cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2096m5
title: CCDC 1855896: Experimental Crystal Structure Determination

description: Related Article: Silvia Carboni, Antonio Zucca, Sergio Stoccoro, Laura Maiore, Massimiliano Arca, Fabrizio Ortu, Christian Artner, Bernhard K. Keppler, Samuel M. Meier-Menches, Angela Casini, Maria Agostina Cinellu|2018|Inorg.Chem.|57|14852|doi:10.1021/acs.inorgchem.8b02604
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.cc2096n6
title: CCDC 1855897: Experimental Crystal Structure Determination

description: Related Article: Silvia Carboni, Antonio Zucca, Sergio Stoccoro, Laura Maiore, Massimiliano Arca, Fabrizio Ortu, Christian Artner, Bernhard K. Keppler, Samuel M. Meier-Menches, Angela Casini, Maria Agostina Cinellu|2018|Inorg.Chem.|57|14852|doi:10.1021/acs.inorgchem.8b02604
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.cc2096p7
title: CCDC 1855898: Experimental Crystal Structure Determination

description: Related Article: Silvia Carboni, Antonio Zucca, Sergio Stoccoro, Laura Maiore, Massimiliano Arca, Fabrizio Ortu, Christian Artner, Bernhard K. Keppler, Samuel M. Meier-Menches, Angela Casini, Maria Agostina Cinellu|2018|Inorg.Chem.|57|14852|doi:10.1021/acs.inorgchem.8b02604
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.cc2096q8
title: CCDC 1855899: Experimental Crystal Structure Determination

description: Related Article: Silvia Carboni, Antonio Zucca, Sergio Stoccoro, Laura Maiore, Massimiliano Arca, Fabrizio Ortu, Christian Artner, Bernhard K. Keppler, Samuel M. Meier-Menches, Angela Casini, Maria Agostina Cinellu|2018|Inorg.Chem.|57|14852|doi:10.1021/acs.inorgchem.8b02604
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.cc21mbpq
title: CCDC 1895423: Experimental Crystal Structure Determination

description: Related Article: Tomohiro Seki, Kentaro Kashiyama, Hajime Ito|2019|Dalton Trans.|48|7105|doi:10.1039/C9DT00566H
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.cc21xzvt
title: CCDC 1904697: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Murray V. Baker, James L. Hickey|2019|CSD Communication|||
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.cc21y629
title: CCDC 1904890: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Murray V. Baker, James L. Hickey|2019|CSD Communication|||
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.cc2531kx
title: CCDC 1998928: Experimental Crystal Structure Determination

description: Related Article:  Uwe Monkowius|2020|CSD Communication|||
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.cc2bkw4y
title: CCDC 2162130: Experimental Crystal Structure Determination

description: Related Article: Ritika Kubba, Omprakash Yadav, Suman Maji, Natalia Fridman, Anil Kumar|2022|J.Mol.Struct.|1269|133780|doi:10.1016/j.molstruc.2022.133780
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.cc2bkw5z
title: CCDC 2162131: Experimental Crystal Structure Determination

description: Related Article: Ritika Kubba, Omprakash Yadav, Suman Maji, Natalia Fridman, Anil Kumar|2022|J.Mol.Struct.|1269|133780|doi:10.1016/j.molstruc.2022.133780
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.cc2bkw60
title: CCDC 2162132: Experimental Crystal Structure Determination

description: Related Article: Ritika Kubba, Omprakash Yadav, Suman Maji, Natalia Fridman, Anil Kumar|2022|J.Mol.Struct.|1269|133780|doi:10.1016/j.molstruc.2022.133780
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.cc2bkw71
title: CCDC 2162133: Experimental Crystal Structure Determination

description: Related Article: Ritika Kubba, Omprakash Yadav, Suman Maji, Natalia Fridman, Anil Kumar|2022|J.Mol.Struct.|1269|133780|doi:10.1016/j.molstruc.2022.133780
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.cc2bsq3z
title: CCDC 2168701: Experimental Crystal Structure Determination

description: Related Article: Meixiang Wang, Xiaoxiao Niu, Rui Cao, Mengyu Zhang, Rongbao Liao, Huajie Xu, Fuying Hao, Zhaodi Liu|2022|J.Mol.Struct.|1269|133777|doi:10.1016/j.molstruc.2022.133777
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.cc2c17k7
title: CCDC 2175938: Experimental Crystal Structure Determination

description: Related Article: Huizhe Han, Vladimir N. Kovtonyuk, Yurii V. Gatilov, Rodion V. Andreev|2022|J.Fluorine Chem.|261-262|110022|doi:10.1016/j.jfluchem.2022.110022
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.cc2cj6kp
title: CCDC 2190322: Experimental Crystal Structure Determination

description: Related Article: M.Z. Wiśniewski, T. Głowiak|1998|Pol.J.Chem.|72|514|
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.cc2ck9t2
title: CCDC 2191384: Experimental Crystal Structure Determination

description: Related Article: M. Bernhard, J.C. Lutter, A. Predecki|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|821|doi:10.1107/S2056989022007423
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: 10.5281/zenodo.6966804
title: Potential and realized distribution at 30m for Scots pine (Pinus sylvestris) in Europe for 2000 - 2020

description: Probability and uncertainty maps showing the potential and realized distribution for the Scots pine (<em>Pinus sylvestris, L.</em>) for Europe from the dataset prepared by Bonannella et al. (2022) and predicted using Ensemble Machine Learning (EML). Potential distribution map cover the period 2018 - 2020; realized distribution cover the period 2000 - 2020, split in the following time periods: 2000 - 2002, 2002 - 2006, 2006 - 2010, 2010 - 2014, 2014 - 2018, 2018 - 2020. Files are named according to the following naming convention, e.g: veg_pinus.sylvestris_anv.eml_md_30m_0..0cm_2000..2002_eumap_epsg3035_v0.3 with the following fields: theme: e.g. <strong>veg</strong>, species code: e.g. <strong>pinus.sylvestris</strong>, species distribution type: e.g. <strong>anv</strong> (= actual natural vegetation), species estimation method: e.g. <strong>eml</strong>, species estimation type: e.g. <strong>md</strong> ( = model deviation), resolution in meters e.g. <strong>30m</strong>, reference depths (vertical dimension): e.g. <strong>0..0cm</strong>, reference period begin end: e.g. <strong>2000..2002</strong>, reference area: e.g. <strong>eumap</strong>, coordinate system: e.g. <strong>epsg3035</strong>, data set version: e.g. <strong>v0.3</strong>. For each species is then easy to identify probability and uncertainty distribution maps: veg_pinus.sylvestris_<strong>anv</strong>.eml_<strong>md</strong>: model uncertainty for realized distribution veg_pinus.sylvestris_<strong>anv</strong>.eml_<strong>p</strong>: probability for realized distribution veg_pinus.sylvestris_<strong>pnv</strong>.eml_<strong>md</strong>: model uncertainty for potential distribution veg_pinus.sylvestris_<strong>pnv</strong>.eml_<strong>p</strong>: probability for potential distribution Files are provided as Cloud Optimized GeoTIFFs and projected in the Coordinate Reference System ETRS89 / LAEA Europe (= EPSG code 3035). Styling files are provided in both <em>SLD</em> and <em>QML</em> format. If you would like to know more about the creation of the maps and the modeling: <strong>watch</strong> the talk at Open Data Science Workshop 2021 (TIB AV-PORTAL) <strong>access </strong>the repository with our R/Python scripts and follow the instructions (GitLab) <strong>access </strong>the repository with the training dataset (Zenodo) <strong>read </strong>the tutorial with executable code on our GitBook A publication describing, in detail, all processing steps, accuracy assessment and general analysis of species distribution maps is available on PeerJ. To suggest any improvement/fix use https://gitlab.com/geoharmonizer_inea/spatial-layers/-/issues.
description: This work is co-financed under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 by the European Union (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.5281/zenodo.5884261
title: Potential and realized distribution at 30m for Scots pine (Pinus sylvestris) in Europe for 2000 - 2020

description: Probability and uncertainty maps showing the potential and realized distribution for the Scots pine (<em>Pinus sylvestris, L.</em>) for Europe from the dataset prepared by Bonannella et al. (2022) and predicted using Ensemble Machine Learning (EML). Potential distribution map cover the period 2018 - 2020; realized distribution cover the period 2000 - 2020, split in the following time periods: 2000 - 2002, 2002 - 2006, 2006 - 2010, 2010 - 2014, 2014 - 2018, 2018 - 2020. Files are named according to the following naming convention, e.g: veg_pinus.sylvestris_anv.eml_md_30m_0..0cm_2000..2002_eumap_epsg3035_v0.3 with the following fields: theme: e.g. <strong>veg</strong>, species code: e.g. <strong>pinus.sylvestris</strong>, species distribution type: e.g. <strong>anv</strong> (= actual natural vegetation), species estimation method: e.g. <strong>eml</strong>, species estimation type: e.g. <strong>md</strong> ( = model deviation), resolution in meters e.g. <strong>30m</strong>, reference depths (vertical dimension): e.g. <strong>0..0cm</strong>, reference period begin end: e.g. <strong>2000..2002</strong>, reference area: e.g. <strong>eumap</strong>, coordinate system: e.g. <strong>epsg3035</strong>, data set version: e.g. <strong>v0.3</strong>. For each species is then easy to identify probability and uncertainty distribution maps: veg_pinus.sylvestris_<strong>anv</strong>.eml_<strong>md</strong>: model uncertainty for realized distribution veg_pinus.sylvestris_<strong>anv</strong>.eml_<strong>p</strong>: probability for realized distribution veg_pinus.sylvestris_<strong>pnv</strong>.eml_<strong>md</strong>: model uncertainty for potential distribution veg_pinus.sylvestris_<strong>pnv</strong>.eml_<strong>p</strong>: probability for potential distribution Files are provided as Cloud Optimized GeoTIFFs and projected in the Coordinate Reference System ETRS89 / LAEA Europe (= EPSG code 3035). Styling files are provided in both <em>SLD</em> and <em>QML</em> format. If you would like to know more about the creation of the maps and the modeling: <strong>watch</strong> the talk at Open Data Science Workshop 2021 (TIB AV-PORTAL) <strong>access </strong>the repository with our R/Python scripts and follow the instructions (GitLab) <strong>access </strong>the repository with the training dataset (Zenodo) <strong>read </strong>the tutorial with executable code on our GitBook A publication describing, in detail, all processing steps, accuracy assessment and general analysis of species distribution maps is available on PeerJ. To suggest any improvement/fix use https://gitlab.com/geoharmonizer_inea/spatial-layers/-/issues.
description: This work is co-financed under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 by the European Union (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.13026/bpnv-4b88
title: Cerebromicrovascular Disease in Elderly with Diabetes

description: This dataset was collected as part of a prospective observational study to
evaluate the effects of type 2 diabetes mellitus (DM) on cerebral
vasoregulation, perfusion and functional outcomes, measured by blood flow
responses to hypocapnia and hypercapnia, Valsalva maneuver, head-up tilt, and
sit-to-stand test. The dataset comprises of observations from 69 diabetic and
control participants (aged 55 to 75 years) with continuous measurements of
cerebral blood flow using transcranial Doppler and MRI (magnetic resonance
imaging), heart rate, blood pressure, and respiratory parameters, balance,
walking, laboratory and retinopathy measures at baseline, and 41 subjects who
completed the two-years of follow-up. Regional gray, white matter and
cerebrospinal fluid volumes were quantified using a segmentation method
applied on T1- and T2- weighted images and perfusion maps, using a continuous
arterial spin labeling (CASL) images at 3 Tesla MRI. White matter integrity
was determined from fluid attenuated inversion recovery (FLAIR) and diffusion
tensor imaging (DTI) MRI. Dynamics of cerebral vasoregulation to CO2 challenge
and orthostatic stress were measured using Transcranial Doppler ultrasound
(TCD).
DOI: 10.13026/00bm-0x81
title: Cerebromicrovascular Disease in Elderly with Diabetes

description: This dataset was collected as part of a prospective observational study to
evaluate the effects of type 2 diabetes mellitus (DM) on cerebral
vasoregulation, perfusion and functional outcomes, measured by blood flow
responses to hypocapnia and hypercapnia, Valsalva maneuver, head-up tilt, and
sit-to-stand test. The dataset comprises of observations from 69 diabetic and
control participants (aged 55 to 75 years) with continuous measurements of
cerebral blood flow using transcranial Doppler and MRI (magnetic resonance
imaging), heart rate, blood pressure, and respiratory parameters, balance,
walking, laboratory and retinopathy measures at baseline, and 41 subjects who
completed the two-years of follow-up. Regional gray, white matter and
cerebrospinal fluid volumes were quantified using a segmentation method
applied on T1- and T2- weighted images and perfusion maps, using a continuous
arterial spin labeling (CASL) images at 3 Tesla MRI. White matter integrity
was determined from fluid attenuated inversion recovery (FLAIR) and diffusion
tensor imaging (DTI) MRI. Dynamics of cerebral vasoregulation to CO2 challenge
and orthostatic stress were measured using Transcranial Doppler ultrasound
(TCD).
DOI: 10.13026/pgn6-6k53
title: Cerebral perfusion and cognitive decline in type 2 diabetes

description: This dataset was collected as part of a study to explore vasoregulation and
blood flow in patients with type 2 Diabetes mellitus. It comprises cerebral
blood, autonomic functions, laboratory and gait variables in 70 patients with
type 2 DM and 70 healthy controls (50-85 years old). Diabetes mellitus is a
prevalent, costly condition with high morbidity and mortality that affects
nearly 6.3% of the population in the United States. Diabetes mellitus alters
the permeability of the blood-brain barrier, thus affecting regional
metabolism and microcirculatory regulation. Predictors of cerebrovascular
complications of diabetes that are evidence-based on cerebral blood flow, MRI
imaging, and cognitive testing are lacking.

Blood flow velocities were measured in the anterior and middle cerebral
arteries using transcranial Doppler ultrasound. Cerebral vasoregulation was
evaluated by comparing blood flow velocity responses during hypocapnia and
hypercapnia, Valsalva maneuver, head-up tilt and sit-to-stand test using
simultaneous recordings of cardiovascular variables, blood flow velocity in
the anterior and middle cerebral artery using transcranial Doppler and
respiratory variables. We applied continuous arterial spin labeling at 3 Tesla
MRI to evaluate regional distribution of cerebral blood flow and vasomotor
reactivity to CO2. Cognitive and executive functions were assessed via a
battery of psychometric measures. Gait and balance were characterized from
dynamics of foot pressure distribution and center of pressure displacement.
DOI: 10.13026/whjz-e968
title: Cerebral perfusion and cognitive decline in type 2 diabetes

description: This dataset was collected as part of a study to explore vasoregulation and
blood flow in patients with type 2 Diabetes mellitus. It comprises cerebral
blood, autonomic functions, laboratory and gait variables in 70 patients with
type 2 DM and 70 healthy controls (50-85 years old). Diabetes mellitus is a
prevalent, costly condition with high morbidity and mortality that affects
nearly 6.3% of the population in the United States. Diabetes mellitus alters
the permeability of the blood-brain barrier, thus affecting regional
metabolism and microcirculatory regulation. Predictors of cerebrovascular
complications of diabetes that are evidence-based on cerebral blood flow, MRI
imaging, and cognitive testing are lacking.

Blood flow velocities were measured in the anterior and middle cerebral
arteries using transcranial Doppler ultrasound. Cerebral vasoregulation was
evaluated by comparing blood flow velocity responses during hypocapnia and
hypercapnia, Valsalva maneuver, head-up tilt and sit-to-stand test using
simultaneous recordings of cardiovascular variables, blood flow velocity in
the anterior and middle cerebral artery using transcranial Doppler and
respiratory variables. We applied continuous arterial spin labeling at 3 Tesla
MRI to evaluate regional distribution of cerebral blood flow and vasomotor
reactivity to CO2. Cognitive and executive functions were assessed via a
battery of psychometric measures. Gait and balance were characterized from
dynamics of foot pressure distribution and center of pressure displacement.
DOI: 10.6084/m9.figshare.20439171.v1
title: Supplementary Tables.zip

description: Supplementary Tables 1-4
DOI: 10.6084/m9.figshare.20439171
title: Supplementary Tables

description: Supplementary Tables 1-4
DOI: 10.6084/m9.figshare.20439171.v3
title: Supplementary Tables

description: Supplementary Tables 1-4
DOI: 10.6084/m9.figshare.20439171.v2
title: Supplementary Tables

description: Supplementary Tables 1-5
DOI: 10.5281/zenodo.6967048
title: Dataset of cryptocurrency & NFT datasets

description: This dataset contains information about various datasets regarding cryptocurrencies and NFTs across the internet
DOI: 10.5281/zenodo.6967047
title: Dataset of cryptocurrency & NFT datasets

description: This dataset contains information about various datasets regarding cryptocurrencies and NFTs across the internet
DOI: 10.6084/m9.figshare.19100510.v1
title: data set.xlsx

description: Data set for the study "HIV prevalence among street connected children in Mwanza". <br>
DOI: 10.6084/m9.figshare.19704289
title: figure_seurat_obj

description: paper related seurat object
DOI: 10.6084/m9.figshare.19704289.v2
title: figure_seurat_obj

description: paper related seurat object
DOI: 10.5281/zenodo.6623603
title: Contrasting molecular profiles of clownfish and damselfish skin mucus-RPLC_negative_mode

description: Raw abf files of data acquired in RPLC negative ionization mode for Lipidomics analysis
DOI: 10.5281/zenodo.6623602
title: Contrasting molecular profiles of clownfish and damselfish skin mucus-RPLC_negative_mode

description: Raw abf files of data acquired in RPLC negative ionization mode for Lipidomics analysis
DOI: 10.6084/m9.figshare.20369313
title: Bootstrapped gene trees

description: All bootstrapped phylogenetic trees for each gene included in this study.