cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5286/isis.e.rb2000194-2
title: Nature of Quantum Spin-liquid Ground State of a Honeycomb Kondo Lattice CePt6Al3 : µSR study

description: Recently, Honeycomb lattice materials have attracted considerable attraction due to the bond dependent exchange proposed by Kitaev. We have synthesised a new Ce-based Honeycomb compound CePt6Al3, which exhibits heavy Fermion behaviour and no clear sign of long range magnetic ordering. However, heat capacity exhibits a broad maximum at 0.55K indicating the development of short range correlations. Our inelastic neutron scattering (INS) study reveals one CEF excitation near 15meV at 5K, but dramatic change in the excitations at 110 and 170K, suggesting new kind of excitations. It is an open question whether the ground state is magnetic or quantum spin-liquid. We therefore propose to investigate the magnetic ground of CePt6Al3 using muon spin rotation and relaxation on MuSR/EMU. The proposed uSR results with our existing INS data will allow us to publish our results in a high impact journal.
DOI: 10.5286/isis.e.rb2000194-3
title: Nature of Quantum Spin-liquid Ground State of a Honeycomb Kondo Lattice CePt6Al3 : µSR study

description: Recently, Honeycomb lattice materials have attracted considerable attraction due to the bond dependent exchange proposed by Kitaev. We have synthesised a new Ce-based Honeycomb compound CePt6Al3, which exhibits heavy Fermion behaviour and no clear sign of long range magnetic ordering. However, heat capacity exhibits a broad maximum at 0.55K indicating the development of short range correlations. Our inelastic neutron scattering (INS) study reveals one CEF excitation near 15meV at 5K, but dramatic change in the excitations at 110 and 170K, suggesting new kind of excitations. It is an open question whether the ground state is magnetic or quantum spin-liquid. We therefore propose to investigate the magnetic ground of CePt6Al3 using muon spin rotation and relaxation on MuSR/EMU. The proposed uSR results with our existing INS data will allow us to publish our results in a high impact journal.
DOI: 10.6084/m9.figshare.14096071
title: Confined water-mediated surface-acetylation of cellulose: figure raw data, calibration curve and regioselectivty

description: Raw data underlying reported averages in tables and figures, the calibration curve, and regioselectivity of the acetylation.
DOI: 10.6084/m9.figshare.14096071.v2
title: Confined water-mediated surface-acetylation of cellulose: figure raw data, calibration curve and regioselectivty

description: Raw data underlying reported averages in tables and figures, the calibration curve, and regioselectivity of the acetylation.
DOI: 10.6084/m9.figshare.13135604.v1
title: Automatically detected contours

description: This table contains polygons (contours) that are automatically created by the baseline model. • Image_url: The name of the base image. • point: The expert-annotated point that marks the MA structure. • polygon: The expert-annotated polygon that marks the boundary of the MA structure. • point_shapely: The representation of ‘point’ in Shapely data format. • poly_shapely: The representation of ‘polygon’ in Shapely data format. • contour_polygon_shapely: The representation of the automatically detected contour in Shapely data format.
DOI: 10.6084/m9.figshare.13135604
title: Automatically detected contours

description: This table contains polygons (contours) that are automatically created by the baseline model. • Image_url: The name of the base image. • point: The expert-annotated point that marks the MA structure. • polygon: The expert-annotated polygon that marks the boundary of the MA structure. • point_shapely: The representation of ‘point’ in Shapely data format. • poly_shapely: The representation of ‘polygon’ in Shapely data format. • contour_polygon_shapely: The representation of the automatically detected contour in Shapely data format.
DOI: 10.6084/m9.figshare.13135610
title: Expert annotated polygons

description: Each entry in the expert segmentation table represents a polygon that marks the boundary around an martensite-austenite structure.
DOI: 10.6084/m9.figshare.13135610.v1
title: Expert annotated polygons

description: Each entry in the expert segmentation table represents a polygon that marks the boundary around an martensite-austenite structure.
DOI: 10.6084/m9.figshare.13135607.v1
title: Point-of-Interest annotations

description: POI annotations table shows the entire set of annotations provided by all three experts. Each entry consists of the image name and an X, Y coordinate tuple that represents the offset coordinates of the point that was marked to indicate an martensite-austenite structure by one of the experts.
DOI: 10.6084/m9.figshare.13135613
title: Expert annotated polygons (pickle)

description: Each entry in the expert segmentation table represents a polygon that marks the boundary around an martensite-austenite structure. This is a pickle file that can be opened with Python and loaded as a Pandas DataFrame.
DOI: 10.6084/m9.figshare.13135616
title: Morphological characteristics of martensite-austenite structures

description: The morphological features data table contains the measured and calculated features of the polygons. This is a pickle file that can be opened with Python and loaded as a Pandas DataFrame. • Image_url: The name of the base image. • point_shapely: The Shapely representation of the point. • poly_shapely: The Shapely representation of the polygon. • polygon_area: The area of polygons in pixel-units. • polygon_area_metric: The area of polygons in micrometers. • polygon_perimeter: The perimeter of the polygon in pixel-units. • polygon_perimeter_metric: The perimeter of the polygon in micrometers. • height: The height of the rectangle that bounds the polygon in pixel-units. • width: The width of the rectangle that bounds the polygon in pixel-units. • aspect_ratio: The height of the bounding box of the polygon divided by the width of the bounding box of the polygon. • polygon_compactness: Calculated Polsby-Popper compactness. • rotation_angle_polygon: The angle of tilted minimum bounding rectangle
DOI: 10.6084/m9.figshare.13135607
title: Point-of-Interest annotations

description: POI annotations table shows the entire set of annotations provided by all three experts. Each entry consists of the image name and an X, Y coordinate tuple that represents the offset coordinates of the point that was marked to indicate an martensite-austenite structure by one of the experts.
DOI: 10.6084/m9.figshare.13135619
title: Evaluation of contour detection model

description: The evaluation table consists of three features; the area of the expert-annotated polygons, the area of the automatically detected contours, and the Intersection-over-Union (IOU) as a measure of segmentation accuracy. This is a pickle file that can be opened with Python and loaded as a Pandas DataFrame.
DOI: 10.6084/m9.figshare.13135613.v1
title: Expert annotated polygons (pickle)

description: Each entry in the expert segmentation table represents a polygon that marks the boundary around an martensite-austenite structure. This is a pickle file that can be opened with Python and loaded as a Pandas DataFrame.
DOI: 10.6084/m9.figshare.13135622
title: Metadata of the steel samples

description: The metadata table shows the image file name, steel-sample composition type, sample-preparation temperature, direction, distance to the edge, magnification level, and angle of the scanning electron detector.
DOI: 10.6084/m9.figshare.13135625.v1
title: Steel microscopy images (PNG)

description: The microscopy images in PNG format.
DOI: 10.6084/m9.figshare.13135616.v1
title: Morphological characteristics of martensite-austenite structures

description: The morphological features data table contains the measured and calculated features of the polygons. This is a pickle file that can be opened with Python and loaded as a Pandas DataFrame. • Image_url: The name of the base image. • point_shapely: The Shapely representation of the point. • poly_shapely: The Shapely representation of the polygon. • polygon_area: The area of polygons in pixel-units. • polygon_area_metric: The area of polygons in micrometers. • polygon_perimeter: The perimeter of the polygon in pixel-units. • polygon_perimeter_metric: The perimeter of the polygon in micrometers. • height: The height of the rectangle that bounds the polygon in pixel-units. • width: The width of the rectangle that bounds the polygon in pixel-units. • aspect_ratio: The height of the bounding box of the polygon divided by the width of the bounding box of the polygon. • polygon_compactness: Calculated Polsby-Popper compactness. • rotation_angle_polygon: The angle of tilted minimum bounding rectangle
DOI: 10.6084/m9.figshare.13135619.v1
title: Evaluation of contour detection model

description: The evaluation table consists of three features; the area of the expert-annotated polygons, the area of the automatically detected contours, and the Intersection-over-Union (IOU) as a measure of segmentation accuracy. This is a pickle file that can be opened with Python and loaded as a Pandas DataFrame.
DOI: 10.6084/m9.figshare.13135622.v1
title: Metadata of the steel samples

description: The metadata table shows the image file name, steel-sample composition type, sample-preparation temperature, direction, distance to the edge, magnification level, and angle of the scanning electron detector.
DOI: 10.6084/m9.figshare.13135625
title: Steel microscopy images (PNG)

description: The microscopy images in PNG format.
DOI: 10.5281/zenodo.4646728
title: Data for "Multiscale representation of very large environments in the hippocampus of flying bats"

description: This dataset contains analysis code and data for the figures associated with the paper: "<strong>Multiscale representation of very large environments in the hippocampus of flying bats</strong>" Eliav <em>et al</em>., Science (2021) [DOI:10.1126/science.abg4020] The repository contains:<br> - MATLAB code to calculate firing rate maps as well as field detection.<br> - Data from the main figures of the paper including cell examples (rasters, firing-rate maps and detected fields) as well as histograms data. Any questions should be sent to the corresponding author of the paper, Nachum Ulanovsky (nachum.ulanovsky@weizmann.ac.il)<br>
DOI: 10.5281/zenodo.4646727
title: Data for "Multiscale representation of very large environments in the hippocampus of flying bats"

description: This dataset contains analysis code and data for the figures associated with the paper: "<strong>Multiscale representation of very large environments in the hippocampus of flying bats</strong>" Eliav <em>et al</em>., Science (2021) [DOI:10.1126/science.abg4020] The repository contains:<br> - MATLAB code to calculate firing rate maps as well as field detection.<br> - Data from the main figures of the paper including cell examples (rasters, firing-rate maps and detected fields) as well as histograms data. Any questions should be sent to the corresponding author of the paper, Nachum Ulanovsky (nachum.ulanovsky@weizmann.ac.il)<br>
DOI: 10.5281/zenodo.4772848
title: PLANMAP - Deliverable D4.2 - Moon/Apollo Basin spectral parameters maps - v1, preliminary

description: Preliminary spectral parameters maps of Apollo Basin on the Moon at 600 m/pixel derived by Chandrayaan-1/M3 data.
DOI: 10.5281/zenodo.4772847
title: PLANMAP - Deliverable D4.2 - Moon/Apollo Basin spectral parameters maps - v1, preliminary

description: Preliminary spectral parameters maps of Apollo Basin on the Moon at 600 m/pixel derived by Chandrayaan-1/M3 data.
DOI: 10.6084/m9.figshare.14618178
title: Microsoft T-Drive dataset

description: Microsoft T-Drive dataset
DOI: 10.6084/m9.figshare.14618178.v1
title: Microsoft T-Drive dataset

description: Microsoft T-Drive dataset
DOI: 10.5281/zenodo.4772950
title: Dataset

description: Dataset and all artifacts used during the experiment.
DOI: 10.5281/zenodo.4723922
title: Dataset

description: Dataset and all artifacts used during the experiment.
DOI: 10.6084/m9.figshare.14618190
title: TN291

description: TN291 dataset data points which are collected from 9 different districts of Tamil Nadu, India.
DOI: 10.5281/zenodo.4762758
title: A tutorial dataset for TransportTools engine

description: This file includes the input data necessary to follow the tutorial for TransportTools standard workflow. - two trajectories and topologies of MD simulations - templates for CAVER and AQUA-DUCT analyses of these simulations - precomputed results of CAVER and AQUA-DUCT analyses
DOI: 10.5281/zenodo.4772908
title: Data of Karhunen-Loéve (KL) ensemble generation algorithm for biogenic emissions from EURAD-IM

description: The files provided here include the input and output of the KL ensemble generation algorithm for a specific application to biogenic emissions. The data refers to the manuscript "Efficient ensemble generation for uncertain correlated parameters in atmospheric chemical models" by A.Vogel and H.Elbern which has been submitted to GMD (discussion preprint available at: https://gmd.copernicus.org/preprints/gmd-2021-26). Further information on the data can be found in the README.txt-File.
DOI: 10.6084/m9.figshare.14226464
title: Lithium-Ion Battery Electrolyte (LIBE) dataset

description: The Lithium-Ion Battery Electrolyte (LIBE) dataset includes the computed properties of over 17,000 molecules relevant to electrolyte and interphase chemistry calculated using density functional theory (DFT) at the ωB97X-V/def2-TZVPPD/SMD level of theory. The dataset was generated by fragmenting a set of principal molecules, including solvents, salts, and SEI products, and then selectively recombining a subset of the fragments. LIBE contains structural, thermochemical, and vibrational information.
DOI: 10.5281/zenodo.4772654
title: UAFSan-datasets

description: Datasets for UAFSan
DOI: 10.5281/zenodo.4772653
title: UAFSan-datasets

description: Datasets for UAFSan
DOI: 10.6084/m9.figshare.14618259.v1
title: Tables and captions (LaTex). Miocene Tuffs from the Dinarides and Eastern Alps as Proxies of the Pannonian Basin Lithosphere Dynamics and Tropospheric Circulation Patterns in Central Europe

description: Tables and captions (LaTex)
DOI: 10.6084/m9.figshare.14618259
title: Tables and captions (LaTex). Miocene Tuffs from the Dinarides and Eastern Alps as Proxies of the Pannonian Basin Lithosphere Dynamics and Tropospheric Circulation Patterns in Central Europe

description: Tables and captions (LaTex)
DOI: 10.5281/zenodo.3941133
title: IODP Expedition 368, Hole U1502B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 368: South China Sea Rifted Margin B
DOI: 10.5281/zenodo.3941132
title: IODP Expedition 368, Hole U1502B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 368: South China Sea Rifted Margin B
DOI: 10.6084/m9.figshare.14160545
title: Sousa et al 2021 Dataset Manuscript

description: Dataset used at the manuscript "<b>Reproductive barriers in cassava: Factors and implications for genetic improvement</b>" submitted at <b>PlosOne</b> JournalThroughout this dataset we evaluated the main reproductive barriers in cassava responsible by the high rates of flower abortion. Aiming to estimate the effects factors of the cassava flower abortion rates: 1) we analysed pre and post zigotic reproductive barriers between intraspecific crosses; 2) we evaluated the pollen-pistil interactions; and 3) identified the population structure among elite clones used as parents in breeding programs.New insights on cassava reproduction are provided to assist in practical crossing to maximize the recombination of contrasting clones.
DOI: 10.6084/m9.figshare.14160545.v1
title: Sousa et al 2020 Dataset Manuscript

description: Dataset used at the manuscript "<b>Reproductive barriers in cassava: Factors and implications for genetic improvement</b>" submitted at <b>Frontiers in Plant Science</b> JournalThroughout this dataset we evaluated the main reproductive barriers in cassava responsible by the high rates of flower abortion. Aiming to estimate the effects factors of the cassava flower abortion rates: 1) we analysed pre and post zigotic reproductive barriers between intraspecific crosses; 2) we evaluated the pollen-pistil interactions; and 3) identified the population structure among elite clones used as parents in breeding programs.New insights on cassava reproduction are provided to assist in practical crossing to maximize the recombination of contrasting clones.
DOI: 10.5281/zenodo.4465809
title: Data for: The circular economy potential of urban organic waste streams in low- and middle-income countries

description: This dataset includes the research data and supporting information for the publication "The circular economy potential of urban organic waste streams in low- and middle-income countries" which was published in the Journal of Environment, Development and Sustainability (DOI: 10.1007/s10668-021-01487-w). This dataset and the associated publication are the basis upon which the REVAMP (Resource Value Mapping) tool has been developed. See more info about the REVAMP tool here: https://www.sei.org/revamp
description: Funding for this work came from the Swedish International Development Cooperation Agency (Sida) and the Swedish Ministry of Environment through core support to SEI for the initiative on Sustainable Sanitation (www.sei.org/sustainable-sanitation) as well as the Swedish Research Council Formas through project grant number 2017-00268 to the UrbanCircle (Urban Waste into Circular Economy Benefits) project (www.sei.org/urbancircle).
DOI: 10.5281/zenodo.4452199
title: Data for: The circular economy potential of urban organic waste streams in low- and middle-income countries

description: This dataset includes the research data and supporting information for the publication "The circular economy potential of urban organic waste streams in low- and middle-income countries" which was published in the Journal of Environment, Development and Sustainability (DOI: 10.1007/s10668-021-01487-w). This dataset and the associated publication are the basis upon which the REVAMP (Resource Value Mapping) tool has been developed. See more info about the REVAMP tool here: https://www.sei.org/revamp
description: Funding for this work came from the Swedish International Development Cooperation Agency (Sida) and the Swedish Ministry of Environment through core support to SEI for the initiative on Sustainable Sanitation (www.sei.org/sustainable-sanitation) as well as the Swedish Research Council Formas through project grant number 2017-00268 to the UrbanCircle (Urban Waste into Circular Economy Benefits) project (www.sei.org/urbancircle).
DOI: 10.5281/zenodo.3941142
title: IODP Expedition 369, Hole U1513A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 369: Australia Cretaceous Climate and Tectonics
DOI: 10.5281/zenodo.3941141
title: IODP Expedition 369, Hole U1513A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 369: Australia Cretaceous Climate and Tectonics
DOI: 10.6084/m9.figshare.14109752
title: Dog Metabolomics DataSet 2021

description: Complete dataset for the large, small, young, old dog fibroblast metabolomics study 2021.<br>
DOI: 10.5281/zenodo.3941146
title: IODP Expedition 369, Hole U1513E - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 369: Australia Cretaceous Climate and Tectonics
DOI: 10.5281/zenodo.3941145
title: IODP Expedition 369, Hole U1513E - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 369: Australia Cretaceous Climate and Tectonics
DOI: 10.5281/zenodo.3941140
title: IODP Expedition 369, Hole U1512A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 369: Australia Cretaceous Climate and Tectonics
DOI: 10.5281/zenodo.3941139
title: IODP Expedition 369, Hole U1512A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 369: Australia Cretaceous Climate and Tectonics