cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17637/rh.23659728
title: LIFE database seasonality data as input for analysis in python for the article 'Small-scale livelihood fire: global spatiotemporal characteristics, and gaps in data'

description: Seasonality data from the LIFE database as input for analysis in Python
DOI: 10.17637/rh.23659728.v1
title: LIFE database seasonality data as input for analysis in python for the article 'Small-scale livelihood fire: global spatiotemporal characteristics, and gaps in data'

description: Seasonality data from the LIFE database as input for analysis in Python
DOI: 10.6084/m9.figshare.23661399
title: interact_3

description: Interact effects between 2 categorical variables
DOI: 10.6084/m9.figshare.23661399.v1
title: interact_3

description: Interact effects between 2 categorical variables
DOI: 10.5281/zenodo.8104788
title: Video Dataset of Respiratory Cilia Motion Phenotypes

description: Respiratory cilia are important components in the lung defense mechanism. The coordinated beating of cilia cleans the airways of pathogens and foreign particles. We present a large-scale validation dataset of cilia motion for characterizing ciliary function. Ciliary beat frequency (CBF) is provided as benchmark metrics. The video dataset of cilia motion phenotypes contains four categories: temperatures, drugs and ACE2 manipulation. Under each category, mouse trachea samples were treated with different stimuli and imaged with a high-speed video microscope to acquire cilia motion. In addition, we generate ground truth masks labeling ciliary area for image segmentation. This validation dataset can serve as a benchmark for the computer vision community to develop models for analyzing ciliary beat pattern. This video dataset contains 872 videos and their ground-truth masks with the ciliary area labeled. The videos were recorded at 250 frames per second for 1 second. The image size is 800x800. Each pixel is 0.07987 μm. The csv file contains the CBF values of each video.
description: Grants: NSF #1845915 CAREER: ABI-Innovation: CiliaWeb: Integrated platform for foundational and reproducible ciliary beat pattern analysis NIH GM139856 Pattern formation and function of PKD2/polycystin-2 in motile cilia
DOI: 10.5281/zenodo.8104789
title: Video Dataset of Respiratory Cilia Motion Phenotypes

description: Respiratory cilia are important components in the lung defense mechanism. The coordinated beating of cilia cleans the airways of pathogens and foreign particles. We present a large-scale validation dataset of cilia motion for characterizing ciliary function. Ciliary beat frequency (CBF) is provided as benchmark metrics. The video dataset of cilia motion phenotypes contains four categories: temperatures, drugs and ACE2 manipulation. Under each category, mouse trachea samples were treated with different stimuli and imaged with a high-speed video microscope to acquire cilia motion. In addition, we generate ground truth masks labeling ciliary area for image segmentation. This validation dataset can serve as a benchmark for the computer vision community to develop models for analyzing ciliary beat pattern. This video dataset contains 872 videos and their ground-truth masks with the ciliary area labeled. The videos were recorded at 250 frames per second for 1 second. The image size is 800x800. Each pixel is 0.07987 μm. The csv file contains the CBF values of each video.
description: Grants: NSF #1845915 CAREER: ABI-Innovation: CiliaWeb: Integrated platform for foundational and reproducible ciliary beat pattern analysis NIH GM139856 Pattern formation and function of PKD2/polycystin-2 in motile cilia
DOI: 10.5281/zenodo.8135892
title: Video Dataset of Respiratory Cilia Motion Phenotypes

description: Respiratory cilia are important components in the lung defense mechanism. The coordinated beating of cilia cleans the airways of pathogens and foreign particles. We present a large-scale validation dataset of cilia motion for characterizing ciliary function. Ciliary beat frequency (CBF) is provided as benchmark metrics. The video dataset of cilia motion phenotypes contains four categories: temperatures, drugs and ACE2 manipulation. Under each category, mouse trachea samples were treated with different stimuli and imaged with a high-speed video microscope to acquire cilia motion. In addition, we generate ground truth masks labeling ciliary area for image segmentation. This validation dataset can serve as a benchmark for the computer vision community to develop models for analyzing ciliary beat pattern. This video dataset contains 872 videos and their ground-truth masks with the ciliary area labeled. The videos were recorded at 250 frames per second for 1 second. The image size is 800x800. Each pixel is 0.07987 μm. The csv file contains the CBF values of each video.
description: Grants: NSF #1845915 CAREER: ABI-Innovation: CiliaWeb: Integrated platform for foundational and reproducible ciliary beat pattern analysis NIH GM139856 Pattern formation and function of PKD2/polycystin-2 in motile cilia
DOI: 10.5281/zenodo.4313996
title: Namelist for the CA20 Dataset

description: This namelist contains the information used to generate the CA20 dataset, a 20-year offshore wind resource assessment in the Outer Continental Shelf off the coast of California. Details of the dataset as well as analysis may be found in the technical report "2020 Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf" doi.org/10.2172/1677466. The dataset itself may accessed through the Registry of Open Data on AWS.
DOI: 10.5281/zenodo.4592280
title: Namelist for the CA20 Dataset

description: These namelist contains the information used to generate the CA20 dataset, a 20-year offshore wind resource assessment in the Outer Continental Shelf off the coast of California. namelist.wps was used by WPS 4.1 to generate boundary conditions. namelist.input was used by WRF 4.1.2 to carry out the CA20 simulation. Details of the CA20 dataset as well as analysis may be found in the technical report "2020 Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf" doi.org/10.2172/1677466. The dataset itself may accessed through the Registry of Open Data on AWS.
DOI: 10.5281/zenodo.4597548
title: Namelists for the CA20 Dataset and Figure Notebooks

description: This dataset contains the namelists used to generate the CA20 dataset, as well as notebooks and post-processed data used to generate figures for "A Twenty-Year Analysis of Winds in California for Offshore Wind Energy Production Using WRF v4.1.2" (in review). CA20 is a 20-year offshore wind resource assessment in the Outer Continental Shelf off the coast of California. namelist.wps was used by WPS 4.1 to generate boundary conditions. namelist.input was used by WRF 4.1.2 to carry out the CA20 simulation. Details of the CA20 dataset as well as analysis may be found in the technical report "2020 Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf" doi.org/10.2172/1677466. The dataset itself may accessed through the Registry of Open Data on AWS.
DOI: 10.5281/zenodo.4313995
title: Namelists for the CA20 Dataset and Figure Notebooks

description: This dataset contains the namelists used to generate the CA20 dataset, as well as notebooks and post-processed data used to generate figures for "A Twenty-Year Analysis of Winds in California for Offshore Wind Energy Production Using WRF v4.1.2" (in review). CA20 is a 20-year offshore wind resource assessment in the Outer Continental Shelf off the coast of California. namelist.wps was used by WPS 4.1 to generate boundary conditions. namelist.input was used by WRF 4.1.2 to carry out the CA20 simulation. Details of the CA20 dataset as well as analysis may be found in the technical report "2020 Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf" doi.org/10.2172/1677466. The dataset itself may accessed through the Registry of Open Data on AWS. Update on July 11, 2023: The previous versions of namelist.input incorrectly listed the surface layer scheme as 1 (MM5) when it should have been 5 (MYNN). This error occurred during manual transcription of a template namelist.
DOI: 10.5281/zenodo.8135940
title: Namelists for the CA20 Dataset and Figure Notebooks

description: This dataset contains the namelists used to generate the CA20 dataset, as well as notebooks and post-processed data used to generate figures for "A Twenty-Year Analysis of Winds in California for Offshore Wind Energy Production Using WRF v4.1.2" (in review). CA20 is a 20-year offshore wind resource assessment in the Outer Continental Shelf off the coast of California. namelist.wps was used by WPS 4.1 to generate boundary conditions. namelist.input was used by WRF 4.1.2 to carry out the CA20 simulation. Details of the CA20 dataset as well as analysis may be found in the technical report "2020 Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf" doi.org/10.2172/1677466. The dataset itself may accessed through the Registry of Open Data on AWS. Update on July 11, 2023: The previous versions of namelist.input incorrectly listed the surface layer scheme as 1 (MM5) when it should have been 5 (MYNN). This error occurred during manual transcription of a template namelist.
DOI: 10.6084/m9.figshare.23661426
title: interact_4

description: evans study on catecholamine and coronary heart disease
DOI: 10.6084/m9.figshare.23661426.v1
title: interact_4

description: evans study on catecholamine and coronary heart disease
DOI: 10.6084/m9.figshare.20301777
title: mouse155_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the matadata file in the same folder.
DOI: 10.6084/m9.figshare.20301777.v1
title: mouse155_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the matadata file in the same folder.
DOI: 10.6084/m9.figshare.20301795
title: mouse156_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301831
title: mouse155_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301831.v1
title: mouse155_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301840
title: mouse156_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301840.v1
title: mouse156_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.5281/zenodo.8088477
title: Database containing Raw Data of Growth and Survival of Pathogens and Microbiota from Fate Studies in Artisanal Fermented Foods

description: Deliverable 5.5 is a spreadsheet containing metadata and raw data obtained from the fate studies conducted in Workpackage 5. In case of reutilisation of these data, the source should be properly cited.
DOI: 10.5281/zenodo.8088476
title: Database containing Raw Data of Growth and Survival of Pathogens and Microbiota from Fate Studies in Artisanal Fermented Foods

description: Deliverable 5.5 is a spreadsheet containing metadata and raw data obtained from the fate studies conducted in Workpackage 5. In case of reutilisation of these data, the source should be properly cited.
DOI: 10.5281/zenodo.8135955
title: Database containing Raw Data of Growth and Survival of Pathogens and Microbiota from Fate Studies in Artisanal Fermented Foods

description: Deliverable 5.5 is a spreadsheet containing metadata and raw data obtained from the fate studies conducted in Workpackage 5. In case of reutilisation of these data, the source should be properly cited.
DOI: 10.6084/m9.figshare.20301846
title: mouse155_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301846.v1
title: mouse155_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301825
title: mouse155_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301825.v1
title: mouse155_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301837
title: mouse156_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301837.v1
title: mouse156_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301834.v1
title: mouse156_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301834
title: mouse156_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.5281/zenodo.8043719
title: Danesi_et_al_Cryosphere_2023-RAW_EVENTS_Waveform

description: The repository contains 2 zipped files with waveforms related to the paper Danesi et al. 2023, Cryosphere. The files are: - cycled_events_2003-04.tar.gz : containing 3-component waveforms for a single station used in the match-filtering analysis - events_waveforms.tar.gz : containing 3-component waveforms for a single station used for absolute location analysis
DOI: 10.5281/zenodo.8043718
title: Danesi_et_al_Cryosphere_2023-RAW_EVENTS_Waveform

description: The repository contains 2 zipped files with waveforms related to the paper Danesi et al. 2023, Cryosphere. The files are: - cycled_events_2003-04.tar.gz : containing 3-component waveforms for a single station used in the match-filtering analysis - events_waveforms.tar.gz : containing 3-component waveforms for a single station used for absolute location analysis
DOI: 10.6084/m9.figshare.20301852
title: mouse157_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301852.v1
title: mouse157_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301849.v1
title: mouse157_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301849
title: mouse157_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301828
title: mouse157_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301828.v1
title: mouse157_Thy1.1positive_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_BetaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.18112/openneuro.ds004632.v1.0.0
title: DTI readouts for designing a preclinical stem-cell therapy trial in experimental stroke
DOI: 10.6084/m9.figshare.20301843
title: mouse157_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.20301843.v1
title: mouse157_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.25403/upresearchdata.21572226.v1
title: Antenna pattern measurements results

description: This dataset contain the process measurement results of anenna array made from printed plastics and titanium metal printing. Files starting with selective laser melting (SLM) contain the data for the titanium printed antennas. Files starting with stereolithography (SLA) contain data for the plastic printed antennas. Files with the name horn are the antenna patterns for the just the horn antenna. The horns were made from plastic (SLA) and titanium (SLM).
DOI: 10.25403/upresearchdata.21572226
title: Antenna pattern measurements results

description: This dataset contain the process measurement results of anenna array made from printed plastics and titanium metal printing. Files starting with selective laser melting (SLM) contain the data for the titanium printed antennas. Files starting with stereolithography (SLA) contain data for the plastic printed antennas. Files with the name horn are the antenna patterns for the just the horn antenna. The horns were made from plastic (SLA) and titanium (SLM).
DOI: 10.25919/d77e-r124
title: Parkes observations for project P1032 semester 2023APRS_04

description: This project aims to continue to perform rapid measurements of relativistic parameters of southern binary pulsar systems using data from the Parkes Ultra Wideband Low (UWL) receiver and the MeerKAT telescope thereby enabling measurement of their component masses and in some cases, test theories of gravity. We will use the UWL data to obtain significant orbital coverage and timing baseline on these pulsars and obtain important constraints on orbital and temporal DM variations that will help in identifying the nature of the companion star. We will then use MeerKAT data at crucial orbital phases to improve our chances of measuring the relativistic parameters. Increase in the number of measured NS masses has profound implications for NS internal structure and for stellar and binary evolution physics.
DOI: 10.5281/zenodo.7777878
title: VQA-Introspect with Logical Relations

description: This is a version of the VQA-Introspect dataset by Selvaraju et al., but with added annotations about logical relations for binary QA pairs. Relations have been predicted using a fine-tuned BERT, which was pre-trained for NLI and fine-tuned on a sub-set of VQA-Introspect. In general, entries have the following fields:<br> img_id: This is the image name without extension (images come from COCO)<br> question_id: Question identifier as int<br> sent: String version of the question<br> question_type: Type of question (how it starts)<br> answer_type: Type of answer<br> label: Answers using soft scores (as required by LXMERT)<br> role: Question role (main, sub or unk)<br> Questions with role='sub' also have a field named parent, which indicates the ID of the QA pair it is related to, and a field named rel, which contains the relation to the parent. Total samples:<br> Train: 215862 (sub: 160085, main: 55777)<br> Val: 69668 (sub: 49882, main: 19786) Images must be downloaded separately from the COCO Dataset website. If you use this dataset, please cite: <pre>@inproceedings{tascon2023logical, title={Logical Implications for Visual Question Answering Consistency}, author={Tascon-Morales, Sergio and M{\'a}rquez-Neila, Pablo and Sznitman, Raphael}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={6725--6735}, year={2023} }</pre> as well as the original publication where VQA-Introspect was presented: <pre>@inproceedings{selvaraju2020squinting, title={Squinting at vqa models: Introspecting vqa models with sub-questions}, author={Selvaraju, Ramprasaath R and Tendulkar, Purva and Parikh, Devi and Horvitz, Eric and Ribeiro, Marco Tulio and Nushi, Besmira and Kamar, Ece}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={10003--10011}, year={2020} } </pre> Note: We respect the original license terms of the VQA-Introspect dataset and make manifest that the liability warranty described in those terms (§ 4.2 and 4.3) apply to this dataset too.
DOI: 10.5281/zenodo.7777877
title: VQA-Introspect with Logical Relations

description: This is a version of the VQA-Introspect dataset by Selvaraju et al., but with added annotations about logical relations for binary QA pairs. Relations have been predicted using a fine-tuned BERT, which was pre-trained for NLI and fine-tuned on a sub-set of VQA-Introspect. In general, entries have the following fields:<br> img_id: This is the image name without extension (images come from COCO)<br> question_id: Question identifier as int<br> sent: String version of the question<br> question_type: Type of question (how it starts)<br> answer_type: Type of answer<br> label: Answers using soft scores (as required by LXMERT)<br> role: Question role (main, sub or unk)<br> Questions with role='sub' also have a field named parent, which indicates the ID of the QA pair it is related to, and a field named rel, which contains the relation to the parent. Total samples:<br> Train: 215862 (sub: 160085, main: 55777)<br> Val: 69668 (sub: 49882, main: 19786) Images must be downloaded separately from the COCO Dataset website. If you use this dataset, please cite: <pre>@inproceedings{tascon2023logical, title={Logical Implications for Visual Question Answering Consistency}, author={Tascon-Morales, Sergio and M{\'a}rquez-Neila, Pablo and Sznitman, Raphael}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={6725--6735}, year={2023} }</pre> as well as the original publication where VQA-Introspect was presented: <pre>@inproceedings{selvaraju2020squinting, title={Squinting at vqa models: Introspecting vqa models with sub-questions}, author={Selvaraju, Ramprasaath R and Tendulkar, Purva and Parikh, Devi and Horvitz, Eric and Ribeiro, Marco Tulio and Nushi, Besmira and Kamar, Ece}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={10003--10011}, year={2020} } </pre> Note: We respect the original license terms of the VQA-Introspect dataset and make manifest that the liability warranty described in those terms (§ 4.2 and 4.3) apply to this dataset too.
DOI: 10.5281/zenodo.7777849
title: Diabetic Macular Edema VQA Dataset with Logical Relations

description: Same as Diabetic Macular Edema VQA Dataset, but logical relations are added between pairs of questions. If you use this dataset, please cite our paper: <pre>@inproceedings{tascon2023logical, title={Logical Implications for Visual Question Answering Consistency}, author={Tascon-Morales, Sergio and M{\'a}rquez-Neila, Pablo and Sznitman, Raphael}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={6725--6735}, year={2023} }</pre>
DOI: 10.5281/zenodo.7777848
title: Diabetic Macular Edema VQA Dataset with Logical Relations

description: Same as Diabetic Macular Edema VQA Dataset, but logical relations are added between pairs of questions. If you use this dataset, please cite our paper: <pre>@inproceedings{tascon2023logical, title={Logical Implications for Visual Question Answering Consistency}, author={Tascon-Morales, Sergio and M{\'a}rquez-Neila, Pablo and Sznitman, Raphael}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={6725--6735}, year={2023} }</pre>