cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7186298
title: Visual P2p component responds to perceived numerosity

description: The folder Data contains two subfolders one for Baseline data and one for Adaptation data. Each subfolder contains Raw EEG traces (.set and .fdt files) and Raw Behavioral data (.mat files) of each participant. <strong>Behavioral Data</strong> Consist of a table (“Tbase” for Baseline and “Tadapt” for Adaptation) with each column reporting the following information: 1<sup>st</sup> column: Numerosity of the test stimulus. 2<sup>nd</sup> column: Side of presentation (in <em>Baseline</em> trials: 1 = Left; 2 = Right; in <em>Adaptation</em> trials: 1 = Adapted condition; 2 = Unadapted condition). 3<sup>rd</sup> column: Response request (1 meaning “yes” and 0 meaning “no”) 4<sup>th</sup> column: Response 5<sup>th</sup> column (only in Adaptation): Adaptors’ arrangement: 1 = High Adaptor on the left and Neutral Adaptor on the right; 2 = High Adaptor on the right and Neutral Adaptor on the left <strong>EEG Data</strong> All EEG traces contain labeled triggers following this code: Baseline traces: “Side” (Left or Right) – “Numerosity” Adaptation traces: “Condition” (AdaptSX, UnadaptSX, AdaptDX, UnadaptDX) – “Numerosity”. Legend for the adaptation conditions: AdaptSX: test stimulus being presented in the left side when the real adaptor appeared on the left side UnadaptSX: test stimulus being presented in the right side when the real adaptor appeared on the left side AdaptDX: test stimulus being presented in the right side when the real adaptor appeared on the right side UnadaptDX: test stimulus being presented in the left side when the real adaptor appeared on the right side Trigger 1: appearance of the two Adaptors
DOI: 10.5281/zenodo.7215544
title: Met4DX: A mass spectrum-oriented computational framework for ion mobility-resolved untargeted metabolomics

description: <strong>Raw LC-IM-MS data</strong> to run Met4DX and <strong>RT recalibration table</strong> for multi-dimensional match Each dataset was archieved into a zip, containing raw LC-IM-MS data (.d format) and corresponding RT recalibration table (.csv format).
DOI: 10.5281/zenodo.7215543
title: Met4DX: A mass spectrum-oriented computational framework for ion mobility-resolved untargeted metabolomics

description: <strong>Raw LC-IM-MS data</strong> to run Met4DX and <strong>RT recalibration table</strong> for multi-dimensional match Each dataset was archieved into a zip, containing raw LC-IM-MS data (.d format) and corresponding RT recalibration table (.csv format).
DOI: 10.6084/m9.figshare.20132186
title: Table S13 for Chapter 13: Michael J. Mahony, Harry B. H, Frank Lemckert, David Newell, J Dale Roberts, Jodi J. L. Rowley, Ben C. Scheele, Matt West. The impacts of the 2019–20 wildfires on Australian frogs. In: Australia's Megafires: Biodiversity Impacts and Lessons from 2019-2020. (Eds L. Rumpff, S.M. Legge, S. van Leeuwen, B. Wintle and J.C.Z. Woinarski.) CSIRO Publishing, Melbourne.

description: <strong>Table S13.</strong> Extent of overlap with wildfire with frog distributions, dependence on fire-sensitive vegetation communities, their use of protective refuges, and ecological group. Genus and species group are used because the large specious genus <em>Litoria</em> is divided into morphotypic groups (Tyler and Davies 1978). Conservation status is based on national threatened species listing (<em>EPBC Act</em> 1999) and Gillespie <em>et al.</em> (2020) with the addition of recently described or redefined species for which assessments are published. Fire overlap is after Legge <em>et al.</em> (2021) and placed into percentage categories (0–20%, 21–40%, 41–60%, 61–80%, 81–100%), with the addition of some species from the southwest of Western Australia not included in Legge <em>et al.</em> (2022). Dependence on fire-sensitive vegetation communities, and use of protective refuge during wildfire; B burrow, H hollow, D under debris, R under rocks, L under leaf litter or topsoil, V dense riparian vegetation, and W wetland, is based on literature and the collective knowledge of the authors. Ecological group (after Murray <em>et al.</em> 2011), T terrestrial breeders, E ephemeral pond, P permanent water mostly lentic (pond), S permanent stream associated (lotic), and M bog or soak.
DOI: 10.6084/m9.figshare.20132186.v1
title: Table S13 for Chapter 13: Michael J. Mahony, Harry B. H, Frank Lemckert, David Newell, J Dale Roberts, Jodi J. L. Rowley, Ben C. Scheele, Matt West. The impacts of the 2019–20 wildfires on Australian frogs. In: Australia's Megafires: Biodiversity Impacts and Lessons from 2019-2020. (Eds L. Rumpff, S.M. Legge, S. van Leeuwen, B. Wintle and J.C.Z. Woinarski.) CSIRO Publishing, Melbourne.

description: <strong>Table S13.</strong> Extent of overlap with wildfire with frog distributions, dependence on fire-sensitive vegetation communities, their use of protective refuges, and ecological group. Genus and species group are used because the large specious genus <em>Litoria</em> is divided into morphotypic groups (Tyler and Davies 1978). Conservation status is based on national threatened species listing (<em>EPBC Act</em> 1999) and Gillespie <em>et al.</em> (2020) with the addition of recently described or redefined species for which assessments are published. Fire overlap is after Legge <em>et al.</em> (2021) and placed into percentage categories (0–20%, 21–40%, 41–60%, 61–80%, 81–100%), with the addition of some species from the southwest of Western Australia not included in Legge <em>et al.</em> (2022). Dependence on fire-sensitive vegetation communities, and use of protective refuge during wildfire; B burrow, H hollow, D under debris, R under rocks, L under leaf litter or topsoil, V dense riparian vegetation, and W wetland, is based on literature and the collective knowledge of the authors. Ecological group (after Murray <em>et al.</em> 2011), T terrestrial breeders, E ephemeral pond, P permanent water mostly lentic (pond), S permanent stream associated (lotic), and M bog or soak.
DOI: 10.5281/zenodo.7220521
title: Codes and datasets related to Leinonen et al (2022) https://doi.org/10.1039/D2EA00048B

description: Codes and datasets related to Leinonen et al (2022) https://doi.org/10.1039/D2EA00048B
DOI: 10.5281/zenodo.7220520
title: Codes and datasets related to Leinonen et al (2022) https://doi.org/10.1039/D2EA00048B

description: Codes and datasets related to Leinonen et al (2022) https://doi.org/10.1039/D2EA00048B
DOI: 10.5281/zenodo.7215402
title: Raster-based dataset for spatio-temporal analysis of forest fires in the Amazon rainforest from 2001 to 2020

description: Forest fire incidents are becoming increasingly common around the world, posing a threat to the environment, economy, and social life. These wildfires are further expected to rise in their frequency and intensity, considering the global climate change and human activities. A variety of attributes must be studied in order to analyse relationships between the probable causes of fire and the characteristics of wildfire incidents, and inform decision-making. Such attributes are available or easily collectable in various regions around the world, but they are not readily available in the South American Amazon. The Amazon rainforest covers such a large area that acquiring a useful dataset necessitates extensive effort and computer intensive pre-processing. The associated study to this dataset investigates potential data sources for the Amazon, establishes a methodological baseline, and prepares a dataset of covariates thought to be contributing to the wildfire ignition process. The dataset is intended to be used for forest fire studies, specifically spatio-temporal and statistical analysis of wildfires. The study provides three sets of (i) raw data (acquired data with a global extent), (ii) pre-processed data (source data transformed to the same projection system and same file format), and (iii) working data (cropped to Amazon region extent with spatial resolution of 500 meters and monthly temporal resolution, to enable the scientific community to work with various possibilities of forest-fire analysis, and to further encourage research in study areas in the other parts of the world.
DOI: 10.5281/zenodo.7215401
title: Raster-based dataset for spatio-temporal analysis of forest fires in the Amazon rainforest from 2001 to 2020

description: Forest fire incidents are becoming increasingly common around the world, posing a threat to the environment, economy, and social life. These wildfires are further expected to rise in their frequency and intensity, considering the global climate change and human activities. A variety of attributes must be studied in order to analyse relationships between the probable causes of fire and the characteristics of wildfire incidents, and inform decision-making. Such attributes are available or easily collectable in various regions around the world, but they are not readily available in the South American Amazon. The Amazon rainforest covers such a large area that acquiring a useful dataset necessitates extensive effort and computer intensive pre-processing. The associated study to this dataset investigates potential data sources for the Amazon, establishes a methodological baseline, and prepares a dataset of covariates thought to be contributing to the wildfire ignition process. The dataset is intended to be used for forest fire studies, specifically spatio-temporal and statistical analysis of wildfires. The study provides three sets of (i) raw data (acquired data with a global extent), (ii) pre-processed data (source data transformed to the same projection system and same file format), and (iii) working data (cropped to Amazon region extent with spatial resolution of 500 meters and monthly temporal resolution, to enable the scientific community to work with various possibilities of forest-fire analysis, and to further encourage research in study areas in the other parts of the world.
DOI: 10.6084/m9.figshare.20132213
title: Supplementary Table S11 for Chapter 11: Jess Marsh, Payal Bal, Hannah Fraser, Aaron Greenville, Tanya Latty, Melinda L. Moir, Libby Rumpff, Kate Umbers and John Woinarski. Prioritisation of 60 invertebrate species for conservation assessment, or uplisting, due to the impacts of the 2019–20 wildfires. In: Australia's Megafires: Biodiversity Impacts and Lessons from 2019-2020. (Eds L. Rumpff, S.M. Legge, S. van Leeuwen, B. Wintle and J.C.Z. Woinarski.) CSIRO Publishing, Melbourne.

description: <strong>Table S11.</strong> The Fire Susceptibility Index (FSI) estimates susceptibility of taxa to fire based upon microhabitat type and the Recovery Risk Index (RRI) estimates post-fire recovery potential of taxa, based on life history and ecological traits. For both indices a high score indicates increased risk. Species marked with a * indicate those species for which our calculated fire overlap is likely to underestimate actual fire overlap, based upon expert recommendation, or where distributional data were not readily available, but which were assessed as fire impacted during an IUCN assessment. One of the GPS points available for the Harvestman, <em>Nunciella kangarooensis, </em>is inaccurate, and when corrected to match the location description, the whole range of this species was overlapped by high severity fire. <em>Leioproctus (Andrenopsis) douglasiellus </em>and <em>Pseudococcus markharveyi</em>, marked by *# are currently listed under the EPBC Act as Critically Endangered. These are included in this table as highly vulnerable species, with <em>Pseudococcus markharveyi </em>likely extinct (Moir 2021).
DOI: 10.6084/m9.figshare.20132213.v1
title: Supplementary Table S11 for Chapter 11: Jess Marsh, Payal Bal, Hannah Fraser, Aaron Greenville, Tanya Latty, Melinda L. Moir, Libby Rumpff, Kate Umbers and John Woinarski. Prioritisation of 60 invertebrate species for conservation assessment, or uplisting, due to the impacts of the 2019–20 wildfires. In: Australia's Megafires: Biodiversity Impacts and Lessons from 2019-2020. (Eds L. Rumpff, S.M. Legge, S. van Leeuwen, B. Wintle and J.C.Z. Woinarski.) CSIRO Publishing, Melbourne.

description: <strong>Table S11.</strong> The Fire Susceptibility Index (FSI) estimates susceptibility of taxa to fire based upon microhabitat type and the Recovery Risk Index (RRI) estimates post-fire recovery potential of taxa, based on life history and ecological traits. For both indices a high score indicates increased risk. Species marked with a * indicate those species for which our calculated fire overlap is likely to underestimate actual fire overlap, based upon expert recommendation, or where distributional data were not readily available, but which were assessed as fire impacted during an IUCN assessment. One of the GPS points available for the Harvestman, <em>Nunciella kangarooensis, </em>is inaccurate, and when corrected to match the location description, the whole range of this species was overlapped by high severity fire. <em>Leioproctus (Andrenopsis) douglasiellus </em>and <em>Pseudococcus markharveyi</em>, marked by *# are currently listed under the EPBC Act as Critically Endangered. These are included in this table as highly vulnerable species, with <em>Pseudococcus markharveyi </em>likely extinct (Moir 2021).
DOI: 10.6084/m9.figshare.21353826
title: Data on the quality of audio streaming of Zoom, Audiomovers and web browsers

description: Fifteen files are available in this dataset. They correspond to the following measurement signals in monophonic format: Maximum Length Sequence (MLS), Logarithmic Sine Sweep (LSS), and Pink Noise (PN). <br> All measurement and recorded signals were created at 48 kHz sampling rate 24-bit depth lasting 2.7307 s.<br> <br> Measurement signals were streamed in real time over the internet using Audiomovers Listento VST3 format plugin v1.10.20210407. Signals from the following platforms were recorded using Reaper v6.45 Digital Audio Workstation: Chrome v99.0.4844.51 Safari v12.1.2 Listento Receiver VST3 format plugin v1.10.20210407 Zoom v5.8.1(1983) The measurement signals are: MLS-MeasurementSignal.csv LSS-MeasurementSignal.csv PN-MeasurementSignal.csv Each signal was recorded three times, corresponding to each column in the following files: MLS-CHROME.csv MLS-SAFARI.csv MLS-AUDIOMOVERS.csv MLS-ZOOM.csv <br> LSS-CHROME.csv LSS-SAFARI.csv LSS-AUDIOMOVERS.csv LSS-ZOOM.csv <br> PN-CHROME.csv PN-SAFARI.csv PN-AUDIOMOVERS.csv PN-ZOOM.csv <br> <br>
DOI: 10.5517/ccdc.csd.cc2497b1
title: CCDC 1975082: Experimental Crystal Structure Determination

description: Related Article: Chinna Ayya Swamy P, Archana V Raveendran, Narra Sivakrishna, Rajendra Prasad Nandi|2022|Dalton Trans.|51|15339|doi:10.1039/D2DT01887J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2497c2
title: CCDC 1975083: Experimental Crystal Structure Determination

description: Related Article: Chinna Ayya Swamy P, Archana V Raveendran, Narra Sivakrishna, Rajendra Prasad Nandi|2022|Dalton Trans.|51|15339|doi:10.1039/D2DT01887J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc277czv
title: CCDC 2062677: Experimental Crystal Structure Determination

description: Related Article: Arpita Barma, Malay Chakraborty, Swapan Kumar Bhattacharya, Pritam Ghosh, Partha Roy|2022|Mat.Advs.|3|7655|doi:10.1039/D2MA00462C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc277d0x
title: CCDC 2062678: Experimental Crystal Structure Determination

description: Related Article: Arpita Barma, Malay Chakraborty, Swapan Kumar Bhattacharya, Pritam Ghosh, Partha Roy|2022|Mat.Advs.|3|7655|doi:10.1039/D2MA00462C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc277d1y
title: CCDC 2062679: Experimental Crystal Structure Determination

description: Related Article: Arpita Barma, Malay Chakraborty, Swapan Kumar Bhattacharya, Pritam Ghosh, Partha Roy|2022|Mat.Advs.|3|7655|doi:10.1039/D2MA00462C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc285psy
title: CCDC 2090850: Experimental Crystal Structure Determination

description: Related Article: Etienne S. Gauthier, Dominika Kaczmarczyk, Samuel Del Fré, Ludovic Favereau, Elsa Caytan, Marie Cordier, Nicolas Vanthuyne, J. A. Gareth Williams, Monika Srebro-Hooper, Jeanne Crassous|2022|Dalton Trans.|51|15571|doi:10.1039/D2DT01925F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bkgcr
title: CCDC 2161734: Experimental Crystal Structure Determination

description: Related Article: Romain Tavernier, Lérys Granado, Monique Tillard, Louis Van Renterghem, Thomas-Xavier Métro, Frédéric Lamaty, Leïla Bonnaud, Jean-Marie Raquez, Ghislain David, Sylvain Caillol|2022|Polym.Chem.|13|5745|doi:10.1039/D2PY00462C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bkjjz
title: CCDC 2161801: Experimental Crystal Structure Determination

description: Related Article: Martin Lämmle, T. David Pilz, Roger Jan Kutta, Marius Müßler, Alexander K. Mengele, Helmar Görls, Frank W. Heinemann, Sven Rau|2022|Dalton Trans.|51|15282|doi:10.1039/D2DT01727J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bkv6z
title: CCDC 2162101: Experimental Crystal Structure Determination

description: Related Article: Martin Lämmle, T. David Pilz, Roger Jan Kutta, Marius Müßler, Alexander K. Mengele, Helmar Görls, Frank W. Heinemann, Sven Rau|2022|Dalton Trans.|51|15282|doi:10.1039/D2DT01727J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bn7kt
title: CCDC 2164406: Experimental Crystal Structure Determination

description: Related Article: Chang Gao, Dexin Wang, Yanshu Liu, Guanyun Zhang, Caiyun Liu, Amir Said, Huihui Niu, Guo Wang, Chen-Ho Tung, Yifeng Wang|2022|Dalton Trans.|51|15385|doi:10.1039/D2DT01882A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bn7lv
title: CCDC 2164407: Experimental Crystal Structure Determination

description: Related Article: Chang Gao, Dexin Wang, Yanshu Liu, Guanyun Zhang, Caiyun Liu, Amir Said, Huihui Niu, Guo Wang, Chen-Ho Tung, Yifeng Wang|2022|Dalton Trans.|51|15385|doi:10.1039/D2DT01882A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bss86
title: CCDC 2168768: Experimental Crystal Structure Determination

description: Related Article: Siyu Dai, Yuqi Liu, Yunjie Mei, Jue Hu, Kaiming Wang, Yanghua Li, Nanhao Jin, Xinying Wang, Huilong Luo, Wei Li|2022|Dalton Trans.|51|15446|doi:10.1039/D2DT01837C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c1gpl
title: CCDC 2176159: Experimental Crystal Structure Determination

description: Related Article: Chengchuang Li, Caijin Lei, Jie Tang, Teng Zhu, Guangbin Cheng, Hongwei Yang|2022|Dalton Trans.|51|15292|doi:10.1039/D2DT02885A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c1gqm
title: CCDC 2176160: Experimental Crystal Structure Determination

description: Related Article: Chengchuang Li, Caijin Lei, Jie Tang, Teng Zhu, Guangbin Cheng, Hongwei Yang|2022|Dalton Trans.|51|15292|doi:10.1039/D2DT02885A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.