cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7925/drs1.duchas_4714333
title: Headless Coach

description: Story collected by Nioclás Ó Connaill, a student at Barrow school (Barrow, Co. Kerry) from informant U. Ó Connaill.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Ml. Ó h Uallacháin.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4931823
title: Funny Stories

description: Story collected by a student at Mount Plunkett school (Mountplunkett, Co. Roscommon) from informant Patrick Kelly.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Bríd Ní Bheirn.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4931824
title: Riddles

description: Story collected by a student at Páirc an Iarla school (Rathpeak, Co. Roscommon) from informant James Murray.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Ss. Ó Maonaigh.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_5192955
title: Story

description: Story collected by Celia Courtney, a student at Carrowbawn, Cill Dá Lua school (Carrowbaun, Co. Clare) from informant Pat Courtney.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Máire, Bean Uí Ghadhnair.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4492717
title: Scéal an Ghasúir Óig

description: Story collected by Maigréad Bean Mhic Amhlaoidh, a student at Dubhchoradh school (Doochary, Co. Donegal) from informant Gráinne Bean Uí Ultaigh.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Máighréad, Bean Mhic Amhlaoidh.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4714336
title: Roger Casement

description: Story collected by Nioclás Ó Connaill, a student at Barrow school (Barrow, Co. Kerry) from informant U. Ó Connaill.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Ml. Ó h Uallacháin.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4492719
title: Póstaithe

description: Story collected by Sorcha Ní Laoghóg, a student at An Róisín school (Saltpans, Co. Donegal) from informant Seamus Ó Laoghóg.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Cathal Ó Ceallaigh.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_5192956
title: Story

description: Story collected by Celia Courtney, a student at Carrowbawn, Cill Dá Lua school (Carrowbaun, Co. Clare) from informant an unidentified informant.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Máire, Bean Uí Ghadhnair.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4714340
title: Headless Coach

description: Story collected by Pádraig Ó Slatra, a student at Barrow school (Barrow, Co. Kerry) from informant Tom Ferris.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Ml. Ó h Uallacháin.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4931829
title: Song - Little May

description: Story collected by a student at Páirc an Iarla school (Rathpeak, Co. Roscommon) from informant Kitty Whyte.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Ss. Ó Maonaigh.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4931832
title: Song - A Fairy went a Marketing

description: Story collected by a student at Páirc an Iarla school (Rathpeak, Co. Roscommon) from informant Kitty Whyte.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Ss. Ó Maonaigh.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4492720
title: Féilte na Bliana - Lá Bealtaine

description: Story collected by a student at Leitir school (Templecrone, Co. Donegal) (no informant identified).
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Proinsias Ó h Eachaidh.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_5192957
title: Story

description: Story collected by John Long, a student at Carrowbawn, Cill Dá Lua school (Carrowbaun, Co. Clare) (no informant identified).
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Máire, Bean Uí Ghadhnair.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.34740/kaggle/dsv/4881136
title: Mahanagar Yatayat Dataset
DOI: 10.25934/pr00001371.2
title: Data Package for study.

description: The investigators are now proposing to compare two laser techniques for treating Benign prostate hyperplasia (BPH); Holmium Laser Enucleation of the Prostate (HOLEP) versus (greenlight) XPS which is a recently available technology in our center and is more efficient hence our choice to include patients with any size prostate. This will confirm whether the two techniques are equivalent in efficacy and safety independent of size as well as cost. The two techniques are available world wide as standard of care
DOI: 10.25934/pr00008748
title: Stan IVP - Test VM #1

description: Stan IVP - Test VM #1
DOI: 10.25934/pr00007528.2
title: Available IPD datapackage for study 'Dextromethorphan in Fibromyalgia'

description: The objective of this protocol is to evaluate if Dextromethorphan (DXM) reduces Fibromyalgia (FM) pain. DXM is a drug found in several over-the-counter products, including cough suppressants. The drug may reduce FM pain by suppressing inflammation in the central nervous system. The investigators will be observing the effects of DXM on daily self-reported pain measures in people with FM. If DXM reduces FM pain, it will provide important information about the nature of FM pathophysiology.
DOI: 10.5281/zenodo.7557037
title: clarias_angolensis_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7557036
title: clarias_angolensis_spades_01.fasta.gz

description: .
DOI: 10.25934/pr00003130.9
title: Available IPD datapackage for study 'Randomized Clinical Trial Comparing Low Power (50W) Holmium Laser Enucleation of the Prostate (HoLEP) Versus High Power (100W) HoLEP'

description: HoLEP (Holmium laser enucleation of the prostate) entails dissection of the whole median and lateral prostatic lobes off the surgical capsule via a retrograde approach starting at the apex. The enucleated lobes were pushed to the bladder followed by hemostasis of the prostate bed then intravesical morcellation of the enucleated adenoma. The investigators are going to compare safety and efficacy of low power; LP-HoLEP vs. high power; HP-HoLEP in treatment of infra-vesical obstruction secondary to BPH (Benign prostate Hyperplasia).
DOI: 10.5281/zenodo.7556437
title: Epiphytic common core bacteria in the microbiomes of co-located green (Ulva), brown (Saccharina, Gelidium) and red (Grateloupia) macroalgae

description: We collected specimens of <em>Ulva </em>sp. (green algae), <em>Saccharina </em>sp. (brown algae), <em>Grateloupia </em>sp., and <em>Gelidium </em>sp. (both red algae) during all four seasons from a coastal reef in Weihai, China, and analyzed their surface-colonizing bacteria in comparison to surrounding seawater and sediment controls. 16S rRNA amplicon sequencing, extensive plate cultivation, sequencing of selected strains, and sequencing of 23 metagenomes were performed in this study. Besides composition, we analyzed the potential of phycosphere bacteria to degrade algal polysaccharides and to produce bioactive secondary metabolites. This comprehensive dataset represents a significant stepping stone towards a better understanding of macroalgal phycosphere bacteria and paves the way to functional studies on representative strains.
DOI: 10.34740/kaggle/dsv/4881196
title: Egypt Gold Prices | Daily Updated
DOI: 10.5281/zenodo.7557046
title: platyallabes_tihoni_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7557045
title: platyallabes_tihoni_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7557054
title: clarias_platycephalus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7557055
title: clarias_platycephalus_spades_01.fasta.gz

description: .
DOI: 10.15784/601645
title: Dissolved Inorganic Nutrient Samples from Station E (Palmer Station, Antarctica) and Associated Incubation Experiments

description: Dissolved inorganic nutrient samples were collected from Station E (Palmer Station, Antarctica) and associated incubation experiments with Station E water. Samples were analyzed for Nitrate plus Nitrite, Nitrite, Ammonium, Phosphate and Silicate. All nutrient analyses were performed at Bigelow Laboratory for Ocean Sciences. An overview of the analytical methods used for these analyses is included in a secondary tab with the uploaded data.
DOI: 10.15784/601647
title: Flow Cytometry Samples from Station E (Palmer Station, Antarctica) and Associated Incubation Experiments

description: Flow cytometry samples were collected from Station E (Palmer Station, Antarctica) and associated incubation experiments with Station E water. Samples were analyzed for Phytoplankton (&lt;20 um), Cryptophytes (&lt;20 um), Heterotrophic Nanoflagellates (&lt;20 um) and Total Bacteria. All flow cytometric analyses were performed at Bigelow Laboratory for Ocean Sciences. An overview of the analytical methods used for these samples is included in a secondary tab with the uploaded data.
DOI: 10.15784/601648
title: Biogenic Sulfur Samples from Station E (Palmer Station, Antarctica) and Associated Incubation Experiments

description: Biogenic sulfur samples were collected from Station E (Palmer Station, Antarctica) and from associated incubation experiments with Station E water. Samples were analyzed for Dimethyl Sulfide (DMS), particulate Dimethylsulfoniopropionate (DMSPp), dissolved Dimethylsulfoniopropionate (DMSPd), particulate Dimethylsulfoxide (DMSOp), dissolved Dimethylsulfoxide (DMSOd) and DMSP lyase activity. All analyses were performed at Palmer Station during scientific deployments. An overview of the methods used for these analyses is included in a secondary tab with the uploaded data.
DOI: 10.15784/601646
title: Dissolved Organic Carbon (DOC) and Total Dissolved Nitrogen (TDN) Samples from Station E (Palmer Station, Antarctica) and Associated Incubation Experiments

description: Dissolved Organic Carbon (DOC) and Total Dissolved Nitrogen (TDN) samples were collected from Station E (Palmer Station, Antarctica) and associated incubation experiments with Station E water. Samples were analyzed for DOC and TDN using a Shimadzu TOC-L system equipped with TNM-L for N detection. All analyses were performed in the Hansell Lab at the University of Miami, FL (USA). References for the analytical methods used for these analyses are included in a secondary tab with the uploaded data.
DOI: 10.5281/zenodo.7557086
title: parauchenoglanis_punctatus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7557085
title: parauchenoglanis_punctatus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7557072
title: Doodleverse/Segmentation Zoo Res-UNet models for 2-class (water, other) segmentation of Sentinel-2 and Landsat-7/8 1-band NDWI images of coasts.

description: <em><strong>Doodleverse/Segmentation Zoo Res-UNet models for 2-class (water, other) segmentation of Sentinel-2 and Landsat-7/8 1-band NDWI images of coasts.</strong></em> These Residual-UNet model data are based on NDWI images of coasts and associated labels. Models have been created using Segmentation Gym* using the following dataset**: https://doi.org/10.5281/zenodo.7384263 Classes: {0=other, 1=water} <strong>File descriptions</strong> For each model, there are 5 files with the same root name: 1. <strong>'.json' </strong>config file: this is the file that was used by Segmentation Gym* to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse. 2.<strong> '.h5'</strong> weights file: this is the file that was created by the Segmentation Gym* function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym* function `seg_images_in_folder.py`. Models may be ensembled. 3.<strong> '_modelcard.json'</strong> model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model 4. <strong> '_model_history.npz'</strong> model training history file: this numpy archive file contains numpy arrays describing the training and validation losses and metrics. It is created by the Segmentation Gym function `train_model.py` 5. <strong> '.png'</strong> model training loss and mean IoU plot: this png file contains plots of training and validation losses and mean IoU scores during model training. A subset of data inside the .npz file. It is created by the Segmentation Gym function `train_model.py` Additionally, BEST_MODEL.txt contains the name of the model with the best validation loss and mean IoU <strong>References</strong> *Segmentation Gym: Buscombe, D., & Goldstein, E. B. (2022). A reproducible and reusable pipeline for segmentation of geoscientific imagery. Earth and Space Science, 9, e2022EA002332. https://doi.org/10.1029/2022EA002332 See: https://github.com/Doodleverse/segmentation_gym ** Buscombe, Daniel. (2022). Images and 2-class labels for semantic segmentation of Sentinel-2 and Landsat RGB, NIR, and SWIR satellite images of coasts (water, other) (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7384263
DOI: 10.5281/zenodo.7557071
title: Doodleverse/Segmentation Zoo Res-UNet models for 2-class (water, other) segmentation of Sentinel-2 and Landsat-7/8 1-band NDWI images of coasts.

description: <em><strong>Doodleverse/Segmentation Zoo Res-UNet models for 2-class (water, other) segmentation of Sentinel-2 and Landsat-7/8 1-band NDWI images of coasts.</strong></em> These Residual-UNet model data are based on NDWI images of coasts and associated labels. Models have been created using Segmentation Gym* using the following dataset**: https://doi.org/10.5281/zenodo.7384263 Classes: {0=other, 1=water} <strong>File descriptions</strong> For each model, there are 5 files with the same root name: 1. <strong>'.json' </strong>config file: this is the file that was used by Segmentation Gym* to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse. 2.<strong> '.h5'</strong> weights file: this is the file that was created by the Segmentation Gym* function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym* function `seg_images_in_folder.py`. Models may be ensembled. 3.<strong> '_modelcard.json'</strong> model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model 4. <strong> '_model_history.npz'</strong> model training history file: this numpy archive file contains numpy arrays describing the training and validation losses and metrics. It is created by the Segmentation Gym function `train_model.py` 5. <strong> '.png'</strong> model training loss and mean IoU plot: this png file contains plots of training and validation losses and mean IoU scores during model training. A subset of data inside the .npz file. It is created by the Segmentation Gym function `train_model.py` Additionally, BEST_MODEL.txt contains the name of the model with the best validation loss and mean IoU <strong>References</strong> *Segmentation Gym: Buscombe, D., & Goldstein, E. B. (2022). A reproducible and reusable pipeline for segmentation of geoscientific imagery. Earth and Space Science, 9, e2022EA002332. https://doi.org/10.1029/2022EA002332 See: https://github.com/Doodleverse/segmentation_gym ** Buscombe, Daniel. (2022). Images and 2-class labels for semantic segmentation of Sentinel-2 and Landsat RGB, NIR, and SWIR satellite images of coasts (water, other) (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7384263
DOI: 10.5281/zenodo.7557095
title: euristhmus_nudiceps_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7557094
title: euristhmus_nudiceps_spades_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.20382297
title: Southern pike populations out of the species native range may help its conservation and management

description: <strong>Raw_Data_16_SSR.csv</strong>: three digit microsatellite genotypes at 16 loci in csv format before the correction for genotyping errors. Dataset contains gentic information on 128 individuals from four populations: Alto Flumendosa Lake (FLU), Trasimeno Lake (TRA), Carignano-La Loggia (CAR), Drava River (DRA). The latter consists of 22 sampled individuals belonging to the species <em>Esox lucius</em>. The remainder of sampled individals were identified as <em>Esox cisalpinus</em> by mtDNA barcoding. <br> <strong>Raw_Data_11_SSR.csv</strong>: three digit microsatellite genotypes at 11 loci in csv format before the correction for genotyping errors. This dataset differ by <strong>Raw_Data_16_SSR.csv</strong> by the removal of five loci, which were characterised by too many missing data and/or were almost monomorphic. <br> <strong>Easypop_workflow.txt</strong>: This is the output from EASYPOP that summarizes the options used to carry out the simulations. <br> <strong>R-scripts.zip</strong>: The archive contains the scripts to carry out analyses the required the R statistical enviironment together with the input files. <br> <strong>Uncorrected_vs_corrected_genetic_data.pdf</strong>: This file shows the outputs of Bayesian clustering, Principal Component Analysis and Discriminant Analysis of Principal Components for both uncorrected and corrected genetic data. <br> <br> <br>
DOI: 10.6084/m9.figshare.20382297.v1
title: Southern pike populations out of the species native range may help its conservation and management

description: <strong>Raw_Data_16_SSR.csv</strong>: three digit microsatellite genotypes at 16 loci in csv format before the correction for genotyping errors. Dataset contains gentic information on 128 individuals from four populations: Alto Flumendosa Lake (FLU), Trasimeno Lake (TRA), Carignano-La Loggia (CAR), Drava River (DRA). The latter consists of 22 sampled individuals belonging to the species <em>Esox lucius</em>. The remainder of sampled individals were identified as <em>Esox cisalpinus</em> by mtDNA barcoding. <br> <strong>Raw_Data_11_SSR.csv</strong>: three digit microsatellite genotypes at 11 loci in csv format before the correction for genotyping errors. This dataset differ by <strong>Raw_Data_16_SSR.csv</strong> by the removal of five loci, which were characterised by too many missing data and/or were almost monomorphic. <br> <strong>Easypop_workflow.txt</strong>: This is the output from EASYPOP that summarizes the options used to carry out the simulations. <br> <strong>R-scripts.zip</strong>: The archive contains the scripts to carry out analyses the required the R statistical enviironment together with the input files. <br> <strong>Uncorrected_vs_corrected_genetic_data.pdf</strong>: This file shows the outputs of Bayesian clustering, Principal Component Analysis and Discriminant Analysis of Principal Components for both uncorrected and corrected genetic data. <br> <br> <br>
DOI: 10.6084/m9.figshare.21937154
title: Sexual crime in Colombia 2010-2022

description: Reports of sexual crimes reported from 1 January 2010 to 31 December 2022 by consulting the Crime Observatory of the Colombian National Police
DOI: 10.6084/m9.figshare.21936962
title: figure data

description: The pictures and curves simulated by fluent. The other file is the file exported using ANSYS workbench.
DOI: 10.6084/m9.figshare.21936962.v1
title: figure data

description: The pictures and curves simulated by fluent. The other file is the file exported using ANSYS workbench.
DOI: 10.5281/zenodo.7557143
title: chrysichthys_thysi_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7557142
title: chrysichthys_thysi_spades_01.fasta.gz

description: .
DOI: 10.25582/data.2020-08.2043832/2162228
title: Data for EMSL Project 51287 from August 2020
DOI: 10.25582/data.2020-10.2073209/2162229
title: Data for EMSL Project 51287 from October 2020
DOI: 10.6084/m9.figshare.24211488
title: Supplementary material for "High frequency of recessive <i>WFS1</i> mutations among Indian children with islet antibody-negative type 1 diabetes"

description: Supplementary data for the manuscript titled "High frequency of recessive <i>WFS1</i> mutations among Indian children with islet antibody-negative type 1 diabetes"