cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16802503.v3
title: Lévy-noise versus Gaussian-noise-induced Transitions in the Ghil-Sellers Energy Balance Model

description: We provide here the majority of the dataset used for the figures of the paper:<br><br>"Lévy-noise versus Gaussian-noise-induced Transitions in the Ghil-Sellers Energy Balance Model" by Lucarini V., Serdukova L, and Margazoglou G. (2021)<br><br>Some datafiles are sufficient to reproduce directly the figures, while others are the raw data one needs to reproduce the figures using the methodologies described in the paper.<br><br>For more information or any question, or access to the particular scripts <br>we implemented to produce the plots, please contact:<br><br>Valerio Lucarini at v.lucarini@reading.ac.uk or<br>Larissa Serdukova at l.i.serdukova@reading.ac.uk or<br>Georgios Margazoglou at g.margazoglou@reading.ac.uk<br>Thank you!<br>
DOI: 10.25919/d745-vt84
title: Parkes observations for project P1101 semester 2021OCTS_18

description: We propose to carry out fortnightly monitoring of a very active repeater, FRB~190520, with the Parkes UWL system. Our current observations show that FRB~190520 is not only the most active FRB that can be observed with Parkes, but also shows unique behaviour at 2 to 3 GHz frequency. This makes UWL the ideal instrument to carry out in-depth studies of this repeating FRB. With this program, we expect to detect a large sample of bursts from FRB~190520, and in collaboration with the FAST telescope we will study emission properties, fluence distributions and polarisation properties over an extremely wide bandwidth with high sensitivity.
DOI: 10.5066/p972p42z
title: Streamflow benchmark locations for hydrologic model evaluation within the conterminous United States (cobalt gages)

description: A list of stream gages within the conterminous United States that will serve as the initial list of sites (version 1.0) used for streamflow benchmarking of hydrologic models. Sites within this list were chosen based on their presence in the GAGES-II dataset, their availability of modeled streamflow data from the most recent version of the National Hydrologic Model application of Precipitation-Runoff Modeling System v1.0, and their availability of modeled streamflow data from the most recent version of the NOAA National Water Model application of WRF-hydro version 2.1 retrospective dataset.
DOI: 10.25345/c5hq3s28t
title: MassIVE MSV000089216 - LC-MS/MS based (pos mode) non-targeted Metabolomics from PPL solid-extracted DOM from EXPORTS ReRun
title: LC-MS/MS based (pos mode) non-targeted Metabolomics from PPL solid-extracted DOM from EXPORTS. Rerun of Samples after 2 month storage at -80 C.
DOI: 10.5066/p9wydyx0
title: Electrical resistivity tomography in the Air Force Research Laboratory NE Groundwater Area, Edwards Air Force Base, California 2020

description: Edwards Air Force Base (EAFB) is located about eight kilometers (km) northeast of the city of Lancaster, California. In 1990 EAFB was placed on the U.S. Environmental Protection Agency's National priorities list due to the presence of contaminated soil and groundwater. The base was divided into Operable Units (OU) based on location and similar contaminant types (Lahontan Staff Report, 2010). The Air Force Research Laboratory (AFRL) was established in the 1950's, and contains facilities for research, development, testing, and evaluation of rocket propulsion systems (Lahontan Staff Report, 2010; AECOM, 2014), and has been in operation under various names since. Past activities at rocket test stands, evaporation ponds, burn pits, catch basins and leaking waste collection tanks has contaminated the groundwater in the AFRL area (AECOM, 2014). The AFRL occupies roughly 125 square miles (mi^2) on Leuhman Ridge and surrounding areas and is part of OU 4 and 9, roughly 5 kilometers (km) south of the community of Boron. Electrical resistivity Tomography (ERT) is a direct current geophysical method that is used to estimate the subsurface distribution of the electrical resistivity (measured in ohm-meters; ohm-m) of a material, and is based on the assumption that measured electric potentials (voltages) near current carrying electrodes are influenced by the electrical resistivities of the underlying material (Zohdy and others, 1974; Loke, 2000). ERT is a popular technique for subsurface investigations because it is based on simple physical principles and for its efficient data acquisition (Dahlin and Zhou, 2004). A combination of the Dipole-Dipole and Strong Gradient arrays was used for this survey and combined to create an optimized dataset (Stummer and others, 2004). The Dipole-Dipole array type yields a high precision dataset, particularly of vertical structures, but can exhibit lower signal to noise ratios (Dahlin and Zhou, 2004; Binley and Kemna, 2005), while the Strong Gradient array provides more complete spatial coverage, and high signal to noise ratio with increased acquisition efficiency (Dahlin and Zhou, 2004; Dahlin and Zhou, 2006, Advanced Geosciences Inc., 2009). The U.S. Geological Survey (USGS) and Air Force Civil Engineering Center (AFCEC) have entered into a cooperative agreement to refine conceptual models of the geology in the NE AFRL. As part of these efforts, two electrical resistivity tomography (ERT) surveys were done in the vicinity of the Leuhman and Spring Faults identified by Dibblee (1960) to better determine the position of these faults. ERT profile AFRL7 was done in the vicinity of the Leuhman Fault, and profile AFRL8 was done in the vicinity of the Spring Fault.
DOI: 10.5517/ccdc.csd.cc2bbjz6
title: CCDC 2155088: Experimental Crystal Structure Determination

description: Related Article: Y. Lin, J.-P. Yu|2022|IUCrData|7|x220231|doi:10.1107/S2414314622002310
DOI: 10.5517/ccdc.csd.cc2bdxth
title: CCDC 2157377: Experimental Crystal Structure Determination

description: Related Article: Martin Nieger, Katharina Gottfried, Siegfried R. Waldvogel|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bf3mj
title: CCDC 2157557: Experimental Crystal Structure Determination

description: Related Article: Frank R. Fronczek|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bf6tt
title: CCDC 2157656: Experimental Crystal Structure Determination

description: Related Article: W. Clegg, J.D. Kennedy, M.G.S. Londesborough|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bf6zz
title: CCDC 2157661: Experimental Crystal Structure Determination

description: Related Article: Michael Bolte|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bf7jk
title: CCDC 2157678: Experimental Crystal Structure Determination

description: Related Article: W. Clegg, J.D. Kennedy, M.G.S. Londesborough|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bflky
title: CCDC 2158020: Experimental Crystal Structure Determination

description: Related Article: Frank R. Fronczek|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bfzzr
title: CCDC 2158405: Experimental Crystal Structure Determination

description: Related Article: Hannes Vitze, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg00v
title: CCDC 2158406: Experimental Crystal Structure Determination

description: Related Article: Hannes Vitze, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg01w
title: CCDC 2158407: Experimental Crystal Structure Determination

description: Related Article: Hannes Vitze, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg02x
title: CCDC 2158408: Experimental Crystal Structure Determination

description: Related Article: Matthias Wagner, Michael Bolte|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg03y
title: CCDC 2158409: Experimental Crystal Structure Determination

description: Related Article: Susanne Bieller, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg04z
title: CCDC 2158410: Experimental Crystal Structure Determination

description: Related Article: Susanne Bieller, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg050
title: CCDC 2158411: Experimental Crystal Structure Determination

description: Related Article: Kerstin Kunz, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg0d7
title: CCDC 2158418: Experimental Crystal Structure Determination

description: Related Article: Kerstin Kunz, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5281/zenodo.6423262
title: de novo transcriptome assemblies for Peperomia dahlstedtii and Peperomia pellucida

description: <em>De novo</em> transcriptome assemblies generated using Trinity using young leaf tissue from <em>Peperomia dahlstedtii</em> and <em>Peperomia pellucida</em>.
DOI: 10.5281/zenodo.6423261
title: de novo transcriptome assemblies for Peperomia dahlstedtii and Peperomia pellucida

description: <em>De novo</em> transcriptome assemblies generated using Trinity using young leaf tissue from <em>Peperomia dahlstedtii</em> and <em>Peperomia pellucida</em>.
DOI: 10.6084/m9.figshare.17086109
title: LncRNAs annotations

description: The genomic coordinates of lncRNAs of BY4742 and SEY6210 yeast strains.
DOI: 10.5281/zenodo.6423286
title: Ecuador Real State data set

description: <pre>This set of data contains information on different characteristics of the properties for rent on the website https://arriendayvende.com, through which analyzes can be carried out on the distribution of prices according to location, area, among others.</pre>
DOI: 10.6084/m9.figshare.19543906
title: Species detected by three different methodologies in forests and savannas of the Pantanal, Poconé, MT, Brazil.

description: Supplemental file<strong> – </strong>Species detected by three different methodologies in sites of forest and savanna over the dry period of 2014 in one region of northeastern Pantanal, Mato Grosso, Brazil. MN – mist net; PC - point count; ARU – autonomous acoustic recording.
DOI: 10.6084/m9.figshare.19543906.v1
title: Species detected by three different methodologies in forests and savannas of the Pantanal, Poconé, MT, Brazil.

description: Supplemental file<strong> – </strong>Species detected by three different methodologies in sites of forest and savanna over the dry period of 2014 in one region of northeastern Pantanal, Mato Grosso, Brazil. MN – mist net; PC - point count; ARU – autonomous acoustic recording.
DOI: 10.1184/r1/19543819
title: Data from The dorsal visual pathway represents object-centered spatial relations for object recognition

description: Data repository for the manuscript: <strong>The dorsal visual pathway represents object-centered spatial relations</strong> <strong>for object recognition</strong>
DOI: 10.5441/001/1.h0t27719/1
title: White-bearded wildebeest in Kenya-accessory

description: Stabach JA, Hughey LF, Crego RD, Fleming CH, Hopcraft JGC, Leimgruber P, Morrison TA, Ogutu JO, Reid RS, Worden JS, Boone RB. 2022. Increasing anthropogenic disturbance restricts wildebeest movement across East African grazing systems. Front Ecol Evol. doi:10.3389/fevo.2022.846171
description: The ability to move is essential for animals to find mates, escape predation, and meet energy and water demands. This is especially important across grazing systems where vegetation productivity can vary drastically between seasons or years. With grasslands undergoing significant changes due to climate change and anthropogenic development, there is an urgent need to determine the relative impacts of these pressures on the movement capacity of native herbivores. To measure these impacts, we fitted 36 white-bearded wildebeest (Connochaetes taurinus) with GPS collars across three study areas in southern Kenya (Amboseli Basin, Athi-Kaputiei Plains, and Mara) to test the relationship between movement (e.g., directional persistence, speed, home range crossing time) and gradients of vegetation productivity (i.e., NDVI) and anthropogenic disturbance. As expected, wildebeest moved the most (21.0 km day–1; CI: 18.7–23.3) across areas where movement was facilitated by low human footprint and necessitated by low vegetation productivity (Amboseli Basin). However, in areas with moderate vegetation productivity (Athi-Kaputiei Plains), wildebeest moved the least (13.3 km day–1; CI: 11.0–15.5). This deviation from expectations was largely explained by impediments to movement associated with a large human footprint. Notably, the movements of wildebeest in this area were also less directed than the other study populations, suggesting that anthropogenic disturbance (i.e., roads, fences, and the expansion of settlements) impacts the ability of wildebeest to move and access available resources. In areas with high vegetation productivity and moderate human footprint (Mara), we observed intermediate levels of daily movement (14.2 km day–1; CI: 12.3–16.1). Wildebeest across each of the study systems used grassland habitats outside of protected areas extensively, highlighting the importance of unprotected landscapes for conserving mobile species. These results provide unique insights into the interactive effects of climate and anthropogenic development on the movements of a dominant herbivore in East Africa and present a cautionary tale for the development of grazing ecosystems elsewhere.
DOI: 10.5441/001/1.h0t27719/2
title: White-bearded wildebeest in Kenya-gps

description: Stabach JA, Hughey LF, Crego RD, Fleming CH, Hopcraft JGC, Leimgruber P, Morrison TA, Ogutu JO, Reid RS, Worden JS, Boone RB. 2022. Increasing anthropogenic disturbance restricts wildebeest movement across East African grazing systems. Front Ecol Evol. doi:10.3389/fevo.2022.846171
description: The ability to move is essential for animals to find mates, escape predation, and meet energy and water demands. This is especially important across grazing systems where vegetation productivity can vary drastically between seasons or years. With grasslands undergoing significant changes due to climate change and anthropogenic development, there is an urgent need to determine the relative impacts of these pressures on the movement capacity of native herbivores. To measure these impacts, we fitted 36 white-bearded wildebeest (Connochaetes taurinus) with GPS collars across three study areas in southern Kenya (Amboseli Basin, Athi-Kaputiei Plains, and Mara) to test the relationship between movement (e.g., directional persistence, speed, home range crossing time) and gradients of vegetation productivity (i.e., NDVI) and anthropogenic disturbance. As expected, wildebeest moved the most (21.0 km day–1; CI: 18.7–23.3) across areas where movement was facilitated by low human footprint and necessitated by low vegetation productivity (Amboseli Basin). However, in areas with moderate vegetation productivity (Athi-Kaputiei Plains), wildebeest moved the least (13.3 km day–1; CI: 11.0–15.5). This deviation from expectations was largely explained by impediments to movement associated with a large human footprint. Notably, the movements of wildebeest in this area were also less directed than the other study populations, suggesting that anthropogenic disturbance (i.e., roads, fences, and the expansion of settlements) impacts the ability of wildebeest to move and access available resources. In areas with high vegetation productivity and moderate human footprint (Mara), we observed intermediate levels of daily movement (14.2 km day–1; CI: 12.3–16.1). Wildebeest across each of the study systems used grassland habitats outside of protected areas extensively, highlighting the importance of unprotected landscapes for conserving mobile species. These results provide unique insights into the interactive effects of climate and anthropogenic development on the movements of a dominant herbivore in East Africa and present a cautionary tale for the development of grazing ecosystems elsewhere.
DOI: 10.25345/c5cz32842
title: MassIVE MSV000089217 - A mRNA motif mediates TGF-beta1 upregulation of NEU3 translation in human lung fibroblasts
title: 4 HLF cell lines (Labeled as F2, F5, M2, and M3; from 2 females and 2 males) were treated with or without TGF-beta 1 for 48 hours. After the TGF-beta 1 treatment, 1 million cells were lysed and the cell lysate which contained 40 micrograms proteins was used for proteomics assay. F2- (F2 cell line with no treatment) F2+ (F2 cell line with TGF-beta 1 treatment) 835725=F2-, 835725=F2+, 835726=F5-, 835727=F5+, 835728=M2-, 835729=M2+, 835730=M3-, 835731=M3+
DOI: 10.5519/qd.wxcvw6hh
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5441/001/1.h0t27719/3
title: White-bearded wildebeest in Kenya-reference-data

description: Stabach JA, Hughey LF, Crego RD, Fleming CH, Hopcraft JGC, Leimgruber P, Morrison TA, Ogutu JO, Reid RS, Worden JS, Boone RB. 2022. Increasing anthropogenic disturbance restricts wildebeest movement across East African grazing systems. Front Ecol Evol. doi:10.3389/fevo.2022.846171
description: The ability to move is essential for animals to find mates, escape predation, and meet energy and water demands. This is especially important across grazing systems where vegetation productivity can vary drastically between seasons or years. With grasslands undergoing significant changes due to climate change and anthropogenic development, there is an urgent need to determine the relative impacts of these pressures on the movement capacity of native herbivores. To measure these impacts, we fitted 36 white-bearded wildebeest (Connochaetes taurinus) with GPS collars across three study areas in southern Kenya (Amboseli Basin, Athi-Kaputiei Plains, and Mara) to test the relationship between movement (e.g., directional persistence, speed, home range crossing time) and gradients of vegetation productivity (i.e., NDVI) and anthropogenic disturbance. As expected, wildebeest moved the most (21.0 km day–1; CI: 18.7–23.3) across areas where movement was facilitated by low human footprint and necessitated by low vegetation productivity (Amboseli Basin). However, in areas with moderate vegetation productivity (Athi-Kaputiei Plains), wildebeest moved the least (13.3 km day–1; CI: 11.0–15.5). This deviation from expectations was largely explained by impediments to movement associated with a large human footprint. Notably, the movements of wildebeest in this area were also less directed than the other study populations, suggesting that anthropogenic disturbance (i.e., roads, fences, and the expansion of settlements) impacts the ability of wildebeest to move and access available resources. In areas with high vegetation productivity and moderate human footprint (Mara), we observed intermediate levels of daily movement (14.2 km day–1; CI: 12.3–16.1). Wildebeest across each of the study systems used grassland habitats outside of protected areas extensively, highlighting the importance of unprotected landscapes for conserving mobile species. These results provide unique insights into the interactive effects of climate and anthropogenic development on the movements of a dominant herbivore in East Africa and present a cautionary tale for the development of grazing ecosystems elsewhere.
DOI: 10.5519/qd.tnnutr7k
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (65 records)
DOI: 10.48366/r38907
title: Application of deep learning for retinal image analysis: A review [ORKG]

description: Machine-readable description of retinal image analysis review.
DOI: 10.6084/m9.figshare.3761562.v2181
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: 10.6084/m9.figshare.19333583
title: Dimensional Stability Method Comparison Raw Data

description: Raw data from a series of tests comparing 4 different dimensional stability tests in wood.The following wood types were compared:Unmodifed radiata pine ('Control')Furfurylated radiata pine ('FA')Commercial (Accoya) acetylated radiata pine ('AC')Commercial (ThermoWood) thermally modified radiata pine ('TH')<br>Four test methods were compared:Short term water soaking ('Swellometer')Repeated water soaking (to calculate Anti-shrink efficiency)Long term exposure to humid airShort term exposure to humid air
DOI: 10.6084/m9.figshare.19333583.v2
title: Dimensional Stability Method Comparison Raw Data

description: Raw data from a series of tests comparing 4 different dimensional stability tests in wood.The following wood types were compared:Unmodifed radiata pine ('Control')Furfurylated radiata pine ('FA')Commercial (Accoya) acetylated radiata pine ('AC')Commercial (ThermoWood) thermally modified radiata pine ('TH')<br>Four test methods were compared:Short term water soaking ('Swellometer')Repeated water soaking (to calculate Anti-shrink efficiency)Long term exposure to humid airShort term exposure to humid air
DOI: 10.6084/m9.figshare.19333583.v1
title: Dimensional Stability Method Comparison Raw Data

description: Raw data from a series of tests comparing 4 different dimensional stability tests in wood.The following wood types were compared:Unmodifed radiata pine ('Control')Furfurylated radiata pine ('FA')Commercial (Accoya) acetylated radiata pine ('AC')Commercial (ThermoWood) thermally modified radiata pine ('TH')<br>Four test methods were compared:Short term water soaking ('Swellometer')Repeated water soaking (to calculate Anti-shrink efficiency)Long term exposure to humid airShort term exposure to humid air
DOI: 10.5517/ccdc.csd.cc2bg0f8
title: CCDC 2158419: Experimental Crystal Structure Determination

description: Related Article: Kerstin Kunz, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg0g9
title: CCDC 2158420: Experimental Crystal Structure Determination

description: Related Article: Kai Ruth, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg0kd
title: CCDC 2158423: Experimental Crystal Structure Determination

description: Related Article: Kerstin Kunz, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg0lf
title: CCDC 2158424: Experimental Crystal Structure Determination

description: Related Article: Sebastian Scheuermann, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg0mg
title: CCDC 2158425: Experimental Crystal Structure Determination

description: Related Article: Kai Ruth, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg0nh
title: CCDC 2158426: Experimental Crystal Structure Determination

description: Related Article: Kerstin Kunz, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg0qk
title: CCDC 2158428: Experimental Crystal Structure Determination

description: Related Article: Thorsten Morawitz, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg0rl
title: CCDC 2158429: Experimental Crystal Structure Determination

description: Related Article: Julia Heilmann, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg0sm
title: CCDC 2158430: Experimental Crystal Structure Determination

description: Related Article: Kerstin Kunz, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bg13z
title: CCDC 2158440: Experimental Crystal Structure Determination

description: Related Article: Kai Ruth, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc29bgvz
title: CCDC 2125231: Experimental Crystal Structure Determination

description: Related Article: Daniel Franz, Michael Bolte|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bjtl9
title: CCDC 2161121: Experimental Crystal Structure Determination

description: Related Article: Weiqiong Zhao, Bolin Pan, Chao Wei|2022|J.Indian Chem.Soc.|99|100448|doi:10.1016/j.jics.2022.100448
DOI: 10.5517/ccdc.csd.cc2bk5ps
title: CCDC 2161465: Experimental Crystal Structure Determination

description: Related Article: N.H. Metwally, G.H. Elgemeie, P.G. Jones|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|445|doi:10.1107/S2056989022003279