cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc25fny7
title: CCDC 2009139: Experimental Crystal Structure Determination

description: Related Article: Knut R. Asmis, Björn B. Beele, Carsten Jenne, Sebastian Kawa, Harald Knorke, Marc C. Nierstenhöfer, Xue-Bin Wang, Jonas Warneke, Ziyan Warneke, Qinqin Yuan|2020|Chem.-Eur.J.|26|14594|doi:10.1002/chem.202003537
DOI: 10.5517/ccdc.csd.cc25fnz8
title: CCDC 2009140: Experimental Crystal Structure Determination

description: Related Article: Knut R. Asmis, Björn B. Beele, Carsten Jenne, Sebastian Kawa, Harald Knorke, Marc C. Nierstenhöfer, Xue-Bin Wang, Jonas Warneke, Ziyan Warneke, Qinqin Yuan|2020|Chem.-Eur.J.|26|14594|doi:10.1002/chem.202003537
DOI: 10.5517/ccdc.csd.cc25fp0b
title: CCDC 2009141: Experimental Crystal Structure Determination

description: Related Article: Knut R. Asmis, Björn B. Beele, Carsten Jenne, Sebastian Kawa, Harald Knorke, Marc C. Nierstenhöfer, Xue-Bin Wang, Jonas Warneke, Ziyan Warneke, Qinqin Yuan|2020|Chem.-Eur.J.|26|14594|doi:10.1002/chem.202003537
DOI: 10.5517/ccdc.csd.cc25fp1c
title: CCDC 2009142: Experimental Crystal Structure Determination

description: Related Article: Knut R. Asmis, Björn B. Beele, Carsten Jenne, Sebastian Kawa, Harald Knorke, Marc C. Nierstenhöfer, Xue-Bin Wang, Jonas Warneke, Ziyan Warneke, Qinqin Yuan|2020|Chem.-Eur.J.|26|14594|doi:10.1002/chem.202003537
DOI: 10.5517/ccdc.csd.cc25fp2d
title: CCDC 2009143: Experimental Crystal Structure Determination

description: Related Article: Knut R. Asmis, Björn B. Beele, Carsten Jenne, Sebastian Kawa, Harald Knorke, Marc C. Nierstenhöfer, Xue-Bin Wang, Jonas Warneke, Ziyan Warneke, Qinqin Yuan|2020|Chem.-Eur.J.|26|14594|doi:10.1002/chem.202003537
DOI: 10.5517/ccdc.csd.cc252z19
title: CCDC 1998850: Experimental Crystal Structure Determination

description: Related Article: Akhil Kumar Singh, Sankar Prasad Rath|2020|Chem.-Eur.J.|26|14405|doi:10.1002/chem.202002188
DOI: 10.5517/ccdc.csd.cc25hky6
title: CCDC 2010968: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hkz7
title: CCDC 2010969: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl09
title: CCDC 2010970: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl1b
title: CCDC 2010971: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl2c
title: CCDC 2010972: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl3d
title: CCDC 2010973: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl4f
title: CCDC 2010974: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl5g
title: CCDC 2010975: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl6h
title: CCDC 2010976: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl7j
title: CCDC 2010977: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl8k
title: CCDC 2010978: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hl9l
title: CCDC 2010979: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hlbm
title: CCDC 2010980: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hlcn
title: CCDC 2010981: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hldp
title: CCDC 2010982: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25hlfq
title: CCDC 2010983: Experimental Crystal Structure Determination

description: Related Article: Caroline M. Storey, Matthew R. Gyton, Rhiann E. Andrew, Adrian B. Chaplin|2020|Chem.-Eur.J.|26|14715|doi:10.1002/chem.202002962
DOI: 10.5517/ccdc.csd.cc25m20x
title: CSD 2014318: Experimental Crystal Structure Determination

description: Related Article: Philip Netzsch, Florian Pielnhofer, Robert Glaum, Henning A. Höppe|2020|Chem.-Eur.J.|26|14745|doi:10.1002/chem.202003214
DOI: 10.5517/ccdc.csd.cc25m21y
title: CSD 2014319: Experimental Crystal Structure Determination

description: Related Article: Philip Netzsch, Florian Pielnhofer, Robert Glaum, Henning A. Höppe|2020|Chem.-Eur.J.|26|14745|doi:10.1002/chem.202003214
DOI: 10.5517/ccdc.csd.cc25m22z
title: CSD 2014320: Experimental Crystal Structure Determination

description: Related Article: Philip Netzsch, Florian Pielnhofer, Robert Glaum, Henning A. Höppe|2020|Chem.-Eur.J.|26|14745|doi:10.1002/chem.202003214
DOI: 10.5517/ccdc.csd.cc25mn5n
title: CCDC 2014881: Experimental Crystal Structure Determination

description: Related Article: Ilya E. Nifant'ev, Andrey V. Shlyakhtin, Vladimir V. Bagrov, Alexander N. Tavtorkin, Pavel D. Komarov, Andrei V. Churakov, Pavel V. Ivchenko|2020|Polym.Chem.|11|6890|doi:10.1039/D0PY01297A
DOI: 10.5517/ccdc.csd.cc25xm5x
title: CCDC 2023499: Experimental Crystal Structure Determination

description: Related Article: Kyu Hyung Lee, Sun Joo Kim, Hee Sun Park, Byung Wook Lim, Byeongno Lee, Young Jun Park, Wonwoo Nam, Nam Hwi Hur|2020|RSC Advances|10|38055|doi:10.1039/D0RA07814J
DOI: 10.5281/zenodo.4034827
title: Machine Learning for Anomaly Detection in Cyanobacterial Fluorescence Signals

description: Excel files containing chlorophyll a and phycocyanin fluorescence data imported from https://www.glerl.noaa.gov/res/HABs_and_Hypoxia/habTracker.html for buoys WE2, WE4, WE8, and WE13. The Python code used to manipulate the data is also included.
DOI: 10.5281/zenodo.3887221
title: Machine Learning for Anomaly Detection in Cyanobacterial Fluorescence Signals

description: Excel files containing chlorophyll a and phycocyanin fluorescence data imported from https://www.glerl.noaa.gov/res/HABs_and_Hypoxia/habTracker.html for buoys WE2, WE4, WE8, and WE13. The Python code used to manipulate the data is also included.
DOI: 10.6084/m9.figshare.13207148.v3
title: More change in task repetition, less cost in task switching: Behavioral and ERP evidence

description: Reproducibility package containing data, code and final plots of Fig.2,4 & 5b of this editorial in the European Journal of Neuroscience<br>More change in task repetition, less cost in task switching: Behavioral and ERP evidence Bingxin Zhuo, Mengqi Zhu, Bihua Cao, Fuhong Li under review Fig.2 & 5b were made in Origin. Fig.4 was made in Matlab.
DOI: 10.25405/data.ncl.13242182
title: M.E. Jarvis et al. 2019: Radio Images, IFU cube and [O III] maps for J1100+0846

description: This relates to: M.E. Jarvis et al. 2019, MNRAS, 485, 2710, "Prevalence of radio jets associated with galactic outflows and feedback from quasars". Available on the pre-print archive: arxiv.org/abs/1902.07727<br>This contains:- The Low Resolution ("LR") image and High Resolution ("HR") image from the Very Large Array (VLA) (see Table 3 and Section 3.1)- The eMERLIN image (see Section 3.2).- The IFU data cube used (see Section 3.3)- One file containing the four [O III] maps as four separate fits extensions (SNR, v50, W80 and A; see Section 4.2). Note the units for the v50 and W80 maps is angstroms.<br>The details of how the images, data cubes and maps were produced are in the paper. The data files also contain extensive meta-data in the header following the standard for astronomical images.
DOI: 10.25405/data.ncl.13242182.v1
title: M.E. Jarvis et al. 2019: Radio Images, IFU cube and [O III] maps for J1100+0846

description: This relates to: M.E. Jarvis et al. 2019, MNRAS, 485, 2710, "Prevalence of radio jets associated with galactic outflows and feedback from quasars". Available on the pre-print archive: arxiv.org/abs/1902.07727<br>This contains:- The Low Resolution ("LR") image and High Resolution ("HR") image from the Very Large Array (VLA) (see Table 3 and Section 3.1)- The eMERLIN image (see Section 3.2).- The IFU data cube used (see Section 3.3)- One file containing the four [O III] maps as four separate fits extensions (SNR, v50, W80 and A; see Section 4.2). Note the units for the v50 and W80 maps is angstroms.<br>The details of how the images, data cubes and maps were produced are in the paper. The data files also contain extensive meta-data in the header following the standard for astronomical images.
DOI: 10.25405/data.ncl.13242185
title: M.E. Jarvis et al. 2019: Radio Images, IFU cube and [O III] maps for J1316+1753

description: This relates to: M.E. Jarvis et al. 2019, MNRAS, 485, 2710, "Prevalence of radio jets associated with galactic outflows and feedback from quasars". Available on the pre-print archive: arxiv.org/abs/1902.07727<br>This contains:- The Low Resolution ("LR") image and High Resolution ("HR") image from the Very Large Array (VLA) (see Table 3 and Section 3.1)- The eMERLIN image (see Section 3.2).- The IFU data cube used (see Section 3.3)- One file containing the four [O III] maps as four separate fits extensions (SNR, v50, W80 and A; see Section 4.2). Note the units for the v50 and W80 maps is angstroms.<br>The details of how the images, data cubes and maps were produced are in the paper. The data files also contain extensive meta-data in the header following the standard for astronomical images.
DOI: 10.25405/data.ncl.13242185.v1
title: M.E. Jarvis et al. 2019: Radio Images, IFU cube and [O III] maps for J1316+1753

description: This relates to: M.E. Jarvis et al. 2019, MNRAS, 485, 2710, "Prevalence of radio jets associated with galactic outflows and feedback from quasars". Available on the pre-print archive: arxiv.org/abs/1902.07727<br>This contains:- The Low Resolution ("LR") image and High Resolution ("HR") image from the Very Large Array (VLA) (see Table 3 and Section 3.1)- The eMERLIN image (see Section 3.2).- The IFU data cube used (see Section 3.3)- One file containing the four [O III] maps as four separate fits extensions (SNR, v50, W80 and A; see Section 4.2). Note the units for the v50 and W80 maps is angstroms.<br>The details of how the images, data cubes and maps were produced are in the paper. The data files also contain extensive meta-data in the header following the standard for astronomical images.
DOI: 10.25405/data.ncl.13242191
title: M.E. Jarvis et al. 2019: Radio Images, IFU cube and [O III] maps for J1338+1503

description: This relates to: M.E. Jarvis et al. 2019, MNRAS, 485, 2710, "Prevalence of radio jets associated with galactic outflows and feedback from quasars". Available on the pre-print archive: arxiv.org/abs/1902.07727<br>This contains:- The Low Resolution ("LR") image from the Very Large Array (VLA) (see Table 3 and Section 3.1)- The IFU data cube used (see Section 3.3)- One file containing the four [O III] maps as four separate fits extensions (SNR, v50, W80 and A; see Section 4.2). Note the units for the v50 and W80 maps is angstroms.<br>The details of how the images, data cubes and maps were produced are in the paper. The data files also contain extensive meta-data in the header following the standard for astronomical images.
DOI: 10.5281/zenodo.4281094
title: CoDEx: A Comprehensive Knowledge Graph Completion Benchmark

description: This repository hosts the <strong>relational-only part</strong> of the CoDEx benchmark, which was presented at the EMNLP 2020 conference. You can access the paper here and the full dataset, including text and pretrained models, on GitHub. Abstract: <em>We present CoDEx, a set of knowledge graph completion datasets extracted from Wikidata and Wikipedia that improve upon existing knowledge graph completion benchmarks in scope and level of difficulty. In terms of scope, CoDEx comprises three knowledge graphs varying in size and structure, multilingual descriptions of entities and relations, and tens of thousands of hard negative triples that are plausible but verified to be false. To characterize CoDEx, we contribute thorough empirical analyses and benchmarking experiments. First, we analyze each CoDEx dataset in terms of logical relation patterns. Next, we report baseline link prediction and triple classification results on CoDEx for five extensively tuned embedding models. Finally, we differentiate CoDEx from the popular FB15K-237 knowledge graph completion dataset by showing that CoDEx covers more diverse and interpretable content, and is a more difficult link prediction benchmark. Data, code, and pretrained models are available here.</em>
DOI: 10.5281/zenodo.4281093
title: CoDEx: A Comprehensive Knowledge Graph Completion Benchmark

description: This repository hosts the <strong>relational-only part</strong> of the CoDEx benchmark, which was presented at the EMNLP 2020 conference. You can access the paper here and the full dataset, including text and pretrained models, on GitHub. Abstract: <em>We present CoDEx, a set of knowledge graph completion datasets extracted from Wikidata and Wikipedia that improve upon existing knowledge graph completion benchmarks in scope and level of difficulty. In terms of scope, CoDEx comprises three knowledge graphs varying in size and structure, multilingual descriptions of entities and relations, and tens of thousands of hard negative triples that are plausible but verified to be false. To characterize CoDEx, we contribute thorough empirical analyses and benchmarking experiments. First, we analyze each CoDEx dataset in terms of logical relation patterns. Next, we report baseline link prediction and triple classification results on CoDEx for five extensively tuned embedding models. Finally, we differentiate CoDEx from the popular FB15K-237 knowledge graph completion dataset by showing that CoDEx covers more diverse and interpretable content, and is a more difficult link prediction benchmark. Data, code, and pretrained models are available here.</em>
DOI: 10.5281/zenodo.4276558
title: Madidi Project Full Dataset

description: This item contains <strong>version 4.1</strong> 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 <strong>Data Use Policy</strong> for this dataset. 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. 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 (<strong>www.madidiproject.weebly.com</strong>).
description: The Madidi project has been supported by generous grants from the National Science Foundation (DEB 0101775, DEB 0743457, DEB 1836353), and the National Geographic Society (NGS 7754-04 and NGS 8047-06). Additional financial support for the Madidi Project has been provided by the Missouri Botanical Garden, the Comunidad de Madrid (Spain), the Universidad Autónima de Madrid, and the Taylor and Davidson families.
DOI: 10.25405/data.ncl.13242197
title: M.E. Jarvis et al. 2019: Radio Images, IFU cube and [O III] maps for J1356+1026

description: This relates to: M.E. Jarvis et al. 2019, MNRAS, 485, 2710, "Prevalence of radio jets associated with galactic outflows and feedback from quasars". Available on the pre-print archive: arxiv.org/abs/1902.07727<br>This contains:- The Low Resolution ("LR") image and High Resolution ("HR") image from the Very Large Array (VLA) (see Table 3 and Section 3.1)- The eMERLIN image (see Section 3.2).- The IFU data cube used (see Section 3.3)- One file containing the four [O III] maps as four separate fits extensions (SNR, v50, W80 and A; see Section 4.2). Note the units for the v50 and W80 maps is angstroms.<br>The details of how the images, data cubes and maps were produced are in the paper. The data files also contain extensive meta-data in the header following the standard for astronomical images.
DOI: 10.25405/data.ncl.13242197.v1
title: M.E. Jarvis et al. 2019: Radio Images, IFU cube and [O III] maps for J1356+1026

description: This relates to: M.E. Jarvis et al. 2019, MNRAS, 485, 2710, "Prevalence of radio jets associated with galactic outflows and feedback from quasars". Available on the pre-print archive: arxiv.org/abs/1902.07727<br>This contains:- The Low Resolution ("LR") image and High Resolution ("HR") image from the Very Large Array (VLA) (see Table 3 and Section 3.1)- The eMERLIN image (see Section 3.2).- The IFU data cube used (see Section 3.3)- One file containing the four [O III] maps as four separate fits extensions (SNR, v50, W80 and A; see Section 4.2). Note the units for the v50 and W80 maps is angstroms.<br>The details of how the images, data cubes and maps were produced are in the paper. The data files also contain extensive meta-data in the header following the standard for astronomical images.
DOI: 10.6073/pasta/ae3a9177915d63c4c49b7ca5afa665e2
title: Using Biodiversity Data to Assess Species-Habitat Relationships in Glacier National Park, Montana

description: Biodiversity surveys are becoming increasingly popular. However, standard analysis techniques for these data have not yet been developed. This paper explores the use of multivariate ordination techniques for assessing species-habitat relationships using biodiversity data. The research was conducted in Glacier National Park, Montana, and birds and butterflies were chosen as the taxonomic groups of study. Biodiversity assessment sites were established through a range of habitats and monitored from 1987 through 1989. Presence/absence sampling over the total number of sampling sites was used to classify species commonness and rarity. Approximately 86% of the historically recorded butterflies and 70% of the historically recorded bird species have been observed in the 3 yr of sampling. During the 3 yr of this study there was a striking continuity of species richness per site. There was also a striking overlap between the sites that support high species diversity and sites that support rare species. Principal components analysis and cluster analysis worked well in discerning species-habitat relationships. Elevation, structural diversity of the site, and moisture were the major factors explaining species distributions. A chi-square analysis also provided some insights into species-habitat relationships, showing birds were more habitat specific than butterflies. Habitat diversity analyses demonstrated a positive but non-significant correlation between remotely sense spectral-class diversity of a site and species richness for both birds and butterflies. Aspect, slope and elevation diversity had a negative or negligible relationship with species richness.
DOI: 10.25405/data.ncl.13242200
title: M.E. Jarvis et al. 2019: Radio Images, IFU cube and [O III] maps for J1430+1339

description: This relates to: M.E. Jarvis et al. 2019, MNRAS, 485, 2710, "Prevalence of radio jets associated with galactic outflows and feedback from quasars". Available on the pre-print archive: arxiv.org/abs/1902.07727<br>This contains:- The Low Resolution ("LR") image and High Resolution ("HR") image from the Very Large Array (VLA) (see Table 3 and Section 3.1)- The eMERLIN image (see Section 3.2).- The IFU data cubes used, GMOS and VIMOS (see Section 3.3)- One file containing the four [O III] maps as four separate fits extensions for each of GMOS and VIMOS (SNR, v50, W80 and A; see Section 4.2). Note the units for the v50 and W80 maps is angstroms.<br>The details of how the images, data cubes and maps were produced are in the paper. The data files also contain extensive meta-data in the header following the standard for astronomical images.