cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3761562.v2123
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5066/p96hnsnl
title: U-Pb zircon data for: The Poncha Pass and Deadman Creek areas, northern Sangre de Cristo mountains of south-central Colorado

description: Geologic mapping, characterization of geologic structures, and sampling for geochronology was completed in two areas of the northwestern Sangre de Cristo mountains from 2011 through 2017. This data release provides the raw analytical data, metadata and sample information for 20 zircon U-Pb age analyses from laser ablation-inductively coupled plasma mass spectrometry (LA-ICPMS). The two areas include the Poncha Pass area where the entire 71/2' Poncha Pass quadrangle and parts of five other quadrangles (Mount Ouray, Maysville, Salida West, Salida East, and Wellsville) were mapped at a scale of 1:24,000 (see Minor and others, 2019). The Deadman thrust fault is the second area, approximately 80 km southwest of the Poncha Pass area, and has been preliminarily mapped at a scale of 1:2,000. Ten new U-Pb ages were determined for each area and include Proterozoic metavolcanic, metasedimentary, and metaigneous rocks as well as non-metamorphosed felsic intrusive rocks of upper Mesozoic-Cenozoic age in the Poncha area. Rocks dated in the Deadman area include Proterozoic basement rocks, detrital zircons in Paleozoic sedimentary rocks, and Mesozoic- Cenozoic felsic intrusive rocks. Minor, S.A., Caine, J.S., Ruleman, C.A., Fridrich, C.J., Chan, C.F., Brandt, T.R., Holm- Denoma, C.S., Morgan, L.E., Cosca, M.A., and Grauch, V.J.S., 2019, Geologic Map of the Poncha Pass Area, Chaffee, Fremont, and Saguache Counties, Colorado: U.S. Geological Survey Scientific Investigations Map 3436, 3 sheets, scale 1:24,000, https://doi.org/10.3133/sim3436
DOI: 10.5281/zenodo.5933726
title: GPUAcceleratedTracking Raw Data

description: This contains the original raw data collected from the benchmarking experiments carried out on the two platforms specified in the paper.
DOI: 10.5281/zenodo.5933725
title: GPUAcceleratedTracking Raw Data

description: This contains the original raw data collected from the benchmarking experiments carried out on the two platforms specified in the paper.
DOI: 10.5066/f7f18x8s
title: Updated aeromagnetic and gravity anomaly compilations and elevation-bathymetry models over Lake Superior

description: New gravity and magnetic compilations and elevation-bathymetry models have been compiled for the Lake Superior region. These data provide continuous sets of observations for geologic interpretations spanning political boundaries such as US States and the US-Canada border where bedrock geology is largely concealed beneath glacial deposits and surface water. These data are providing constraints for on-going 3D geologic modeling of the Midcontinent Rift System and are helping to understand the metallogeny of the region.
DOI: 10.25505/fiz.icsd.cc20jz0k
title: CSD 1863348: Experimental Crystal Structure Determination

description: Related Article: K. Rajkumar, S. Sivakumar, R. Arulraj, M. Kaur, J.P. Jasinski, A. Manimekalai, A. Thiruvalluvar|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|483|doi:10.1107/S2056989018003766
description: Related Article: R.M. Danisi, T. Armbruster|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|483|doi:10.1107/S2052520618011423
DOI: 10.25505/fiz.icsd.cc20jz1l
title: CSD 1863349: Experimental Crystal Structure Determination

description: Related Article: K. Rajkumar, S. Sivakumar, R. Arulraj, M. Kaur, J.P. Jasinski, A. Manimekalai, A. Thiruvalluvar|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|483|doi:10.1107/S2056989018003766
description: Related Article: R.M. Danisi, T. Armbruster|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|483|doi:10.1107/S2052520618011423
DOI: 10.25505/fiz.icsd.cc20n8sr
title: CSD 1866534: Experimental Crystal Structure Determination

description: Related Article: Thomas Friedrich Fässler, Benedikt J. L. Witzel, Wilhelm Klein, Jasmin V. Dums, Marina Boyko|2019|Angew.Chem.,Int.Ed.|58|12908|doi:10.1002/anie.201907127
DOI: 10.25505/fiz.icsd.cc20n8ts
title: CSD 1866535: Experimental Crystal Structure Determination

description: Related Article: Thomas Friedrich Fässler, Benedikt J. L. Witzel, Wilhelm Klein, Jasmin V. Dums, Marina Boyko|2019|Angew.Chem.,Int.Ed.|58|12908|doi:10.1002/anie.201907127
DOI: 10.25505/fiz.icsd.cc20pfkq
title: CSD 1867643: Experimental Crystal Structure Determination

description: Related Article: Minfeng Lü, Jianhua Jiang, Bei Zhu, Yuwei Zhao, Tianyu Zhu, Haoming Yang, Yong Jin, Houria Kabbour, Kwang-Yong Choi, William T. A. Harrison|2020|Dalton Trans.|49|2234|doi:10.1039/C9DT04176A
DOI: 10.5517/ccdc.csd.cc20vgv6
title: CCDC 1872488: Experimental Crystal Structure Determination

description: Related Article: Shigeru Arai|2018|CSD Communication|||
description: Related Article: Shigeru Arai, Koki Matsumoto, Atsushi Nishida|2019|Tetrahedron|75|1145|doi:10.1016/j.tet.2018.12.031
DOI: 10.5517/ccdc.csd.cc20vmn5
title: CCDC 1872637: Experimental Crystal Structure Determination

description: Related Article: Shigeru Arai|2018|CSD Communication|||
description: Related Article: Shigeru Arai, Koki Matsumoto, Atsushi Nishida|2019|Tetrahedron|75|1145|doi:10.1016/j.tet.2018.12.031
DOI: 10.25505/fiz.icsd.cc20vm3m
title: CSD 1872620: Experimental Crystal Structure Determination

description: Related Article: Magdalena Priestner, Gerald Singer, Matthias Weil, Reinhard K. Kremer, Eugen Libowitzky|2019|J.Solid State Chem.|277|209|doi:10.1016/j.jssc.2019.06.005
DOI: 10.5517/ccdc.csd.cc20vx60
title: CCDC 1872902: Experimental Crystal Structure Determination

description: Related Article: Shigeru Arai|2018|CSD Communication|||
description: Related Article: Shigeru Arai, Koki Matsumoto, Atsushi Nishida|2019|Tetrahedron|75|1145|doi:10.1016/j.tet.2018.12.031
DOI: 10.5517/ccdc.csd.cc20vx71
title: CCDC 1872903: Experimental Crystal Structure Determination

description: Related Article: Shigeru Arai|2018|CSD Communication|||
description: Related Article: Shigeru Arai, Koki Matsumoto, Atsushi Nishida|2019|Tetrahedron|75|1145|doi:10.1016/j.tet.2018.12.031
DOI: 10.5517/ccdc.csd.cc20vx82
title: CCDC 1872904: Experimental Crystal Structure Determination

description: Related Article: Shigeru Arai|2018|CSD Communication|||
description: Related Article: Shigeru Arai, Koki Matsumoto, Atsushi Nishida|2019|Tetrahedron|75|1145|doi:10.1016/j.tet.2018.12.031
DOI: 10.25505/fiz.icsd.cc20xz0y
title: CSD 1874880: Experimental Crystal Structure Determination

description: Related Article: R. Vishnupriya, C. Selva Meenatchi, J. Suresh, R.V. Sumesh, R.R. Kumar, P.L.N. Lakshman|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|660|doi:10.1107/S2056989018005455
description: Related Article: P. Fabrykiewicz, R. Przeniosło, I. Sosnowska, F. Fauth|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|660|doi:10.1107/S2052520618014968
DOI: 10.25505/fiz.icsd.cc20xz1z
title: CSD 1874881: Experimental Crystal Structure Determination

description: Related Article: R. Vishnupriya, C. Selva Meenatchi, J. Suresh, R.V. Sumesh, R.R. Kumar, P.L.N. Lakshman|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|660|doi:10.1107/S2056989018005455
description: Related Article: P. Fabrykiewicz, R. Przeniosło, I. Sosnowska, F. Fauth|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|660|doi:10.1107/S2052520618014968
DOI: 10.25505/fiz.icsd.cc20xz20
title: CSD 1874882: Experimental Crystal Structure Determination

description: Related Article: R. Vishnupriya, C. Selva Meenatchi, J. Suresh, R.V. Sumesh, R.R. Kumar, P.L.N. Lakshman|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|660|doi:10.1107/S2056989018005455
description: Related Article: P. Fabrykiewicz, R. Przeniosło, I. Sosnowska, F. Fauth|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|660|doi:10.1107/S2052520618014968
DOI: 10.25505/fiz.icsd.cc20xz31
title: CSD 1874883: Experimental Crystal Structure Determination

description: Related Article: R. Vishnupriya, C. Selva Meenatchi, J. Suresh, R.V. Sumesh, R.R. Kumar, P.L.N. Lakshman|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|660|doi:10.1107/S2056989018005455
description: Related Article: P. Fabrykiewicz, R. Przeniosło, I. Sosnowska, F. Fauth|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|660|doi:10.1107/S2052520618014968
DOI: 10.25505/fiz.icsd.cc20xz42
title: CSD 1874884: Experimental Crystal Structure Determination

description: Related Article: R. Vishnupriya, C. Selva Meenatchi, J. Suresh, R.V. Sumesh, R.R. Kumar, P.L.N. Lakshman|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|660|doi:10.1107/S2056989018005455
description: Related Article: P. Fabrykiewicz, R. Przeniosło, I. Sosnowska, F. Fauth|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|660|doi:10.1107/S2052520618014968
DOI: 10.25505/fiz.icsd.cc20xz53
title: CSD 1874885: Experimental Crystal Structure Determination

description: Related Article: R. Vishnupriya, C. Selva Meenatchi, J. Suresh, R.V. Sumesh, R.R. Kumar, P.L.N. Lakshman|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|660|doi:10.1107/S2056989018005455
description: Related Article: P. Fabrykiewicz, R. Przeniosło, I. Sosnowska, F. Fauth|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|660|doi:10.1107/S2052520618014968
DOI: 10.25505/fiz.icsd.cc20xz64
title: CSD 1874886: Experimental Crystal Structure Determination

description: Related Article: R. Vishnupriya, C. Selva Meenatchi, J. Suresh, R.V. Sumesh, R.R. Kumar, P.L.N. Lakshman|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|660|doi:10.1107/S2056989018005455
description: Related Article: P. Fabrykiewicz, R. Przeniosło, I. Sosnowska, F. Fauth|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|660|doi:10.1107/S2052520618014968
DOI: 10.25505/fiz.icsd.cc20xz75
title: CSD 1874887: Experimental Crystal Structure Determination

description: Related Article: R. Vishnupriya, C. Selva Meenatchi, J. Suresh, R.V. Sumesh, R.R. Kumar, P.L.N. Lakshman|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|660|doi:10.1107/S2056989018005455
description: Related Article: P. Fabrykiewicz, R. Przeniosło, I. Sosnowska, F. Fauth|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|660|doi:10.1107/S2052520618014968
DOI: 10.25505/fiz.icsd.cc20xz86
title: CSD 1874888: Experimental Crystal Structure Determination

description: Related Article: R. Vishnupriya, C. Selva Meenatchi, J. Suresh, R.V. Sumesh, R.R. Kumar, P.L.N. Lakshman|2018|Acta Crystallogr.,Sect.E:Cryst.Commun.|74|660|doi:10.1107/S2056989018005455
description: Related Article: P. Fabrykiewicz, R. Przeniosło, I. Sosnowska, F. Fauth|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|660|doi:10.1107/S2052520618014968
DOI: 10.25345/c5ng4r
title: MassIVE MSV000088754 - Shotgun proteomics of soybean root nodules infected by Bradyrhizobium japonicum
title: Global bottom-up proteomics analysis of proteins purified from soybean root nodules infected with either WT or nifH- mutant Bradyrhizobium japonicum. Nine glycoproteins containing Lewis-a N-glycans, with 3 distinct Lewis-a epitopes (Hex:5 HexNAc:4 dHex:3 Pent:1, Hex:4 HexNAc:4 dHex:2 Pent:1, and Hex:4 HexNAc:3 dHex:2 Pent:1) were observed. Proteins purified from WT and nifH- infected soybean root nodules (five biological replicates each) were reduced using dithiothreitol, alkylated with iodoacetamide and trypsin digested followed by C18 SPE clean-up and LC-MS/MS analysis. Raw data files were processed using FragPipe v17.1, then output files 'combined_modified_peptide.tsv' and 'combined_protein.tsv' were used to identify glycopeptides and for global protein quantitation. These files, along with Excel files containing global quantitation analysis files for soybean nodule (Glycine max) and bacterial (Bradyrhizobium), are available in directory 'Quantification/MSFragger_results'. Glycopeptide data were also processed with PMI Byonic, and Excel file results are available in directory 'Quantification/PMI_Byonic_results'.
DOI: 10.25380/iastate.12644940
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2008

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2008 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.<br><b>Change log</b>: gf_Day2008_188.TIF was replaced and should now open correctly. <br>
DOI: 10.25380/iastate.12644940.v1
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2008

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2008 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.6459086.v2
title: Data for: Formation of Multilayer Cu Islands Embedded beneath the Surface of Graphite: Characterization and Fundamental Insights

description: The file contains raw scanning tunneling microscopy (STM) images and x-ray photoelectron spectroscopy (XPS) spectra. To view and process STM images, the user can use a software called WSxM. To view XPS spectra, the program CASA XPS is recommended. The STM and XPS data uploaded herein are used to generate figures in the published paper, which can be found in J. Phys. Chem. C 2018, 122, 4454-4469.<br><b>curation change log</b>: added link to paper; updated title to distinguish from paper; updated funding metadata - MNO<br>
DOI: 10.25380/iastate.7828334
title: Data for: Squeezed Nanocrystals: Equilibrium Configuration of Metal Clusters Embedded Beneath the Surface of a Layered Material

description: Shapes of functional metallic nanocrystals, typically synthesized either free in solution or supported on surfaces, are key for controlling properties. Here, we consider a novel new class of metallic nanocrystals, copper clusters embedded near the surface of graphite, which can be considered a model system for metals embedded beneath surfaces of layered materials, or beneath supported membranes. We develop a continuum elasticity (CE) model for the equilibrium shape of these islands, and compare its predictions with experimental data. The CE model incorporates appropriate surface energy, adhesion energies, and strain energy. The agreement between the CE model and the data is—with one exception—excellent, both qualitatively and quantitatively, and is achieved with a single adjustable parameter. The model predicts that the embedded island shape is invariant with size, manifest both by constant side slope and by constant aspect ratio. This prediction is rationalized by dimensional analysis of the relevant energetic contributions. The aspect ratio of an embedded Cu cluster is much larger than that of a supported but non-embedded Cu cluster, due to resistance of the graphene membrane to deformation. Experimental data diverge from the model predictions only in the case of the aspect ratio of small islands, below a critical height of ~10 nm. The divergence may be due to bending strain, which is treated only approximately in the model. Strong support for the CE model and its interpretation is provided by additional data for embedded Fe clusters. Most of these observations and insights should be generally applicable to systems where a metal cluster is embedded beneath a layered material or supported membrane, provided that shape equilibration is possible.<br><b>curation change log:</b> added link to paper; updated title to distinguish from paper; updated funding metadata - MNO<br>
DOI: 10.25380/iastate.7828334.v2
title: Data for: Squeezed Nanocrystals: Equilibrium Configuration of Metal Clusters Embedded Beneath the Surface of a Layered Material

description: Shapes of functional metallic nanocrystals, typically synthesized either free in solution or supported on surfaces, are key for controlling properties. Here, we consider a novel new class of metallic nanocrystals, copper clusters embedded near the surface of graphite, which can be considered a model system for metals embedded beneath surfaces of layered materials, or beneath supported membranes. We develop a continuum elasticity (CE) model for the equilibrium shape of these islands, and compare its predictions with experimental data. The CE model incorporates appropriate surface energy, adhesion energies, and strain energy. The agreement between the CE model and the data is—with one exception—excellent, both qualitatively and quantitatively, and is achieved with a single adjustable parameter. The model predicts that the embedded island shape is invariant with size, manifest both by constant side slope and by constant aspect ratio. This prediction is rationalized by dimensional analysis of the relevant energetic contributions. The aspect ratio of an embedded Cu cluster is much larger than that of a supported but non-embedded Cu cluster, due to resistance of the graphene membrane to deformation. Experimental data diverge from the model predictions only in the case of the aspect ratio of small islands, below a critical height of ~10 nm. The divergence may be due to bending strain, which is treated only approximately in the model. Strong support for the CE model and its interpretation is provided by additional data for embedded Fe clusters. Most of these observations and insights should be generally applicable to systems where a metal cluster is embedded beneath a layered material or supported membrane, provided that shape equilibration is possible.<br><b>curation change log:</b> added link to paper; updated title to distinguish from paper; updated funding metadata - MNO<br>
DOI: 10.25380/iastate.7828334.v1
title: Squeezed Nanocrystals: Equilibrium Configuration of Metal Clusters Embedded Beneath the Surface of a Layered Material

description: Shapes of functional metallic nanocrystals, typically synthesized either free in solution or supported on surfaces, are key for controlling properties. Here, we consider a novel new class of metallic nanocrystals, copper clusters embedded near the surface of graphite, which can be considered a model system for metals embedded beneath surfaces of layered materials, or beneath supported membranes. We develop a continuum elasticity (CE) model for the equilibrium shape of these islands, and compare its predictions with experimental data. The CE model incorporates appropriate surface energy, adhesion energies, and strain energy. The agreement between the CE model and the data is—with one exception—excellent, both qualitatively and quantitatively, and is achieved with a single adjustable parameter. The model predicts that the embedded island shape is invariant with size, manifest both by constant side slope and by constant aspect ratio. This prediction is rationalized by dimensional analysis of the relevant energetic contributions. The aspect ratio of an embedded Cu cluster is much larger than that of a supported but non-embedded Cu cluster, due to resistance of the graphene membrane to deformation. Experimental data diverge from the model predictions only in the case of the aspect ratio of small islands, below a critical height of ~10 nm. The divergence may be due to bending strain, which is treated only approximately in the model. Strong support for the CE model and its interpretation is provided by additional data for embedded Fe clusters. Most of these observations and insights should be generally applicable to systems where a metal cluster is embedded beneath a layered material or supported membrane, provided that shape equilibration is possible.
DOI: 10.6073/pasta/19e23e0c161a794a2761d40142c164fc
title: PBG03 Disk pasture meter measurements to estimate plant standing biomass in the Patch-Burn Grazing experiment at Konza Prairie

description: "PBG" datasets are associated with a long-term, large-scale study that is addressing the effects of fire-grazing interactions in the context of a Patch-Burn Grazing management system designed to promote grassland heterogeneity. Effects of patch-burn grazing management on plant and animal diversity and the nature and variety of wildlife habitat are being assessed in two replicate management units, each consisting of three pastures (watersheds) designated C03A/C03B/C03C and C3SA/C3SB/C3SC. In each patch-burn grazing unit, one watershed is burned and two that are left unburned in a given year. The burning treatments are rotated annually so that each pasture is burned every third year. Each patch-burn grazing unit is paired with an annually-burned pasture for comparison with traditional grazing systems (C01A and C1SB). All grazing units are stocked with cow/calf pairs from approximately 1 May until 1 Oct at a stocking density equal to 3.2 ha per cow/calf. To examine the impact of patch burning and grazing in all 8 units, we monitor changes in plant species composition, residual biomass, grassland bird populations, insect populations, small mammal populations, soil nutrients, and stream water quality1 (1C3SA/C3SB/C3SC unit only). The KSU Department of Animal Science monitors cattle performance, including weight gain and body condition to assess the economic feasibility of using patch-burn management on a widespread basis. This dataset includes both the annual calibration data for the disk pasture meter measurements (PBG031) and the actual disk pasture meter measurements in the PBG experiment (PBG032). Measurements were taken at a total of 64 transects (8 watersheds x 4 sites per watershed x 2 pasture meter transects per site). Each cattle-grazed watershed (designated as of May 2011 C3A, C3B, C3C, and C1A) and the four Shane cattle-grazed watersheds (C1B, C3SA, C3SB, and C3SC) includes 4 plant composition sampling transects (A-D). Pasture meter measurements were taken along two transects adjacent and parallel to the plant composition transects in each of these watersheds. Standing biomass samples for pasture meter calibration were also collected near the plant composition transects in the same 8 watersheds.