cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1135285
title: Biodiversity atlas data

description: <strong>Introdution</strong><br> This dataset contains six sets of biodiversity atlas data that have been used as a test of occupancy downscaling methods. They are derived from two taxonomic groups, vascular plants and birds and are either regional or national atlases. The original atlas have already been published and the references are below. Should these data be used these citations should be used. <strong>File contents</strong><br> Each zip file contains a set of text files, one for each taxa. Each text file has three tab seperated columns, longitude, latitude and presence. The presence column indicates whether the grid cell was occupied (1) or unoccupied (0). The longitude and latitude columns are the grid references of each grid cell surveyed. For Ireland the Irish grid system is used (EPSG:29903); for the UK the Ordnance Survey Grid (EPSG:27700) and for Belgian the Lambert 72 system (EPSG:31370). The grid cell area for all plant datasets is 4 km<sup>2</sup>. Whereas the grid areas for the Flemish birds is 25 km&lt;sup&gt;2&lt;/sup&gt; and for the Irish breeding birds is 100 km<sup>2</sup>. <strong>References</strong> Evans, P., Evans, I. & Rothero, G. (2002) Flora of Assynt: fowering plants and ferns. P.A. Evans and I.M. Evans. ISBN 0954181301. Forbes, R.S. & Northridge, R.H. (2012) The Flora of County Fermanagh. National Museums Northern Ireland. ISBN 1905989288 Halliday, G. (1997) A Flora of Cumbria. Centre for North-West Regional Studies, University of Lancaster. ISBN 1862200203. National Biodiversity Data Centre (2011) The Second Atlas of Breeding Birds in Britain and Ireland: 1988-1991. URL https://doi.org/10.15468/pkhsnb Shropshire Ecological Data Network (2017) Shropshire Ecological Data Network database. Occurrence Dataset. URL https://doi.org/10.15468/5v5pvk Lockton, A.J. & Whild, S.J. (2015) The Flora and Vegetation of Shropshire. Shropshire Botanical Society. ISBN 0953093727. Vermeersch, G., Anselin, A., Devos, K., Herremans, M., Stevens, J., Gabriëls, J., Van Der Krieken, B., Brosens, D. & Desmet, P. (2014) Broedvogels - Atlas of the breeding birds in Flanders 2000-2002. v1.5. URL http://doi.org/10.15468/sccg5a
description: {"references": ["Groom QJ, Marsh CJ, Gavish Y, Kunin WE. How to predict fine resolution occupancy from coarse occupancy data. Methods Ecol Evol. 2018;00:1\u201310. https://doi.org/10.1111/2041-210X.13078"]}
DOI: 10.5281/zenodo.1135284
title: Biodiversity atlas data

description: <strong>Introdution</strong><br> This dataset contains six sets of biodiversity atlas data that have been used as a test of occupancy downscaling methods. They are derived from two taxonomic groups, vascular plants and birds and are either regional or national atlases. The original atlas have already been published and the references are below. Should these data be used these citations should be used. <strong>File contents</strong><br> Each zip file contains a set of text files, one for each taxa. Each text file has three tab seperated columns, longitude, latitude and presence. The presence column indicates whether the grid cell was occupied (1) or unoccupied (0). The longitude and latitude columns are the grid references of each grid cell surveyed. For Ireland the Irish grid system is used (EPSG:29903); for the UK the Ordnance Survey Grid (EPSG:27700) and for Belgian the Lambert 72 system (EPSG:31370). The grid cell area for all plant datasets is 4 km<sup>2</sup>. Whereas the grid areas for the Flemish birds is 25 km&lt;sup&gt;2&lt;/sup&gt; and for the Irish breeding birds is 100 km<sup>2</sup>. <strong>References</strong> Evans, P., Evans, I. & Rothero, G. (2002) Flora of Assynt: fowering plants and ferns. P.A. Evans and I.M. Evans. ISBN 0954181301. Forbes, R.S. & Northridge, R.H. (2012) The Flora of County Fermanagh. National Museums Northern Ireland. ISBN 1905989288 Halliday, G. (1997) A Flora of Cumbria. Centre for North-West Regional Studies, University of Lancaster. ISBN 1862200203. National Biodiversity Data Centre (2011) The Second Atlas of Breeding Birds in Britain and Ireland: 1988-1991. URL https://doi.org/10.15468/pkhsnb Shropshire Ecological Data Network (2017) Shropshire Ecological Data Network database. Occurrence Dataset. URL https://doi.org/10.15468/5v5pvk Lockton, A.J. & Whild, S.J. (2015) The Flora and Vegetation of Shropshire. Shropshire Botanical Society. ISBN 0953093727. Vermeersch, G., Anselin, A., Devos, K., Herremans, M., Stevens, J., Gabriëls, J., Van Der Krieken, B., Brosens, D. & Desmet, P. (2014) Broedvogels - Atlas of the breeding birds in Flanders 2000-2002. v1.5. URL http://doi.org/10.15468/sccg5a
description: {"references": ["Groom QJ, Marsh CJ, Gavish Y, Kunin WE. How to predict fine resolution occupancy from coarse occupancy data. Methods Ecol Evol. 2018;00:1\u201310. https://doi.org/10.1111/2041-210X.13078"]}
DOI: 10.5281/zenodo.50946
title: Ash dieback mortality and damage at the Botanic Garden Meise, Belgium, 2016

description: These data add to the data already published for previous years and are available at Groom, Quentin J. (2015). Ash dieback mortality and damage at the Botanic Garden Meise, Belgium. Zenodo. 10.5281/zenodo.17640. Four 10m × 10m plots were laid out in the naturally regenerating woodland at the Botanic Garden Meise (WGS84: 50° 55ʹ 37ʺ N, 4° 19ʹ 18ʺ E; 50° 55ʹ 37ʺ N, 4° 19ʹ 17ʺ E; 50° 55' 38.6" N 4° 19ʹ 21ʺ E; 50° 55ʹ 39ʺ N, 4° 19ʹ 29ʺ E). They were selected because the areas contained a large number of ash saplings. Within these plots all ash seedlings greater than 40 cm tall were labelled with a small (2 cm × 4 cm) plastic tag attached with stretchable plant tie. Each tag was engraved with a unique number so that the tree could be identified. These plots were not intended to be replicates but just a convenient method of refinding the tagged trees. In the first year either the height or the girth of the tree was measured with a tape measure, depending upon whether the tree was small enough to measure the height. In 2013 and each subsequent year each tree was scored for the apparent damage caused by ash dieback (<em>Hymenoscyphus pseudoalbidus</em>). The same scoring scheme was used as that by Pliūra et al. (2011). This is a 5 point system where 1 is a dead tree; 5 is an undamaged tree and 2–4 are progressively less damaged trees. In 2016 the plots were scored on 4<sup>th</sup> May.
DOI: 10.6084/m9.figshare.13469307
title: 2020-10-20-001-data-reshape

description: qRT-PCR results<br>
DOI: 10.6084/m9.figshare.13469307.v1
title: 2020-10-20-001-data-reshape

description: qRT-PCR results<br>
DOI: 10.6084/m9.figshare.13469316
title: Abstinence among alcohol use disorder patients during the COVID-19 pandemic: Insights from Spain (Data set)

description: Data set of patients attending the outpatient service of the Addictive Behaviors Unit of a tertiary hospital in Barcelona, Spain.
DOI: 10.6084/m9.figshare.13469316.v1
title: Abstinence among alcohol use disorder patients during the COVID-19 pandemic: Insights from Spain (Data set)

description: Data set of patients attending the outpatient service of the Addictive Behaviors Unit of a tertiary hospital in Barcelona, Spain.
DOI: 10.6084/m9.figshare.13469241
title: Data - Project on Individualized Leadership and Creativity

description: Data includes survey responses from employees where they have rated the leadership behavior of their supervisor. Further, it also includes measures on their creative process engagement and the creative performance they produced, in addition to responses on their stress levels and job autonomy.
DOI: 10.6084/m9.figshare.13469241.v2
title: Data - Project on Individualized Leadership and Creativity

description: Data includes survey responses from employees where they have rated the leadership behavior of their supervisor. Further, it also includes measures on their creative process engagement and the creative performance they produced, in addition to responses on their stress levels and job autonomy.
DOI: 10.6084/m9.figshare.13469241.v1
title: Data - Project on Individualized Leadership and Creativity

description: Data includes survey responses from employees where they have rated the leadership behavior of their supervisor. Further, it also includes measures on their creative process engagement and the creative performance they produced, in addition to responses on their stress levels and job autonomy.
DOI: 10.5281/zenodo.4382201
title: An Excel spreadsheet including eddy covariance, meteorological, and tidal data measured at Yunxiao mangrove flux tower.

description: An Excel spreadsheet including eddy covariance, meteorological, and tidal data at Yunxiao mangrove flux tower required to reproduce key findings in Figures 4-9 in the main text (each figure corresponds to a single sheet). Contact Xudong Zhu at Xiamen University (xdzhu@xmu.edu.cn) if you have any question.
DOI: 10.48370/ofd/kuutga/8zesio
title: 0031-0021.jpg

description: :unav
DOI: 10.34740/kaggle/dsv/1767936
title: US counties COVID 19 dataset
DOI: 10.48370/ofd/xb3iru/nhqaow
title: 0031-0027.jpg

description: :unav
DOI: 10.21227/ba6c-zq72
title: Measurement and Simulation of Human Sitting and Standing Movement Biomechanics

description: Previous studies on robotic exoskeletons and prostheses with regenerative actuators have focused exclusively on level-ground walking applications. Here we analyzed the lower-limb joint mechanical power during stand-to-sit movements using inverse dynamic simulations to estimate the biomechanical energy available for electrical regeneration. Nine subjects performed 20 sitting and standing movements while lower-limb kinematics and ground reaction forces were measured. Subject-specific body segment parameters were estimated using parameter identification. Joint mechanical power was calculated from net joint torques and rotational velocities and numerically integrated over time to estimate the joint biomechanical energy. The hip joint produced the largest peak negative mechanical power (1.8 ± 0.5 W/kg), followed by the knee (0.8 ± 0.3 W/kg) and ankle (0.2 ± 0.1 W/kg). Negative mechanical work from the hip, knee, and ankle joints per stand-to-sit movement were 0.35 ± 0.06 J/kg, 0.15 ± 0.08 J/kg, and 0.02 ± 0.01 J/kg, respectively. Assuming known regenerative actuator efficiencies (i.e., maximum 63%), robotic exoskeletons and prostheses could theoretically regenerate ~26 Joules of electrical energy while sitting down, compared to ~19 Joules per walking stride. Given that these regeneration performance calculations are based on healthy young adults, future research should include seniors and/or rehabilitation patients to better estimate the biomechanical energy available for electrical regeneration in persons with mobility impairments.Reference:Laschowski B, Razavian RS, and McPhee J. (2020). Simulation of Stand-to-Sit Biomechanics for Design of Lower-Limb Exoskeletons and Prostheses with Energy Regeneration. bioRxiv. DOI: 10.1101/801258.
DOI: 10.48370/ofd/y9zxpm/iad0my
title: IBL_coll_190_MicromysMinutus_1946_scan.jpg

description: :unav
DOI: 10.48370/ofd/y9zxpm
title: Micromys minutus - 190, Zoological collection of the Mammal Research Institute, PAS

description: Micromys minutus (Eurasian harvest mouse) from Zoological collection of the Mammal Research Institute PAS. Collected 1946-10-09, in: Białowieża National Park, Poland.
DOI: 10.48370/ofd/5t7c2l/nj8nzs
title: 0031-0024.jpg

description: :unav
DOI: 10.48370/ofd/fkyxcc/2ux8gn
title: IBL_coll_190_MicromysMinutus_1946_scan.jpg

description: :unav
DOI: 10.48370/ofd/fkyxcc
title: Micromys minutus - 190, Zoological collection of the Mammal Research Institute, PAS

description: Micromys minutus (Eurasian harvest mouse) from Zoological collection of the Mammal Research Institute PAS. Collected 1946-10-09, in: Białowieża National Park, Poland.
DOI: 10.48370/ofd/t0shjo/hqevsa
title: 0031-0025.jpg

description: :unav
DOI: 10.21227/7j8k-xd70
title: Measurement and Simulation of Human Sitting and Standing Movement Biomechanics

description: Previous research on robotic exoskeletons and prostheses with regenerative actuators has focused exclusively on level-ground walking applications. Here we analyzed the lower-limb joint mechanical power during stand-to-sit movements using inverse dynamic simulations to estimate the biomechanical energy available for electrical regeneration. Nine subjects performed 20 sitting and standing movements while lower-limb kinematics and ground reaction forces were measured. Subject-specific body segment parameters were estimated using parameter identification. Joint mechanical power was calculated from net joint torques and rotational velocities and numerically integrated over time to estimate the joint biomechanical energy. The hip joint produced the largest peak negative mechanical power (1.8 ± 0.5 W/kg), followed by the knee (0.8 ± 0.3 W/kg) and ankle (0.2 ± 0.1 W/kg). Negative mechanical work from the hip, knee, and ankle joints per stand-to-sit movement were 0.35 ± 0.06 J/kg, 0.15 ± 0.08 J/kg, and 0.02 ± 0.01 J/kg, respectively. Assuming known regenerative actuator efficiencies (i.e., maximum 63%), robotic exoskeletons and prostheses could theoretically regenerate ~26 Joules of electrical energy while sitting down, compared to ~19 Joules per walking stride. Given that these regeneration performance calculations are based on healthy young adults, future research should include seniors and/or rehabilitation patients to better estimate the biomechanical energy available for electrical regeneration in persons with mobility impairments.Reference:Laschowski B, Razavian RS, and McPhee J. (2020). Simulation of Stand-to-Sit Biomechanics for Design of Lower-Limb Exoskeletons and Prostheses with Energy Regeneration. bioRxiv. DOI: 10.1101/801258.
DOI: 10.48370/ofd/vy6hjq/shvsob
title: IBL_coll_190_MicromysMinutus_1946_scan.jpg

description: :unav
DOI: 10.48370/ofd/vy6hjq
title: Micromys minutus - 190, Zoological collection of the Mammal Research Institute, PAS

description: Micromys minutus (Eurasian harvest mouse) from Zoological collection of the Mammal Research Institute PAS. Collected 1946-10-09, in: Białowieża National Park, Poland.
DOI: 10.48370/ofd/kuutga/z2gkti
title: 0031-0021.jpg

description: :unav
DOI: 10.21227/82m6-2n60
title: Measurement and Simulation of Human Sitting and Standing Movement Biomechanics

description: Previous studies on robotic exoskeletons and prostheses with regenerative actuators have focused exclusively on level-ground walking applications. Here we analyzed the lower-limb joint mechanical power during stand-to-sit movements using inverse dynamic simulations to estimate the biomechanical energy available for electrical regeneration. Nine subjects performed 20 sitting and standing movements while lower-limb kinematics and ground reaction forces were measured. Subject-specific body segment parameters were estimated using parameter identification. Joint mechanical power was calculated from net joint torques and rotational velocities and numerically integrated over time to estimate the joint biomechanical energy. The hip joint produced the largest peak negative mechanical power (1.8 ± 0.5 W/kg), followed by the knee (0.8 ± 0.3 W/kg) and ankle (0.2 ± 0.1 W/kg). Negative mechanical work from the hip, knee, and ankle joints per stand-to-sit movement were 0.35 ± 0.06 J/kg, 0.15 ± 0.08 J/kg, and 0.02 ± 0.01 J/kg, respectively. Assuming known regenerative actuator efficiencies (i.e., maximum 63%), robotic exoskeletons and prostheses could theoretically regenerate ~26 Joules of electrical energy while sitting down, compared to ~19 Joules per walking stride. Given that these regeneration performance calculations are based on healthy young adults, future research should include seniors and/or rehabilitation patients to better estimate the biomechanical energy available for electrical regeneration in persons with mobility impairments.Reference:Laschowski B, Razavian RS, and McPhee J. (2020). Simulation of Stand-to-Sit Biomechanics for Design of Lower-Limb Exoskeletons and Prostheses with Energy Regeneration. bioRxiv. DOI: 10.1101/801258.
DOI: 10.5281/zenodo.4382176
title: Supplementary MRSI data for "Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7T"

description: Intended as supplementary data to the manuscript "Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7T" Authors:<br> Gilbert Hangel, Benjamin Spurny, Philipp Lazen, Cornelius Cadrien, Sukrit Sharma, Lukas Hingerl, Eva Hečková, Bernhard Strasser, Stanislav Motyka, Alexandra Lipka, Stephan Gruber, Christoph Brandner, Rupert Lanzenberger, Karl Rössler, Siegfried Trattnig, Wolfgang Bogner ###################################################<br> MRSI Maps from the Vienna 7T scanner in MINC/NIFTI format<br> ################################################### Contact: wolfgang.bogner@meduniwien.ac.at , gilbert.hangel@meduniwien.ac.at<br> https://hfmr.meduniwien.ac.at/ For use with and MINC- and NIFTI-displaying software. MRSI method published as Hingerl et al 2020, doi: 10.1097/RLI.0000000000000626 Volunteers 7,11,13,19,23 as described in Tables 1 and 2.
DOI: 10.5517/ccdc.csd.cc20rr3n
title: CCDC 1869861: Experimental Crystal Structure Determination

description: Related Article: In‐Hwan Choi,  Sukbin Yoon,  Seong Huh,  Sung‐Jin Kim,  Youngmee Kim|2020|Chem.-Eur.J.|26|14580|doi:10.1002/chem.202003743
DOI: 10.5517/ccdc.csd.cc20rr7s
title: CCDC 1869865: Experimental Crystal Structure Determination

description: Related Article: In‐Hwan Choi,  Sukbin Yoon,  Seong Huh,  Sung‐Jin Kim,  Youngmee Kim|2020|Chem.-Eur.J.|26|14580|doi:10.1002/chem.202003743
DOI: 10.5517/ccdc.csd.cc20rvn9
title: CCDC 1869971: Experimental Crystal Structure Determination

description: Related Article: In‐Hwan Choi,  Sukbin Yoon,  Seong Huh,  Sung‐Jin Kim,  Youngmee Kim|2020|Chem.-Eur.J.|26|14580|doi:10.1002/chem.202003743
DOI: 10.5517/ccdc.csd.cc23jyk5
title: CCDC 1952707: Experimental Crystal Structure Determination

description: Related Article: Teresa Lauria, Creina Slator, Vickie McKee, Markus Müller, Samuele Stazzoni, Antony L. Crisp, Thomas Carell, Andrew Kellett|2020|Chem.-Eur.J.|26|16782|doi:10.1002/chem.202002860
DOI: 10.5517/ccdc.csd.cc23jyl6
title: CCDC 1952708: Experimental Crystal Structure Determination

description: Related Article: Teresa Lauria, Creina Slator, Vickie McKee, Markus Müller, Samuele Stazzoni, Antony L. Crisp, Thomas Carell, Andrew Kellett|2020|Chem.-Eur.J.|26|16782|doi:10.1002/chem.202002860
DOI: 10.5517/ccdc.csd.cc23jym7
title: CCDC 1952709: Experimental Crystal Structure Determination

description: Related Article: Teresa Lauria, Creina Slator, Vickie McKee, Markus Müller, Samuele Stazzoni, Antony L. Crisp, Thomas Carell, Andrew Kellett|2020|Chem.-Eur.J.|26|16782|doi:10.1002/chem.202002860
DOI: 10.5517/ccdc.csd.cc23jyn8
title: CCDC 1952710: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc250wps
title: CCDC 1996855: Experimental Crystal Structure Determination

description: Related Article: Sonia Bajo, Macarena G. Alférez, María M. Alcaide, Joaquín López-Serrano, Jesús Campos|2020|Chem.-Eur.J.|26|16833|doi:10.1002/chem.202003167
DOI: 10.5517/ccdc.csd.cc250wqt
title: CCDC 1996856: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc250wrv
title: CCDC 1996857: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc250wsw
title: CCDC 1996858: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc250wtx
title: CCDC 1996859: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc2535s8
title: CCDC 1999059: Experimental Crystal Structure Determination

description: Related Article: Yueze Gao, Vroni Walter, Michael J. Ferguson, Rik R. Tykwinski|2020|Chem.-Eur.J.|26|16712|doi:10.1002/chem.202002030
DOI: 10.5517/ccdc.csd.cc2535t9
title: CCDC 1999060: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc256lvv
title: CCDC 2002347: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc256lww
title: CCDC 2002348: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc256lzz
title: CCDC 2002351: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc256m12
title: CCDC 2002353: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc2576m8
title: CCDC 2002929: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc2576qc
title: CCDC 2002932: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc2576sf
title: CCDC 2002934: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc2576n9
title: CCDC 2002930: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc2576wj
title: CCDC 2002937: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc2576pb
title: CCDC 2002931: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc2576l7
title: CCDC 2002928: Experimental Crystal Structure Determination

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