cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.17009024.v1
title: Untitled ItemAge correlations with identified significantly altered measurements of adolescent PCOS and healthy couterparts in Spearman and p-value

description: Table
DOI: 10.6084/m9.figshare.17009027
title: Plant community data from a statewide survey of paired serpentine and non-serpentine soils in California, USA

description: Soils derived from ultramafic parent materials (hereafter serpentine) provide habitat for unique plant communities containing species with adaptations to the low nutrient levels, high magnesium: calcium ratios, and high metal content (Ni, Zn) that characterize serpentine. Plants on serpentine have long been studied in evolution and ecology, and plants adapted to serpentine contribute disproportionately to plant diversity in many parts of the world.In 2000-2003, serpentine plant communities were sampled at 107 locations representing the full range of occurrence of serpentine in California, USA, spanning large gradients in climate. In 2009-2010, plant communities were similarly sampled at 97 locations on nonserpentine soil, near to and paired with 97 of the serpentine sampling locations. (Some serpentine locations were revisited in 2009-2010 to assess the degree of change since 2000-2003, which was minimal.) At each serpentine or nonserpentine location, a north- and a south-facing 50 m x10 m plot were sampled. This design produced 97 “sites” each consisting of four “plots” (north-south exposure, serpentine-nonserpentine soil). All plots were initially visited &gt;3 times over 2 years to record plant diversity and cover, and a subset were revisited in 2014 to examine community change after a drought.The original question guiding the study was how plant diversity is shaped by the spatially patchy nature of the serpentine habitat. Subsequently, we investigated how climate drives plant diversity at multiple scales (within locations, between locations on the same and different soil types, and across entire regions) and at different levels of organization (taxonomic, functional, and phylogenetic).
DOI: 10.6084/m9.figshare.17009027.v1
title: Plant community data from a statewide survey of paired serpentine and non-serpentine soils in California, USA

description: Soils derived from ultramafic parent materials (hereafter serpentine) provide habitat for unique plant communities containing species with adaptations to the low nutrient levels, high magnesium: calcium ratios, and high metal content (Ni, Zn) that characterize serpentine. Plants on serpentine have long been studied in evolution and ecology, and plants adapted to serpentine contribute disproportionately to plant diversity in many parts of the world.In 2000-2003, serpentine plant communities were sampled at 107 locations representing the full range of occurrence of serpentine in California, USA, spanning large gradients in climate. In 2009-2010, plant communities were similarly sampled at 97 locations on nonserpentine soil, near to and paired with 97 of the serpentine sampling locations. (Some serpentine locations were revisited in 2009-2010 to assess the degree of change since 2000-2003, which was minimal.) At each serpentine or nonserpentine location, a north- and a south-facing 50 m x10 m plot were sampled. This design produced 97 “sites” each consisting of four “plots” (north-south exposure, serpentine-nonserpentine soil). All plots were initially visited &gt;3 times over 2 years to record plant diversity and cover, and a subset were revisited in 2014 to examine community change after a drought.The original question guiding the study was how plant diversity is shaped by the spatially patchy nature of the serpentine habitat. Subsequently, we investigated how climate drives plant diversity at multiple scales (within locations, between locations on the same and different soil types, and across entire regions) and at different levels of organization (taxonomic, functional, and phylogenetic).
DOI: 10.6084/m9.figshare.17009003.v3
title: CCTransformationExtraction.zip

description: CCTransformationExtraction is designed for extracting concept transforamtions from geo-analytical questions.
DOI: 10.6084/m9.figshare.17009042
title: sf86282.bw

description: Chip seq sf8628 K27m
DOI: 10.6084/m9.figshare.17009042.v1
title: sf86282.bw

description: Chip seq sf8628 K27m
DOI: 10.5281/zenodo.5634125
title: Sea or summit? Wild reindeer spatial responses to changing high-arctic winters

description: Data for the article “Sea or summit? Wild reindeer spatial responses to changing high-arctic winters” By ÅØ Pedersen, LT Beumer, R Aanes, BB Hansen The data set includes four files: A readme file describing the data files, and three data files accompanying the above publication. For further queries please contact Åshild Ø. Pedersen: Ashild.Pedersen@npolar.no
DOI: 10.5281/zenodo.5634124
title: Sea or summit? Wild reindeer spatial responses to changing high-arctic winters

description: Data for the article “Sea or summit? Wild reindeer spatial responses to changing high-arctic winters” By ÅØ Pedersen, LT Beumer, R Aanes, BB Hansen The data set includes four files: A readme file describing the data files, and three data files accompanying the above publication. For further queries please contact Åshild Ø. Pedersen: Ashild.Pedersen@npolar.no
DOI: 10.6084/m9.figshare.17009063.v1
title: anonymized dataset.xlsx

description: Esami Ematochimici Dataset
DOI: 10.6084/m9.figshare.17009063
title: anonymized dataset.xlsx

description: Esami Ematochimici Dataset
DOI: 10.5281/zenodo.5701329
title: Instances for Multi-Commodity Supply Vessel Planning Problem With Order Selection and Time Window Decisions

description: Instances for Multi-Commodity Supply Vessel Planning Problem With Order Selection and Time Window Decisions
DOI: 10.5281/zenodo.5701328
title: Instances for Multi-Commodity Supply Vessel Planning Problem With Order Selection and Time Window Decisions

description: Instances for Multi-Commodity Supply Vessel Planning Problem With Order Selection and Time Window Decisions
DOI: 10.5281/zenodo.5701333
title: Supplementary Table 1

description: Supplementary Table 1
DOI: 10.5281/zenodo.5701332
title: Supplementary Table 1

description: Supplementary Table 1
DOI: 10.3886/e118082v1-101500
title: Data and Code for: Business Cycle Anatomy

description: We propose a new strategy for dissecting the macroeconomic time series, provide a template for the business-cycle propagation mech- anism that best describes the data, and use its properties to ap- praise models of both the parsimonious and the medium-scale va- riety. Our findings support the existence of a main business-cycle driver but rule out the following candidates for this role: technology or other shocks that map to TFP movements; news about future productivity; and inflationary demand shocks of the textbook type. Models aimed at accommodating demand-driven cycles without a strict reliance on nominal rigidity appear promising.<br><br>
DOI: 10.6084/m9.figshare.17003545
title: Total surface shortwave flux distributions 1901-2017 in support of carbon cycle modelling: No stratospheric aerosols

description: This dataset offers 6-hourly distributions of the total downward shortwave flux over the period 1901-2017. Radiative transfer calculations are based on monthly-averaged distributions of tropospheric aerosol optical depth, and 6-hourly distributions of cloud fraction. Methods follow those described in the Methods section of Mercado et al. (doi:10.1038/nature07949, 2009), but with updated input datasets. This version of the dataset excludes the radiative effects of stratospheric aerosols.<br><br>The time series of speciated tropospheric aerosol optical depth is taken from the historical and RCP8.5 simulations by the HadGEM2-ES climate model (Bellouin et al., doi:10.1029/2011JD016074, 2011). To correct for biases in HadGEM2-ES, tropospheric aerosol optical depths are scaled over the whole period to match the global and monthly averages obtained over the period 2003-2017 by the CAMS Reanalysis of atmospheric composition (Inness et al., doi:10.5194/acp-19-3515-2019, 2019), which assimilates satellite retrievals of aerosol optical depth.<br><br>The time series of cloud fraction is obtained by scaling the 6-hourly distributions simulated in the Japanese Reanalysis (JRA; Kobayashi et al., doi:10.2151/jmsj.2015-001, 2015) to match the monthly-averaged cloud cover in the CRU TS v4.03 dataset (Harris et al. doi:10.1038/s41597-020-0453-3, 2020).<br><br>Surface radiative fluxes account for aerosol-radiation interactions from both tropospheric and stratospheric aerosols, and for aerosol-cloud interactions from tropospheric aerosols, except mineral dust. Tropospheric aerosols are also assumed to exert interactions with cloud. The radiative effects of those aerosol-cloud interactions are assumed to scale with the radiative effects of aerosol-radiation interactions of tropospheric aerosols, using regional scaling factors derived from HadGEM2-ES.<br><br>Atmospheric constituent other than aerosols and clouds are set to a constant standard mid-latitude summer atmosphere.
DOI: 10.6084/m9.figshare.17003545.v1
title: Total surface shortwave flux distributions 1901-2017 in support of carbon cycle modelling: No stratospheric aerosols

description: This dataset offers 6-hourly distributions of the total downward shortwave flux over the period 1901-2017. Radiative transfer calculations are based on monthly-averaged distributions of tropospheric aerosol optical depth, and 6-hourly distributions of cloud fraction. Methods follow those described in the Methods section of Mercado et al. (doi:10.1038/nature07949, 2009), but with updated input datasets. This version of the dataset excludes the radiative effects of stratospheric aerosols.<br><br>The time series of speciated tropospheric aerosol optical depth is taken from the historical and RCP8.5 simulations by the HadGEM2-ES climate model (Bellouin et al., doi:10.1029/2011JD016074, 2011). To correct for biases in HadGEM2-ES, tropospheric aerosol optical depths are scaled over the whole period to match the global and monthly averages obtained over the period 2003-2017 by the CAMS Reanalysis of atmospheric composition (Inness et al., doi:10.5194/acp-19-3515-2019, 2019), which assimilates satellite retrievals of aerosol optical depth.<br><br>The time series of cloud fraction is obtained by scaling the 6-hourly distributions simulated in the Japanese Reanalysis (JRA; Kobayashi et al., doi:10.2151/jmsj.2015-001, 2015) to match the monthly-averaged cloud cover in the CRU TS v4.03 dataset (Harris et al. doi:10.1038/s41597-020-0453-3, 2020).<br><br>Surface radiative fluxes account for aerosol-radiation interactions from both tropospheric and stratospheric aerosols, and for aerosol-cloud interactions from tropospheric aerosols, except mineral dust. Tropospheric aerosols are also assumed to exert interactions with cloud. The radiative effects of those aerosol-cloud interactions are assumed to scale with the radiative effects of aerosol-radiation interactions of tropospheric aerosols, using regional scaling factors derived from HadGEM2-ES.<br><br>Atmospheric constituent other than aerosols and clouds are set to a constant standard mid-latitude summer atmosphere.
DOI: 10.13012/b2idb-8967648_v1
title: Closed microbial communities self-organize to persistently cycle carbon -- 16S Sequencing data

description: Shared dataset consists of 16S sequencing data of microbial communities. Each community is composed of heterotrophic bacteria derived from one of two soil samples and the model algae Chlamydomonas reinhardtii. Each comunity was placed in a materially closed environment with an initial supply of carbon in the media and subjected to light-dark cycles. The closed microbial ecosystems (CES) survived via carbon cycling. Each CES was subjected to rounds of dilution, after which the community was sequenced (data provided here). The shared dataset allowed us to conclude that CES consistently self-assembled to cycle carbon (data not provided) via conserved metabolic capabilites (data not provided) dispite differences in taxonomic composition (data provided). --------------------------- Naming convention: [soil sample = A or B][CES replicate = 1,2,3, or 4]_[round number = 1,2,3,or 4]_[reverse read = R or forward read = F]_filt.fastq Example -- A1_r1_F_filt.fastq means soil sample A, CES replicate 1, end of round1, forward read
DOI: 10.6084/m9.figshare.17009003.v4
title: 12ewr

description: 12sdfwe
DOI: 10.5281/zenodo.5142180
title: Compendium of examples: good practice in evaluating measurement uncertainty

description: This document illustrates good practice in the evaluation of measurement uncertainty. It contains examples from a variety of areas in calibration and testing, and illustrates the use of the methods from the “Guide to the expression of Uncertainty in Measurement” and its supplements, as well as Bayesian approaches. Compendium_M36.pdf: document
DOI: 10.5281/zenodo.4282088
title: Compendium of examples: good practice in evaluating measurement uncertainty

description: This document illustrates good practice in the evaluation of measurement uncertainty. It contains examples from a variety of areas in calibration and testing, and illustrates the use of the methods from the “Guide to the expression of Uncertainty in Measurement” and its supplements, as well as Bayesian approaches. Compendium_M36.pdf: document
DOI: 10.6084/m9.figshare.12755876
title: Supplementary data of Savannas of the Brazilian semiarid region: what do we learn from floristics?

description: <b>Supplementary data 1:</b> Raunkiaer life-forms percentage in sites used in NMS analyse.<br><b>Supplementary data 2:</b> Number of woody and non-woody species in sites used in the UPGMA analyse.<br>
DOI: 10.6084/m9.figshare.12755876.v1
title: Supplementary data of Savannas of the Brazilian semiarid region: what do we learn from floristics?

description: <b>Supplementary data 1:</b> Raunkiaer life-forms percentage in sites used in NMS analyse.<br><b>Supplementary data 2:</b> Number of woody and non-woody species in sites used in the UPGMA analyse.<br>
DOI: 10.5281/zenodo.5701320
title: FW306_01

description: Reads, assembly and bins for FW306_01
DOI: 10.5281/zenodo.5701319
title: FW306_01

description: Reads, assembly and bins for FW306_01
DOI: 10.5281/zenodo.5188961
title: Subtle alterations in neonatal neurodevelopment following early or late exposure to prenatal maternal immune activation

description: Structural MRI
DOI: 10.5281/zenodo.5188960
title: Subtle alterations in neonatal neurodevelopment following early or late exposure to prenatal maternal immune activation

description: Structural MRI
DOI: 10.6084/m9.figshare.3761562.v2042
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5281/zenodo.5701412
title: Sabuloglossum arenarium SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5701411
title: Sabuloglossum arenarium SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5701424
title: League of Legends' Champion Statistics by server. End Season 11.

description: This dataset contains the statistic data related to each League of Legends champion's profile of the op.gg webpage. It contains data related to every champion within the last month of ranked season 11. It has been created only for educational purposes with a web scraper based on scrapy.
description: This dataset has been generated during the development of homework within the frame of the Master in Data Science of the UOC.
DOI: 10.5281/zenodo.5701423
title: League of Legends' Champion Statistics by server. End Season 11.

description: This dataset contains the statistic data related to each League of Legends champion's profile of the op.gg webpage. It contains data related to every champion within the last month of ranked season 11. It has been created only for educational purposes with a web scraper based on scrapy.
description: This dataset has been generated during the development of homework within the frame of the Master in Data Science of the UOC.
DOI: 10.5281/zenodo.5701433
title: Channel Estimation and Performance Analysis of SISO Molecular Communications

description: This file is to support the claim marked by footnote #2.
DOI: 10.5281/zenodo.5701440
title: Diagonal Example Dataset - DiRo2C

description: The two datasets are used to simulate two different black boxes that are supposed to predict different results in certain data areas. Dataset diro2c_diagonal_example_dataset.csv: Two-dimensional dataset with the continuous features x1 and x2. It contains 300 instances with the following properties: min = -126.19, max = 362.16, µ = 139.14, and σ = 77.79 for feature x1 and min = -429.45, max = 265.10, µ = 9.98, and σ = 157.80 for feature x2. The instances of the datasets are classified into two classes “0” and “1”. The instances are generated by the sklearn “make_classification” function with the following parameters: make_classification(n_samples = 300, n_features = 2, n_informative = 2, n_redundant = 0, n_clusters_per_class = 1, class_sep = 1.3, random_state = 0, flip_y = 0, scale = 100). Dataset diro2c_diagonal_example_manipulated_dataset.csv: This dataset is manipulated on the basis of the first dataset as follows: (x1 &lt; 100 : y = 0), (x1 &gt;= 100 : y = 1)
DOI: 10.5281/zenodo.5701439
title: Diagonal Example Dataset - DiRo2C

description: The two datasets are used to simulate two different black boxes that are supposed to predict different results in certain data areas. Dataset diro2c_diagonal_example_dataset.csv: Two-dimensional dataset with the continuous features x1 and x2. It contains 300 instances with the following properties: min = -126.19, max = 362.16, µ = 139.14, and σ = 77.79 for feature x1 and min = -429.45, max = 265.10, µ = 9.98, and σ = 157.80 for feature x2. The instances of the datasets are classified into two classes “0” and “1”. The instances are generated by the sklearn “make_classification” function with the following parameters: make_classification(n_samples = 300, n_features = 2, n_informative = 2, n_redundant = 0, n_clusters_per_class = 1, class_sep = 1.3, random_state = 0, flip_y = 0, scale = 100). Dataset diro2c_diagonal_example_manipulated_dataset.csv: This dataset is manipulated on the basis of the first dataset as follows: (x1 &lt; 100 : y = 0), (x1 &gt;= 100 : y = 1)
DOI: 10.5281/zenodo.5701393
title: FW306_02

description: Reads, assembly and bins for FW306_02
DOI: 10.5281/zenodo.5701392
title: FW306_02

description: Reads, assembly and bins for FW306_02
DOI: 10.5063/f1nk3cfq
title: A GBIF endangered species diversity analysis of burn sites in the Southwestern, USA

description: The purpose of this dataset is to evaluate the impact of fires on endangered species biodiversity in California's southwest desert. Species data was downloaded from the Global Diversity Information Facility (GBIF).
DOI: 10.18112/openneuro.ds003885.v1.0.4
title: Capacity for movement is a major organisational principle in object representations: EEG data from Experiment 2
DOI: 10.5281/zenodo.5701474
title: VIPER Test Image HeLa

description: 3000 x 3000 px test images for the VIPER pipeline
DOI: 10.5281/zenodo.5701473
title: VIPER Test Image HeLa

description: 3000 x 3000 px test images for the VIPER pipeline
DOI: 10.5281/zenodo.5701464
title: Dataset associated with Gullin et al.

description: This data is provide to reproduce the figures of Gullin et al. (arXiv:2109.13242). Please use the GitHub repository located at https://github.com/evanoconnor/NeutrinoEchos and place this tar file in the data directory. Then tar -xf gullinetal_dataset.tar and tar -zxf GR1D_output_files.tar.gz the untarred, unzipped dataset is roughly 3GB
description: {"references": ["Gullin et al., software associated with arXiv:2109.13242"]}
DOI: 10.5281/zenodo.5701463
title: Dataset associated with Gullin et al.

description: This data is provide to reproduce the figures of Gullin et al. (arXiv:2109.13242). Please use the GitHub repository located at https://github.com/evanoconnor/NeutrinoEchos and place this tar file in the data directory. Then tar -xf gullinetal_dataset.tar and tar -zxf GR1D_output_files.tar.gz the untarred, unzipped dataset is roughly 3GB
description: {"references": ["Gullin et al., software associated with arXiv:2109.13242"]}
DOI: 10.25959/91sf-t535
title: Author publications per year

description: This dataset contains two samples - one for authors publishing in multidisciplinary journals in 2020 (Nature, Science, PNAS) and one publishing in a list of disciplinary journals in 2020
DOI: 10.6084/m9.figshare.16902778
title: Influence of physical parameters and bisphosphonate therapy on serum sclerostin levels in pediatric osteogenesis imperfecta patients

description: This study aimed to reveal the relationship between serum sclerostin levels and clinical parameters in children with osteogenesis imperfecta. These data were supplemental data, including Correlations of serum sclerostin values with continuous variable parameters in pediatric OI patients (Suppl data 1), Correlation of each nominal variables and serum sclerostin values in each clinical type (I or III/IV) (Suppl data 2), Correlation of each continuous variables and serum sclerostin values in each clinical type (I or III/IV) (Suppl data 3), Correlation of each nominal variables and serum sclerostin values in each patient group with or without BP treatment (Suppl data 4), Correlation of each continuous variables and serum sclerostin values in each patient group with or without BP treatment (Suppl data 5), and Changes in the serum sclerostin levels and parameters in the patients without bisphosphonate treatment at the first measurement, induced the treatment at that date, and followed again after at least one year (Suppl data 6).
DOI: 10.6084/m9.figshare.16902778.v1
title: Influence of physical parameters and bisphosphonate therapy on serum sclerostin levels in pediatric osteogenesis imperfecta patients

description: This study aimed to reveal the relationship between serum sclerostin levels and clinical parameters in children with osteogenesis imperfecta. These data were supplemental data, including Correlations of serum sclerostin values with continuous variable parameters in pediatric OI patients (Suppl data 1), Correlation of each nominal variables and serum sclerostin values in each clinical type (I or III/IV) (Suppl data 2), Correlation of each continuous variables and serum sclerostin values in each clinical type (I or III/IV) (Suppl data 3), Correlation of each nominal variables and serum sclerostin values in each patient group with or without BP treatment (Suppl data 4), Correlation of each continuous variables and serum sclerostin values in each patient group with or without BP treatment (Suppl data 5), and Changes in the serum sclerostin levels and parameters in the patients without bisphosphonate treatment at the first measurement, induced the treatment at that date, and followed again after at least one year (Suppl data 6).
DOI: 10.17632/xfb43nvwfc.1
title: Cross-district inequality and sectoral employment share of Indonesia 1990s-2000s

description: This dataset is arguably unique in at least two counts. First, for Indonesia, this is the first dataset of employment share by economic sectors covering districts (finer than provinces) and spanning from 1990s toward the end of 2000s. Second, it encompasses the period before and after significant multidimensional structural breaks in Indonesia during the Asian Financial Crisis (AFC) in 1997-1999, involving major shifts in Indonesia’s political institutions and economic development.