaDS_ASB_outputs.txt file includes the following: Glacier Drainage System (GlaDS) model inputs: node easting (m), node northing (m), bed elevation (m), ice thickness (m), basal velocity (m/year) and basal water production (m/year). GlaDS model results for water pressure as a fraction of overburden (Pw/Pi) and water depth (m):base line model, high conductivity, low conductivity, static water and static velocity model runs. Specularity content data for Aurora Subglacial Basin as an xyz file called: filtered.spec.asb.xyz with easting (m), northing (m) and specularity content. The ICECAP basal interface specularity content profiles can also be found at the U.S Antarctic Program (USAP) Data Center: https://doi.org/10.15784/601371
DOI: 10.5281/zenodo.4031841
title: Visible and NIR Upconverting Er3+–Yb3+ Luminescent Nanorattles and Other Hybrid PMO‐Inorganic Structures for In Vivo Nanothermometry

description: Dataset accompanying figures published in the publication DOI: 10.5281/zenodo.4001573
description: This project has received funding from the European Union's Horizon 2020 FET Open programme under grant agreement No 801305 (NanoTBTech).
DOI: 10.5281/zenodo.4031840
title: Visible and NIR Upconverting Er3+–Yb3+ Luminescent Nanorattles and Other Hybrid PMO‐Inorganic Structures for In Vivo Nanothermometry

description: Dataset accompanying figures published in the publication DOI: 10.5281/zenodo.4001573
description: This project has received funding from the European Union's Horizon 2020 FET Open programme under grant agreement No 801305 (NanoTBTech).
DOI: 10.5281/zenodo.4030687
title: Diamond Light Source Visit NT23252 Dataset

description: Tomography dataset for work carried out with the support of the Diamond Light Source, instrument I12 (proposal NT23252). Contains -- Data 86250.nxs pco1-86250.hdf -- Savu Config system_parameters.yml tomo_86250_pipeline_cpu.nxs
DOI: 10.5281/zenodo.4030686
title: Diamond Light Source Visit NT23252 Dataset

description: Tomography dataset for work carried out with the support of the Diamond Light Source, instrument I12 (proposal NT23252). Contains -- Data 86250.nxs pco1-86250.hdf -- Savu Config system_parameters.yml tomo_86250_pipeline_cpu.nxs
DOI: 10.6084/m9.figshare.12959930
title: R0216_20180216a_videos

description: Rat 0216, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.12959930.v1
title: R0216_20180216a_videos

description: Rat 0216, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.5281/zenodo.4029770
title: FM IQ sampling from balloonsat

description: This is the data from a balloonsat launched on September 14th 2020 from Carter Park in Bowling Green, Ohio, which ascended to approximately 112,000 feet. The payload was recovered in North Fairfield, Ohio. The Digital RF data in ch0.zip was collected by an RTL-SDR connected to a Raspberry Pi 3B+, using topblock.py, created with GNU Radio Companion. The antenna used was a dipole antenna base with 13cm telescopic antennas (probably should have used longer antennas, but the shorter ones were used to prevent fouling with the lines.) The objective of this experiment was to record stations in the low end of the FM broadcast spectrum (90-92 MHz) during the balloon's ascent. The files Crown Space Odyssey.x contain the sensor data from the Eagle flight computer. Time stamps are GMT. All data is metric. The .xlsx file includes data plots. The .csv file is the raw data as saved by the flight computer. This balloonsat launch was sponsored by High Altitude Science.
DOI: 10.5281/zenodo.4029769
title: FM IQ sampling from balloonsat

description: This is the data from a balloonsat launched on September 14th 2020 from Carter Park in Bowling Green, Ohio, which ascended to approximately 112,000 feet. The payload was recovered in North Fairfield, Ohio. The Digital RF data in ch0.zip was collected by an RTL-SDR connected to a Raspberry Pi 3B+, using topblock.py, created with GNU Radio Companion. The antenna used was a dipole antenna base with 13cm telescopic antennas (probably should have used longer antennas, but the shorter ones were used to prevent fouling with the lines.) The objective of this experiment was to record stations in the low end of the FM broadcast spectrum (90-92 MHz) during the balloon's ascent. The files Crown Space Odyssey.x contain the sensor data from the Eagle flight computer. Time stamps are GMT. All data is metric. The .xlsx file includes data plots. The .csv file is the raw data as saved by the flight computer. This balloonsat launch was sponsored by High Altitude Science.
DOI: 10.5517/ccdc.csd.cc25dvq5
title: CCDC 2008357: Experimental Crystal Structure Determination

description: Related Article: O.I. Bol’shakov, I.D. Yushina, E.V. Bartashevich, A.I. Stash, R.R. Aysin, O.A. Rakitin|2020|Struct.Chem.|31|1729|doi:10.1007/s11224-020-01584-y
DOI: 10.5281/zenodo.3958214
title: ECMWF data for analysing smoked-charged vortices after the 2019-2020 Australian wildfires

description: The dataset contains GRIB2 files produced from the operational IFS model and assimilation system of the European Centre for Medium Range Weather Forecast (ECMWF). OPZLWDA2020mmdd-SH.grd files contain log of surface pressure, zonal wind, meridional wind, temperature, relative vorticity and ozone mixing ratio for the 137 levels of the model on a 1°x1° grid in the southern hemisphere for the long window analysis at 6UTC and 18UTC every day from 1st January 2020 to 31 March 2020. OPZFCST2020mmdd-SH.grd files contain log of surface pressure, temperature, relative vorticity and ozone mixing ratio for the 137 levels of the model on a 1°x1° grid in the southern hemisphere every day for the 10-day forecast run starting at 00UTC every four days from 7 January 2020 to 31 March 2020. For basic access, these files are readable using python tools. The package pygrib available under conda-forge is recommended. The eccode library that allows read from C or Fortran is freely available from ECMWF and is installed along pygrib. Reading with eccode library is also possible in C and Fortran. A simple reader using pygrib is provided. Dedicated packages for the project are available on github/bernard-legras/STC/STC-Australia with dependencies in github/bernard-legras/STC/STC/pylib. The package that reads and process ECMWF data is github/bernard-legras/STC/STC/pylib/ECMWF_N.py. This package needs setup modification to discover the files where they have been copied. All requirements should be made to bernard.legras@lmd.ipsl.fr
description: {"references": ["Dataset associated to http://arxiv.org/abs/2006.07284", "\"The 2019/2020 Australian wildfires generated a persistent smoke-charged vortex rising to 35 km altitude\", Khaykin S., Legras B., Bucci, S."]}
DOI: 10.5281/zenodo.3958213
title: ECMWF data for analysing smoked-charged vortices after the 2019-2020 Australian wildfires

description: The dataset contains GRIB2 files produced from the operational IFS model and assimilation system of the European Centre for Medium Range Weather Forecast (ECMWF). OPZLWDA2020mmdd-SH.grd files contain log of surface pressure, zonal wind, meridional wind, temperature, relative vorticity and ozone mixing ratio for the 137 levels of the model on a 1°x1° grid in the southern hemisphere for the long window analysis at 6UTC and 18UTC every day from 1st January 2020 to 31 March 2020. OPZFCST2020mmdd-SH.grd files contain log of surface pressure, temperature, relative vorticity and ozone mixing ratio for the 137 levels of the model on a 1°x1° grid in the southern hemisphere every day for the 10-day forecast run starting at 00UTC every four days from 7 January 2020 to 31 March 2020. For basic access, these files are readable using python tools. The package pygrib available under conda-forge is recommended. The eccode library that allows read from C or Fortran is freely available from ECMWF and is installed along pygrib. Reading with eccode library is also possible in C and Fortran. A simple reader using pygrib is provided. Dedicated packages for the project are available on github/bernard-legras/STC/STC-Australia with dependencies in github/bernard-legras/STC/STC/pylib. The package that reads and process ECMWF data is github/bernard-legras/STC/STC/pylib/ECMWF_N.py. This package needs setup modification to discover the files where they have been copied. All requirements should be made to bernard.legras@lmd.ipsl.fr
description: {"references": ["Dataset associated to http://arxiv.org/abs/2006.07284", "\"The 2019/2020 Australian wildfires generated a persistent smoke-charged vortex rising to 35 km altitude\", Khaykin S., Legras B., Bucci, S."]}
DOI: 10.5281/zenodo.4031446
title: Viewable Snow Covered Area Validation Masks over Rugged and Forested Terrain

description: These data are maps of viewable snow cover generated from panchromatically sharpened cloud-free WorldView-2 and -3 data within 2 days of a Landsat 8 OLI acquisition or near-nadir MODIS acquisition. The spatial resolution of these validation data ranges from 0.34 m to 0.55 m, depending on the view angle of WorldView. ValKey.csv shows the list of validation dates and the corresponding Landsat 8 OLI and MODIS imagery. Validation images from December to June were selected to account for variability in illumination conditions, snow cover, and snow albedo. The imagery spans diverse locations across California’s Sierra Nevada that represent the heavily forested western slope, higher elevation regions, and drier eastern slopes. The WorldView images range from well illuminated alpine scenes above the tree line in June to heavily shadowed scenes below the tree line in December. The snow-covered WorldView pixels are assumed to be pure endmembers of 100% snow, which are then coarsened to Landsat or MODIS spatial resolutions and provided here as geotiffs. Neither WorldView, Landsat, nor MODIS can see through thick tree canopies, so the data is comprised of snow that an optical sensor identifies. Complete methods used to generate the dataset are available in the companion publication: tbd Binary snow cover maps at the native worldview resolution are unsigned 8 bit integers with fill pixels set to zero, snow pixels set to one, and snow free pixels set to two. Fill Pixels [0] Snow Covered Pixels [1] Snow Free Pixels [2] Fractional snow covered area geotiffs in the projections and at the spatial resolution of Landsat 8 and MODIS products are signed 16-bit integers with a fill value of -32768. The divisor and offset are 1000 & 0 respectively. Fractional snow covered area [0-1000)] (divisor of 1000 and offset of 0 for measurement range of 0-1) Fill Pixels [-32768]
description: This work was supported by University of California award LFR‐18‐548316, NASA awards 80NSSC18K1489 and 80NSSC18K0427, and NOAA award NA18OAR4590380. T. Stillinger and E.H. Bair are with the Earth Research Institute, University of California, Santa Barbara, CA 93106-3060 (emails: tcs@ucsb.edu, nbair@eri.ucsb.edu).
DOI: 10.5281/zenodo.4031445
title: Viewable Snow Covered Area Validation Masks over Rugged and Forested Terrain

description: These data are maps of viewable snow cover generated from panchromatically sharpened cloud-free WorldView-2 and -3 data within 2 days of a Landsat 8 OLI acquisition or near-nadir MODIS acquisition. The spatial resolution of these validation data ranges from 0.34 m to 0.55 m, depending on the view angle of WorldView. ValKey.csv shows the list of validation dates and the corresponding Landsat 8 OLI and MODIS imagery. Validation images from December to June were selected to account for variability in illumination conditions, snow cover, and snow albedo. The imagery spans diverse locations across California’s Sierra Nevada that represent the heavily forested western slope, higher elevation regions, and drier eastern slopes. The WorldView images range from well illuminated alpine scenes above the tree line in June to heavily shadowed scenes below the tree line in December. The snow-covered WorldView pixels are assumed to be pure endmembers of 100% snow, which are then coarsened to Landsat or MODIS spatial resolutions and provided here as geotiffs. Neither WorldView, Landsat, nor MODIS can see through thick tree canopies, so the data is comprised of snow that an optical sensor identifies. Complete methods used to generate the dataset are available in the companion publication: tbd Binary snow cover maps at the native worldview resolution are unsigned 8 bit integers with fill pixels set to zero, snow pixels set to one, and snow free pixels set to two. Fill Pixels [0] Snow Covered Pixels [1] Snow Free Pixels [2] Fractional snow covered area geotiffs in the projections and at the spatial resolution of Landsat 8 and MODIS products are signed 16-bit integers with a fill value of -32768. The divisor and offset are 1000 & 0 respectively. Fractional snow covered area [0-1000)] (divisor of 1000 and offset of 0 for measurement range of 0-1) Fill Pixels [-32768]
description: This work was supported by University of California award LFR‐18‐548316, NASA awards 80NSSC18K1489 and 80NSSC18K0427, and NOAA award NA18OAR4590380. T. Stillinger and E.H. Bair are with the Earth Research Institute, University of California, Santa Barbara, CA 93106-3060 (emails: tcs@ucsb.edu, nbair@eri.ucsb.edu).
DOI: 10.3886/e120308v1-44388
title: Knowledge, attitudes and practices related to COVID-19 in the U.S.

description: Given the urgent need for data to inform public health messaging to mitigate the spread of the COVID-19 pandemic, this national survey sought to assess the state of COVID-19-related knowledge, beliefs, mental health, substance use changes, and behaviors among a sample of U.S. adults. A survey of U.S. adults was administered online from March 20-30, 2020. The survey collected data on socio-demographic characteristics; COVID-19-related knowledge, awareness and adoption of preventive practices; depression and anxiety (assessed by the Patient Health Questionnaire-4); stress (adapted Impact of Event Scale-6); pessimism; and changes in tobacco and alcohol use.
description: Presence of Common Scales: PHQ-4, IES-6
description: web-based survey;
description: US residents aged 18+ Facebook users. Smallest Geographic Unit: United States
description: Users of Facebook and associated platforms recruited via a Facebook add campaign
DOI: 10.3886/e120308v1-44400
title: Knowledge, attitudes and practices related to COVID-19 in the U.S.

description: Given the urgent need for data to inform public health messaging to mitigate the spread of the COVID-19 pandemic, this national survey sought to assess the state of COVID-19-related knowledge, beliefs, mental health, substance use changes, and behaviors among a sample of U.S. adults. A survey of U.S. adults was administered online from March 20-30, 2020. The survey collected data on socio-demographic characteristics; COVID-19-related knowledge, awareness and adoption of preventive practices; depression and anxiety (assessed by the Patient Health Questionnaire-4); stress (adapted Impact of Event Scale-6); pessimism; and changes in tobacco and alcohol use.
description: Presence of Common Scales: PHQ-4, IES-6
description: web-based survey;
description: US residents aged 18+ Facebook users. Smallest Geographic Unit: United States
description: Users of Facebook and associated platforms recruited via a Facebook add campaign
DOI: 10.3886/e117405v1-44401
title: Data and code for: Bartik Instruments: What, When, Why, and How

description: This repository contains code and data associated with our paper title "Bartik Instruments: What, When, Why, and How." The abstract of the paper is: The Bartik instrument is formed by interacting local industry shares and national industry growth rates. We show that the typical use of a Bartik instrument assumes a pooled exposure research design, where the shares measure differential exposure to common shocks, and identification is based on exogeneity of the shares. Next, we show how the Bartik instrument weights each of the exposure designs. Finally, we discuss how to assess the plausibility of the research design. We illustrate our results through two applications: estimating the elasticity of labor supply, and estimating the elasticity of substitution between immigrants and natives.