cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7284/152282
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise LMG0304 using a SeaBird SBE-911+ instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149504
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG0304A using a Ashtech ADU2 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149509
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG0304A using a Trimble Centurion P(Y) instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149510
title: Gyrocompass data collected during research cruise LMG0304A using a SGB Meridian instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.22250926
title: Heifer Feed Efficiency Blood Parameters

description: These data were collected from Angus heifers during a feed efficiency trial. Data were collected using an iStat per manufacturer protocol.
DOI: 10.6084/m9.figshare.22250926.v1
title: Heifer Feed Efficiency Blood Parameters

description: These data were collected from Angus heifers during a feed efficiency trial. Data were collected using an iStat per manufacturer protocol.
DOI: 10.6073/pasta/cb9e7d40ae96a4895d83156a4fb960ef
title: MCR LTER: Coral Reef: Farmerfish gardens help buffer stony corals against marine heat waves, data for Honeycutt et al., PLOS One 2023

description: These data were generated in support of the manuscript: Honeycutt RC, Holbrook SJ, Brooks, AJ, and RJ Schmitt, PLOS One In Moorea, French Polynesia, we evaluated the response and fate of stony coral following a major thermal stress event in 2019 that caused a substantial amount of branching coral (dominantly Pocillopora) to bleach and die. We investigated whether Pocillopora colonies that occurred within territorial gardens protected by the farmerfish Stegastes nigricans were less susceptible to or survived bleaching better than Pocillopora on adjacent, undefended substrate. Bleaching prevalence and severity, which were quantified for &gt;1,100 colonies shortly after they bleached, did not differ between colonies within or outside of defended gardens. By contrast, 399 focal colonies followed for one year revealed that a bleached coral within a garden was a third less likely to suffer complete colony death and, for survivors, about twice as likely to recover to its pre-bleaching cover of living tissue compared to Pocillopora outside of a farmerfish garden. Our findings indicate that while residing in a farmerfish garden may not reduce the bleaching susceptibility of a coral during thermal stress, it does help buffer a bleached coral against severe outcomes. This oasis effect of farmerfish gardens, where survival and recovery of thermally-damaged corals are enhanced, is another mechanism that helps explain why large Pocillopora colonies are far more abundant in farmerfish territories than elsewhere in the lagoons of Moorea, despite gardens being much less common. As such, farmerfish may have a growing role in maintaining the resilience of branching corals as the frequency and intensity of marine heat waves continue to increase. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2023). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
DOI: 10.6073/pasta/b8b3c1a927b7639459a244ff2ceef4e2
title: MCR LTER: Coral Reef: Benthic Water Temperature, ongoing since 2005

description: A continuous time series of benthic water temperature is measured with bottom-mounted thermistors at six sites around the shores of Moorea, on the fringing reef, backreef, and forereef. The forereef temperature is recorded with SBE 39s at 10, 20, 30 and 40 m, starting between 2005 to 2007, except FOR00 starting in 2010. These are ongoing except the 40 m deployments were discontinued after August 2019. The backreef SBE 39s are mounted on plates at 1 m depth at LTER 1 and at 2 m depth at the other five sites. Onset HOBOs are deployed on the fringing reef at one shallow 1 m depth and one deeper depth varying by site as follows: 6 m at LTER 1, 4 m at LTER 2, 7 m at LTER 3, 6 m at LTER 4, 3 m at LTER 5 and 4 m at LTER 6. Those depths do not vary. The mounting plate is fixed to the reef. These depths are not measured by the thermistors and should be considered categorical. Temperature data are processed and resampled to a 20 minute time step. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2022). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
DOI: 10.6084/m9.figshare.22250698
title: Supplementary Table 1

description: <strong>Supplementary Table 1.</strong> Echocardiographic characteristics in <em>db/db</em> mice treated with GCGR mAb or IgG (as control) for 4 weeks.
DOI: 10.6084/m9.figshare.22250704
title: Supplementary Table 2

description: <strong>Supplementary Table 2.</strong> Differentially expressed proteins in CMECs between <em>db/db</em> mice and <em>db/m</em> mice
DOI: 10.6084/m9.figshare.22250704.v1
title: Supplementary Table 2

description: <strong>Supplementary Table 2.</strong> Differentially expressed proteins in CMECs between <em>db/db</em> mice and <em>db/m</em> mice
DOI: 10.6084/m9.figshare.22250716
title: Supplementary Table 3

description: <strong>Supplementary Table 3. </strong>Differentially expressed proteins in CMECs between GCGR mAb- and IgG control (Ctrl)-treated <em>db/db</em> mice
DOI: 10.6084/m9.figshare.22250716.v1
title: Supplementary Table 3

description: <strong>Supplementary Table 3. </strong>Differentially expressed proteins in CMECs between GCGR mAb- and IgG control (Ctrl)-treated <em>db/db</em> mice
DOI: 10.6073/pasta/cc877612927ede00304f08fde2f163ff
title: Data in support of Primack et al. 2022 Frontiers in Ecology & Environment: Historically excluded groups in ecology are undervalued and poorly treated

description: Hostile workplaces undermine efforts to make the ecological sciences more inclusive and welcoming. A survey sent to the Ecological Society of America membership and ECOLOG-L listserv subscribers provides a snapshot of a range of workplace experiences in ecology. The results of this survey are published as Primack et al. 2022. Historically excluded groups in ecology are undervalued and poorly treated. Frontiers in Ecology and the Environment. This dataset includes the survey results and code for data analysis.
DOI: 10.5281/zenodo.7699779
title: 3DIdentBox_part1

description: <strong>3DIdentBox datasets featured in <em>Daunhawer, Imant, et al. "Identifiability Results for Multimodal Contrastive Learning.". </em></strong>The .zip file contains 6 datasets comprising image pairs and their corresponding generative factors. Generative factors are structured according to design choices described in <em>Bizeul, Alice, et al. "3DIdentBox: A Toolbox for Identifiability Benchmarking". </em><strong>In 3DIdentBox part 1, no causal dependencies exist between generative factors. </strong>For more information regarding the structure of datasets, please refer to our Github repository.
DOI: 10.5281/zenodo.7699778
title: 3DIdentBox_part1

description: <strong>3DIdentBox datasets featured in <em>Daunhawer, Imant, et al. "Identifiability Results for Multimodal Contrastive Learning.". </em></strong>The .zip file contains 6 datasets comprising image pairs and their corresponding generative factors. Generative factors are structured according to design choices described in <em>Bizeul, Alice, et al. "3DIdentBox: A Toolbox for Identifiability Benchmarking". </em><strong>In 3DIdentBox part 1, no causal dependencies exist between generative factors. </strong>For more information regarding the structure of datasets, please refer to our Github repository.
DOI: 10.18434/mds2-2913
title: Supplementary data from the NIST  lattice comparator  associated with paper "The NIST Silicon Lattice Comparator Upgrade"
DOI: 10.18434/mds2-2863
title: Historic test velocity data used for chronograph/light screen system uncertainty analysis.
DOI: 10.5281/zenodo.7699773
title: 3DIdentBox_part2

description: <strong>3DIdentBox datasets featured in <em>Daunhawer, Imant, et al. "Identifiability Results for Multimodal Contrastive Learning.". </em></strong>The .zip file contains 6 datasets comprising image pairs and their corresponding generative factors. Generative factors are structured according to design choices described in <em>Bizeul, Alice, et al. "3DIdentBox: A Toolbox for Identifiability Benchmarking". </em><strong>In 3DIdentBox, non-trivial causal dependencies exist between generative factors. </strong>For more information regarding the structure of datasets, please refer to our Github repository.
DOI: 10.5281/zenodo.7699772
title: 3DIdentBox_part2

description: <strong>3DIdentBox datasets featured in <em>Daunhawer, Imant, et al. "Identifiability Results for Multimodal Contrastive Learning.". </em></strong>The .zip file contains 6 datasets comprising image pairs and their corresponding generative factors. Generative factors are structured according to design choices described in <em>Bizeul, Alice, et al. "3DIdentBox: A Toolbox for Identifiability Benchmarking". </em><strong>In 3DIdentBox, non-trivial causal dependencies exist between generative factors. </strong>For more information regarding the structure of datasets, please refer to our Github repository.
DOI: 10.5281/zenodo.7716862
title: Vehicle trajectory and pavement behavior data

description: The dataset includes three documents. <strong>HDV_data_NGSIM_I_80.xlsx</strong> The vehicle trajectory data from Next Generation SIMulation (NGSIM) dataset was collected on eastbound I-80 in the San Francisco Bay area, in Emeryville, CA, on April 13, 2005, from 4:03:56 pm to 4:08:56 pm. Including vehicle id, frame id, the total count of frames of each vehicle, global time, local position, global position, vehicle length, vehicle width, vehicle class, speed, acceleration, lane id, preceding vehicle id, following vehicle id, space headway, time headway, and time. <strong>CAV_data_CARLA_SUMO.xml</strong> The simulated CAV trajectory data with CARLA and SUMO, including vehicle id, position, angle, type, speed, lane id, and slope of each frame. <strong>LTPP_data.csv</strong> The table including 21 columns is calculated from the Long-Term Pavement Performance (LTPP) database. IRI The IRI value measured when age was 0. (m/km) Cr_Gator Area of alligator cracking in square meters. (m^2) Cr_Lwp Length of longitudinal cracks within the defined wheel paths in meters. (m) Cr_Lnwp Length of longitudinal cracks not in the defined wheel paths in meters. (m) Pt_A Area of patches in square meters. (m^2) Pt_N Number of patches in square meters. (m^2) Cr_Wp Length of wheelpath cracks in meters. (m) Cr_Gt183 Total length of transverse cracks greater than 1.83. (m) Rt The depth of rutting in millimeters. (mm) Fr Friction number between the vehicle wheel tire and the pavement IRI_0 The IRI value measured when age was 0. (m/km) Tk_Sb Layer thickness measurement for surface coarse and binder course. (in) Md_s Average backcalculated elastic modulus of the surface layer.(psi) Hydr Average measured hydraulic conductivity of the specimen. (cm/sec) Prcp Average monthly precipitation in millimeters. (mm) Fz Average freeze index. (℃/day) Esal Annual average ESAL (kESAL) Esal_q quadratic form of Kesal (kESAL^2) Age Time duration between new construction to roughness survey date. (year) Gr Mean specific gravity of asphalt cement Pt_Ca Coarse aggregate amount percent by total weight of aggregate in percentage. (%)
DOI: 10.5281/zenodo.7716010
title: Bioclimatic outputs for Last Glacial Maximum South America for LPX, bias-corrected to pollen records

description: LPX model output for South America for the Last Glacial Maximum. We provide outputs for LPX driven by four GCM simulated climates along with an ensemble average: MIROC.tar.gz: LPX driven by MIROC3.2 FGOALS.tar.gz: driven by FGOALS-1.0g HAD.tar.gz: HadCM3M2 CNRM.tar.gz: CNRM-CM33 Ensemble.tar.gz: The mean of each output variable for the four models. Driving data comes from the Palaeoclimate Modelling Intercomparison Project Phase II (PMIP2)<sup>1,2</sup>. See Sato et al. <sup>3</sup> for modelling protocol. Each model’s directory contains “uncorrected” and “corrected” directories. With each of these are bioclimatic maps outputted from LPX and biome information: fpc.nc: fractional projected cover of all vegetation height.nc: mean height of vegetations gdd.nc: Growing Degree Days base 2 tropical.nc: proportion of vegetated areas taken up by tropical trees and c4 grasses temperate.nc: proportion of vegetated areas taken up by temperate trees and c3 grasses evergreen.nc: proportion of tree cover that is composed of evergreen trees biome.nc: the assigned biomes from these data, based on a modified version of Sato et al. <sup>3</sup>. See “biomisation” below. cluster.nc: In “corrected” only. The spatial location of kmean clusters of fpc vs height. See <sup>4</sup> for details. “Uncorrected” is from Sato et al. <sup>3</sup>. “Corrected” is bias-corrected to match the 42 pollen-core observations taken from Marchant et al. <sup>5</sup> We do this by shifting the total vegetation cover and composition, height, and growing degree day (GDD) DVM output to the closest boundary of the corresponding biome of the pollen core in that specific location. We then extrapolate this correction between pollen-core locations across the Neotropics. See Kelley et al. <sup>4</sup> for details. <strong>Biomeisation</strong> "Biomeisation.png" displays the scheme. We primarily split biomes by FPCs of 0.3 and 0.6, with biomes &gt; 0.6 split by a height of 10m. Forests (&gt;0.6 FPC and &gt; 10m) is split by GDD, Evergreen FPC (EG) and Tropical or temperate FPC (TR, TM). Likewise, we split FPCs&gt; 0.6 and heights &lt;10m into savanna, woodland and parkland using EG and TR. We additionally assign Tropical savanna &gt;5m to Woodland/Tropical savanna. We divided desert, dry grassland and (shrub)-tundra by FPC of 0.3 and GDD of 350°C. See Kelley et al. <sup>4</sup> for details.
description: DIK was supported by the UK Natural Environment Research Council as part of the LTSM2 TerraFIRMA project delivering National Capability and The UK Earth System Modelling Project (UKESM, grant no. NE/N017951/1). CB was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). JMB, HS, and JMGC were supported by Dimensions US-Biota-São Paulo: Assembly and evolution of the Amazonian biota and its environment: an integrated approach, co-funded by the US National Science Foundation (NSF DEB 1241056) and the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP grant #2012/50260-6).
DOI: 10.5281/zenodo.7716009
title: Bioclimatic outputs for Last Glacial Maximum South America for LPX, bias-corrected to pollen records

description: LPX model output for South America for the Last Glacial Maximum. We provide outputs for LPX driven by four GCM simulated climates along with an ensemble average: MIROC.tar.gz: LPX driven by MIROC3.2 FGOALS.tar.gz: driven by FGOALS-1.0g HAD.tar.gz: HadCM3M2 CNRM.tar.gz: CNRM-CM33 Ensemble.tar.gz: The mean of each output variable for the four models. Driving data comes from the Palaeoclimate Modelling Intercomparison Project Phase II (PMIP2)<sup>1,2</sup>. See Sato et al. <sup>3</sup> for modelling protocol. Each model’s directory contains “uncorrected” and “corrected” directories. With each of these are bioclimatic maps outputted from LPX and biome information: fpc.nc: fractional projected cover of all vegetation height.nc: mean height of vegetations gdd.nc: Growing Degree Days base 2 tropical.nc: proportion of vegetated areas taken up by tropical trees and c4 grasses temperate.nc: proportion of vegetated areas taken up by temperate trees and c3 grasses evergreen.nc: proportion of tree cover that is composed of evergreen trees biome.nc: the assigned biomes from these data, based on a modified version of Sato et al. <sup>3</sup>. See “biomisation” below. cluster.nc: In “corrected” only. The spatial location of kmean clusters of fpc vs height. See <sup>4</sup> for details. “Uncorrected” is from Sato et al. <sup>3</sup>. “Corrected” is bias-corrected to match the 42 pollen-core observations taken from Marchant et al. <sup>5</sup> We do this by shifting the total vegetation cover and composition, height, and growing degree day (GDD) DVM output to the closest boundary of the corresponding biome of the pollen core in that specific location. We then extrapolate this correction between pollen-core locations across the Neotropics. See Kelley et al. <sup>4</sup> for details. <strong>Biomeisation</strong> "Biomeisation.png" displays the scheme. We primarily split biomes by FPCs of 0.3 and 0.6, with biomes &gt; 0.6 split by a height of 10m. Forests (&gt;0.6 FPC and &gt; 10m) is split by GDD, Evergreen FPC (EG) and Tropical or temperate FPC (TR, TM). Likewise, we split FPCs&gt; 0.6 and heights &lt;10m into savanna, woodland and parkland using EG and TR. We additionally assign Tropical savanna &gt;5m to Woodland/Tropical savanna. We divided desert, dry grassland and (shrub)-tundra by FPC of 0.3 and GDD of 350°C. See Kelley et al. <sup>4</sup> for details.
description: DIK was supported by the UK Natural Environment Research Council as part of the LTSM2 TerraFIRMA project delivering National Capability and The UK Earth System Modelling Project (UKESM, grant no. NE/N017951/1). CB was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). JMB, HS, and JMGC were supported by Dimensions US-Biota-São Paulo: Assembly and evolution of the Amazonian biota and its environment: an integrated approach, co-funded by the US National Science Foundation (NSF DEB 1241056) and the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP grant #2012/50260-6).
DOI: 10.25934/pr00008720
title: Association between statin treatment and risk of cardiovascular outcomes and death in patients with atrial fibrillation: an individual patient data meta-analysis

description: Atrial fibrillation (also called AFib or AF) is an irregular heartbeat (arrhythmia) that begins in the heart’s upper chambers (atria). It can lead to blood clots, stroke, heart failure and other heart-related complications. It is estimated that 12.1 million people in the United States will have AFib in 2030. There is increasing evidence suggesting that statin treatment improves cardiovascular outcomes in patients with AF. Statins are a class of lipid-lowering medications and are the most common cholesterol-lowering drugs. However, the quality of this evidence is not high. This meta-analysis aims to pool individual patient data from two randomized controlled trials (ENGAGE-AF and RE-LY) in patients with atrial fibrillation to investigate this question This will provide further evidence about the rols of statin treatment in patients with AF, and promote further research in this field.
DOI: 10.5281/zenodo.7705090
title: Effects of disorder on deformation and failure of brittle porous materials: dataset

description: <strong>Data from:</strong> [1] Ritter, J.; Shegufta, S. & Zaiser, M. "Effects of disorder on deformation and failure of brittle porous materials" <em>arXiv, </em><strong>2023</strong> <strong>Abstract:</strong> from [1] The mechanical behavior of porous materials depends strongly on porosity and pore geometry, but also on morphological parameters characterizing the spatial arrangement of pores. Here we use bond-based peridynamics to study effects of disorder on the deformation and failure behavior of brittle porous solids both in the quasi-static limit and in case of dynamic loading scenarios. We show that structural disorder, which has a strong influence on stiffness, strength and toughness in the quasi-static limit, becomes less relevant under dynamic loading conditions. <strong>Contact:</strong> Jonas Ritter<br> Institute of Materials Simulation<br> Friedrich-Alexander-Universität Erlangen-Nürnberg<br> Dr.-Mack-Str. 77<br> 90762 Fürth<br> Germany <strong>Software:</strong><br> Peridigm <strong>Content:</strong> The dataset consists of the input geometries as well as the combined results (values for each simulation and mean values and standard deviation of each parameter set). Each folder contains a README.md that lists the content and provides description of the data and further metadata.
description: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 377472739/GRK 2423/1-2019 (Research Training Group GRK 2423 'Fracture across Scales - FRASCAL'). The authors gratefully acknowledge this support.
DOI: 10.5281/zenodo.7705091
title: Effects of disorder on deformation and failure of brittle porous materials: dataset

description: <strong>Data from:</strong> [1] Ritter, J.; Shegufta, S. & Zaiser, M. "Effects of disorder on deformation and failure of brittle porous materials" <em>arXiv, </em><strong>2023</strong> <strong>Abstract:</strong> from [1] The mechanical behavior of porous materials depends strongly on porosity and pore geometry, but also on morphological parameters characterizing the spatial arrangement of pores. Here we use bond-based peridynamics to study effects of disorder on the deformation and failure behavior of brittle porous solids both in the quasi-static limit and in case of dynamic loading scenarios. We show that structural disorder, which has a strong influence on stiffness, strength and toughness in the quasi-static limit, becomes less relevant under dynamic loading conditions. <strong>Contact:</strong> Jonas Ritter<br> Institute of Materials Simulation<br> Friedrich-Alexander-Universität Erlangen-Nürnberg<br> Dr.-Mack-Str. 77<br> 90762 Fürth<br> Germany <strong>Software:</strong><br> Peridigm <strong>Content:</strong> The dataset consists of the input geometries as well as the combined results (values for each simulation and mean values and standard deviation of each parameter set). Each folder contains a README.md that lists the content and provides description of the data and further metadata.
description: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 377472739/GRK 2423/1-2019 (Research Training Group GRK 2423 'Fracture across Scales - FRASCAL'). The authors gratefully acknowledge this support.
DOI: 10.7284/152492
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise LMG0401 using a SeaBird SBE-911+ instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/152493
title: Expendable Probe data collected during research cruise LMG0401 using a Sippican MK21 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/152494
title: Expendable Probe data collected during research cruise LMG0401 using a Sippican MK21 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition