cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48372/7432a8c0-8e29-4a77-a1c0-f4b0cc87f626
title: Benthic macroinvertebrate communities data of the Mediterranean and Black Sea lagoons.

description: The dataset contains occurence data for 184 macroinvertebrate communities in Mediterranean and Black Sea transitional water ecosystems. Dataset includes a species list, obtained by species lists reported in published papers or books (89.24%) and grey literature or unpublished data collected by the authors (10.76%). It includes data on 1721 macroinvertebrate species.
DOI: 10.25721/6twv-1f58
title: Bourrée
DOI: 10.5281/zenodo.5705449
title: Datasets for the Carpentry-style RNA-seq lesson

description: <strong>Lesson files</strong> File descriptions:<br> - <strong>counts.txt</strong>: a dataframe of the sample raw counts. It is a tab separated file therefore data are in tabulated separated columns.<br> - <strong>experimental_design_modified.txt</strong> dataframe indicates the correspondence between samples and experimental conditions (e.g. control, treated). <br> - <strong>differential_genes.tsv</strong> dataframe contains the result of the DESeq2 analysis. The counts.txt file was obtained by running the `v0.1.1` version of a RNA-Seq bioinformatic pipeline on the mRNA-Seq sequencing files from Vogel et al. (2016): https://www.ebi.ac.uk/ena/data/view/PRJEB13938. Please read the original study (Vogel et al. 2016): https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.14036 ==== <strong>Project files</strong> The NASA GeneLab experiment GLDS-38 performed transcriptomics and proteomics of Arabidopsis seedlings in microgravity by sending seedlings to the International Space Station (ISS). The raw counts, scaled counts and sample to conditions files are available in the ZIP archive
DOI: 10.15468/u7z9fj
title: Monotypic no more: A new species of the unusual genus Mayagueza Wheeler, 1960 from the Neotropical region (Diptera: Drosophilidae: Steganinae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Costa, Sávio Cunha, Pirani, Gabriela, Oliveira, Sarah Siqueira (2021): Monotypic no more: A new species of the unusual genus Mayagueza Wheeler, 1960 from the Neotropical region (Diptera: Drosophilidae: Steganinae). Zootaxa 5068 (2): 287-294, DOI: https://doi.org/10.11646/zootaxa.5068.2.8
DOI: 10.25721/azcc-cw75
title: Valse
DOI: 10.25721/97ne-jf29
title: Le Turlututu
DOI: 10.25721/9rz3-9r69
title: Valse
DOI: 10.15468/5f8nts
title: New and little-known bees of the genus Sphecodes Latreille, 1804 (Hymenoptera: Apoidea: Halictidae) from the Himalayas

description: This dataset contains the digitized treatments in Plazi based on the original journal article Astafurova, Yulia, Proshchalykin, Maxim (2020): New and little-known bees of the genus Sphecodes Latreille, 1804 (Hymenoptera: Apoidea: Halictidae) from the Himalayas. European Journal of Taxonomy 729: 74-120, DOI: https://doi.org/10.5852/ejt.2020.729.1195
DOI: 10.18434/mds2-2361
title: Process and robot data from a two robot workcell representative performing representative manufacturing operations.
DOI: 10.5281/zenodo.5705506
title: msd-errors - Data for the LLZO figure

description: Data for the figure showing the diffusion and Arrhenius plots for a short simulation of LLZO. <br><br>Created using showyourwork from this GitHub repo.
DOI: 10.5281/zenodo.5705507
title: msd-errors - Data for AgCrSe2 figures

description: Data for the figures Results of the analysis of AgCrSe2 systems by kinisi at a series of temperatures.<br><br>Created using showyourwork from this GitHub repo.
DOI: 10.5517/ccdc.csd.cc27wr85
title: CCDC 2082247: Experimental Crystal Structure Determination

description: Related Article: kaibo zheng|2021|CSD Communication|||
description: Related Article: Kaibo Zheng, Hui Chen, Yufeng Xiao, Xiang Liu, Jiaying Yan, Nuonuo Zhang|2021|Chem.-Eur.J.|27|14964|doi:10.1002/chem.202102578
DOI: 10.5517/ccdc.csd.cc2816g0
title: CCDC 2086531: Experimental Crystal Structure Determination

description: Related Article: Mengyang Shen, Jie Zhao, Yuanshuang Xu, Xinying Zhang, Xuesen Fan|2021|J.Org.Chem.|86|15203|doi:10.1021/acs.joc.1c01814
DOI: 10.5517/ccdc.csd.cc282qz2
title: CCDC 2088004: Experimental Crystal Structure Determination

description: Related Article: Youhei Miura, Kazuki Murai, Kazufumi Yamada, Naoki Yoshioka|2021|Bull.Chem.Soc.Jpn.|94|2444|doi:10.1246/bcsj.20210247
DOI: 10.5517/ccdc.csd.cc282r04
title: CCDC 2088005: Experimental Crystal Structure Determination

description: Related Article: Youhei Miura, Kazuki Murai, Kazufumi Yamada, Naoki Yoshioka|2021|Bull.Chem.Soc.Jpn.|94|2444|doi:10.1246/bcsj.20210247
DOI: 10.5517/ccdc.csd.cc2844h2
title: CCDC 2089353: Experimental Crystal Structure Determination

description: Related Article: Ye-Cheng Wang, Chengsen Cui, Mingji Dai|2021|Angew.Chem.,Int.Ed.|60|24828|doi:10.1002/anie.202109625
DOI: 10.5517/ccdc.csd.cc2846yl
title: CCDC 2089429: Experimental Crystal Structure Determination

description: Related Article: Yi-Fang Huang, Lin Xiang, Yan Feng, Zhen An, Le-Ping Miao, Jian-Rong Li, Heng-Yun Ye, Chao Shi|2021|Eur.J.Inorg.Chem.|2021|4439|doi:10.1002/ejic.202100624
DOI: 10.5517/ccdc.csd.cc2846zm
title: CCDC 2089430: Experimental Crystal Structure Determination

description: Related Article: Yi-Fang Huang, Lin Xiang, Yan Feng, Zhen An, Le-Ping Miao, Jian-Rong Li, Heng-Yun Ye, Chao Shi|2021|Eur.J.Inorg.Chem.|2021|4439|doi:10.1002/ejic.202100624
DOI: 10.5517/ccdc.csd.cc28470p
title: CCDC 2089431: Experimental Crystal Structure Determination

description: Related Article: Yi-Fang Huang, Lin Xiang, Yan Feng, Zhen An, Le-Ping Miao, Jian-Rong Li, Heng-Yun Ye, Chao Shi|2021|Eur.J.Inorg.Chem.|2021|4439|doi:10.1002/ejic.202100624
DOI: 10.5517/ccdc.csd.cc286qks
title: CCDC 2091835: Experimental Crystal Structure Determination

description: Related Article: Qing Mao, Qian Zhao, Mu-Ze Li, Rui Qin, Meng-Lan Luo, Jing Xue, Ben-Hong Chen, Hai-Jun Leng, Cheng Peng, Gu Zhan, Bo Han|2021|J.Org.Chem.|86|14844|doi:10.1021/acs.joc.1c01631
DOI: 10.5517/ccdc.csd.cc286qlt
title: CCDC 2091836: Experimental Crystal Structure Determination

description: Related Article: Qing Mao, Qian Zhao, Mu-Ze Li, Rui Qin, Meng-Lan Luo, Jing Xue, Ben-Hong Chen, Hai-Jun Leng, Cheng Peng, Gu Zhan, Bo Han|2021|J.Org.Chem.|86|14844|doi:10.1021/acs.joc.1c01631
DOI: 10.5281/zenodo.5705510
title: msd-errors - Data for variance and covariance figure

description: Data for a figure that presents the variance and covariance for a true random walk. There is a comparison shown between the numerical result from 1024 unique random walks and the analysis, by kinisi, of the same 1024 random walks.<br><br>Created using showyourwork from this GitHub repo.
DOI: 10.18434/m31827
title: STEP File Analyzer and Viewer Software
DOI: 10.5281/zenodo.5705401
title: autocasc_gene_plausibility_data_dump

description: This is the data used for calculation of gene plausibility scores used by AutoCaSc.
DOI: 10.5281/zenodo.5705400
title: autocasc_gene_plausibility_data_dump

description: This is the data used for calculation of gene plausibility scores used by AutoCaSc.
DOI: 10.17894/ucph.32e4e990-1619-45ba-a941-866c9f6ef179
title: Superconductivity and parity preservation in as-grown In islands on InAs nanowires
DOI: 10.5281/zenodo.5705516
title: 4WD command frame prototype tests

description: Tests performed on the 4WD command frame circular prototype developed in ECOBULK.
DOI: 10.5281/zenodo.5705515
title: 4WD command frame prototype tests

description: Tests performed on the 4WD command frame circular prototype developed in ECOBULK.
DOI: 10.18434/mds2-2362
title: Supporting scripts and datasets for manuscript "A modified Vegetation Photosynthesis and Respiration Model (VPRM) for the eastern USA and Canada, evaluated with comparison to atmospheric observations and other biospheric models"
DOI: 10.5281/zenodo.5705526
title: msd-errors - Data for diffusion coefficient and offset figures

description: Data for a figure that shows the distributions of the mean and varance of the diffusion coefficient and offset that are found from the analysis of 1024 unique random walks using kinisi. This is performed for both a truely random walk and a temporally anti-correlated random walk.<br><br>Created using showyourwork from this GitHub repo.
DOI: 10.6084/m9.figshare.17026571
title: (Triggering drug release..)original data.zip

description: anti-bacterial; hydrogel; TA;PB;PAAM
DOI: 10.5281/zenodo.5704192
title: Code and data sets for "MS²Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates"

description: Code used to prepare data sets, train and evaluate new MS²PIP models, evaluate MS²Rescore for immunopeptidomics, and generate figures. See README.md for more information on how to use these files and reproduce the results reported in the manuscript titled "MS²Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates".
DOI: 10.18112/openneuro.ds003810.v2.0.2
title: Motor Imagery vs Rest - Low-Cost EEG System
DOI: 10.6073/pasta/83dcd48a0d7351acc55b795f307b6f38
title: Seed dispersal data for Warneke et al "Habitat fragmentation alters the distance of abiotic seed dispersal through edge effects and direction of dispersal"

description: This csv file contains seed dispersal data for five species (Carphephorus bellidifolius, Aristida beyrichiana, Liatris squarrulosa, Sorghastrum secundum, and Anthenantia villosa). Data were collected at the Savannah River Site, near Aiken, South Carolina, United States. Data were collected between November 17, 2009, to January 22, 2010 and were collected using the methods outlined in this document.
DOI: 10.5281/zenodo.5705597
title: msd-errors - Data for diffusion coefficient and offset figures

description: Data for a figure that shows the distributions of the mean and varance of the diffusion coefficient and offset that are found from the analysis of 1024 unique random walks using kinisi. This is performed for both a truely random walk and a temporally anti-correlated random walk.<br><br>Created using showyourwork from this GitHub repo.
DOI: 10.5281/zenodo.5705310
title: Mapping canopy cover in African dry forests from combined use of Sentinel-1 and Sentinel-2 data: 2018 maps for Tanzania

description: The monitoring of tropical forests has benefited from the increased availability of high-resolution earth observation data. However, the seasonality and openness of the canopy of dry tropical forests remains a challenge for optical sensors. The availability of time series of remote sensing images at 10-meters is changing this paradigm. In the context of REDD+ national reporting requirements, we investigated a methodology that is reproducible and adaptable in order to ensure user appropriation. The overall methodology consists of three main steps: (i) the generation of Sentinel-1 (S1) and Sentinel-2 (S2) layers, (ii) the collection of an ad-hoc training/validation dataset and (iii) the classification of the satellite data. Three different classification workflows are compared in terms of their capability to capture the canopy cover of forests in East Africa. Two types of maps are derived from these mapping approaches: i) binary tree cover/no tree cover (TC/NTC) maps, and ii) maps of canopy cover classes. The method is applied at scale, over Tanzania and one final map for each workflow is shared. Two big data computing platforms are combined to exploit the important volume of satellite data available over a yearly period. The reference dataset (training and validation), the three best maps and the codes to produce the S1 and S2 composites on Google Earth Engine are shared here. The folder “reference_dataset.zip” contains the expert based training and validation dataset. The point shapefile corresponding to the center of the plot as well as the 3x3 and 5x5 polygon shapefile are shared together with qml layer file for each type of shapefile. Three maps (binary TC-NTC “pixel” RF, forest type “pixel” RF and “window” ETC) are shared. A 40 km buffer from national boundaries is kept in order to let users refine their area of interest. The qml style file are also shared. In the “script.zip” folder, the javascript codes to generate the S1 and S2 mosaics are shared.
DOI: 10.5281/zenodo.5701254
title: Mapping canopy cover in African dry forests from combined use of Sentinel-1 and Sentinel-2 data: 2018 maps for Tanzania

description: The monitoring of tropical forests has benefited from the increased availability of high-resolution earth observation data. However, the seasonality and openness of the canopy of dry tropical forests remains a challenge for optical sensors. The availability of time series of remote sensing images at 10-meters is changing this paradigm. In the context of REDD+ national reporting requirements, we investigated a methodology that is reproducible and adaptable in order to ensure user appropriation. The overall methodology consists of three main steps: (i) the generation of Sentinel-1 (S1) and Sentinel-2 (S2) layers, (ii) the collection of an ad-hoc training/validation dataset and (iii) the classification of the satellite data. Three different classification workflows are compared in terms of their capability to capture the canopy cover of forests in East Africa. Two types of maps are derived from these mapping approaches: i) binary tree cover/no tree cover (TC/NTC) maps, and ii) maps of canopy cover classes. The method is applied at scale, over Tanzania and one final map for each workflow is shared. Two big data computing platforms are combined to exploit the important volume of satellite data available over a yearly period. The reference dataset (training and validation), the three best maps and the codes to produce the S1 and S2 composites on Google Earth Engine are shared here. The folder “reference_dataset.zip” contains the expert based training and validation dataset. The point shapefile corresponding to the center of the plot as well as the 3x3 and 5x5 polygon shapefile are shared together with qml layer file for each type of shapefile. Three maps (binary TC-NTC “pixel” RF, forest type “pixel” RF and “window” ETC) are shared. A 40 km buffer from national boundaries is kept in order to let users refine their area of interest. The qml style file are also shared. In the “script.zip” folder, the javascript codes to generate the S1 and S2 mosaics are shared.
DOI: 10.5281/zenodo.5705636
title: T2Dv2 numeric columns annotation

description: This files contains the annotation of numeric columns of the T2Dv2 dataset.
DOI: 10.25345/c56851
title: MassIVE MSV000088391 - Regulatory and Conventional T cells treated by exosomes
title: Regulatory and Conventional T cells treated by exosomes and analyzed at proteomic level by LTQ Orbitrap XL ETD (Thermo Scientific instrument model). Specifically, T cells not treated (Ctrl; n=4 biological replicates x n=2 technical replicates), T cells treated by EXO-Treg (EXO_TReg; n=4 biological replicates x n=2 technical replicates) and Tcells treated by EXO-TConv (EXO_Tconv; n=4 biological replicates x n=2 technical replicates) were analyzed for a total of 24 LC-MS/MS runs.
DOI: 10.6084/m9.figshare.17026622
title: Datasheet Role of Org Commitment in career growth and turnover intention

description: This research aims to measure career growth's influence on turnover intention, mediated by employees’ commitment.
DOI: 10.5281/zenodo.4692646
title: Four organic sea surface temperature proxies (UK'37, TEXH86, RI-OH' and LDI) in the westernmost Mediterranean for the last 35 kyr

description: We present a high-resolution paleotemperature reconstruction from a marine sediment core (GP04PC) recovered in the westernmost Mediterranean, the Alboran Sea basin, over the last 35 kyr using for the first time in pararell four independent organic sea surface temperature (SST) proxies (U<sup>K'</sup><sub>37</sub>,<sup> </sup>TEX<sup>H</sup><sub>86</sub>,RI-OH' and LDI). We also present the δ<sup>18</sup>O of planktonic foraminifera <em>G. bulloides</em> record together with records of bulk parameters (total organic carbon content, δ<sup>13</sup>C<sub>org</sub>) and the accumulation rates of different biomarkers, providing insights in terrestrial input and primary productivity variations. We have also examined the Bayesian calibrations BAYSPLINE for U<sup>K'</sup><sub>37 </sub>and BAYSPAR for TEX<sub>86</sub>, although the non-Bayesian calibrations are used in this study.
description: Sample information: - Name of the oceanographic cruise: Gasalb onboard the R/V Pelagia in November 2011 - Name of the marine sediment record: GP04PC - Method: Piston corer - Latitude: 35.7871º N - Longitude: 4.5343º W - Elevation: 1306.5 m bsl - Lenght: 872.25 cm - Date: last 35 kyr cal BP - Age model used: Bayesian statistic of 10 AMS 14C calibrated ages and 6 tie-points and the Marine20 calibration curve
DOI: 10.5281/zenodo.5534933
title: DOE1 and DOE2 - Sensor data set radial forging at AFRC testbed

description: <strong>Sensor data set, radial forging at AFRC testbed</strong> <strong>General information on the data set</strong> Radial forging is widely used in industry to manufacture components for a broad range of sectors including automotive, medical, aerospace, rail and industrial. The Advanced Forming Research Centre (AFRC) at the University of Strathclyde, Glasgow, houses a GFM SKK10/R radial forge that has been used as a testbed for this project. Using two pairs of hammers operating at 1200 strokes/min, and providing a maximum forging force per hammer of 150 tons, the radial forge is capable of processing a range of metals, including steel, titanium and inconel. Both hollow and solid material can be formed with the added benefit of creating internal features on hollow parts using a mandrel. Parts can be formed at a range of temperatures from ambient temperature to 1200 °C. For the provided data set, a total of 95 parts were forged over two days of operation. Each part was forged with machine parameters outlined in the file <code>Met4FoF STRATH test plan v4.xlsx</code>. Deviations from the test plan occurred during the second batch and are outline in the sheet <code>Batch 2</code>. Each forged part was then measured using a CMM to provide dimensional output relative to a target specification and tolerances. T<strong>he CMM records 16 dimensional measurements</strong>. The aim of the measurement setup is to predict the quality (in terms of dimensional properties) of the forged part from the sensor measurements during the forging process. <strong>Structure of the data</strong> The sensor readings for the forging of the parts are provided in csv files in the folders <code>ScopeTraces_DOE1</code> and <code>ScopeTraces_DOE2</code> for DOE1 and DOE2 respectively. For DOE1 the scope traces are named <code>Scope0001.csv</code> to <code>Scope0050.csv</code>. For DOE2 there were deviations and the Scope Traces to billet mapping is outlined in <code>Met4FoF STRATH test plan v4.xlsx</code>. Each file contains the readings (columns) against time (rows). The first column displays the clock times (in milliseconds). A commentary on the sensors is provided in the file <code>ForgedPartDataStructureSummaryv3.xlsx </code>(NOTE: Some columns do not have sensor descriptions as this information is not available). The CMM data is provided in the file <code>CMM_DOE1.xlsx</code> and <code>CMM_DOE2.xlsx</code> for DOE1 and DOE2 respectively.
DOI: 10.5281/zenodo.4692645
title: Four organic sea surface temperature proxies (UK'37, TEXH86, RI-OH' and LDI) in the westernmost Mediterranean for the last 35 kyr

description: We present a high-resolution paleotemperature reconstruction from a marine sediment core (GP04PC) recovered in the westernmost Mediterranean, the Alboran Sea basin, over the last 35 kyr using for the first time in pararell four independent organic sea surface temperature (SST) proxies (U<sup>K'</sup><sub>37</sub>,<sup> </sup>TEX<sup>H</sup><sub>86</sub>,RI-OH' and LDI). We also present the δ<sup>18</sup>O of planktonic foraminifera <em>G. bulloides</em> record together with records of bulk parameters (total organic carbon content, δ<sup>13</sup>C<sub>org</sub>) and the accumulation rates of different biomarkers, providing insights in terrestrial input and primary productivity variations. We have also examined the Bayesian calibrations BAYSPLINE for U<sup>K'</sup><sub>37 </sub>and BAYSPAR for TEX<sub>86</sub>, although the non-Bayesian calibrations are used in this study.
description: Sample information: - Name of the oceanographic cruise: Gasalb onboard the R/V Pelagia in November 2011 - Name of the marine sediment record: GP04PC - Method: Piston corer - Latitude: 35.7871º N - Longitude: 4.5343º W - Elevation: 1306.5 m bsl - Lenght: 872.25 cm - Date: last 35 kyr cal BP - Age model used: Bayesian statistic of 10 AMS 14C calibrated ages and 6 tie-points and the Marine20 calibration curve
DOI: 10.6084/m9.figshare.17026739
title: COVID-19 DTA Depression Data

description: The data file includes the filter to recreate the exclusion criteria for the Study. We also present the individual exclusion criteria below: · DTAfragmentattempts &gt; 5 · Progress &gt; 97 · DTAtasktime &lt; 3600 · Covidindex_3dayav &gt; 325 (i.e., those who took part on the day or after Boris Johnson’s announcement)
DOI: 10.5281/zenodo.5705645
title: T2Dv2 numeric columns annotation

description: This files contains the annotation of numeric columns of the T2Dv2 dataset.
DOI: 10.5281/zenodo.5705163
title: Data for Fluid simulations accelerated with 16 bits: Approaching 4x speedup on A64FX

description: Dataset for M Kloewer, S Hatfield, M Croci, PD Dueben and TN Palmer, 2021. Fluid simulations accelerated with 16 bits: Approaching 4x speedup on A64FX by squeezing ShallowWaters.jl into Float16, in review. This dataset contains data from simulations with ShallowWaters.jl with varying number formats and with or without a compensated time integration. All other parameters are shared between simulations. All .tar.gz are packed folders of the same name that contain netCDF files presenting velocities u,v, sea surface height eta, and tracer sst (sea surface temperature) run0002. Float16 simulation with compensated summation in the time integration. run0003. Float16 simulation without compensated summation in the time integration. run0004. Float64 reference simulation (without compensated summation in the time integration). run0005. Float16/32 mixed-precision simulation. No compensated time integration. Additionally, parameter.txt in each run summarizes all model parameters and progress.txt was created to monitor the progress of the data output during simulation. The file benchmarking.jld2 stores data for the benchmarking of the different runs as Julia's JLD2 format (a subset of HDF5). This dataset was created using the Isambard UK National Tier-2 HPC Service operated by GW4 and the UK Met Office, and funded by the Engineering and Physical Sciences Research Council EPSRC. For more details, see ShallowWaters.jl or the preprint Kloewer et al, 2021.