cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17876/plate/dr.3/plates/1_23435
title: Digital object identifier (DOI) for the plate 23435 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23436
title: Digital object identifier (DOI) for the plate 23436 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23437
title: Digital object identifier (DOI) for the plate 23437 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23438
title: Digital object identifier (DOI) for the plate 23438 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23439
title: Digital object identifier (DOI) for the plate 23439 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23440
title: Digital object identifier (DOI) for the plate 23440 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23441
title: Digital object identifier (DOI) for the plate 23441 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23442
title: Digital object identifier (DOI) for the plate 23442 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23443
title: Digital object identifier (DOI) for the plate 23443 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23444
title: Digital object identifier (DOI) for the plate 23444 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23445
title: Digital object identifier (DOI) for the plate 23445 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23446
title: Digital object identifier (DOI) for the plate 23446 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23447
title: Digital object identifier (DOI) for the plate 23447 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23448
title: Digital object identifier (DOI) for the plate 23448 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23449
title: Digital object identifier (DOI) for the plate 23449 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23450
title: Digital object identifier (DOI) for the plate 23450 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23451
title: Digital object identifier (DOI) for the plate 23451 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23452
title: Digital object identifier (DOI) for the plate 23452 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23453
title: Digital object identifier (DOI) for the plate 23453 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23454
title: Digital object identifier (DOI) for the plate 23454 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23455
title: Digital object identifier (DOI) for the plate 23455 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23456
title: Digital object identifier (DOI) for the plate 23456 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23457
title: Digital object identifier (DOI) for the plate 23457 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23458
title: Digital object identifier (DOI) for the plate 23458 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23459
title: Digital object identifier (DOI) for the plate 23459 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23460
title: Digital object identifier (DOI) for the plate 23460 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23461
title: Digital object identifier (DOI) for the plate 23461 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23462
title: Digital object identifier (DOI) for the plate 23462 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23463
title: Digital object identifier (DOI) for the plate 23463 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23464
title: Digital object identifier (DOI) for the plate 23464 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23465
title: Digital object identifier (DOI) for the plate 23465 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23466
title: Digital object identifier (DOI) for the plate 23466 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23467
title: Digital object identifier (DOI) for the plate 23467 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23468
title: Digital object identifier (DOI) for the plate 23468 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23469
title: Digital object identifier (DOI) for the plate 23469 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23470
title: Digital object identifier (DOI) for the plate 23470 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23471
title: Digital object identifier (DOI) for the plate 23471 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23472
title: Digital object identifier (DOI) for the plate 23472 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23473
title: Digital object identifier (DOI) for the plate 23473 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23474
title: Digital object identifier (DOI) for the plate 23474 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23475
title: Digital object identifier (DOI) for the plate 23475 in archive 1 from the APPLAUSE DR3
DOI: 10.17876/plate/dr.3/plates/1_23476
title: Digital object identifier (DOI) for the plate 23476 in archive 1 from the APPLAUSE DR3
DOI: 10.14469/hpc/10197
title: NMR

description: NMR analysis of synthesised esther.
DOI: 10.6084/m9.figshare.19485569
title: Whole-exome sequencing in a recombinant inbred line population of hexaploid wheat as a useful resource for allele mining

description: Sequence variants (SNPs) identified through whole exome sequencing in bread wheat
DOI: 10.5281/zenodo.5815579
title: CO2 NEE and ER + air and soil meteorological and climate parameters in Arctic tundra, Ny Ålesund (Svalbard, NO) - summer 2019

description: The dataset “fluxes_meteoclimate_NyAlesund” is a .csv file reporting CO2 fluxes and basic meteoclimatic variables measured in the Bayelva Basin near Ny Ålesund, in the Brøgger peninsula, Spitsbergen, Norway (78°55’24’’ N, 11°55’15’’E) during the 2019 growing season peak (July-August). Average coordinates of the measuring site are: 78°55’25.7” N,11°53’29.4” E. Fluxes were measured using the flux chamber method: the Net Ecosystem Exchange (NEE) was measured with a transparent flux chamber, while the Ecosystem Respiration (ER) with a shaded chamber. Three types of sampling were performed: at a fixed point during 24h ('point' in column sampling); in points randomly distributed over a site ('site' in column sampling); and in points covered with specific species ('species' in column sampling). Flux data are complemented by measurements of soil temperature (Ts, in Celsius degrees), soil volumetric water content (VWC, in %), atmospheric pressure (Pr, in hPa), air temperature (Ta, in Celsius degrees), air moisture (RH, in %), and solar radiance (rs , in W/m2). The Green Fractional Cover (GFC, between 0 and 1) of the vegetation inscribed within the sampling surface was estimated from digital RGB pictures taken at nadir. Measurements were divided into 4 classes, depending on the prevailing cover type: bare soil (BS), vascular vegetation (V), non-vascular vegetation (NV, including lichens, mosses and bacterial soil crust) and mix of vascular and non-vascular vegetation (MIX). Class V was further split into 5 subclasses: Carex spp. (CX), Dryas octopetala (DR), Salix Polaris (SL), Saxifraga oppostifolia (SX) and Silene acaulis (SI).
DOI: 10.5281/zenodo.5815578
title: CO2 NEE and ER + air and soil meteorological and climate parameters in Arctic tundra, Ny Ålesund (Svalbard, NO) - summer 2019

description: The dataset “fluxes_meteoclimate_NyAlesund” is a .csv file reporting CO2 fluxes and basic meteoclimatic variables measured in the Bayelva Basin near Ny Ålesund, in the Brøgger peninsula, Spitsbergen, Norway (78°55’24’’ N, 11°55’15’’E) during the 2019 growing season peak (July-August). Average coordinates of the measuring site are: 78°55’25.7” N,11°53’29.4” E. Fluxes were measured using the flux chamber method: the Net Ecosystem Exchange (NEE) was measured with a transparent flux chamber, while the Ecosystem Respiration (ER) with a shaded chamber. Three types of sampling were performed: at a fixed point during 24h ('point' in column sampling); in points randomly distributed over a site ('site' in column sampling); and in points covered with specific species ('species' in column sampling). Flux data are complemented by measurements of soil temperature (Ts, in Celsius degrees), soil volumetric water content (VWC, in %), atmospheric pressure (Pr, in hPa), air temperature (Ta, in Celsius degrees), air moisture (RH, in %), and solar radiance (rs , in W/m2). The Green Fractional Cover (GFC, between 0 and 1) of the vegetation inscribed within the sampling surface was estimated from digital RGB pictures taken at nadir. Measurements were divided into 4 classes, depending on the prevailing cover type: bare soil (BS), vascular vegetation (V), non-vascular vegetation (NV, including lichens, mosses and bacterial soil crust) and mix of vascular and non-vascular vegetation (MIX). Class V was further split into 5 subclasses: Carex spp. (CX), Dryas octopetala (DR), Salix Polaris (SL), Saxifraga oppostifolia (SX) and Silene acaulis (SI).
DOI: 10.5517/ccdc.csd.cc29ghx6
title: CCDC 2129108: Experimental Crystal Structure Determination

description: Related Article: Xiang Li, Pinhong Chen, Guosheng Liu|2022|Chem.Commun.|58|2544|doi:10.1039/D1CC07092D
description: Related Article: Pinhong Chen|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc29gmr5
title: CCDC 2129227: Experimental Crystal Structure Determination

description: Related Article: Jared P. Smit|2021|CSD Communication|||
DOI: 10.5281/zenodo.6395931
title: SuperDARN data in netCDF format (2016-Jan)

description: 2016-Jan SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication. The RST is available here: https://github.com/SuperDARN/rst The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below. Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview) <strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong> 'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6392337
title: SuperDARN data in netCDF format (2016-Feb)

description: 2016-Feb SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6385872
title: SuperDARN data in netCDF format (2016-Oct)

description: 2016-Oct SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6386530
title: SuperDARN data in netCDF format (2017-Feb)

description: 2017-Feb SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6388206
title: SuperDARN data in netCDF format (2016-Sep)

description: 2016-Sep SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6387764
title: SuperDARN data in netCDF format (2017-Jan)

description: 2017-Jan SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6391599
title: SuperDARN data in netCDF format (2016-Aug)

description: 2016-Aug SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6416069
title: Remotely Sensing River Greenhouse Gas Exchange Velocity Using the SWOT Satellite

description: Scripts and results for our "Remotely Sensing River Greenhouse Gas Exchange Velocity Using the SWOT Satellite" manuscript. Consult the README file for a more detailed description of the data, results, and scripts.
DOI: 10.6084/m9.figshare.16943833.v4
title: Data & Scripts FigureS3

description: Data and scripts to generate Figure S3.<br>
DOI: 10.5281/zenodo.6418235
title: IoT nodes movement and job requests

description: This dataset contains information about the movements of IoT nodes in an urban area with a 22KM x 8 KM dimension. The workload that is created by these nodes is originated from the requests submitted by these IoT nodes. Every event is logged with a timestamp along with other required information. Dataset files are in CSV format.
DOI: 10.5281/zenodo.6344515
title: Peaks N-body z=0.65

description: numpy.ndarray containing the peak counts distributions computed on weak lensing convergence maps at z=0.65 obtained by interpolating the maps from the MassiveNus simulations at z=0.5 and z=1.0. These peaks distributions are obtained assuming a CFIS-like noise with shape noise = 0.44 and number galaxy density = 7/arcmin^2.
DOI: 10.5281/zenodo.6344514
title: Peaks N-body z=0.65

description: numpy.ndarray containing the peak counts distributions computed on weak lensing convergence maps at z=0.65 obtained by interpolating the maps from the MassiveNus simulations at z=0.5 and z=1.0. These peaks distributions are obtained assuming a CFIS-like noise with shape noise = 0.44 and number galaxy density = 7/arcmin^2.
DOI: 10.6084/m9.figshare.19525681.v1
title: Table_S4_158_samples

description: Bacterial samples (158, 5.3% of total) with a much higher aPMNLE for all proteins than the chromosomal ones alone. This indicated that the plasmid-related proteins contributed more indirect PPIs.
DOI: 10.5281/zenodo.6418359
title: Data for rehydrated experiment of isotopic offset

description: This is the dataset for rehydration experiment for isotopic offest evaluation of 12 plants which published in GRL.
DOI: 10.5281/zenodo.6418358
title: Data for rehydrated experiment of isotopic offset

description: This is the dataset for rehydration experiment for isotopic offest evaluation of 12 plants which published in GRL.
DOI: 10.6084/m9.figshare.16943818.v5
title: Data & Scripts Figure 4

description: Data and scripts to generate Figure 4 and SuppTable 7Please see README.txt file<br>
DOI: 10.3886/e160142
title: Data and Code for: Cash is Alive: How Economists Explain Holding and Use of Cash

description: Research on holding and use of cash involves many aspects such as: reasons for holding and hoarding cash, transactional demand for cash, cash management, type of spending paid with cash, type of consumer who pays cash, merchant acceptance, how consumers get cash, currency denominations, legal aspects, cash substitutes, and cost of cash. The purpose of this article is to introduce the reader to some of the research economists do on consumer holding and use of cash.<br><br>
DOI: 10.3886/e160142v1
title: Data and Code for: Cash is Alive: How Economists Explain Holding and Use of Cash

description: Research on holding and use of cash involves many aspects such as: reasons for holding and hoarding cash, transactional demand for cash, cash management, type of spending paid with cash, type of consumer who pays cash, merchant acceptance, how consumers get cash, currency denominations, legal aspects, cash substitutes, and cost of cash. The purpose of this article is to introduce the reader to some of the research economists do on consumer holding and use of cash.<br><br>
DOI: 10.6073/pasta/0daf62f03df4ebad013eb7849ba55e01
title: Eriophorum vaginatum tiller nitrogen content at the 2007 Anaktuvuk River fire scar and nearby unburned tundra measured in 2019.

description: Tillers from 24 Eriophorum vaginatum individuals were sampled in late July 2019 to examine differences in percent nitrogen between previously burned (Anaktuvuk River Fire) and unburned tussocks at a nearby unburned control site. At the burned site tussocks exhibiting evidence of rodent grazing were also sampled to separate herbivore effects from those of the fire. From each tussock, 3-4 new leaves were sampled (as indicated by lack of brown tips) and dried at 60°C for 24 hours, before being ground and analyzed for percent nitrogen. The goals of the project were to examine the impact of post-fire changes in plant community composition, nutrient quality and structure on habitat suitability and rodent herbivore activity in response to a large, severe, and unprecedented fire in northern Alaska moist acidic tundra.