cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6554830
title: Data generated and analysed for Santos Neves, Lambert, Valente & Etienne 2022

description: This repository contains the data and metadata for accompanying the publication of Santos Neves, P., Lambert, J. W., Valente, L., & Etienne, R. S. (2022). The robustness of a simple dynamic model of island biodiversity to geological and sea-level change. <br> All files apart from metadata contained within this repository were obtained via computation at University of Groningen Peregrine High Performance Computing Cluster (HPCC).<br> Data was generated using the pipeline implemented on the R package DAISIErobustness, which itself greatly depends on the R package DAISIE. The code for these packages is version controlled on GitHub and is freely available in open-source repositories. See the Related Identifiers section for links to relevant archived versions of both these packages.
description: A pre-print BiorXiv making use of a previous version of this data, which corresponds to the journal submission without peer-review is available as: Santos Neves, P., Lambert, J. W., Valente, L., & Etienne, R. S. (2021). The robustness of a simple dynamic model of island biodiversity to geological and eustatic change. BiorXiv. https://doi.org/10.1101/2021.07.26.453064.
description: {"references": ["Santos Neves, P., Lambert, J. W., Valente, L., & Etienne, R. S. (2021). The robustness of a simple dynamic model of island biodiversity to geological and eustatic change. BiorXiv"]}
DOI: 10.5281/zenodo.5119924
title: Data generated and analysed for Santos Neves, Lambert, Valente & Etienne 2022

description: This repository contains the data and metadata for accompanying the publication of Santos Neves, P., Lambert, J. W., Valente, L., & Etienne, R. S. (2022). The robustness of a simple dynamic model of island biodiversity to geological and sea-level change. <br> All files apart from metadata contained within this repository were obtained via computation at University of Groningen Peregrine High Performance Computing Cluster (HPCC).<br> Data was generated using the pipeline implemented on the R package DAISIErobustness, which itself greatly depends on the R package DAISIE. The code for these packages is version controlled on GitHub and is freely available in open-source repositories. See the Related Identifiers section for links to relevant archived versions of both these packages.
description: A pre-print BiorXiv making use of a previous version of this data, which corresponds to the journal submission without peer-review is available as: Santos Neves, P., Lambert, J. W., Valente, L., & Etienne, R. S. (2021). The robustness of a simple dynamic model of island biodiversity to geological and eustatic change. BiorXiv. https://doi.org/10.1101/2021.07.26.453064.
description: {"references": ["Santos Neves, P., Lambert, J. W., Valente, L., & Etienne, R. S. (2021). The robustness of a simple dynamic model of island biodiversity to geological and eustatic change. BiorXiv"]}
DOI: 10.6084/m9.figshare.19802119
title: Transcriptome analysis provides new insights into the diverse roles of SREBP in Penaeus vannamei

description: The annotation data (NR, Swiss-Prot, KEGG, COG, GO database annotations) of differentially expressed genes (DEGs) in transcriptome of SREBP-depleted <em>Penaeus Vannamei</em> shrimp
DOI: 10.6084/m9.figshare.19802119.v1
title: Transcriptome analysis provides new insights into the diverse roles of SREBP in Penaeus vannamei

description: The annotation data (NR, Swiss-Prot, KEGG, COG, GO database annotations) of differentially expressed genes (DEGs) in transcriptome of SREBP-depleted <em>Penaeus Vannamei</em> shrimp
DOI: 10.6084/m9.figshare.19787296
title: Data

description: Data used in the analyses reported in the paper.
DOI: 10.6084/m9.figshare.19787296.v1
title: Data

description: Data used in the analyses reported in the paper.
DOI: 10.5281/zenodo.6335037
title: Predicting the failure of two-dimensional silica glasses

description: Datasets for the paper: Font-Clos F, Zanchi M, Hiemer S, Bonfanti S, Guerra R, Zaiser M, Zapperi S. Predicting the failure of two-dimensional silica glasses. arXiv preprint arXiv:2201.09723. 2022 Jan 24. https://arxiv.org/abs/2201.09723 The datasets can be used together with the codes available at https://github.com/ComplexityBiosystems/2D-silica-ML to reproduce the resuts of the paper above. In particular, the datasets contain the the following data The dataset '20201222-var02-onethousand.zip' contains configurations at fixed disorder (s<sup>2</sup>= 0.2). The dataset '20210209-variable-disorder.zip' contains configurations at variable disorder. The dataset 'ml_dataset_fracture_atoms_var02.tar.gz' contains the images for the prediction of the crack path. The dataset 'ml_dataset_var02.tar.gz' contains images of silica at fixed disorder (s<sup>2</sup>= 0.2). for the prediction of disorder, rupture strain and location. The dataset 'ml_dataset_variable_var.tar.gz' contains images of silica at variable disorder for the prediction of disorder, rupture strain and location. The dataset 'trained_models' contains an example of a ResNet trained for predicting rupture strain at variable disorder (it can be used for testing the Grad-CAM method).
DOI: 10.5281/zenodo.6335036
title: Predicting the failure of two-dimensional silica glasses

description: Datasets for the paper: Font-Clos F, Zanchi M, Hiemer S, Bonfanti S, Guerra R, Zaiser M, Zapperi S. Predicting the failure of two-dimensional silica glasses. arXiv preprint arXiv:2201.09723. 2022 Jan 24. https://arxiv.org/abs/2201.09723 The datasets can be used together with the codes available at https://github.com/ComplexityBiosystems/2D-silica-ML to reproduce the resuts of the paper above. In particular, the datasets contain the the following data The dataset '20201222-var02-onethousand.zip' contains configurations at fixed disorder (s<sup>2</sup>= 0.2). The dataset '20210209-variable-disorder.zip' contains configurations at variable disorder. The dataset 'ml_dataset_fracture_atoms_var02.tar.gz' contains the images for the prediction of the crack path. The dataset 'ml_dataset_var02.tar.gz' contains images of silica at fixed disorder (s<sup>2</sup>= 0.2). for the prediction of disorder, rupture strain and location. The dataset 'ml_dataset_variable_var.tar.gz' contains images of silica at variable disorder for the prediction of disorder, rupture strain and location. The dataset 'trained_models' contains an example of a ResNet trained for predicting rupture strain at variable disorder (it can be used for testing the Grad-CAM method).
DOI: 10.5517/ccdc.csd.cc298p1b
title: CCDC 2123501: Experimental Crystal Structure Determination

description: Related Article: Siqin Wu, Bo Zhou, Xiaoyu Fang, Dongpeng Yan|2022|Chem.Commun.|58|6136|doi:10.1039/D2CC01485H
DOI: 10.5517/ccdc.csd.cc298p7j
title: CCDC 2123507: Experimental Crystal Structure Determination

description: Related Article: Siqin Wu, Bo Zhou, Xiaoyu Fang, Dongpeng Yan|2022|Chem.Commun.|58|6136|doi:10.1039/D2CC01485H
DOI: 10.5517/ccdc.csd.cc29h915
title: CCDC 2129856: Experimental Crystal Structure Determination

description: Related Article: Jiang-Lin Zhao, Shuguang Xuan, Kai Chen, Carl Redshaw, Yan Chen, Zongwen Jin|2022|Chem.Commun.|58|6112|doi:10.1039/D2CC01609E
DOI: 10.5517/ccdc.csd.cc24x5fp
title: CCDC 1993282: Experimental Crystal Structure Determination

description: Related Article: Benjamin Wittwer, Nicole Dickmann, Stephan Berg, Daniel Leitner, Lorenzo Tesi, David Hunger, Raphael Gratzl, Joris van Slageren, Nicolas I. Neuman, Dominik Munz, Stephan Hohloch|2022|Chem.Commun.|58|6096|doi:10.1039/D2CC00097K
DOI: 10.5517/ccdc.csd.cc2bb5c7
title: CCDC 2154728: Experimental Crystal Structure Determination

description: Related Article: Ludovic Leleu, Thomas Martzel, Arona Fall, Morgane Sanselme, Vincent Levacher, Sylvain Oudeyer, Jean-François Brière|2022|Chem.Commun.|58|6100|doi:10.1039/D2CC01795D
DOI: 10.5517/ccdc.csd.cc2bb5d8
title: CCDC 2154729: Experimental Crystal Structure Determination

description: Related Article: Ludovic Leleu, Thomas Martzel, Arona Fall, Morgane Sanselme, Vincent Levacher, Sylvain Oudeyer, Jean-François Brière|2022|Chem.Commun.|58|6100|doi:10.1039/D2CC01795D
DOI: 10.5517/ccdc.csd.cc2bd834
title: CCDC 2156735: Experimental Crystal Structure Determination

description: Related Article: Saiprasad Nunewar, Sanjeev Kumar, Pendam Priyanka, Pradeep Girase, Vinaykumar Kanchupalli|2022|Chem.Commun.|58|6140|doi:10.1039/D2CC01386J
DOI: 10.21942/uva.19416215
title: Dataset for predictive bird migration model

description: These datasets are used for developing a predictive model for bird migration. Bird densities are derived from weather data provided by the KNMI (NL/DBL: https://dataplatform.knmi.nl/dataset/radar-tar-volume-debilt-1-0 & NL/HRW: https://dataplatform.knmi.nl/dataset/radar-tar-vol-full-herwijnen-1-0 ). Annotated weather data is derived from the ECMWF ERA 5 dataset: https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5 , https://doi.org/10.1002/qj.3803 <br> Column naming:<br> Surface temperature: t2m<br> Surface pressure: sp<br> Surface pressure 24 hours before: spDayBefore<br> Average air temperate between 400 and a 1000m: tHeightAvg<br> Wind between 400 and 1000m: uHeightAvg & vHeightAvg<br> Surface pressure and wind ad remote locations: FranceCoast_sp, UK_sp, Noorway_sp, MeckPom_sp, Denmark_sp, Sweden_sp, Noorway_u10, Noorway_v10, MeckPom_u10, MeckPom_v10, Denmark_u10, Denmark_v10, Sweden_u10, Sweden_v10,<br> FranceCoast_u10, FranceCoast_v10, UK_u10, UK_v10<br> Wind at 10 and a 100 m of height: u10, v10, u100, v100<br> Total cloud cover: tcc<br> Source radar: radarId<br> Timestamp (UTC): datetime<br> Total percepitation: tp<br> Solar position: solar_pos_elevation, solar_pos_elevation_change<br> Vertically integrated bird density: vid<br> Accumulation and change of accumulation in the number of birds: rain_acc_t3_4_diff, tcc_acc_t3_4_diff, tp_tcc_acc_t3_4_diff, rain_acc_t3_4, tcc_acc_t3_4, tp_tcc_acc_t3_4, wind_rain_acc_t3_4_diff, wind_rain_acc_t3_4
DOI: 10.6084/m9.figshare.19802635
title: Electronic supplementary material from Insect cross-tolerance to freezing and drought stress: role of metabolic re-arrangement

description: Methods and results of metabolomics analyses of Chymomyza costata larvae.
DOI: 10.5281/zenodo.6563189
title: Comparing health of migrant and native populations over time. Testing intercultural and longitudinal measurement equivalence of the SF-12 Health Survey.

description: Dataset, script and variable codebook for publication: "<strong>Comparing health of migrant and native populations over time. Testing intercultural and longitudinal measurement equivalence of the SF-12 Health Survey."</strong> <strong>Content:</strong> - data_long.dta: GSOEP data set in long format - script_1: R script for measurement equivalence tests - script_2: R script for latent mean calculation - script_3: R script output gathering and visualization - variable_codebook: txt-file with variable description
DOI: 10.5281/zenodo.6563188
title: Comparing health of migrant and native populations over time. Testing intercultural and longitudinal measurement equivalence of the SF-12 Health Survey.

description: Dataset, script and variable codebook for publication: "<strong>Comparing health of migrant and native populations over time. Testing intercultural and longitudinal measurement equivalence of the SF-12 Health Survey."</strong> <strong>Content:</strong> - data_long.dta: GSOEP data set in long format - script_1: R script for measurement equivalence tests - script_2: R script for latent mean calculation - script_3: R script output gathering and visualization - variable_codebook: txt-file with variable description
DOI: 10.6084/m9.figshare.19802650.v1
title: Data on litter, sex and gestation length from Sex reversal explains some, but not all, climate mediated sex ratio variation within a viviparous reptile

description: Offspring sex, female gestation length and population for C. ocellatus females held in thermal manipulation experiments
DOI: 10.6084/m9.figshare.19802650
title: Data on litter, sex and gestation length from Sex reversal explains some, but not all, climate mediated sex ratio variation within a viviparous reptile

description: Offspring sex, female gestation length and population for C. ocellatus females held in thermal manipulation experiments
DOI: 10.25345/c5222r954
title: MassIVE MSV000089502 - GNPS - Aplysina cavernicola exo-metabolites
title: Project Title : "Capture and identification of seawater released bromotyrosine alkaloids from the sponge Aplysina cavernicola"
DOI: 10.14459/2021mp1621941
title: MITI: SLAM Benchmark for Laparoscopic Surgery

description: Our MITI Dataset provides all the necessary data by a complete recording of a handheld surgical intervention at Research Hospital Rechts der Isar of TUM. It contains multimodal sensor information from IMU, stereoscopic video, and infrared (IR) tracking as ground truth for evaluation. Furthermore, calibration for the stereoscope, accelerometer, magnetometer, the rigid transformations in the sensor setup, and time-offsets are available. We wisely chose a suitable intervention that contains very few cutting and tissue deformation and shows a full scan of the abdomen with a handheld camera such that it is ideal for testing SLAM algorithms. Intending to promote the progress of visual-inertial algorithms designed for MIS application, we hope that our clinical training dataset helps and enables researchers to enhance algorithms.
DOI: 10.17028/rd.lboro.14213831
title: Do mathematicians and undergraduates agree about explanation quality? - Dataset

description: Materials associated with the manuscript "Do mathematicians and undergraduates agree about explanation quality?". <br> Raw judgement data from both groups are in the tab "RawJudgements-All" in the excel sheet. Each line represents a judgement by the judge listed in the Judge column. The candidates are identified by file names from the zip folder (which contains 10 pdf files, one for each of the 10 explanations). <br> Data were analysed using the AnalysisScriptForSharing.R script, separately for the mathematician and undergraduate groups. <br> This resulted in the results in the ModelledResults tab of the excel sheet. Column headings are: - individual: the explanation file name - math.Ntot: total number of judgements made by mathematicians for this explanation - math.N1: number of 'wins' by this explanation - math.N0: number of 'losses' by this explanation - math.theta: the beta parameter for this explanation derived from mathematicians' judgements - math.se.theta: the SE around the beta parameter derived from mathematicians' judgements - ug columns are all analogous to the math columns. <br>
DOI: 10.17028/rd.lboro.14213831.v1
title: Do mathematicians and undergraduates agree about explanation quality? - Dataset

description: Materials associated with the manuscript "Do mathematicians and undergraduates agree about explanation quality?". <br> Raw judgement data from both groups are in the tab "RawJudgements-All" in the excel sheet. Each line represents a judgement by the judge listed in the Judge column. The candidates are identified by file names from the zip folder (which contains 10 pdf files, one for each of the 10 explanations). <br> Data were analysed using the AnalysisScriptForSharing.R script, separately for the mathematician and undergraduate groups. <br> This resulted in the results in the ModelledResults tab of the excel sheet. Column headings are: - individual: the explanation file name - math.Ntot: total number of judgements made by mathematicians for this explanation - math.N1: number of 'wins' by this explanation - math.N0: number of 'losses' by this explanation - math.theta: the beta parameter for this explanation derived from mathematicians' judgements - math.se.theta: the SE around the beta parameter derived from mathematicians' judgements - ug columns are all analogous to the math columns. <br>
DOI: 10.34740/kaggle/dsv/3667911
title: WallStreetBets 2022
DOI: 10.5281/zenodo.6490935
title: Evaluation of aquaculture regulations' adaptiveness to low trophic aquaculture (LTA) in selected countries and regions of the Atlantic.

description: Assessments of documents relevant for LTA according to 15 adaptiveness criteria. Scores are assigned on the scale between -2 and 2. In total 22 documents are analyzed (5 for Galicia, Spain; 2 for Schleswig-Holstein, Germany; 8 for Scotland; 6 for Norway, 1 for South Africa and). General analysis is done for Brazilian aquaculture legislation. The data consists of an Excel file with scores and 6 pdf files with explanation of each score.
DOI: 10.5281/zenodo.6490934
title: Evaluation of aquaculture regulations' adaptiveness to low trophic aquaculture (LTA) in selected countries and regions of the Atlantic.

description: Assessments of documents relevant for LTA according to 15 adaptiveness criteria. Scores are assigned on the scale between -2 and 2. In total 22 documents are analyzed (5 for Galicia, Spain; 2 for Schleswig-Holstein, Germany; 8 for Scotland; 6 for Norway, 1 for South Africa and). General analysis is done for Brazilian aquaculture legislation. The data consists of an Excel file with scores and 6 pdf files with explanation of each score.
DOI: 10.25919/2rfh-hg31
title: Pest Suppressive Landscapes Project Habitat Data

description: Data from study regions in three States on populations of pest and beneficial insects in agricultural landscapes of Australia were collected for this project. In order to understand how the population dynamics of grain pests are affected by landscape composition, we identified source habitats of pests and natural enemies (this data). The habitats studied include grain crops, pastures, and weeds and native plants in remnant vegetation patches. This work was conducted in agricultural landscapes in north, south and west Australia monthly over a two-year period (2010-2011).
DOI: 10.17032/shu-180034
title: The Real Level of Unemployment 2022 Dataset

description: The Real Level of Unemployment 2022 presents an alternative set of unemployment figures for every district and unitary authority in Great Britain. It is the sixth in a series of similar reports, published at five-yearly intervals going back to 1997.
DOI: 10.6084/m9.figshare.19802773
title: Bank efficiency and staff training policy dataset

description: Dataset containing results and survey responses for the article "<strong>Does it pay off to invest in bank staff training?</strong> <strong>Survey-based evidence from the Romanian banking sector"</strong>
DOI: 10.11583/dtu.19222434
title: Complementary data for Machine Learning-Driven Energy Management of a Hybrid Nuclear-Wind-Solar-Desalination Plant

description: Author: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk), ORCID: https://orcid.org/0000-0001-5664-9421 <br> -------------------------------------------------------------------------------<br> <br> The paper related to this dataset is currently In Press. <br> Title: Machine Learning-Driven Energy Management of a Hybrid Nuclear-Wind-Solar-Desalination Plant Submmited: Feb 2022 Accepted: May 2022 Published: ------------------------------------------------------------------------------- The folder contains the data implemented in the study cases of the related paper.
DOI: 10.11583/dtu.17040767.v1
title: The SOLETE dataset

description: Author: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk), ORCID: https://orcid.org/0000-0001-5664-9421-------------------------------------------------------------------------------This item includes the SOLETE dataset which is disclosed to increase the transparency and replicability of [1] and [2], which are at different stages of the review process.<br>SOLETE includes 15 months of 5 minute and hourly measurements from the 1st June 2018 to 1st September 2019 covering: Timestamp, air temperature, relative humidity, pressure, wind speed, wind direction, global horizontal irradiance, plane of array irradiance, and active power recorded from an 11 kW Gaia wind turbine and a 10 kW PV inverter.<br><b>Note: </b>Until the final acceptance of the related papers, only a minimum piece of the dataset is shared for illustration purposes. If you want to get a reminder once the full set is made public drop me an email.<br>The origin of the data is SYSLAB, part of DTU Elektro. If you want to learn more about the dataset, you should check out [3].<br>You can use the SOLETE dataset with the codes available here: https://doi.org/10.11583/DTU.17040626<br>The different scripts have various functions. One allows to import SOLETE and show some plots. Another is a platform where you can play with different Machine Learning models for time series forecasting. The application focuses on predicting PV power, but it can be easily edited by the user.<br><br>The publications related to this item are:<br><br>[1] D.V. Pombo, H.W. Bindner, S.V. Spataru, P. Sørensen, P. Bacher, Increasing the Accuracy of Hourly Multi-Output Solar Power Forecast with Physics-Informed Machine Learning, Sensors. In Press. <br>[2] D.V. Pombo, P. Bacher, C. Ziras, H.W. Bindner, S.V. Spataru, P. Sørensen, Benchmarking Physics-Informed Machine Learning-based Short Term PV-Power Forecasting Tools, Under Review. <br>[3] D.V. Pombo, O.G. Gehrke, H.W. Bindner, Solete, a 15-month long holistic dataset including: meteorology, co-located wind and solar PV power from Denmark with hourly resolution, Data in Brief. Under Review.<br>
DOI: 10.25500/edata.bham.00000839
title: Data that was used in the publication, Methanolysis of Poly(lactic acid) Using Catalyst Mixtures and the Kinetics of Methyl Lactate Production
DOI: 10.5281/zenodo.6566315
title: Single Photon Switch and Facilitation Induced Transparency with Dual-channel Rydberg Interactions

description: Original data for "Single Photon Switch and Facilitation Induced Transparency with Dual-channel Rydberg Interactions". Data can be opened with Matlab.
DOI: 10.5281/zenodo.6566314
title: Single Photon Switch and Facilitation Induced Transparency with Dual-channel Rydberg Interactions

description: Original data for "Single Photon Switch and Facilitation Induced Transparency with Dual-channel Rydberg Interactions". Data can be opened with Matlab.
DOI: 10.15468/gpxggj
title: O_WESTERSCHELDE - Eurasian oystercatchers (Haematopus ostralegus, Haematopodidae) breeding in East Flanders (Belgium) [subsampled representation]

description: This animal tracking dataset is derived from Spanoghe et al. (2022, https://doi.org/10.5281/zenodo.5879096) a deposit of Movebank study 1099562810. Data have been standardized to Darwin Core using the movepub R package and are downsampled to the first GPS position per hour. The original dataset description follows. <em>O_WESTERSCHELDE - Eurasian oystercatchers (Haematopus ostralegus, Haematopodidae) breeding in East Flanders (Belgium)</em> is a bird tracking dataset published by the Research Institute for Nature and Forest (INBO). It contains animal tracking data collected by the LifeWatch GPS tracking network for large birds (http://lifewatch.be/en/gps-tracking-network-large-birds) for the project/study <strong>O_WESTERSCHELDE</strong>, using trackers developed by the University of Amsterdam Bird Tracking System (UvA-BiTS, http://www.uva-bits.nl). The study has been operational since 2018. In total 13 individuals of Eurasian oystercatchers (<em>Haematopus ostralegus</em>) have been tagged in their breeding area in East Flanders (Belgium), west of the river Scheldt, mainly to study their habitat use on mudflats of the Western Scheldt (the Netherlands). Data are uploaded from the UvA-BiTS database to Movebank and from there archived on Zenodo (see https://github.com/inbo/bird-tracking). No new data are expected. This dataset was collected using infrastructure provided by INBO and funded by Research Foundation - Flanders (FWO) as part of the Belgian contribution to LifeWatch. Additional funding was provided by the Sovon Dutch Centre for Field Ornithology.
DOI: 10.14278/rodare.1627
title: Data for: Spectral X-ray Computed Micro Tomography: 3-dimensional chemical imaging

description: The files show the data we used for the publication.