cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2cprkd
title: CCDC 2195654: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprlf
title: CCDC 2195655: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprmg
title: CCDC 2195656: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprnh
title: CCDC 2195657: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprpj
title: CCDC 2195658: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprqk
title: CCDC 2195659: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprrl
title: CCDC 2195660: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprsm
title: CCDC 2195661: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprtn
title: CCDC 2195662: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprvp
title: CCDC 2195663: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprwq
title: CCDC 2195664: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprxr
title: CCDC 2195665: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprys
title: CCDC 2195666: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cprzt
title: CCDC 2195667: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cps0w
title: CCDC 2195668: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cps1x
title: CCDC 2195669: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cps2y
title: CCDC 2195670: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cps40
title: CCDC 2195672: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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.cc2cps51
title: CCDC 2195673: Experimental Crystal Structure Determination

description: Related Article: Zhuanling Bai, Benjamin Scheibe, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2022|Inorg.Chem.|61|19193|doi:10.1021/acs.inorgchem.2c02840
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: 10.5522/04/21696008
title: Gamma Training Dataset

description: This training dataset included optical network topologies that are generated via SNR-BA method [1] with nodes scattered uniformly randomly over a grid the size of the north american continent. Here there is a minimum radius that is adhered to (100km) between the nodes. The nodes are between scales of 55-100 nodes. The routings of the network are computed under uniform bandwidth conditions with the first-fit k-shortest-path (FF-kSP) algorithm and sequential loading (SL) until the maximum state of the network is found at zero blocking. The Gaussian noise (GN) model is used to calculate the signal-to-noise ratio of paths and the total throughput of the network. This throughput is given as a training label. [1] R. Matzner, D. Semrau, R. Luo, G. Zervas, and P. Bayvel, ‘Making intelligent topology design choices: understanding structural and physical property performance implications in optical networks [Invited]’, <em>J. Opt. Commun. Netw., JOCN</em>, vol. 13, no. 8, pp. D53–D67, Aug. 2021, doi: 10.1364/JOCN.423490.
DOI: 10.5522/04/21696008.v1
title: Gamma Training Dataset

description: This training dataset included optical network topologies that are generated via SNR-BA method [1] with nodes scattered uniformly randomly over a grid the size of the north american continent. Here there is a minimum radius that is adhered to (100km) between the nodes. The nodes are between scales of 55-100 nodes. The routings of the network are computed under uniform bandwidth conditions with the first-fit k-shortest-path (FF-kSP) algorithm and sequential loading (SL) until the maximum state of the network is found at zero blocking. The Gaussian noise (GN) model is used to calculate the signal-to-noise ratio of paths and the total throughput of the network. This throughput is given as a training label. [1] R. Matzner, D. Semrau, R. Luo, G. Zervas, and P. Bayvel, ‘Making intelligent topology design choices: understanding structural and physical property performance implications in optical networks [Invited]’, <em>J. Opt. Commun. Netw., JOCN</em>, vol. 13, no. 8, pp. D53–D67, Aug. 2021, doi: 10.1364/JOCN.423490.
DOI: 10.5522/04/21689078
title: Alpha Test Datset

description: This set of data houses the 6000 graphs used for testing the beta model that has been trained on the beta dataset. It houses topologies generated via SNR-BA [1] with nodes scattered uniformly randomly with a minimum radius of 100km between them over a grid the size of north america. The throughput labels are calculated via maximising the routing and wavelength assignment with zero blocking using an integer linear programming formulation and implementing the physical layer impairments using the gaussian noise model. <br> [1] R. Matzner, D. Semrau, R. Luo, G. Zervas, and P. Bayvel, ‘Making intelligent topology design choices: understanding structural and physical property performance implications in optical networks [Invited]’, J. Opt. Commun. Netw., JOCN, vol. 13, no. 8, pp. D53–D67, Aug. 2021, doi: 10.1364/JOCN.423490.
DOI: 10.5522/04/21689078.v1
title: Alpha Test Datset

description: This set of data houses the 6000 graphs used for testing the beta model that has been trained on the beta dataset. It houses topologies generated via SNR-BA [1] with nodes scattered uniformly randomly with a minimum radius of 100km between them over a grid the size of north america. The throughput labels are calculated via maximising the routing and wavelength assignment with zero blocking using an integer linear programming formulation and implementing the physical layer impairments using the gaussian noise model. <br> [1] R. Matzner, D. Semrau, R. Luo, G. Zervas, and P. Bayvel, ‘Making intelligent topology design choices: understanding structural and physical property performance implications in optical networks [Invited]’, J. Opt. Commun. Netw., JOCN, vol. 13, no. 8, pp. D53–D67, Aug. 2021, doi: 10.1364/JOCN.423490.
DOI: 10.5522/04/21689072
title: Alpha Training Dataset

description: Training dataset for nodes between 10-15 nodes with throughput labels. The graphs are generated by the SNR-BA [1] model with nodes scattered uniformly over a grid the size of north america with mimum distances between nodes set to 100km. The throughput labels are generated by maximising the routing and wavelength assignment by a integer linear programming formulation at zero blocking and calculating the physical layer impairements via the gaussian noise model.
DOI: 10.5522/04/21689072.v1
title: Alpha Training Dataset

description: Training dataset for nodes between 10-15 nodes with throughput labels. The graphs are generated by the SNR-BA [1] model with nodes scattered uniformly over a grid the size of north america with mimum distances between nodes set to 100km. The throughput labels are generated by maximising the routing and wavelength assignment by a integer linear programming formulation at zero blocking and calculating the physical layer impairements via the gaussian noise model.
DOI: 10.5281/zenodo.7415485
title: Supplementary Figure 1 Gating strategy for Treg phenotype analysis.

description: <strong>Supplementary Figure 1. Gating strategy for Treg phenotype analysis. |</strong> Isolated and purified cells (see Methods) were analysed by flow cytometry with <strong>(A)</strong> gating performed as indicated including the exclusion of dead cells (by Live/Dead staining kit) and analysing only CD4+CD25+ double-positive cells. <strong>(B)</strong> These cells were then stained with indicated marker antibodies. The histogram quantification areas indicated by the black bars were set against control staining performed with non-specific isotype antibodies corresponding to each marker antibody.
DOI: 10.5281/zenodo.7415484
title: Supplementary Figure 1 Gating strategy for Treg phenotype analysis.

description: <strong>Supplementary Figure 1. Gating strategy for Treg phenotype analysis. |</strong> Isolated and purified cells (see Methods) were analysed by flow cytometry with <strong>(A)</strong> gating performed as indicated including the exclusion of dead cells (by Live/Dead staining kit) and analysing only CD4+CD25+ double-positive cells. <strong>(B)</strong> These cells were then stained with indicated marker antibodies. The histogram quantification areas indicated by the black bars were set against control staining performed with non-specific isotype antibodies corresponding to each marker antibody.
DOI: 10.3886/e180241
title: Data and Code for: Debt Revenue and the Sustainability of Public Debt

description: While public debt has risen in the last two decades, the return that it offers to investors has fallen, especially relative to the return on private investment. This creates a revenue for the government as the supplier of the special services offered by public bonds, which include storage of value, safety, liquidity, and reprieve from repression. The present value of this debt revenue is large relative to the stock of public debt, keeping it sustainable even as the present value of primary balances is zero or negative. It gives rise to different policy tradeoffs than the conventional analysis of primary balances and makes different recommendation on the effects of austerity, the optimal amount of debt, or the spillovers between monetary and fiscal policy.
DOI: 10.3886/e180241v1
title: Data and Code for: Debt Revenue and the Sustainability of Public Debt

description: While public debt has risen in the last two decades, the return that it offers to investors has fallen, especially relative to the return on private investment. This creates a revenue for the government as the supplier of the special services offered by public bonds, which include storage of value, safety, liquidity, and reprieve from repression. The present value of this debt revenue is large relative to the stock of public debt, keeping it sustainable even as the present value of primary balances is zero or negative. It gives rise to different policy tradeoffs than the conventional analysis of primary balances and makes different recommendation on the effects of austerity, the optimal amount of debt, or the spillovers between monetary and fiscal policy.
DOI: 10.5281/zenodo.7410609
title: Hydrochemistry of the Leverett Glacier proglacial river, Southwest Greenland (2009-2012)

description: This dataset describes the dissolved major ion (Ca2+, Mg2+, K+, Na+, Cl-, SO4 2-), nutrient (NO3-, NH4+, PO4 3-, DSi, TDN) and organic carbon (DOC) concentrations in the proglacial rivers of the Leverett Glacier (LG) in Southwest Greenland for the 2009, 2010 and 2012 melt seasons. The data have already been part of 3 different publications (Lawson et al. 2014, Hawkings et al. 2015, Wadham et al. 2016) but are archived here for the first time. For similar data at LG and/or Kiattut Sermia (South Greenland) for the 2015 and 2013 melt seasons, respectively, see Hatton et al. 2018 (see 'related identifiers').
description: The obtention and archiving of these data were also allowed thanks to: NERC CASE studentship to E. C. Lawson (NERC DTG/GEOG SN1316.6525); NERC PhD studentship to J. Hawkings; NERC studentship and MOSS scholarship to A. Tedstone; Carnegie Trust for University of Scotland and The University of Edinburgh Development Trust to P. W. Nienow; Leverhulme Trust, via a Leverhulme research fellowship to J. L. Wadham
DOI: 10.5281/zenodo.7410608
title: Hydrochemistry of the Leverett Glacier proglacial river, Southwest Greenland (2009-2012)

description: This dataset describes the dissolved major ion (Ca2+, Mg2+, K+, Na+, Cl-, SO4 2-), nutrient (NO3-, NH4+, PO4 3-, DSi, TDN) and organic carbon (DOC) concentrations in the proglacial rivers of the Leverett Glacier (LG) in Southwest Greenland for the 2009, 2010 and 2012 melt seasons. The data have already been part of 3 different publications (Lawson et al. 2014, Hawkings et al. 2015, Wadham et al. 2016) but are archived here for the first time. For similar data at LG and/or Kiattut Sermia (South Greenland) for the 2015 and 2013 melt seasons, respectively, see Hatton et al. 2018 (see 'related identifiers').
description: The obtention and archiving of these data were also allowed thanks to: NERC CASE studentship to E. C. Lawson (NERC DTG/GEOG SN1316.6525); NERC PhD studentship to J. Hawkings; NERC studentship and MOSS scholarship to A. Tedstone; Carnegie Trust for University of Scotland and The University of Edinburgh Development Trust to P. W. Nienow; Leverhulme Trust, via a Leverhulme research fellowship to J. L. Wadham