cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1408651
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS drybean

description: This is model output from LPJ-GUESS for drybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5517/ccdc.csd.cc1mrvpx
title: CCDC 1512480: Experimental Crystal Structure Determination

description: Related Article: Mohammad Kazem Mohammadi, Payam Hayati, Samira Jafari, Mehdi Karimi, Angel Gutierrez|2019|J.Mol.Struct.|1176|434|doi:10.1016/j.molstruc.2018.09.001
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.cc1q5jv8
title: CCDC 1584250: Experimental Crystal Structure Determination

description: Related Article: André Delavault, Frank R. Fronczek, Wu Xu, Radhey S. Srivastava|2018|J.Organomet.Chem.|875|29|doi:10.1016/j.jorganchem.2018.08.027
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.cc1q5jw9
title: CCDC 1584251: Experimental Crystal Structure Determination

description: Related Article: André Delavault, Frank R. Fronczek, Wu Xu, Radhey S. Srivastava|2018|J.Organomet.Chem.|875|29|doi:10.1016/j.jorganchem.2018.08.027
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: 10.7910/dvn/ojbz67/cxcxsu
title: 17723370_55_1335324_TP_0_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/etn9eh
title: 17723370_54_17985393_TP_1_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/geh2qg
title: 17723370_54_17985393_TP_1_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/kwn5mm
title: 17723368_49_1598560_TP_1_VarLen_Wave500Hz_Pleth.txt
DOI: 10.7910/dvn/ojbz67/mss8ox
title: 17723370_54_17985393_TP_1_VarLen_Wave500Hz_ECG II.txt
DOI: 10.7910/dvn/ojbz67/towcq1
title: 17723370_54_17985393_TP_1_VarLen_Wave500Hz_Pleth.txt
DOI: 10.7910/dvn/ojbz67/ud6thh
title: 17723370_54_17985393_TP_1_VarLen_Trend4Hz_IHR.txt
DOI: 10.7910/dvn/ojbz67/zgz2gv
title: 17723370_55_1335324_TP_0_VarLen_Trend4Hz_IHR.txt
DOI: 10.1285/i22390359v26p27
title: Sulle vocali nasali e nasalizzate dell'albanese

description: Nasalization of stressed vowels in Albanian (especially in the northern Albania Geg dialect) is considered by Albanologists as a very problematic phenomenon and a case study difficult to be solved. The current paper proposes an analysis that frames the phenomenon both at a synchronic and diachronic level. The development of vowel nasalization is investigated by taking into account the most accredited theories in the acoustic-coarticulatory field as well as linguistic universals concerning the spreading of nasalization in the vowel systems of various languages of the world. From a diachronic point of view, particular attention is paid to the original conditions of Albanian vocalism and, above all, to the aspects concerning the results of IE *o and and *e (as well as *a and *e from Latin borrowings). The evolution of these sounds helps to determine both the phonetic conditioning which originated nasalization and its periodization: nasalization developed only before a tautosyllabic nasal consonant (except for those cases where it is a result of analogical leveling) and must have been stabilized after the diphthongization of mid vowels *e and *o. Finally, based on the data available today concerning the geographical distribution of nasal vowels in the Albanian speaking area (including Kosovo, Macedonia and Montenegro), an alternative hypothesis about the diffusion of the phenomenon is offered. Nasalization in Albanian may have had a gradual spreading, relatively to the number of vowels involved, through a process blocked at its initial stage in the southern Tosk area and in some peripheral Geg areas, and not uniformly extended to the whole Albanian speaking region.
DOI: 10.1285/i22390359v26p7
title: (Co)constructing use, belonging and legitimacy. A study of English language ownership in Italy

description: The conviction that the ownership of English is shared among its users worldwide has long been held by linguists whose work has ushered in new paradigms in the ways of conceptualizing and researching language. Yet, research that explores how English users understand and construct ownership is lacking in many contexts. The present article aims to fill this gap by investigating the nature of language ownership among English learners in Naples, Italy. Drawing on the framework for language ownership delineated in Seilhamer (2015), questionnaire data and interview moments with four case study participants are analyzed to explore how high school students construct relationships with English and understandings of ownership in terms of prevalent usage, affective belonging, and legitimate knowledge. The findings unveil the dynamic ways in which understandings of language ownership, which is agentively (co)constructed and negotiated, are capable of continuously shifting in different settings and with different interlocutors.
DOI: 10.5281/zenodo.1408272
title: Open-Source Shared Memory Implementation Of The Hpcg Benchmark: Analysis, Improvements And Evaluation On Cavium Thunderx2

description: This archive contains the output files used to gerenate tables and plots in the paper "Open-Source Shared Memory implementation of the HPCG benchmark: analysis, improvements and evaluation on Cavium ThunderX2" submitted to the 9th IEEE International Workshop on "Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems" (PMBS18) held as part of ACM/IEEE Supercomputing 2018 (SC18), Dallas, TX, USA.
DOI: 10.5281/zenodo.1408273
title: Open-Source Shared Memory Implementation Of The Hpcg Benchmark: Analysis, Improvements And Evaluation On Cavium Thunderx2

description: This archive contains the output files used to gerenate tables and plots in the paper "Open-Source Shared Memory implementation of the HPCG benchmark: analysis, improvements and evaluation on Cavium ThunderX2" submitted to the 9th IEEE International Workshop on "Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems" (PMBS18) held as part of ACM/IEEE Supercomputing 2018 (SC18), Dallas, TX, USA.
DOI: 10.5281/zenodo.1408646
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS maize

description: This is model output from LPJ-GUESS for maize as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408647
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS maize

description: This is model output from LPJ-GUESS for maize as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408650
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS drybean

description: This is model output from LPJ-GUESS for drybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408652
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS cassava

description: This is model output from LPJ-GUESS for cassava as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408653
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS cassava

description: This is model output from LPJ-GUESS for cassava as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408654
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS barley

description: This is model output from LPJ-GUESS for barley as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408655
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS barley

description: This is model output from LPJ-GUESS for barley as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1409816
title: The Lsst Dark Energy Science Collaboration (Desc) Science Requirements Document V1 Released Data Products

description: This tarball includes software and data products associated with the DESC Science Requirements Document (SRD) v1.  See the "Executive Summary and User Guide" in the enclosed PDF of the DESC SRD for instructions on how to use and cite those products.  The DESC SRD is described on arXiv as follows:

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. The Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment.
DOI: 10.5517/ccdc.csd.cc1z6cyh
title: CCDC 1823387: Experimental Crystal Structure Determination

description: Related Article: Ming-Han Chung, Isaac Furay Yu, Yi-Hung Liu, Tien-Sung Lin, Shie-Ming Peng, Ching-Wen Chiu|2018|Inorg.Chem.|57|11732|doi:10.1021/acs.inorgchem.8b01865
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.cc1z6czj
title: CCDC 1823388: Experimental Crystal Structure Determination

description: Related Article: Ming-Han Chung, Isaac Furay Yu, Yi-Hung Liu, Tien-Sung Lin, Shie-Ming Peng, Ching-Wen Chiu|2018|Inorg.Chem.|57|11732|doi:10.1021/acs.inorgchem.8b01865
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: 10.7910/dvn/ojbz67/3z8yzh
title: 17723379_53_8367855_TP_0_VarLen_Trend4Hz_IHR.txt
DOI: 10.7910/dvn/ojbz67/5ql9xr
title: 17723370_55_1335324_TP_0_VarLen_Wave500Hz_Pleth.txt
DOI: 10.7910/dvn/ojbz67/7889lc
title: 17723379_53_8367855_TP_0_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/gt8bti
title: 17723378_52_18452735_TP_0_VarLen_Trend4Hz_IHR.txt
DOI: 10.7910/dvn/ojbz67/lo8bvu
title: 17723370_55_1335324_TP_0_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/pjwkvd
title: 17723378_52_18452735_TP_0_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/teij95
title: 17723378_52_18452735_TP_0_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/x1smqz
title: 17723378_52_18452735_TP_0_VarLen_Wave500Hz_ECG II.txt
DOI: 10.7910/dvn/ojbz67/xqn0ux
title: 17723370_55_1335324_TP_0_VarLen_Wave500Hz_ECG II.txt