cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13244243
title: Salivary metatranscriptome for oral cancer diagnostic dataset

description: The dataset provided will enable reproducibility of key findings in the paper.
DOI: 10.5281/zenodo.4275587
title: Toxic bait as an alternative tool in the management of Spodoptera frugiperda in second corn crops

description: The attached file Data_base_JEN-2020-0374 (To upload in repository) refers to the article "Toxic bait as an alternative tool in the management of Spodoptera frugiperda in second corn crops"which was submitted to the Journal Applied Entomology (JEN-2020-0374)
DOI: 10.5281/zenodo.4275586
title: Toxic bait as an alternative tool in the management of Spodoptera frugiperda in second corn crops

description: The attached file Data_base_JEN-2020-0374 (To upload in repository) refers to the article "Toxic bait as an alternative tool in the management of Spodoptera frugiperda in second corn crops"which was submitted to the Journal Applied Entomology (JEN-2020-0374)
DOI: 10.26135/koa1
title: KODIAQ Data Release 3

description: This dataset or service is made available by the Keck Observatory Archive (KOA) at IPAC, which is operated by the California Institute of Technology under contract with the National Aeronautics and Space Administration.
DOI: 10.35111/zf5w-xq73
title: Global TIMIT Learner Simple English

description: 
Introduction<br>

Global TIMIT Learner Simple English was developed by the Linguistic Data Consortium and Shanghai Jiao Tong University and consists of approximately 12 hours of L1 and L2 English read speech and transcripts.<br>

The Global TIMIT project aimed to create a series of corpora in a variety of languages with a similar set of key features as in the original TIMIT Acoustic-Phonetic Continuous Speech Corpus (LDC93S1) which was designed for acoustic-phonetic studies and for the development and evaluation of automatic speech recognition systems. Specifically, these features included:<br>

    A large number of fluently-read sentences, containing a representative sample of phonetic, lexical, syntactic, semantic, and pragmatic patterns
    A relatively large number of speakers
    Time-aligned lexical and phonetic transcription of all utterances
    Some sentences read by all speakers, others read by a few speakers, and others read by just one speaker<br>

Data<br>

Global TIMIT Learner Simple English consists of two separate data sets of 50 speakers reading 120 sentences from the original TIMIT data set. These sentences were selected as "simple" to read by Chinese learners of English. Among the 120 sentences, 20 sentences were read by all speakers, 40 sentences were read by 10 speakers, and 60 sentences were read by five speakers, for a total of 820 sentence types.<br>

L1 Simple English was recorded at the University of Pennsylvania, USA; participants were 25 female and 25 male native American English speakers. L2 Simple English was recorded at Shanghai Jiao Tong University, China. L2 speakers (25 female, 25 male) were Chinese learners of English considered fluent.<br>

All speech data are presented as 16kHz, 16-bit flac compressed wav files. Each file has accompanying phone and word segmentation files, as well as Praat TextGrid files.
Acknowledgements<br>

The authors acknowledge the generous support of the University of Pennsylvania's Office of the Vice Provost for Global Initiatives (PennGlobal) through its Penn China Research and Engagement Fund, and the School of Arts and Sciences through its Global Engagement Fund as well as the Linguistic Data Consortium.
Samples<br>

Please view the following samples:<br>

    L1 Audio (FLAC)
    L1 Word (TXT)
    L1 Phones (TXT)
    L1 TextGrid (TXT)
    L2 Audio (FLAC)
    L2 Word (TXT)
    L2 Phones (TXT)
    L2 TextGrid (TXT)<br>

Updates<br>

None at this time.
Copyright
Portions © 1993, 2020 Trustees of the University of Pennsylvania
DOI: 10.21227/w8pq-7f68
title: USA Nov.2020 Election 20 Mil. Tweets (with Sentiment and Party Name Labels) Dataset

description: This dataset includes 24,201,654 tweets related to the US Presidential Election on November 3, 2020, collected between July 1, 2020, and November 11, 2020. The related party name and sentiment scores of tweets, also the words that affect the score were added to the data set.
DOI: 10.6084/m9.figshare.13244270
title: Madidi Project Full Dataset - version 4.1

description: This item contains version 4.1 of the Madidi Project's full dataset. The zip file contains: (1) raw data, which was downloaded from Tropicos (www.tropicos.org) on September 7 2020; (2) R scripts used to modify, correct and clean the raw data; (3) clean data that are the output of the R scripts, and which are the point of departure for most uses of the Madidi Dataset; (4) additional post-cleaning scripts that obtain some additional but non-essential information from the clean data (e.g. by extracting environmental data from rasters); and (5) a miscellaneous collection of additional non-essential information and figures. This item also includes the Data Use Policy for these data.<br>The core dataset of the Madidi Project consists of a network of ~500 forest plots distributed in and around the Madidi National Park in Bolivia. This network contains 50 permanently marked large plots (1-ha), as well as &gt;450 temporary small plots (0.1-ha). Within the large plots, all woody individuals with a dbh ≥10 cm have been mapped, tagged, measured and identified. Some of these plots have also been re-visited and information on mortality, recruitment and growth exists. Within the small plots, all woody individuals with a dbh ≥2.5 cm have been measured and identified. Each plot has some edaphic and topographic information, and some large plots have information on various plant functional traits. <br><br>The Madidi Project is a collaborative research effort to document and study plant biodiversity in the Amazonia and Tropical Andes of northwestern Bolivia. The project is currently lead by the Missouri Botanical Garden (MBG), in collaboration with the Herbario Nacional de Bolivia. The management of the project is at MBG, where J. Sebastian Tello (sebastian.tello@mobot.org) is the scientific director and Olga Martha Montiel (olgamartha.montiel@mobot.org) is the administrative director. The directors oversee the activities of a research team based in Bolivia. MBG works in collaboration with other data contributors (currently: Manuel J. Macía [manuel.macia@uam.es], Gabriel Arellano [gabriel.arellano.torres@gmail.com] and Beatriz Nieto [sonneratia@gmail.com]), with a representative from the Herbario Nacional de Bolivia (LPB; Carla Maldonado [carla.maldonado1@gmail.com]), as well as with other close associated researchers from various institutions. For more information regarding the organization and objectives of the Madidi Project, you can visit the project’s website (www.madidiproject.weebly.com).
DOI: 10.21227/vzmz-4v48
title: USA Nov.2020 Election 20 Mil. Tweets (with Sentiment and Party Name Labels) Dataset

description: This dataset includes 24,201,654 tweets related to the US Presidential Election on November 3, 2020, collected between July 1, 2020, and November 11, 2020. The related party name and sentiment scores of tweets, also the words that affect the score were added to the data set.
DOI: 10.5517/ccdc.csd.cc1zj1vd
title: CCDC 1832684: Experimental Crystal Structure Determination

description: Related Article: Leonel Llanos, Cristian Vera, Andrés Vega, Daniel Aravena, Luis Lemus|2020|Inorg.Chem.|59|15061|doi:10.1021/acs.inorgchem.0c02037
DOI: 10.5517/ccdc.csd.cc120w65
title: CCDC 983946: Experimental Crystal Structure Determination

description: Related Article: Khurram Shahzad Munawar, Saqib Ali, Muhammad Nawaz Tahir, Nasir Khalid, Qamar Abbas, Irfan Zia Qureshi, Shabbir Hussain, Muhammad Ashfaq|2020|J.Coord.Chem.|73|2275|doi:10.1080/00958972.2020.1813282
DOI: 10.5517/ccdc.csd.cc24nlw9
title: CCDC 1986011: Experimental Crystal Structure Determination

description: Related Article: Khurram Shahzad Munawar, Saqib Ali, Muhammad Nawaz Tahir, Nasir Khalid, Qamar Abbas, Irfan Zia Qureshi, Shabbir Hussain, Muhammad Ashfaq|2020|J.Coord.Chem.|73|2275|doi:10.1080/00958972.2020.1813282
DOI: 10.5517/ccdc.csd.cc120wb9
title: CCDC 983950: Experimental Crystal Structure Determination

description: Related Article: Khurram Shahzad Munawar, Saqib Ali, Muhammad Nawaz Tahir, Nasir Khalid, Qamar Abbas, Irfan Zia Qureshi, Shabbir Hussain, Muhammad Ashfaq|2020|J.Coord.Chem.|73|2275|doi:10.1080/00958972.2020.1813282
DOI: 10.5517/ccdc.csd.cc2581cw
title: CCDC 2003727: Experimental Crystal Structure Determination

description: Related Article: Zhong Liu, Xian-Shuang Tu, Le-Tao Guo, Xiao-Chen Wang|2020|Chemical Science|11|11548|doi:10.1039/D0SC03883K
DOI: 10.5517/ccdc.csd.cc2581dx
title: CCDC 2003728: Experimental Crystal Structure Determination

description: Related Article: Zhong Liu, Xian-Shuang Tu, Le-Tao Guo, Xiao-Chen Wang|2020|Chemical Science|11|11548|doi:10.1039/D0SC03883K
DOI: 10.5517/ccdc.csd.cc25lmgw
title: CCDC 2013898: Experimental Crystal Structure Determination

description: Related Article: Andrey N. Usoltsev, Alexander S. Novikov, Maxim N. Sokolov, Sergey A. Adonin|2020|Solid State Sciences|109|106441|doi:10.1016/j.solidstatesciences.2020.106441
DOI: 10.5517/ccdc.csd.cc25lmhx
title: CCDC 2013899: Experimental Crystal Structure Determination

description: Related Article: Andrey N. Usoltsev, Alexander S. Novikov, Maxim N. Sokolov, Sergey A. Adonin|2020|Solid State Sciences|109|106441|doi:10.1016/j.solidstatesciences.2020.106441
DOI: 10.5517/ccdc.csd.cc25m3pm
title: CCDC 2014370: Experimental Crystal Structure Determination

description: Related Article: Thomas M. Horsley Downie, Jonathan W. Hall, Thomas P. Collier Finn, David J. Liptrot, John P. Lowe, Mary F. Mahon, Claire L. McMullin, Michael K. Whittlesey|2020|Chem.Commun.|56|13359|doi:10.1039/D0CC05694D
DOI: 10.5517/ccdc.csd.cc25m3qn
title: CCDC 2014371: Experimental Crystal Structure Determination

description: Related Article: Thomas M. Horsley Downie, Jonathan W. Hall, Thomas P. Collier Finn, David J. Liptrot, John P. Lowe, Mary F. Mahon, Claire L. McMullin, Michael K. Whittlesey|2020|Chem.Commun.|56|13359|doi:10.1039/D0CC05694D
DOI: 10.5517/ccdc.csd.cc25m3rp
title: CCDC 2014372: Experimental Crystal Structure Determination

description: Related Article: Thomas M. Horsley Downie, Jonathan W. Hall, Thomas P. Collier Finn, David J. Liptrot, John P. Lowe, Mary F. Mahon, Claire L. McMullin, Michael K. Whittlesey|2020|Chem.Commun.|56|13359|doi:10.1039/D0CC05694D
DOI: 10.5517/ccdc.csd.cc25m3sq
title: CCDC 2014373: Experimental Crystal Structure Determination

description: Related Article: Thomas M. Horsley Downie, Jonathan W. Hall, Thomas P. Collier Finn, David J. Liptrot, John P. Lowe, Mary F. Mahon, Claire L. McMullin, Michael K. Whittlesey|2020|Chem.Commun.|56|13359|doi:10.1039/D0CC05694D
DOI: 10.5517/ccdc.csd.cc25m3tr
title: CCDC 2014374: Experimental Crystal Structure Determination

description: Related Article: Thomas M. Horsley Downie, Jonathan W. Hall, Thomas P. Collier Finn, David J. Liptrot, John P. Lowe, Mary F. Mahon, Claire L. McMullin, Michael K. Whittlesey|2020|Chem.Commun.|56|13359|doi:10.1039/D0CC05694D
DOI: 10.5517/ccdc.csd.cc25m3vs
title: CCDC 2014375: Experimental Crystal Structure Determination

description: Related Article: Thomas M. Horsley Downie, Jonathan W. Hall, Thomas P. Collier Finn, David J. Liptrot, John P. Lowe, Mary F. Mahon, Claire L. McMullin, Michael K. Whittlesey|2020|Chem.Commun.|56|13359|doi:10.1039/D0CC05694D
DOI: 10.5517/ccdc.csd.cc25m3wt
title: CCDC 2014376: Experimental Crystal Structure Determination

description: Related Article: Thomas M. Horsley Downie, Jonathan W. Hall, Thomas P. Collier Finn, David J. Liptrot, John P. Lowe, Mary F. Mahon, Claire L. McMullin, Michael K. Whittlesey|2020|Chem.Commun.|56|13359|doi:10.1039/D0CC05694D
DOI: 10.5517/ccdc.csd.cc23wj7s
title: CCDC 1962865: Experimental Crystal Structure Determination

description: Related Article: Jianxin Ma, Na Xu, Yu Liu, Yue Wang, Hui Li, Guocheng Liu, Xiuli Wang, Jianrong Li|2020|Inorg.Chem.|59|15495|doi:10.1021/acs.inorgchem.0c02523
DOI: 10.5517/ccdc.csd.cc25rz31
title: CCDC 2019033: Experimental Crystal Structure Determination

description: Related Article: Shuai-Liang Yang, Wan-Shan Liu, Gen Li, Ran Bu, Peng Li, En-Qing Gao|2020|Inorg.Chem.|59|15421|doi:10.1021/acs.inorgchem.0c02419
DOI: 10.5517/ccdc.csd.cc25rz42
title: CCDC 2019034: Experimental Crystal Structure Determination

description: Related Article: Shuai-Liang Yang, Wan-Shan Liu, Gen Li, Ran Bu, Peng Li, En-Qing Gao|2020|Inorg.Chem.|59|15421|doi:10.1021/acs.inorgchem.0c02419
DOI: 10.5517/ccdc.csd.cc24229m
title: CCDC 1968199: Experimental Crystal Structure Determination

description: Related Article: V. M. Vidya, Someshwar Pola, Prabhakar Chetti|2021|Spectrochim.Acta,Part A|245|118940|doi:10.1016/j.saa.2020.118940
DOI: 10.17632/34pjbr4kg4.1
title: Magico-religious Practitioners

description: Coding of magico-religious practitioners in a subsample of the SCCS
DOI: 10.17632/5r94cfmdwj.1
title: Factors Associated with Presenting to a First Antenatal Care Appointment with a Male Partner in Northern Tanzania

description: This dataset was used in analysis for a quantitative paper submitted to Global Public Health. It is an anonymized SPSS dataset containing only variables relevant to this analysis.
DOI: 10.17632/gx39r48w3b.1
title: Data repository for 'Shape perception via a high-channel-count neuroprosthesis in monkey visual cortex'

description: Refer to Science article: Chen et al. Shape perception via a high-channel-count neuroprosthesis in monkey visual cortex. 2020
DOI: 10.17632/6pm5zwjv9w.1
title: Pre-existing basement faults controlling deformation in the Jura Mountains fold-and-thrust belt: supplementary material

description: We conducted brittle-viscous analogue models to test the influence of pre-existing fault-steps on the evolution of structures in a viscous layer overlain by a brittle layer of granular material. The brittle layer is pushed horizontally (from right to left in videos and CT cross-sections). The viscous layer is ca. 13 mm thick and is made of a mixture of Polydimethylsiloxane (PDMS) and corundum sand that has a density of ca. 1600 kg/m^3 (Zwaan et al., 2018). The brittle layer has a thickness of 70 mm (except in model U20-45-RC, where the thickness is 40 mm) and consists of quartz sand that has a bulk density of 1560 kg/m^3 (Klinkmüller et al., 2016). Analogue models test oblique and frontal fault-steps and represent the case of the Jura Mountains fold-and-thrust belt (JFTB) in the Northern Alpine Foreland, where pre-existing faults in the pre-Mesozoic basement are suspected to have localised and controlled deformation during JFTB evolution (Laubscher 1961). The viscous layer at the base simulates a décollement zone made of Trassic evaporites (salt and anhydrite), whereas the brittle quartz layer simulates the Mesozoic carbonate cover (limestone, dolomite, marl) of the JFTB. This supplementary material contains top-view videos of brittle-viscous analogue model experiments, which feature flat-base, frontal and oblique steps. Thick, black lines across models indicate the position of the vertical base-plate step (absent in flat-base models F1 and F2). Thin black lines to the left and right of the step indicate the calculated position of thrusts at the surface, which nucleate above the step (step-controlled thrusts). The dip angle of thrust planes, used to calculate the position of step-controlled thrust lines, is given in the parameter list at the bottom left of each video. The parameters specify (1) the throw of the base-plate step and the obliquity angle α of the oblique step in respect to frontal steps (α = 0°). (2) Scaling ratio of the image in pixels per centimetres. (3) The dip, which was used to construct the surface line of step-controlled fore-thrusts (thin, black line across the model to the left of the thick black line). Step-controlled thrusts are presumed to nucleate above the upper step-edge. (4) The dip assumed to construct the backthrust line across the model (thin, black line to the right of the thick black line). (5) Velocity of backstop displacement. (6) Thickness of the brittle cover. (7) Thickness of the viscous base layer with comments in uneven distributions. In addition to top-view videos, this supplementary material also comprises a PDF file with five cross-sections across model U20-45°-CT, which features an oblique upward step with a throw of 20 mm and an obliquity angle of 45°. Cross-sections are raw slices across computed tomography (CT) scans of model U20-45°-CT. CT-scans were conducted in 15 minute intervals.
DOI: 10.17632/3km4b3sfcw.2
title: Elastic buckling and post-buckling strength of CFS decks in bending: FE simulation results

description: The dataset contains results of FE simulations of CFS decks in bending. The FE models are described in detail in the referenced paper.
DOI: 10.24431/rw1k479
title: A citizen science mediated Optical Character Recognition (OCR) module for large-scale data rescue

description: Access to retrospective data is essential for understanding environmental variability and change, it is important for initializing and validating models of all kinds, and for illuminating the relationships between ecosystems and societies that depend on them. A major barrier to effective use of historical data in any discipline is the need to transform large quantities of manuscript or printed text, especially complex data tables, into formats that can be collated and analyzed by computers. However, there is currently no Optical Character Recognition (OCR) engine that can render scanned images of documents into digital text with a level of accuracy that renders human intervention unnecessary. This is especially true with respect to scientific data presented in tables or other matrix formats. The goal of this project was to build an open source citizen science mediated OCR module to facilitate transcription of complex data tables and other typescript or printed material (e.g Arctic and worldwide weather observations recorded in ship's logs), and integrate it into the Zooniverse transcription software bundle. This module will be available to the public via Zooniverse: https://www.zooniverse.org/projects/zooniverse/oldweather-ocr.
DOI: 10.5519/qd.iu4pk65o
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.4276357
title: Artifact for "A Data-Centric Study of Software Tutorial Design"

description: This artifact contains an evaluation sample of the data necessary to independently validate and replicate the findings on tutorial design that are presented in the paper "A Data-Centre Study of Software Tutorial Design". We plan to make the complete version of the artifact public concurrently with eventual publication of the article.
DOI: 10.6084/m9.figshare.13138361
title: RyczkoEtAl_2020_Astro_Cortex_Data

description: These are the datasets used in Ryczko et al.
DOI: 10.6084/m9.figshare.13138361.v2
title: RyczkoEtAl_2020_Astro_Cortex_Data

description: These are the datasets used in Ryczko et al.
DOI: 10.6084/m9.figshare.13138361.v1
title: RyczkoEtAl_2020_Astro_Cortex_Data

description: These are the datasets used in Ryczko et al.
DOI: 10.6084/m9.figshare.12743615
title: Online data for dissertation Chapter 3: "Carbon sequestration and niche preference track phylogeny in <i>Sphagnum</i> (peat moss)"

description: A folder containing the following items:<br><b>Supporting Information Dataset (</b>SI_Dataset.xlsx)<br><br>An Excel document containing the following:Spreadsheet 1 = Litter decomposability data for species of Sphagnum.Spreadsheet 2 = Collection information for samples used in the decomposition experiment.Spreadsheet 3 = Species mean litter decomposability (K, yr-1).Spreadsheet 4 = AICc values for evolutionary models fitted using maximum likelihood on 1,000 randomly-drawn trees from the Bayesian posterior tree distribution and the full 54-species decomposability dataset<br><b>Multiple Sequence Alignments (</b>MSA.tar.gz)<br>A compressed folder containing the following:*.best = best PRANK alignment for individual loci*.nex = dataset partitionsmcmc.Rev = RevBayes script used to perform the phylogenetic analysis<br><b>Maximum Clade Credibility Tree </b>(mcc.tre)<br>The maximum clade credibility tree from the RevBayes phylogenetic inference in Newick format.<br><b>Posterior Distribution Subset</b> (posterior_subset.tre)<br>A subset of 1,000 trees randomly drawn from the RevBayes posterior distribution. These trees were used to incorporate phylogenetic uncertainty into the analyses of trait evolution.<br>
DOI: 10.6084/m9.figshare.12743615.v2
title: Online data for dissertation Chapter 3: "Carbon sequestration and niche preference track phylogeny in <i>Sphagnum</i> (peat moss)"

description: A folder containing the following items:<br><b>Supporting Information Dataset (</b>SI_Dataset.xlsx)<br><br>An Excel document containing the following:Spreadsheet 1 = Litter decomposability data for species of Sphagnum.Spreadsheet 2 = Collection information for samples used in the decomposition experiment.Spreadsheet 3 = Species mean litter decomposability (K, yr-1).Spreadsheet 4 = AICc values for evolutionary models fitted using maximum likelihood on 1,000 randomly-drawn trees from the Bayesian posterior tree distribution and the full 54-species decomposability dataset<br><b>Multiple Sequence Alignments (</b>MSA.tar.gz)<br>A compressed folder containing the following:*.best = best PRANK alignment for individual loci*.nex = dataset partitionsmcmc.Rev = RevBayes script used to perform the phylogenetic analysis<br><b>Maximum Clade Credibility Tree </b>(mcc.tre)<br>The maximum clade credibility tree from the RevBayes phylogenetic inference in Newick format.<br><b>Posterior Distribution Subset</b> (posterior_subset.tre)<br>A subset of 1,000 trees randomly drawn from the RevBayes posterior distribution. These trees were used to incorporate phylogenetic uncertainty into the analyses of trait evolution.<br>
DOI: 10.6084/m9.figshare.12743615.v1
title: Online data for dissertation Chapter 2: "Carbon sequestration and niche preference track phylogeny in <i>Sphagnum</i> (peat moss)"

description: A folder containing the following items:<br><b>Supporting Information Dataset (</b>SI_Dataset.xlsx)<br><br>An Excel document containing the following:Spreadsheet 1 = Litter decomposability data for species of Sphagnum.Spreadsheet 2 = Collection information for samples used in the decomposition experiment.Spreadsheet 3 = Species mean litter decomposability (K, yr-1).Spreadsheet 4 = AICc values for evolutionary models fitted using maximum likelihood on 1,000 randomly-drawn trees from the Bayesian posterior tree distribution and the full 54-species decomposability dataset<br><b>Multiple Sequence Alignments (</b>MSA.tar.gz)<br>A compressed folder containing the following:*.best = best PRANK alignment for individual loci*.nex = dataset partitionsmcmc.Rev = RevBayes script used to perform the phylogenetic analysis<br><b>Maximum Clade Credibility Tree </b>(mcc.tre)<br>The maximum clade credibility tree from the RevBayes phylogenetic inference in Newick format.<br><b>Posterior Distribution Subset</b> (posterior_subset.tre)<br>A subset of 1,000 trees randomly drawn from the RevBayes posterior distribution. These trees were used to incorporate phylogenetic uncertainty into the analyses of trait evolution.<br>