cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2d3b3z
title: CCDC 2207730: Experimental Crystal Structure Determination

description: Related Article: María Murillo, Javier Álvarez-Conde, Reinhold Wannemacher, Juan Cabanillas-González, Javier González-Platas, Ulises R. Rodríguez-Mendoza, Akun Liang, Robin Turnbull, Daniel Errandonea, Jose Ignacio Martínez, Pilar Amo-Ochoa|2022|J.Mater.Chem.C|10|18004|doi:10.1039/D2TC04127H
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.cc2d3b40
title: CCDC 2207731: Experimental Crystal Structure Determination

description: Related Article: María Murillo, Javier Álvarez-Conde, Reinhold Wannemacher, Juan Cabanillas-González, Javier González-Platas, Ulises R. Rodríguez-Mendoza, Akun Liang, Robin Turnbull, Daniel Errandonea, Jose Ignacio Martínez, Pilar Amo-Ochoa|2022|J.Mater.Chem.C|10|18004|doi:10.1039/D2TC04127H
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.cc2d3b51
title: CCDC 2207732: Experimental Crystal Structure Determination

description: Related Article: María Murillo, Javier Álvarez-Conde, Reinhold Wannemacher, Juan Cabanillas-González, Javier González-Platas, Ulises R. Rodríguez-Mendoza, Akun Liang, Robin Turnbull, Daniel Errandonea, Jose Ignacio Martínez, Pilar Amo-Ochoa|2022|J.Mater.Chem.C|10|18004|doi:10.1039/D2TC04127H
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.cc2d3b62
title: CCDC 2207733: Experimental Crystal Structure Determination

description: Related Article: María Murillo, Javier Álvarez-Conde, Reinhold Wannemacher, Juan Cabanillas-González, Javier González-Platas, Ulises R. Rodríguez-Mendoza, Akun Liang, Robin Turnbull, Daniel Errandonea, Jose Ignacio Martínez, Pilar Amo-Ochoa|2022|J.Mater.Chem.C|10|18004|doi:10.1039/D2TC04127H
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.cc2d3b73
title: CCDC 2207734: Experimental Crystal Structure Determination

description: Related Article: María Murillo, Javier Álvarez-Conde, Reinhold Wannemacher, Juan Cabanillas-González, Javier González-Platas, Ulises R. Rodríguez-Mendoza, Akun Liang, Robin Turnbull, Daniel Errandonea, Jose Ignacio Martínez, Pilar Amo-Ochoa|2022|J.Mater.Chem.C|10|18004|doi:10.1039/D2TC04127H
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.cc2d3b84
title: CCDC 2207735: Experimental Crystal Structure Determination

description: Related Article: María Murillo, Javier Álvarez-Conde, Reinhold Wannemacher, Juan Cabanillas-González, Javier González-Platas, Ulises R. Rodríguez-Mendoza, Akun Liang, Robin Turnbull, Daniel Errandonea, Jose Ignacio Martínez, Pilar Amo-Ochoa|2022|J.Mater.Chem.C|10|18004|doi:10.1039/D2TC04127H
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.cc2d3b95
title: CCDC 2207736: Experimental Crystal Structure Determination

description: Related Article: María Murillo, Javier Álvarez-Conde, Reinhold Wannemacher, Juan Cabanillas-González, Javier González-Platas, Ulises R. Rodríguez-Mendoza, Akun Liang, Robin Turnbull, Daniel Errandonea, Jose Ignacio Martínez, Pilar Amo-Ochoa|2022|J.Mater.Chem.C|10|18004|doi:10.1039/D2TC04127H
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.cc2d3bb6
title: CCDC 2207737: Experimental Crystal Structure Determination

description: Related Article: María Murillo, Javier Álvarez-Conde, Reinhold Wannemacher, Juan Cabanillas-González, Javier González-Platas, Ulises R. Rodríguez-Mendoza, Akun Liang, Robin Turnbull, Daniel Errandonea, Jose Ignacio Martínez, Pilar Amo-Ochoa|2022|J.Mater.Chem.C|10|18004|doi:10.1039/D2TC04127H
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.cc2d3bc7
title: CCDC 2207738: Experimental Crystal Structure Determination

description: Related Article: María Murillo, Javier Álvarez-Conde, Reinhold Wannemacher, Juan Cabanillas-González, Javier González-Platas, Ulises R. Rodríguez-Mendoza, Akun Liang, Robin Turnbull, Daniel Errandonea, Jose Ignacio Martínez, Pilar Amo-Ochoa|2022|J.Mater.Chem.C|10|18004|doi:10.1039/D2TC04127H
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.7415763
title: Intranasal Insulin Treatment Alters Gene Expression Profile in the Hippocampus of Rats with Perinatal Iron Deficiency

description: Datasets for rat hippocampal RNAseq experiment.
DOI: 10.5281/zenodo.7415762
title: Intranasal Insulin Treatment Alters Gene Expression Profile in the Hippocampus of Rats with Perinatal Iron Deficiency

description: Datasets for rat hippocampal RNAseq experiment.
DOI: 10.5517/ccdc.csd.cc2d5q6j
title: CCDC 2210027: Experimental Crystal Structure Determination

description: Related Article: Sayak Gupta, Cassandra L. Ward, S. Sameera Perera, Conor T. Gowan, Timothy M. Dittrich, Matthew J. Allen, Shawn P. McElmurry, Jeremy J. Kodanko|2022|Inorg.Chem.|61|19492|doi:10.1021/acs.inorgchem.2c03441
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.cc2cpxjj
title: CCDC 2195808: Experimental Crystal Structure Determination

description: Related Article: Diana Temerova, Tai-Che Chou, Kristina S. Kisel, Toni Eskelinen, Niko Kinnunen, Janne Jänis, Antti J. Karttunen, Pi-Tai Chou, Igor O. Koshevoy|2022|Inorg.Chem.|61|19220|doi:10.1021/acs.inorgchem.2c02867
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.cc2d6bvt
title: CCDC 2210636: Experimental Crystal Structure Determination

description: Related Article: Xuezhen Si, Xuze Pan, Jintang Xue, Qingxia Yao, Xianqiang Huang, Wenzeng Duan, Yi Qiu, Jie Su, Minglei Cao, Jun Li|2022|RSC Advances|12|33501|doi:10.1039/D2RA06545B
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.cc2d74mf
title: CCDC 2211404: Experimental Crystal Structure Determination

description: Related Article: Marco T. Klein, Bernhard M. Krause, Jörg-Martin Neudörfl, Ronald Kühne, Hans-Günther Schmalz|2022|Org.Biomol.Chem.|20|9368|doi:10.1039/D2OB01857H
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: 10.6073/pasta/61d49b1acd05440ba795ca242bed80ee
title: Cascade project at North Temperate Lakes LTER - High-resolution spatial analysis of CASCADE lakes during experimental nutrient enrichment 2015 - 2016

description: This dataset contains high-resolution spatio-temporal water quality data from two experimental lakes during a whole-ecosystem experiment. Through gradual nutrient addition, we induced a cyanobacteria bloom in an experimental lake (Peter Lake) while leaving a nearby reference lake (Paul Lake) as a control. Peter and Paul Lakes (Gogebic county, MI USA), were sampled using the FLAMe platform (Crawford et al. 2015) multiple times during the summers of 2015 and 2016. In 2015 nutrient additions to Peter Lake began on 1 June, and ceased on 29 June, Paul Lake was left unmanipulated. In 2016 no nutrients were added to either lake. Measurements were taken using a YSI EXO2 probe and a Garmin echoMap 50s. Sensor- data were collected continuously at 1 Hz and linked via timestamp to create spatially explicit data for each lake. Crawford, J. T., L. C. Loken, N. J. Casson, C. Smith, A. G. Stone, and L. A. Winslow. 2015. High-speed limnology: Using advanced sensors to investigate spatial variability in biogeochemistry and hydrology. Environmental Science & Technology 49:442â€“450.
DOI: 10.18112/openneuro.ds004346.v1.0.2
title: FLUX: A pipeline for MEG analysis
DOI: 10.18119/n98s3b
title: 8. IXE-psoriasis-repressed transcriptomic node family HCT intersection network
DOI: 10.18119/n9j88j
title: 6. Plaque psoriasis-induced transcriptomic node family HCT intersection network
DOI: 10.18119/n9dk6n
title: 7. IXE-psoriasis-repressed ChIP-Seq node HCT intersection network
DOI: 10.18119/n9p31d
title: 5. Plaque psoriasis-induced ChIP-Seq node HCT intersection network
DOI: 10.25573/serc.21521601
title: Patapsco River Spring Water Temperatures 2021-2022

description: Hourly measures of water temperature were collected from February or early March to June in the Patapsco River using HOBO water temperature loggers (Onset Computer Corp, UA-002-08 or Pro V2 U22-001). All temperature data was set to a local standard time of GMT/UTC-5.
DOI: 10.25573/serc.21521601.v1
title: Patapsco River Spring Water Temperatures 2021-2022

description: Hourly measures of water temperature were collected from February or early March to June in the Patapsco River using HOBO water temperature loggers (Onset Computer Corp, UA-002-08 or Pro V2 U22-001). All temperature data was set to a local standard time of GMT/UTC-5.
DOI: 10.25573/serc.21521601.v2
title: Patapsco River Spring Water Temperatures 2021-2022

description: Hourly measures of water temperature were collected from February or early March to June in the Patapsco River using HOBO water temperature loggers (Onset Computer Corp, UA-002-08 or Pro V2 U22-001). All temperature data was set to a local standard time of GMT/UTC-5.
DOI: 10.6084/m9.figshare.21696941
title: mCPP9rfo

description: StrinViz inputs and outputs of m[9+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696941.v1
title: mCPP9rfo

description: StrinViz inputs and outputs of m[9+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696938
title: CPPa9rfo

description: StrinViz inputs and outputs of [9+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696935
title: CPP11_StrainViz

description: StrinViz inputs and outputs of [11+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696935.v1
title: CPP11_StrainViz

description: StrinViz inputs and outputs of [11+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696932
title: 4FCPPa11_StrainViz

description: StrinViz inputs and outputs of fluor[11+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696932.v1
title: 4FCPPa11_StrainViz

description: StrinViz inputs and outputs of fluor[11+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696878
title: CPPa9rfo.xyz

description: Initial geometry of [9+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696878.v1
title: CPPa9rfo.xyz

description: Initial geometry of [9+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696881
title: mCPP9rfo.xyz

description: Initial geometry of m[9+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696881.v1
title: mCPP9rfo.xyz

description: Initial geometry of m[9+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696869
title: CPP11.xyz

description: Initial geometry of [11+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696875
title: 4FCPPa11.xyz

description: Initial geometry of fluor[11+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.21696875.v1
title: 4FCPPa11.xyz

description: Initial geometry of fluor[11+1]CPP generated by Gaussian09 geometry optimization using B3LYP/6-31G(d,p) and "opt=rfo NoSymm" as keywords.
DOI: 10.6084/m9.figshare.12118575
title: Doubly Robust Estimation of Optimal Dosing Strategies

description: The goal of precision medicine is to tailor treatment strategies on an individual patient level. Although several estimation techniques have been developed for determining optimal treatment rules, the majority of methods focus on the case of a dichotomous treatment, an example being the dynamic weighted ordinary least squares regression approach of Wallace and Moodie. We propose an extension to the aforementioned framework to allow for a continuous treatment with the ultimate goal of estimating optimal dosing strategies. The proposed method is shown to be doubly robust against model misspecification whenever the implemented weights satisfy a particular balancing condition. A broad class of weight functions can be derived from the balancing condition, providing a flexible regression based estimation method in the context of adaptive treatment strategies for continuous valued treatments. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12118575.v4
title: Doubly Robust Estimation of Optimal Dosing Strategies

description: The goal of precision medicine is to tailor treatment strategies on an individual patient level. Although several estimation techniques have been developed for determining optimal treatment rules, the majority of methods focus on the case of a dichotomous treatment, an example being the dynamic weighted ordinary least squares regression approach of Wallace and Moodie. We propose an extension to the aforementioned framework to allow for a continuous treatment with the ultimate goal of estimating optimal dosing strategies. The proposed method is shown to be doubly robust against model misspecification whenever the implemented weights satisfy a particular balancing condition. A broad class of weight functions can be derived from the balancing condition, providing a flexible regression based estimation method in the context of adaptive treatment strategies for continuous valued treatments. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12118575.v3
title: Doubly Robust Estimation of Optimal Dosing Strategies

description: The goal of precision medicine is to tailor treatment strategies on an individual patient level. Although several estimation techniques have been developed for determining optimal treatment rules, the majority of methods focus on the case of a dichotomous treatment, an example being the dynamic weighted ordinary least squares regression approach of Wallace and Moodie. We propose an extension to the aforementioned framework to allow for a continuous treatment with the ultimate goal of estimating optimal dosing strategies. The proposed method is shown to be doubly robust against model misspecification whenever the implemented weights satisfy a particular balancing condition. A broad class of weight functions can be derived from the balancing condition, providing a flexible regression based estimation method in the context of adaptive treatment strategies for continuous valued treatments. Supplementary materials for this article are available online.
DOI: 10.12754/data-2022-0010
title: Ocean near-surface Chlorophyll-a concentration
DOI: 10.5281/zenodo.7415613
title: AIS data prepared by Statsat AS for April 2020

description: AIS data prepared and provided by Statsat AS (Norway) in the framework of the T-SAR project (<em>IKTPLUSS programme on reducing digital vulnerabilities, </em><strong>10 MNOK from the Research Council of Norway, Norway</strong>). The dataset contains AIS data (satellite + other) on a global coverage for 2020. There is one zip file and its name is the month (01 for January to 12 for December) ending with '.zip' and the zip file contains zipped Comma Separated Values (CSV) files; one per day. The CSV zipped files are named with the following convention: ais_YYYYMMDD.zip where YYYY is the year (here 2020), MM the month (01 to 12) and DD the day (01 to 31 depending on the month). For instance, ais_20200101.zip contains one single CSV file called ais_20200101.csv that corresponds to the 1st January 2020. The csv files have one header line: mmsi;lon;lat;date_time_utc;sog;cog;true_heading;nav_status;rot;message_nr;source where: <strong>mmii</strong> integer MMSI number of the vessel (AIS identifier). All records belonging to the same vessel will have the same identifier. <strong>lon</strong> float Geographical longitude (WGS84) between -180 to 180 <strong>lat</strong> float Geographical latitude (WGS84) between -90 to 90 <strong>date_time_utc</strong> datetime Date and Time (in UTC) when position was recorded by AIS. It is represented as: YYYY-MM-DD HH:MM:SS (for instance 2020-01-01 00:00:00). <strong>sog</strong> float Speed over ground (knots) <strong>cog</strong> float Course over ground (degrees) <strong>true_heading</strong> integer Heading (degrees) of the vessel's hull. A value of 511 indicates there is no heading data. <strong>nav_status</strong> integer Navigation status according to <strong>AIS Specification</strong> <strong>rot</strong> integer rate of turn <strong>message_nr</strong> integer message number <strong>source</strong> integer source is the source of AIS data ('g' for ground or 's' for satellite). One row in the CSV file corresponds to one message.
description: This dataset is not public and has been provided by Statsat AS (Norway). It has been used for developing new machine learning algorithms for detecting Intentional AIS Shutdown in Open Sea Maritime Surveillance in the framework of the T-SAR project (IKTPLUSS programme on reducing digital vulnerabilities, 10 MNOK from the Research Council of Norway, Norway) led by Simula Research Laboratory (Oslo, Norway).
DOI: 10.5281/zenodo.7415612
title: AIS data prepared by Statsat AS for April 2020

description: AIS data prepared and provided by Statsat AS (Norway) in the framework of the T-SAR project (<em>IKTPLUSS programme on reducing digital vulnerabilities, </em><strong>10 MNOK from the Research Council of Norway, Norway</strong>). The dataset contains AIS data (satellite + other) on a global coverage for 2020. There is one zip file and its name is the month (01 for January to 12 for December) ending with '.zip' and the zip file contains zipped Comma Separated Values (CSV) files; one per day. The CSV zipped files are named with the following convention: ais_YYYYMMDD.zip where YYYY is the year (here 2020), MM the month (01 to 12) and DD the day (01 to 31 depending on the month). For instance, ais_20200101.zip contains one single CSV file called ais_20200101.csv that corresponds to the 1st January 2020. The csv files have one header line: mmsi;lon;lat;date_time_utc;sog;cog;true_heading;nav_status;rot;message_nr;source where: <strong>mmii</strong> integer MMSI number of the vessel (AIS identifier). All records belonging to the same vessel will have the same identifier. <strong>lon</strong> float Geographical longitude (WGS84) between -180 to 180 <strong>lat</strong> float Geographical latitude (WGS84) between -90 to 90 <strong>date_time_utc</strong> datetime Date and Time (in UTC) when position was recorded by AIS. It is represented as: YYYY-MM-DD HH:MM:SS (for instance 2020-01-01 00:00:00). <strong>sog</strong> float Speed over ground (knots) <strong>cog</strong> float Course over ground (degrees) <strong>true_heading</strong> integer Heading (degrees) of the vessel's hull. A value of 511 indicates there is no heading data. <strong>nav_status</strong> integer Navigation status according to <strong>AIS Specification</strong> <strong>rot</strong> integer rate of turn <strong>message_nr</strong> integer message number <strong>source</strong> integer source is the source of AIS data ('g' for ground or 's' for satellite). One row in the CSV file corresponds to one message.
description: This dataset is not public and has been provided by Statsat AS (Norway). It has been used for developing new machine learning algorithms for detecting Intentional AIS Shutdown in Open Sea Maritime Surveillance in the framework of the T-SAR project (IKTPLUSS programme on reducing digital vulnerabilities, 10 MNOK from the Research Council of Norway, Norway) led by Simula Research Laboratory (Oslo, Norway).