cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc288ps1
title: CCDC 2093733: Experimental Crystal Structure Determination

description: Related Article: Kun Wang, Saisai Niu, Xin Guo, Weijun Tang, Dong Xue, Jianliang Xiao, Huaming Sun, Chao Wang|2022|J.Org.Chem.|87|3804|doi:10.1021/acs.joc.1c02916
description: Related Article: Chao Wang|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28bx0k
title: CCDC 2095848: Experimental Crystal Structure Determination

description: Related Article: Xiao-Di Nie, Zhuo-Ya Mao, Jia-Ming Guo, Chang-Mei Si, Bang-Guo Wei, Guo-Qiang Lin|2022|J.Org.Chem.|87|2380|doi:10.1021/acs.joc.1c02263
DOI: 10.5517/ccdc.csd.cc28bxtc
title: CCDC 2095873: Experimental Crystal Structure Determination

description: Related Article: Xiao-Di Nie, Zhuo-Ya Mao, Jia-Ming Guo, Chang-Mei Si, Bang-Guo Wei, Guo-Qiang Lin|2022|J.Org.Chem.|87|2380|doi:10.1021/acs.joc.1c02263
DOI: 10.5517/ccdc.csd.cc28lqcz
title: CCDC 2103361: Experimental Crystal Structure Determination

description: Related Article: Xu-Long Qin, Guo-Jie Wu, Fu-She Han|2022|J.Org.Chem.|87|3223|doi:10.1021/acs.joc.1c02928
description: Related Article: Xu-Long Qin, Guo-Jie Wu, Fu-She Han|2021|Org.Lett.|23|8570|doi:10.1021/acs.orglett.1c03293
DOI: 10.5517/ccdc.csd.cc28yn41
title: CCDC 2113863: Experimental Crystal Structure Determination

description: Related Article: Pei Wu, Yue Zhang, Ying Cheng|2022|J.Org.Chem.|87|2779|doi:10.1021/acs.joc.1c02703
DOI: 10.5517/ccdc.csd.cc28yn52
title: CCDC 2113864: Experimental Crystal Structure Determination

description: Related Article: Pei Wu, Yue Zhang, Ying Cheng|2022|J.Org.Chem.|87|2779|doi:10.1021/acs.joc.1c02703
DOI: 10.5517/ccdc.csd.cc28yn74
title: CCDC 2113866: Experimental Crystal Structure Determination

description: Related Article: Pei Wu, Yue Zhang, Ying Cheng|2022|J.Org.Chem.|87|2779|doi:10.1021/acs.joc.1c02703
DOI: 10.5517/ccdc.csd.cc28yn85
title: CCDC 2113867: Experimental Crystal Structure Determination

description: Related Article: Pei Wu, Yue Zhang, Ying Cheng|2022|J.Org.Chem.|87|2779|doi:10.1021/acs.joc.1c02703
DOI: 10.5517/ccdc.csd.cc28ysrs
title: CCDC 2114006: Experimental Crystal Structure Determination

description: Related Article: Pei Wu, Yue Zhang, Ying Cheng|2022|J.Org.Chem.|87|2779|doi:10.1021/acs.joc.1c02703
DOI: 10.6084/m9.figshare.19313957.v1
title: data summary

description: The data of LUVs and stopped flow
DOI: 10.6084/m9.figshare.19313957.v2
title: Foldamer-Based Ultrapermeable and Highly Selective Artificial Water Channels that Exclude Protons

description: The data of LUVs and stopped flow
DOI: 10.6084/m9.figshare.16881970.v2
title: A study on the association between the inferior nasal turbinate volume and the maxillary sinus mucosal lining using cone beam tomography

description: data
DOI: 10.6084/m9.figshare.16881970.v3
title: A study on the association between the inferior nasal turbinate volume and the maxillary sinus mucosal lining using cone beam tomography

description: data
DOI: 10.6084/m9.figshare.16881970
title: A study on the association between the inferior nasal turbinate volume and the maxillary sinus mucosal lining using cone beam tomography

description: data
DOI: 10.6084/m9.figshare.16881970.v5
title: A study on the association between the inferior nasal turbinate volume and the maxillary sinus mucosal lining using cone beam tomography

description: data
DOI: 10.6084/m9.figshare.16881970.v4
title: A study on the association between the inferior nasal turbinate volume and the maxillary sinus mucosal lining using cone beam tomography

description: data
DOI: 10.5281/zenodo.6331511
title: Data and code for Zheng et al. Contrasting coloured ventral wings are a visual collision avoidance signal in birds

description: This repository contains codes and data for Zheng et al. Contrasting coloured ventral wings are a visual collision avoidance signal in birds. We have three folders, each containing one of the three datasets of contrast scores of avian ventral wings. These include the mean manual contrast ventral wing scores for 1745 species, the mean manual contrast ventral wing scores for 648 species, and the mean Root-Mean-Square (RMS) contrast ventral wing scores for the same 648 species. We tested the collision avoidance hypothesis for each dataset by assessing the relationships between the contrast scores and ecological traits. We used the Bayesian Generalized Linear Mixed Models in MCMCglmm with considering the phylogenetic relatedness among species and the uncertainties of 100 phylogenetic trees (downloaded in birdtree.org). We included body mass, flock size, coloniality, the number of sympatric predators, and the interaction between coloniality and body mass as the predictors. In each folder, we included four files, including a R source file, a dataset containing the contrast scores and the ecological traits of the corresponding species, and a tree file containing 100 randomly sampled phylogenetic trees among these species. See the Methods of the paper for detail.
DOI: 10.6084/m9.figshare.19313960
title: gwas result.xlsx

description: We map a quantitative trait locus affecting the abundance of <i>Erysipelotrichaceae</i>species and show that it is caused by a 2.3-Kb deletion in the N-acetyl-galactosaminyl-transferase gene underpinning the ABO blood group in humans.
DOI: 10.5281/zenodo.6329715
title: Genetic and phenotypic diversity of banana-infecting Fusarium strains

description: Genetic and phenotypic diversity of banana-infecting <em>Fusarium</em> strains. Dataset1 contains molecular diagnosis and pathogenicity assays of Fusarium isolates. Dataset2 describes the sequenced isolates used in the study.
DOI: 10.5281/zenodo.6331549
title: Genetic and phenotypic diversity of banana-infecting Fusarium strains

description: Genetic and phenotypic diversity of banana-infecting <em>Fusarium</em> strains. Dataset1 contains molecular diagnosis and pathogenicity assays of Fusarium isolates. Dataset2 describes the sequenced isolates used in the study.
DOI: 10.5281/zenodo.6092456
title: Genetic and phenotypic diversity of banana-infecting Fusarium strains

description: Genetic and phenotypic diversity of banana-infecting <em>Fusarium</em> strains. Dataset1 contains molecular diagnosis and pathogenicity assays of Fusarium isolates. Dataset2 describes the sequenced isolates used in the study.
DOI: 10.5281/zenodo.6331544
title: Acrochordus granulatus SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6331543
title: Acrochordus granulatus SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6330711
title: Pin-tailed whydah (Vidua macroura) calls for passive acoustic monitoring

description: Data accompanying the paper: "Passive Acoustic Monitoring and Transfer Learning" <strong>Please cite this dataset as:</strong> Dufourq, Emmanuel and Batist, Carly and Foquet, Ruben and Durbach, Ian. (2022). Passive Acoustic Monitoring and Transfer Learning. BioRxiv doi: This dataset contains approximately 6 hours of audio that contained calls of the pin-tailed whydah (Vidua macroura). The audio data was collected in the Intaka Island Nature Reserve in Cape Town, South Africa using 1 Audiomoth. The sampling rate was set to 48,000Hz and the recordings were obtained over four days in January 2021. A larger dataset exists. The annotations files are in (.svl) format which is compatible with SonicVisualiser (https://www.sonicvisualiser.org/). Each audio file has a corresponding .svl file. Each .svl has segments of audio that were manually annotated as either ''thyolo-alethe" (presence class) or "noise" (absence class) -- this dataset can be used to train a binary classification model. The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip".
description: ED is supported by a research chairship from the African Institute for Mathematical Sciences South Africa. This work was carried out with the aid of a grant from the International Development Research Centre, Ottawa, Canada, www.idrc.ca, and with financial support from the Government of Canada, provided through Global Affairs Canada (GAC), www.international.gc.ca. This work was supported by funding from Microsoft's AI for Earth program.
DOI: 10.5281/zenodo.6330710
title: Pin-tailed whydah (Vidua macroura) calls for passive acoustic monitoring

description: Data accompanying the paper: "Passive Acoustic Monitoring and Transfer Learning" <strong>Please cite this dataset as:</strong> Dufourq, Emmanuel and Batist, Carly and Foquet, Ruben and Durbach, Ian. (2022). Passive Acoustic Monitoring and Transfer Learning. BioRxiv doi: This dataset contains approximately 6 hours of audio that contained calls of the pin-tailed whydah (Vidua macroura). The audio data was collected in the Intaka Island Nature Reserve in Cape Town, South Africa using 1 Audiomoth. The sampling rate was set to 48,000Hz and the recordings were obtained over four days in January 2021. A larger dataset exists. The annotations files are in (.svl) format which is compatible with SonicVisualiser (https://www.sonicvisualiser.org/). Each audio file has a corresponding .svl file. Each .svl has segments of audio that were manually annotated as either ''thyolo-alethe" (presence class) or "noise" (absence class) -- this dataset can be used to train a binary classification model. The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip".
description: ED is supported by a research chairship from the African Institute for Mathematical Sciences South Africa. This work was carried out with the aid of a grant from the International Development Research Centre, Ottawa, Canada, www.idrc.ca, and with financial support from the Government of Canada, provided through Global Affairs Canada (GAC), www.international.gc.ca. This work was supported by funding from Microsoft's AI for Earth program.
DOI: 10.5281/zenodo.6328319
title: Hainan gibbons (Nomascus hainanus) calls for passive acoustic monitoring

description: <em>This dataset extends an existing one (10.5281/zenodo.3991714).</em> Data accompanying the paper: "Passive Acoustic Monitoring and Transfer Learning" <strong>Please cite this dataset as:</strong> Dufourq, Emmanuel and Batist, Carly and Foquet, Ruben and Durbach, Ian. (2022). Passive Acoustic Monitoring and Transfer Learning. BioRxiv doi: This dataset contains approximately 10 hours of audio that contained calls of the critically endangered Hainan gibbons (Nomascus hainanus). The audio data was collected in the Bawangling National Nature Reserve, Malawi using 8 Song Meter SM3 recorders. The sampling rate was set to 9,600Hz and the recordings were collected between March to August 2016. The annotations files are in (.svl) format which is compatible with SonicVisualiser (https://www.sonicvisualiser.org/). Each audio file has a corresponding .svl file. Each .svl has segments of audio that were manually annotated as either ''gibbon" (presence class) or "no-gibbon" (absence class) -- this dataset can be used to train a binary classification model. The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip".
description: ED is supported by a research chairship from the African Institute for Mathematical Sciences South Africa. This work was carried out with the aid of a grant from the International Development Research Centre, Ottawa, Canada, www.idrc.ca, and with financial support from the Government of Canada, provided through Global Affairs Canada (GAC), www.international.gc.ca. This work was supported by funding from Microsoft's AI for Earth program. We thank the Management Office of Bawangling National Nature Reserve for logistical assistance in the field. Fieldwork was funded by an Arcus Foundation grant to STT and a Wildlife Acoustics grant to JVB. We also thank the following rangers who contributed to data collection: Guang Wei, Zhong Zhao, Qing Lin, Jinbing Zhang, Zhicheng Zhang, Quanjin Li, Xiaoliang Fu, Zhengchong Zhou, Lubiao Huang, Zhengkun Ye, Zhenghai Zou, Jinqiang Wang, Wentao Han and Zengnan Xie.
DOI: 10.5281/zenodo.6328318
title: Hainan gibbons (Nomascus hainanus) calls for passive acoustic monitoring

description: <em>This dataset extends an existing one (10.5281/zenodo.3991714).</em> Data accompanying the paper: "Passive Acoustic Monitoring and Transfer Learning" <strong>Please cite this dataset as:</strong> Dufourq, Emmanuel and Batist, Carly and Foquet, Ruben and Durbach, Ian. (2022). Passive Acoustic Monitoring and Transfer Learning. BioRxiv doi: This dataset contains approximately 10 hours of audio that contained calls of the critically endangered Hainan gibbons (Nomascus hainanus). The audio data was collected in the Bawangling National Nature Reserve, Malawi using 8 Song Meter SM3 recorders. The sampling rate was set to 9,600Hz and the recordings were collected between March to August 2016. The annotations files are in (.svl) format which is compatible with SonicVisualiser (https://www.sonicvisualiser.org/). Each audio file has a corresponding .svl file. Each .svl has segments of audio that were manually annotated as either ''gibbon" (presence class) or "no-gibbon" (absence class) -- this dataset can be used to train a binary classification model. The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip".
description: ED is supported by a research chairship from the African Institute for Mathematical Sciences South Africa. This work was carried out with the aid of a grant from the International Development Research Centre, Ottawa, Canada, www.idrc.ca, and with financial support from the Government of Canada, provided through Global Affairs Canada (GAC), www.international.gc.ca. This work was supported by funding from Microsoft's AI for Earth program. We thank the Management Office of Bawangling National Nature Reserve for logistical assistance in the field. Fieldwork was funded by an Arcus Foundation grant to STT and a Wildlife Acoustics grant to JVB. We also thank the following rangers who contributed to data collection: Guang Wei, Zhong Zhao, Qing Lin, Jinbing Zhang, Zhicheng Zhang, Quanjin Li, Xiaoliang Fu, Zhengchong Zhou, Lubiao Huang, Zhengkun Ye, Zhenghai Zou, Jinqiang Wang, Wentao Han and Zengnan Xie.
DOI: 10.34740/kaggle/dsv/3261942
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.6328244
title: Thyolo alethe (Chamaetylas choloensis) calls for passive acoustic monitoring

description: Data accompanying the paper: "Passive Acoustic Monitoring and Transfer Learning" <strong>Please cite this dataset as:</strong> Dufourq, Emmanuel and Batist, Carly and Foquet, Ruben and Durbach, Ian. (2022). Passive Acoustic Monitoring and Transfer Learning. BioRxiv doi: This dataset contains approximately 10 hours of audio that contained calls of the vulnerable Thyolo Alethe (Chamaetylas choloensis). The audio data was collected in the Mount Mulanje Biosphere Reserve, Malawi using 10 Audiomoths. The sampling rate was set to 32,000Hz and the recordings were obtained over five days in November 2020. A larger dataset exists. The annotations files are in (.svl) format which is compatible with SonicVisualiser (https://www.sonicvisualiser.org/). Each audio file has a corresponding .svl file. Each .svl has segments of audio that were manually annotated as either ''thyolo-alethe" (presence class) or "noise" (absence class) -- this dataset can be used to train a binary classification model. The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip".
description: ED is supported by a research chairship from the African Institute for Mathematical Sciences South Africa. This work was carried out with the aid of a grant from the International Development Research Centre, Ottawa, Canada, www.idrc.ca, and with financial support from the Government of Canada, provided through Global Affairs Canada (GAC), www.international.gc.ca. This work was supported by funding from Microsoft's AI for Earth program. The audio data containing calls of the Thyolo Alethe was collected by an international team of researchers from the Biodiversity Inventory for Conservation (BINCO) and the Wildlife and Environmental Society of Malawi (WESM), led by Ruben Foquet (BINCO) and Dr. Tiwonge Gawa (WESM and the Malawi University of Science and Technology, MUST).
DOI: 10.5281/zenodo.6328243
title: Thyolo alethe (Chamaetylas choloensis) calls for passive acoustic monitoring

description: Data accompanying the paper: "Passive Acoustic Monitoring and Transfer Learning" <strong>Please cite this dataset as:</strong> Dufourq, Emmanuel and Batist, Carly and Foquet, Ruben and Durbach, Ian. (2022). Passive Acoustic Monitoring and Transfer Learning. BioRxiv doi: This dataset contains approximately 10 hours of audio that contained calls of the vulnerable Thyolo Alethe (Chamaetylas choloensis). The audio data was collected in the Mount Mulanje Biosphere Reserve, Malawi using 10 Audiomoths. The sampling rate was set to 32,000Hz and the recordings were obtained over five days in November 2020. A larger dataset exists. The annotations files are in (.svl) format which is compatible with SonicVisualiser (https://www.sonicvisualiser.org/). Each audio file has a corresponding .svl file. Each .svl has segments of audio that were manually annotated as either ''thyolo-alethe" (presence class) or "noise" (absence class) -- this dataset can be used to train a binary classification model. The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip".
description: ED is supported by a research chairship from the African Institute for Mathematical Sciences South Africa. This work was carried out with the aid of a grant from the International Development Research Centre, Ottawa, Canada, www.idrc.ca, and with financial support from the Government of Canada, provided through Global Affairs Canada (GAC), www.international.gc.ca. This work was supported by funding from Microsoft's AI for Earth program. The audio data containing calls of the Thyolo Alethe was collected by an international team of researchers from the Biodiversity Inventory for Conservation (BINCO) and the Wildlife and Environmental Society of Malawi (WESM), led by Ruben Foquet (BINCO) and Dr. Tiwonge Gawa (WESM and the Malawi University of Science and Technology, MUST).
DOI: 10.34740/kaggle/dsv/3261965
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.6331560
title: Pareas carinatus SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6331559
title: Pareas carinatus SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6331571
title: Tropidonophis doriae SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6331570
title: Tropidonophis doriae SPAdes preassembly

description: .
DOI: 10.34740/kaggle/dsv/3262137
title: COVID Vaccination in World (updated daily)
DOI: 10.5281/zenodo.6331600
title: NULL

description: .
DOI: 10.5281/zenodo.6331599
title: NULL

description: .
DOI: 10.6084/m9.figshare.19314029
title: Data File for "The Effect of Judicial Selection Processes on Judicial Quality"

description: Data file for paper:<br>Russell Sobel and Joshua Hall, “The Effect of Judicial Selection Processes on Judicial Quality: The Role of Partisan Politics,” <i>Cato Journal</i> 27(1) 2007: 67-82. <br>
DOI: 10.6084/m9.figshare.19314029.v1
title: Data File for "The Effect of Judicial Selection Processes on Judicial Quality"

description: Data file for paper:<br>Russell Sobel and Joshua Hall, “The Effect of Judicial Selection Processes on Judicial Quality: The Role of Partisan Politics,” <i>Cato Journal</i> 27(1) 2007: 67-82. <br>
DOI: 10.6084/m9.figshare.14822838.v2
title: Cuckoo catfish learning

description: Primary data (and R script) for the paper on cuckoo catfish learning needed to reproduce reported results. Revised version.
DOI: 10.5281/zenodo.6331605
title: Liobagrus marginatus SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6331604
title: Liobagrus marginatus SPAdes preassembly

description: .
DOI: 10.6084/m9.figshare.14822838.v3
title: Cuckoo catfish learning

description: Primary data (and R script) for the paper on cuckoo catfish learning needed to reproduce reported results. Revised version.
DOI: 10.5281/zenodo.6331621
title: Toxicocalamus goodenoughensis SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6331620
title: Toxicocalamus goodenoughensis SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6331619
title: Data set figures 1-3 article Reaux et al; Communications Biology 2022

description: The files attached are : - the manuscript and figures of our article entitled ".." accepted for publication in Communication Biology in February 2022. - A supplementary material, which is an Excel file is the dataset of the figures 1 to 3. It is composed of two sheets in which the values of cerebral blood volume are given for every single animal included in our study: before and during each stimulation (been mechanical or chemical stimulation in sheet 1 - figure 2 or mechanical stimulations of either the ophthalmic or maxillary territories - 2d sheet - figure 3). - A Matlab file with dataset of the figure 4 (ULM of the saggital brain showing the rich and complex vasculature in the trigeminal ganglion)
DOI: 10.5281/zenodo.6331618
title: Data set figures 1-3 article Reaux et al; Communications Biology 2022

description: The files attached are : - the manuscript and figures of our article entitled ".." accepted for publication in Communication Biology in February 2022. - A supplementary material, which is an Excel file is the dataset of the figures 1 to 3. It is composed of two sheets in which the values of cerebral blood volume are given for every single animal included in our study: before and during each stimulation (been mechanical or chemical stimulation in sheet 1 - figure 2 or mechanical stimulations of either the ophthalmic or maxillary territories - 2d sheet - figure 3). - A Matlab file with dataset of the figure 4 (ULM of the saggital brain showing the rich and complex vasculature in the trigeminal ganglion)
DOI: 10.5281/zenodo.5734101
title: Deprecated. Digitized wood core samples

description: Deprecated version of. Please visit the new one: <em>https://doi.org/10.5281/zenodo.6331613</em> Wood samples in digitized cores with CaptuRING (CR_ in files) and scanned with Epson 750VPRO (scan_) for sample digitization comparison. Species: <em>Fagus sylvatica </em>(fs) <em>Quercus faginea </em>(qf) <em>Quercus ilex </em>(qi) <em>Quercus pyrenaica </em>(qy) <em>Juniperus cedrus </em>(jc) <em>Juniperus thurifera </em>(jt) <em>Pinus nigra </em>(pn) <em>Pinus pinaster </em>(pp)
description: Founded by Spanish Ministry of Science (CGL2017-87309-P and PROWARM PID2020-118444GA-I00, Junta de Castilla y León (OUTBREAK VA171P20 and IR2020-1-UVA08) and UPM (RP200060107).
DOI: 10.5281/zenodo.6331646
title: Sediment supply effects in hydrology-sediment modelling of an Alpine basin

description: Discharge, sediment and precipitation data used in the pubblication "Sediment supply effects in hydrology-sediment modelling of an Alpine basin" by Battista et al., WRR, in review.
DOI: 10.5281/zenodo.6331645
title: Sediment supply effects in hydrology-sediment modelling of an Alpine basin

description: Discharge, sediment and precipitation data used in the pubblication "Sediment supply effects in hydrology-sediment modelling of an Alpine basin" by Battista et al., WRR, in review.
DOI: 10.6084/m9.figshare.19312607
title: scDRS_data_release_030122.score_file_tmsfacs

description: scDRS results for TMS FACS + 75 diseases/traits (.score.gz and .full_score.gz files) (revision 1). <br>The 75 diseases/traits contain 74 diseases/traits analyzed in revision 1 and PASS_BIP_Stahl2019 analyzed in the initial submission.<br>Results are computed using weighted gene sets (top 1,000 MAGMA genes with MAGMA z-score weights).
DOI: 10.5281/zenodo.6331648
title: Grayia smithii SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6331647
title: Grayia smithii SPAdes preassembly

description: .
DOI: 10.6084/m9.figshare.19314068
title: Supplements

description: <b>Supplements</b>
DOI: 10.6084/m9.figshare.19314068.v1
title: Supplements

description: <b>Supplements</b>