cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15131/shef.data.24573370.v1
title: Data on Pulmonary Arterial Hypertension supporting the paper titled "Individualised Survival Predictions using State Space Model with Longitudinal and Survival Data".

description: Training and testing data sets for longitudinal and survival analysis on pulmonary hypertension including baseline information and the longitudinal walking distance from exercise tests. For method, reader is referred to: https://github.com/mcauchi1/LSDSMData is extracted from the ASPIRE registry. The ASPIRE registry is an ethically approved research database managed by Sheffield Teaching Hospitals NHS Foundation Trust (STH14169, REC 22/EE/0011).Data consists of an exerpt of the exercise tests routinely performed by patients at the Pulmonary Vascular Disease Unit in Sheffield.Data columns are:id - Patient IDEvTime - Event Time (in months)event - Event (Binary variable indicating event happened or not)time - Time at which measurement is taken (in months)dx - Diagnosis of PH groupbaseAge - Age at BaselineisMale - Binary variable indicating male or femalewhoFC3-4 - Binary variable indicating the classification WHO Functional Class III/IV (or I/II)y - Measurement value (walking distance in metres)Training data consists of 773 unique patients while testing data consists of 332 unique patients.
DOI: 10.5517/ccdc.csd.cc204j7y
title: CCDC 1851389: Experimental Crystal Structure Determination

description: Related Article: Terrance J. Hadlington, Tibor Szilvási, Matthias Driess|2018|Chem.Commun.|54|9352|doi:10.1039/C8CC05238G
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.cc204j8z
title: CCDC 1851390: Experimental Crystal Structure Determination

description: Related Article: Terrance J. Hadlington, Tibor Szilvási, Matthias Driess|2018|Chem.Commun.|54|9352|doi:10.1039/C8CC05238G
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.cc204y9f
title: CCDC 1851794: Experimental Crystal Structure Determination

description: Related Article: Etienne A. LaPierre, Warren E. Piers, Chris Gendy|2018|Organometallics|37|3394|doi:10.1021/acs.organomet.8b00440
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.cc202r0w
title: CCDC 1849677: Experimental Crystal Structure Determination

description: Related Article: Ipsita Chatterjee,  Mou Chakraborty,  Pradip Ghosh,  and Sreebrata Goswami|2018|J.Indian Chem.Soc.|95|771|
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.cc2066t8
title: CCDC 1853019: Experimental Crystal Structure Determination

description: Related Article: Dawei Xiao, Loi H. Do|2018|Organometallics|37|3079|doi:10.1021/acs.organomet.8b00454
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.cc2076gy
title: CCDC 1853969: Experimental Crystal Structure Determination

description: Related Article: Ömer Yurdakul, Zarife Sibel Şahin, Dursun Ali Köse, Onur Şahin, Fatih Akkurt|2020|J.Mol.Struct.|1218|128514|doi:10.1016/j.molstruc.2020.128514
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.cc209zkw
title: CCDC 1856638: Experimental Crystal Structure Determination

description: Related Article: Casper M. Macaulay, Takahiko Ogawa, Robert McDonald, Orson L. Sydora, Mark Stradiotto, Laura Turculet|2019|Dalton Trans.|48|9581|doi:10.1039/C8DT04221G
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.cc20c9yn
title: CCDC 1857921: Experimental Crystal Structure Determination

description: Related Article: Yoshifumi Hashikawa, Shota Hasegawa, Yasujiro Murata|2018|Chem.Commun.|54|13686|doi:10.1039/C8CC07339B
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.cc209zlx
title: CCDC 1856639: Experimental Crystal Structure Determination

description: Related Article: Casper M. Macaulay, Takahiko Ogawa, Robert McDonald, Orson L. Sydora, Mark Stradiotto, Laura Turculet|2019|Dalton Trans.|48|9581|doi:10.1039/C8DT04221G
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: 10.15468/dl.3w7hps
title: Occurrence Download

description: A dataset containing 21169 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "TaxonKey is Squamata",
 "TaxonKey is Crocodylia",
 "TaxonKey is Testudines",
 "TaxonKey is Sphenodontia",
 "TaxonKey is Amphibia"
 ]
 },
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "and" : [
 "DecimalLongitude is greater than 19.6365261",
 "DecimalLongitude is less than 24.945313",
 "DecimalLatitude is greater than 34.8034706",
 "DecimalLatitude is less than 41.5665398",
 "Country is Greece"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 21169 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036687-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mn4v8z
title: Occurrence Download

description: A dataset containing 2268 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-65.29725 -19.06857, -65.22695 -19.06857, -65.22695 -19.00247, -65.29725 -19.00247, -65.29725 -19.06857))",
 "Year is greater than or equal to 2010",
 "HasGeospatialIssue is false",
 "TaxonKey is Aves",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 2268 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036688-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/icpsr23764.v1
title: Federal Justice Statistics Program: Guideline Computations for Defendants Sentenced Under the Sentencing Reform Act, 1999 [United States]
title: Version 1
DOI: 10.3886/icpsr23764.v2
title: Federal Justice Statistics Program: Guideline Computations for Defendants Sentenced Under the Sentencing Reform Act, 1999 [United States]
title: Version 2

description: These data contain records of guideline computations and adjustments for each count of conviction for criminal defendants who were sentenced pursuant to provisions of the Sentencing Reform Act (SRA) of 1984 and reported to the United States Sentencing Commission (USSC) during fiscal year 1999. The data are one of two supplementary files that should be used in conjunction with the primary analysis file, which contains records for all defendants sentenced under the guidelines. These data can be linked to the primary analysis file using the unique identifier variable USSCIDN. The number of records for a defendant in the current data corresponds to the total number of guideline computations, which may or may not equal the total counts of conviction for that defendant, dependent upon the grouping rules of the particular guideline in question (see Section 3D1.2 of the guidelines manual). As an example, a defendant with five counts of drug trafficking will only have one guideline computation because each of the drug weights for each count are simply added together and only one calculation is necessary. However, if a defendant has five counts of bank robbery, he or she will have five separate guideline computations because bank robbery is considered to be a nongroupable offense. The data were obtained from the United States Sentencing Commission's Office of Policy Analysis' (OPA) Standardized Research Data File. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.
description: Datasets: DS1: Federal Justice Statistics Program: Guideline Computations for Defendants Sentenced Under the Sentencing Reform Act, 1999 [United States]
description: Defendants sentenced pursuant to provisions of the Sentencing Reform Act (SRA) of 1984 and reported to the United States Sentencing Commission during fiscal year 1999.
DOI: 10.15468/dl.f2vuaj
title: Occurrence Download

description: A dataset containing 3834 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-70.79231 -34.21429, -70.67555 -34.21429, -70.67555 -34.11869, -70.79231 -34.11869, -70.79231 -34.21429))",
 "Year is greater than or equal to 2010",
 "HasGeospatialIssue is false",
 "TaxonKey is Aves",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 3834 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036689-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15131/shef.data.24785883
title: Exploring physical and digital architectures in magnetic nanoring array reservoir computers

description: Physical reservoir computing (RC) is a machine learning technique that is ideal for processing of time dependent data series. It is also uniquely well- aligned to in materio computing realisations that allow the inherent memory and non-linear responses of functional materials to be directly exploited for computation. We have previously shown that square arrays of interconnected magnetic nanorings are attractive candidates for in materio reservoir computing, and experimentally demonstrated their strong performance in a range of benchmark tasks. Here, we extend these studies to other lattice arrangements of rings, including trigonal and Kagome grids, to explore how these affect both the magnetic behaviours of the arrays, and their computational properties. We show that while lattice geometry substantially affects the microstate behaviour of the arrays, these differences manifest less profoundly when averaging magnetic behaviour across the arrays. Consequently the computational properties (as measured using task agnostic metrics) of devices with a single electrical readout are found to be only subtly different, with the approach used to time-multiplex data into and out of the arrays having a stronger effect on properties than the lattice geometry. However, we also find that hybrid reservoirs that combine the outputs from arrays with different lattice geometries show enhanced computational properties compared to any single array.
DOI: 10.15131/shef.data.24785883.v1
title: Exploring physical and digital architectures in magnetic nanoring array reservoir computers

description: Physical reservoir computing (RC) is a machine learning technique that is ideal for processing of time dependent data series. It is also uniquely well- aligned to in materio computing realisations that allow the inherent memory and non-linear responses of functional materials to be directly exploited for computation. We have previously shown that square arrays of interconnected magnetic nanorings are attractive candidates for in materio reservoir computing, and experimentally demonstrated their strong performance in a range of benchmark tasks. Here, we extend these studies to other lattice arrangements of rings, including trigonal and Kagome grids, to explore how these affect both the magnetic behaviours of the arrays, and their computational properties. We show that while lattice geometry substantially affects the microstate behaviour of the arrays, these differences manifest less profoundly when averaging magnetic behaviour across the arrays. Consequently the computational properties (as measured using task agnostic metrics) of devices with a single electrical readout are found to be only subtly different, with the approach used to time-multiplex data into and out of the arrays having a stronger effect on properties than the lattice geometry. However, we also find that hybrid reservoirs that combine the outputs from arrays with different lattice geometries show enhanced computational properties compared to any single array.
DOI: 10.15468/dl.c9vf46
title: Occurrence Download

description: A dataset containing 6604 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingCountry is Luxembourg",
 "TaxonKey is Artiodactyla"
 ]
}

 The dataset includes 6604 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036690-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13868917
title: AURORA Energy Tracker App

description: The Excel document contains the algorithm of the AURORA Energy Tracker app. Each of the sheets of the document corresponds to each of the 27 EU member states. This document serves as a calculator of CO2 emissions and energy consumption by entering the data in the corresponding cells. The last version corresponds to April 2024.
DOI: 10.5281/zenodo.13868918
title: AURORA Energy Tracker App

description: The Excel document contains the algorithm of the AURORA Energy Tracker app. Each of the sheets of the document corresponds to each of the 27 EU member states. This document serves as a calculator of CO2 emissions and energy consumption by entering the data in the corresponding cells. The last version corresponds to April 2024.
DOI: 10.6084/m9.figshare.27144360
title: ARRIVE checklist for A reference genome for the eastern bettong (<i>Bettongia gaimardi</i>)

description: The eastern or Tasmanian bettong (<i>Bettongia gaimardi</i>) is one of four extant bettong species and is listed as ‘Near Threatened’ by the IUCN. We sequenced short read data on the 10x system to generate a reference genome 3.46Gb in size and contig N50 of 87.36Kb. Additionally, we used GeMoMa to provide and accompanying annotation for the reference genome. The generation of a reference genome for the eastern bettong provides a vital resource for the conservation of the species.
DOI: 10.6084/m9.figshare.27144360.v1
title: ARRIVE checklist for A reference genome for the eastern bettong (<i>Bettongia gaimardi</i>)

description: The eastern or Tasmanian bettong (<i>Bettongia gaimardi</i>) is one of four extant bettong species and is listed as ‘Near Threatened’ by the IUCN. We sequenced short read data on the 10x system to generate a reference genome 3.46Gb in size and contig N50 of 87.36Kb. Additionally, we used GeMoMa to provide and accompanying annotation for the reference genome. The generation of a reference genome for the eastern bettong provides a vital resource for the conservation of the species.
DOI: 10.15468/mqjqwt
title: Colección de Helechos y grupos emparentados del Herbario LIL (FML-Tucumán)

description: Plantas de las Familia Salviniaceae Martinov, perteneciente al género Azolla Lam, colectadas en Argentina, Perú, Uruguay y Honduras. Los coleccionistas fueron diversos, entre los que se encuentran Miguel Lillo, Castillón, T. Meyer, S. Venturi y Castellanos, entre los años 1885-1958. Los especímenes corresponden a Argentina, Bolivia, Uruguay, Perú y Honduras. La colección es curada actualmente por la Dra. Marcela A. Hernández en el Herbario Criptogámico de la Fundación Miguel Lillo
DOI: 10.5281/zenodo.13866980
title: GEOLAB - Transnational Access project SHARP - Soil Heterogeneity for soil Amelioration in Road Projects

description: The SHARP - Soil Heterogeneity for soil Amelioration in Road Projects experiment proposes a novel approach to subgrade improvement: the strategic placement of gravel or other recycled aggregates in a layered configuration. This methodology aims to achieve a sufficient enhancement of the subgrade's mechanical properties, potentially eliminating the need for more resource-intensive and environmentally impactful techniques. The current research phase focuses on the evaluation of performance improvement in silt through the introduction of gravel layers via large-scale triaxial testing. Numerical simulations have already yielded promising results, highlighting the potential of this approach. However, the inherent size disparity between gravel and silt particles necessitates the use of large-scale testing equipment to accurately capture their composite behavior and avoid scale issues. Conventional triaxial equipment, typically limited to 10 cm diameter specimens, is inadequate for this purpose. The utilization of a large-scale triaxial apparatus facilitates the acquisition of reliable data directly applicable to real-world road and railway construction practices.

The traditional Terzaghi method for analyzing consolidation (settling) in soils is not accurate for layered soils with different compressibility characteristics. This is a well-established fact (Schiffman & Stein, 1970; Lee et al., 1992). Previous research (Huang & Griffiths, 2010) has also shown that using the Terzaghi method for layered soils in finite element modeling can lead to inaccurate results due to issues with flow continuity at the interfaces between layers. This highlights the importance of studying consolidation in layered soils, both for practical reasons (ensuring the proposed solution is viable) and to gain a deeper theoretical understanding (the heterogeneity effect on consolidating silty soil).

While numerical simulations have suggested that adding gravel layers to silty soil can significantly improve slope stability (Bossi et al., 2016), this needs experimental validation. Smaller lab specimens are not suitable due to the size difference between gravel and silt.

The test performed within the SHARP project aimed to investigate the effectiveness of a "patchy" gravel-in-silt mix on volumetric changes and shear strength. This approach aims to be practical for construction crews by allowing the gravel to be spread in lenses within the existing subgrade. This would simplify construction and ensure a minimum level of performance for the improved subgrade.

Ultimately, the goal is to use the data from these tests to assess the validity of using an "average friction angle" approach (Elkateb, 2003) for layered soils, considering the impact of the spatial distribution of the gravel layers. Numerical modeling can help answer these questions, but data for validation are necessary.