cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23521935
title: Supplementary Material for: Melatonin Attenuates Cerebral Ischemia/Reperfusion Injury Through Inducing Autophagy

description: Introduction: The aim of this study was to investigate how melatonin administration for 3 days or 7 days following cerebral ischemia injury (CI/R) would affect autophagy, and therefore, survival in neurons of the penumbra region. Moreover, it was also aimed to determine how this melatonin treatment would affect the neurological deficit score and rotarod and adhesive removal test durations. Methods: Focal CI (90 min) was achieved in a total of 105 rats utilizing a middle cerebral artery occlusion model. After the start of reperfusion, the groups were treated with melatonin (10 mg/kg/day) for 3-days or 7-days. On all groups, neurological deficit scoring, rotarod and adhesive removal test were executed during reperfusion. Infarct areas were determined by TTC (2,3,5-triphenyltetrazolium chloride) staining at the end of the 3rd and 7th days of reperfusion. Beclin-1, LC3, p62 and caspase-3 protein levels were assessed using Western blot and immunofluorescence methods in the brain tissues. Moreover, penumbra areas were evaluated by transmission electron microscopy (TEM). Results: Following CI, it was observed that melatonin treatment improved the rotarod and adhesive removal test durations from day 5 and reduced the infarct area after CI. It also induced autophagic proteins Beclin-1, LC3 and p62 and suppressed the apoptotic protein cleaved caspase-3. According to TEM findings, melatonin treatment partially reduced the damage in neurons after CI. Conclusion: Melatonin treatment following CI reduced the infarct area and induced the autophagic proteins Beclin-1, LC3 and p62 via inhibiting the apoptotic caspase-3 protein. The functional reflection of melatonin treatment on neurological tests scores was became significant from the 5th day onward.
DOI: 10.5281/zenodo.8238361
title: Parhyale 3D segmentation dataset

description: The Parhyale 3D Segmentation dataset consists of 50 timepoints (TP01-TP50) of 3D images (512x512x34), where the manual annotations can be found at discrete 6 timepoints (at TP01, TP11, TP21, TP31, TP41 and TP50). For further details, see README file. This version fixes the duplicated label IDs found in the previous version of label files. This version ensures that each instance has a unique ID. Thanks to Jackson Borchardt for reporting that error.
description: Research was funded by the Agence Nationale de la Recherche (image data collection, grant ANR-12-CHEX-0001-01) and by the European Research Council (image analysis, grant ERC-2015-AdG #694918).
description: {"references": ["Alwes, Enjolras & Averof (2016) Live imaging reveals the progenitors and cell dynamics of limb regeneration. eLife 5: e19766. doi:10.7554/eLife.19766", "Weigert, Schmidt, Haase, Sugawara and Myers (2020) Star-convex polyhedra for 3D object detection and segmentation in microscopy. Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020 3655-3662. doi:10.1109/WACV45572.2020.9093435"]}
DOI: 10.5281/zenodo.8238362
title: Parhyale 3D segmentation dataset

description: The Parhyale 3D Segmentation dataset consists of 50 timepoints (TP01-TP50) of 3D images (512x512x34), where the manual annotations can be found at discrete 6 timepoints (at TP01, TP11, TP21, TP31, TP41 and TP50). For further details, see README file.
description: Research was funded by the Agence Nationale de la Recherche (image data collection, grant ANR-12-CHEX-0001-01) and by the European Research Council (image analysis, grant ERC-2015-AdG #694918).
description: {"references": ["Alwes, Enjolras & Averof (2016) Live imaging reveals the progenitors and cell dynamics of limb regeneration. eLife 5: e19766. doi:10.7554/eLife.19766", "Weigert, Schmidt, Haase, Sugawara and Myers (2020) Star-convex polyhedra for 3D object detection and segmentation in microscopy. Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020 3655-3662. doi:10.1109/WACV45572.2020.9093435"]}
DOI: 10.5281/zenodo.8252039
title: Parhyale 3D segmentation dataset

description: The Parhyale 3D Segmentation dataset consists of 50 timepoints (TP01-TP50) of 3D images (512x512x34), where the manual annotations can be found at discrete 6 timepoints (at TP01, TP11, TP21, TP31, TP41 and TP50). For further details, see README file. This version fixes the duplicated label IDs found in the previous version of label files. This version ensures that each instance has a unique ID. Thanks to Jackson Borchardt for reporting that error.
description: Research was funded by the Agence Nationale de la Recherche (image data collection, grant ANR-12-CHEX-0001-01) and by the European Research Council (image analysis, grant ERC-2015-AdG #694918).
description: {"references": ["Alwes, Enjolras & Averof (2016) Live imaging reveals the progenitors and cell dynamics of limb regeneration. eLife 5: e19766. doi:10.7554/eLife.19766", "Weigert, Schmidt, Haase, Sugawara and Myers (2020) Star-convex polyhedra for 3D object detection and segmentation in microscopy. Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020 3655-3662. doi:10.1109/WACV45572.2020.9093435"]}
DOI: 10.25345/c5d50g759
title: MassIVE MSV000092666 - GNPS_positive-mode_analise-Marcos_formiato de amonio
title: analise feita em tampao de NH4OAc 1000x diluido em metanol
DOI: 10.25345/c58c9rf1m
title: MassIVE MSV000092667 - Qualea dichotoma comparative quantitative analysis
title: 1234567890 1234567890 1234567890 1234567890 1234567890 1234567890 1234567890 1234567890 1234567890
DOI: 10.5281/zenodo.8247281
title: PARALLEL G-QUADRUPLEX FOLDS VIA MULTIPLE PATHS INVOLVING G-TRACT STACKING AND STRUCTURING FROM COIL ENSEMBLE

description: Data from all-atom molecular dynamics simulations of DNA G-quadruplex and various G-hairpins: input files (Gromacs and Amber), stripped trajectory files (reactive trajectories and reference replicas for G4, and reactive trajectories, and reference replicas for selected hairpin simulations), metadynamics bias files, and the ΔG_fold calculation protocol.
DOI: 10.5281/zenodo.8247280
title: PARALLEL G-QUADRUPLEX FOLDS VIA MULTIPLE PATHS INVOLVING G-TRACT STACKING AND STRUCTURING FROM COIL ENSEMBLE

description: Data from all-atom molecular dynamics simulations of DNA G-quadruplex and various G-hairpins: input files (Gromacs and Amber), stripped trajectory files (reactive trajectories and reference replicas for G4, and reactive trajectories, and reference replicas for selected hairpin simulations), metadynamics bias files, and the ΔG_fold calculation protocol.
DOI: 10.26050/wdcc/ar6.c6dagige1
title: IPCC DDC: NASA-GISS GISS-E2.1G model output prepared for CMIP6 DAMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.DAMIP.NASA-GISS.GISS-E2-1-G' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. NOTE (NASA-GISS 2019-09-16): variables nbp, nep, cSoil, cSoilAbove1m, rh were retracted for all dataset versions earlier than 2019-09-16. The GISS-E2.1G climate model, released in 2019, includes the following components: aerosol: Varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2.5x2 degree; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: Varies with physics-version (p==1 Non-interactive, p&gt;1 GPUCCINI), land: GISS LSM, ocean: GISS Ocean (GO1, 1 degree; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: GISS SI. The model was run by the Goddard Institute for Space Studies, New York, NY 10025, USA (NASA-GISS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, seaIce: 250 km.
DOI: 10.26050/wdcc/ar6.c6dagige1hs3
title: IPCC DDC: NASA-GISS GISS-E2.1G model output prepared for CMIP6 DAMIP hist-stratO3

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.DAMIP.NASA-GISS.GISS-E2-1-G.hist-stratO3' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The GISS-E2.1G climate model, released in 2019, includes the following components: aerosol: Varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2.5x2 degree; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: Varies with physics-version (p==1 Non-interactive, p&gt;1 GPUCCINI), land: GISS LSM, ocean: GISS Ocean (GO1, 1 degree; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: GISS SI. The model was run by the Goddard Institute for Space Studies, New York, NY 10025, USA (NASA-GISS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, seaIce: 250 km.
DOI: 10.26050/wdcc/ar6.c6dagige1hs
title: IPCC DDC: NASA-GISS GISS-E2.1G model output prepared for CMIP6 DAMIP hist-sol

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.DAMIP.NASA-GISS.GISS-E2-1-G.hist-sol' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The GISS-E2.1G climate model, released in 2019, includes the following components: aerosol: Varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2.5x2 degree; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: Varies with physics-version (p==1 Non-interactive, p&gt;1 GPUCCINI), land: GISS LSM, ocean: GISS Ocean (GO1, 1 degree; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: GISS SI. The model was run by the Goddard Institute for Space Studies, New York, NY 10025, USA (NASA-GISS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, seaIce: 250 km.
DOI: 10.26050/wdcc/ar6.c6dagige1hv
title: IPCC DDC: NASA-GISS GISS-E2.1G model output prepared for CMIP6 DAMIP hist-volc

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.DAMIP.NASA-GISS.GISS-E2-1-G.hist-volc' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The GISS-E2.1G climate model, released in 2019, includes the following components: aerosol: Varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2.5x2 degree; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: Varies with physics-version (p==1 Non-interactive, p&gt;1 GPUCCINI), land: GISS LSM, ocean: GISS Ocean (GO1, 1 degree; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: GISS SI. The model was run by the Goddard Institute for Space Studies, New York, NY 10025, USA (NASA-GISS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, seaIce: 250 km.
DOI: 10.26050/wdcc/ar6.c6dagigegs2co
title: IPCC DDC: NASA-GISS GISS-E2.1G model output prepared for CMIP6 DAMIP ssp245-covid

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.DAMIP.NASA-GISS.GISS-E2-1-G.ssp245-covid' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The GISS-E2.1G climate model, released in 2019, includes the following components: aerosol: Varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2.5x2 degree; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: Varies with physics-version (p==1 Non-interactive, p&gt;1 GPUCCINI), land: GISS LSM, ocean: GISS Ocean (GO1, 1 degree; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: GISS SI. The model was run by the Goddard Institute for Space Studies, New York, NY 10025, USA (NASA-GISS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, seaIce: 250 km.
DOI: 10.6084/m9.figshare.23695385
title: S2: Physicochemical hazard assessment of ash and dome rock from the 2021 eruption of La Soufrière, St Vincent, for the assessment of respiratory health impacts and water contamination

description: Particle size data
DOI: 10.6084/m9.figshare.23695385.v1
title: S2: Physicochemical hazard assessment of ash and dome rock from the 2021 eruption of La Soufrière, St Vincent, for the assessment of respiratory impacts and water contamination

description: Particle size data
DOI: 10.6084/m9.figshare.23695385.v2
title: S2: Physicochemical hazard assessment of ash and dome rock from the 2021 eruption of La Soufrière, St Vincent, for the assessment of respiratory health impacts and water contamination

description: Particle size data
DOI: 10.6084/m9.figshare.23695391
title: S3: Physicochemical hazard assessment of ash and dome rock from the 2021 eruption of La Soufrière, St Vincent, for the assessment of respiratory health impacts and water contamination

description: XRD data
DOI: 10.6084/m9.figshare.23695391.v2
title: S3: Physicochemical hazard assessment of ash and dome rock from the 2021 eruption of La Soufrière, St Vincent, for the assessment of respiratory health impacts and water contamination

description: XRD data
DOI: 10.6084/m9.figshare.23695391.v1
title: S3: Physicochemical hazard assessment of ash and dome rock from the 2021 eruption of La Soufrière, St Vincent, for the assessment of respiratory impacts and water contamination

description: XRD data
DOI: 10.34777/pw5d-ka13
title: ChildPlay Gaze

description: he ChildPlay Gaze dataset is a curated collection of short video clips featuring children playing and interacting with adults in uncontrolled environments (e.g. kindergarten, therapy centers, preschools etc.), which we annotate with rich gaze information. It contains 401 clips extracted from 95 YouTube videos, totaling 120549 frames.
DOI: 10.17028/rd.lboro.23968134
title: Supplementary information files for The hamstrings to quadriceps functional ratio expressed over the full angle-angular velocity range using a limited number of data points

description: Supplementary files for article The hamstrings to quadriceps functional ratio expressed over the full angle-angular velocity range using a limited number of data pointsThe hamstring to quadriceps (H : Q) strength ratio is widely used to identify individuals at risk of sustaining hamstring strain injuries. However, its efficacy is not supported by the current evidence. Current methods for the calculation of the H : Q ratio provide only a one- or two-dimensional ratio, often ignoring fundamental muscle mechanical properties. Based on isokinetic torque measurements of the knee flexors and extensors (0-400° s<sup>-1</sup>) in 25 young, physically active males, we derived a model equation that creates a threedimensional H : Q functional ratio profile. The model robustness was tested against a different number of input torque data (8, 11, 14 and 17 pairs of points) and small perturbation of the knee joint angle data (5°). The model was consistent and behaved well under all conditions apart from the eight pairs of points (R<sup>2</sup>= 0.84-0.96; RMSE = 0.14-0.25; NRMSE = 0.12-0.27), and the H : Q functional ratio was successfully described even at angles and velocities that cannot be normally assessed with isokinetic dynamometry. Overall, our results suggest that the model can provide a fast and accurate three-dimensional description of the knee joint muscle strength balance using as few as 11 experimental data points and this could be an easy-to-employ screening tool.<br>