cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25502/hmrd-ba78/d
title: The influence of minisett size and time of planting on the yield of seed yam (Dioscorea rotundata) in Abuja, Nigeria

description: The data is from an investigation of the influence of planting different minisett sizes at different periods on yield. The trial was carried out on the experimental field at IITA Abuja Station (9.164694 N, 7.345136 E) during the cropping seasons of 2015 and 2016. It was laid out in a Randomized Complete Block Design (RCBD) with three replications with nine treatment combinations: 30 g minisetts planted early (Early); 30 g minisetts planted 21 days after the early planting (Mid); 30 g minisetts planted 21 days after the mid planting (Late). Similarly, 60 g and 90 g minisetts were planted early, mid and late, respectively. The D. rotundata landrace ‘Meccakusa’ was used.
DOI: 10.5281/zenodo.4288459
title: SciGRID_gas IGGIN

description: This data set has been was generated by combining the following data sources:<br> • InternetDaten data set (INET)<br> • Gas Infrastructure Europe data set (GIE)<br> • Gas Storages Europe data set (GSE)<br> • International Gas Union data set (IGU)<br> • Norway data set (NO).<br>
DOI: 10.5281/zenodo.4288458
title: SciGRID_gas IGGIN

description: This data set has been was generated by combining the following data sources:<br> • InternetDaten data set (INET)<br> • Gas Infrastructure Europe data set (GIE)<br> • Gas Storages Europe data set (GSE)<br> • International Gas Union data set (IGU)<br> • Norway data set (NO).<br>
DOI: 10.21227/gjbh-p254
title: Dataset for classification of handwritten and printed text in a Doctor's prescription

description: Optical Character Recognition (OCR) system is used to convert the document images, either printed or handwritten, into its electronic counterpart. But dealing with handwritten texts is much more challenging than printed ones due to erratic writing style of the individuals. Problem becomes more severe when the input image is doctor's prescription. Before feeding such image to the OCR engine, the classification of printed and handwritten texts is a necessity as doctor's prescription contains both handwritten and printed texts which are to be processed separately. Much work have been done in the domain of handwritten and printed text separation albeit work related to doctor's handwriting. This dataset consists of various localized and extracted images of handwritten and printed texts from various prescriptions of doctors.The images are categorized into 4 categories namely:HandwrittenMixedOtherPrintedThere are 11340 images in total after using augmentation techniques. Our model has achieved 99.5% accuracy in classifying the images. The publication link for the same will be added soon. To try out the gui for the same visit:https://garain.vision/Authentication/prescriptionIf you are unable to access the dataset drop a mail at avishekgarain@gmail.com.Please cite the dataset and research paper if it comes to any use.Link to research paper:https://doi.org/10.1007/s11042-020-10151-w
DOI: 10.5281/zenodo.4288447
title: Dublin Boundary Shapefile

description: A simple boundary of Dublin was extracted from a shapefile created by the Central Statistics Office (CSO) via GeoPandas. GeoPandas script: extract_dublin_boundaries.py CSO shapefile: Local_Electoral_Areas_-_OSi_National_Statutory_Boundaries-shp.zip Source: https://www.cso.ie/en/census/census2016reports/census2016smallareapopulationstatistics/
DOI: 10.5281/zenodo.4288468
title: SciGRID_gas IGGI

description: This data set has been was generated by combining the following data sources:<br> • InternetDaten data set (INET)<br> • Gas Infrastructure Europe data set (GIE)<br> • Gas Storages Europe data set (GSE)<br> • International Gas Union data set (IGU)<br>
DOI: 10.5281/zenodo.4288467
title: SciGRID_gas IGGI

description: This data set has been was generated by combining the following data sources:<br> • InternetDaten data set (INET)<br> • Gas Infrastructure Europe data set (GIE)<br> • Gas Storages Europe data set (GSE)<br> • International Gas Union data set (IGU)<br>
DOI: 10.5281/zenodo.3697514
title: Data: Breeding progress for pathogen resistance is a second major driver for yield increase in German winter wheat at contrasting N levels

description: This is the experimental data set of Zetzsche, et. al. (2020, Scientific Reports: doi.org/10.1038/s41598-020-77200-0) based on a three-year field trial (2014/15, 2015/16, 2016/7) of 178 German elite winter wheat cultivars. The table (QLB_BRIWECS_WW_fieldtrial_adjustMeans_treatments.csv) subsumes the adjusted mean values of four fungal disease scores (average ordinates) and six yield-related traits investigated at four treatments (T1: 110 kg N ha<sup>-1</sup>, no fungicides; T2: 110 kg N ha<sup>-1</sup> + fungicide; T3: 220 kg N ha<sup>-1</sup>, no fungicides; T4: 220 kg N ha<sup>-1</sup> + fungicide) of two replicates each over three years. Data of each trait are considered independent for all four treatments. Details of the plant material, the experimental site, the trail design as well as the phenotyping of the diseases and agronomical traits are given in the material and methods section of the related publication. Further metadata on the plant material and the trial design are provided in the Supplementary information of the publication.
description: The study was funded by the German Federal Ministry of Education and Research (BMBF, 031A354F) through Projektträger Jülich (PtJ) within the project "Breeding Innovations in Wheat for Efficient Cropping Systems" (BRIWECS).
DOI: 10.5281/zenodo.3697513
title: Data: Breeding progress for pathogen resistance is a second major driver for yield increase in German winter wheat at contrasting N levels

description: This is the experimental data set of Zetzsche, et. al. (2020, Scientific Reports: doi.org/10.1038/s41598-020-77200-0) based on a three-year field trial (2014/15, 2015/16, 2016/7) of 178 German elite winter wheat cultivars. The table (QLB_BRIWECS_WW_fieldtrial_adjustMeans_treatments.csv) subsumes the adjusted mean values of four fungal disease scores (average ordinates) and six yield-related traits investigated at four treatments (T1: 110 kg N ha<sup>-1</sup>, no fungicides; T2: 110 kg N ha<sup>-1</sup> + fungicide; T3: 220 kg N ha<sup>-1</sup>, no fungicides; T4: 220 kg N ha<sup>-1</sup> + fungicide) of two replicates each over three years. Data of each trait are considered independent for all four treatments. Details of the plant material, the experimental site, the trail design as well as the phenotyping of the diseases and agronomical traits are given in the material and methods section of the related publication. Further metadata on the plant material and the trial design are provided in the Supplementary information of the publication.
description: The study was funded by the German Federal Ministry of Education and Research (BMBF, 031A354F) through Projektträger Jülich (PtJ) within the project "Breeding Innovations in Wheat for Efficient Cropping Systems" (BRIWECS).
DOI: 10.34777/payf-vb10
title: Multispectral-Spoof  (MSSpoof)

description:  Multispectral-Spoof is a dataset for multi-spectral face recognition and presentation attack detection (anti-spoofing). The dataset contains images of Bona Fide VIS and NIR images as well as VIS and NIR printed presentation attacks (spoofing attacks) to VIS and NIR systems. The number of clients in the dataset is 21. The recordings are done using a uEye camera with resolution 1280x1024. When recording the images in NIR, a NIR filter of 800nm has been mounted to the camera.
DOI: 10.26050/wdcc/rcm_cmip6_amip-hr_r1
title: CMIP6 CMIP MPI-M MPI-ESM1-2-HR amip_r1i1p1f1 - RCM-forcing data

description: Project: RCM forcing data from MPI-ESM1-2 (ECHAM6/JSBACH/MPIOM/HAMOCC) CMIP6 experiments - This project provides variables from MPI-ESM1-2 CMIP6 experiments performed by DKRZ, MPI-M and DWD in the context of the BMBF funded CMIP6 DICAD project (FKZ 01LP1605A). The experiments are described at https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip6 . Essential variables for regional climate modelling (RCM) are available. They are stored in native GRIB-format (e.g. spectral). The CMIP6 experiments have been performed with various model versions of MPI-ESM1-2. The low-resolution version MPI-ESM1-2-LR has been run with T63L47 (192 x 96 gridpoints; 47 vertical layers) for ECHAM6/JSBACH and GR15 (ca. 1.5 deg) of MPIOM/HAMOCC. The high-resolution version MPI-ESM1-2-HR has been run with T127L95 (384 x 192 gridpoints; 95 vertical layers) for ECHAM6/JSBACH and TP04 (tripolar grid, ca. 0.4 deg) of MPIOM/HAMOCC. CMIP6 ensemble members are named 'rNiNpNfN': rN is the realisation, iN is the initialisation method, pN stands for the parametrisation or physics variant and fN stands for the forcing variant of the experiment. Different experiment realisations (rN) differ with respect to their restart files. For each experiment-member five datasets are provided: 1 .._rcm_c5 contains: divergence, vorticity, and air temperature 2 .._rcm_c5_133 contains: specific_humidity and surface pressure 3 .._rcm_etc contains: cloud water/ice; land/sea surface - and ice temperature; sea ice thickness/area fraction; soil moisture content; snow thickness on sea ice 4 .._rcm_land contains: temperature (5 soil levels) 5 .._rcm_fx contains: land/sea - and glacier mask, orographie (as geopotential) and soil moisture at field capacity . Abbreviatons in the dataset-acronyms: echam6: eh6 jsbach: jsb The variables of frequency 6hrPt on model levels are contained in the first and second dataset. However, ua and va have to be calculated from divergence and vorticity (e.g. with 'cdo dv2uv ...'). Spectral to gridpoint transformation can be done with 'cdo sp2gp ...'. Summary: RCM forcing data from the first realisation r1i1p1f1 of the CMIP6/CMIP DECK experiment amip (original name of the simulation "amip-HR"), conducted with the MPI-ESM1-2-HR on the Mistral supercomputer of the DKRZ. The experiment covers the years 1979 to 2014. The file format is gzip-compressed GRIB (*.grb.gz). CMIP6 website: https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip6 CMIP6 paper: https://www.geosci-model-dev.net/9/1937/2016/gmd-9-1937-2016.html Experiment description amip: An atmosphere only climate simulation using prescribed sea surface temperature and sea ice concentrations but with other conditions as in the Historical simulation.
DOI: 10.25502/brgp-tj11/d
title: Seed yam (Dioscorea rotundata Poir.) production from whole tubers versus minisetts 

description: An experiment was conducted to investigate the effects of using whole tubers versus minisetts to produce seed yams. Six treatments were combinations of whole tubers and minisetts and three tuber-size classes of 30 – 59 g, 60 - 89 g, and 90 – 120 g (referred to as 45 g, 75 g, and 105 g, respectively). The eExperiment was conducted as a Randomized Complete Block Design with three replications.
DOI: 10.34777/e480-td44
title: ODESSA

description: ODESSA is a speaker diarization dataset. The dataset contains 42 short conversations via VoIP, in pairs of speakers among 14 individuals. Pre-prepared scripts are given to the speakers, they will start reading their assigned roles. Each of the  speakers is using a PC. The session animator is using a third PC for recording while muting himself.
DOI: 10.5281/zenodo.4009138
title: Machine-learning method for predicting the scanning parameters influence on random measurement error

description: Data acompaniing the study.
DOI: 10.5281/zenodo.4005718
title: Machine-learning method for predicting the scanning parameters influence on random measurement error

description: Data acompaniing the study.
DOI: 10.34740/kaggle/dsv/1677507
title: Binary Dataset of Phishing and Legitimate URLs
DOI: 10.5281/zenodo.4282483
title: Database of Parenthetic Biomedical Abbreviations

description: This dataset includes the biomedical abbreviations stated between parentheses in the titles of the scholarly publications indexed by PubMed between 1947 and 2019. Each abbreviation is extracted thanks to the parenthetic level count algorithm and is assigned to the title, PMID and year of publication of each corresponding research paper. Then, every acronym is allocated its length and the number of upper and lower case letters it involves. Finally, the entities including one or no upper case letter, less than three characters, eight characters or more, or a high rate of non-alphanumeric characters are semi-automatically eliminated to ensure the consistency of the research database.
description: To cite the work: Turki, H., Hadj Taieb, M. A., & Ben Aouicha, M. (2020). Enhancing filter-based parenthetic abbreviation extraction methods. Journal of the American Medical Informatics Association. doi:10.1093/jamia/ocaa314.
DOI: 10.5281/zenodo.4281524
title: Database of Parenthetic Biomedical Abbreviations

description: This dataset includes the biomedical abbreviations stated between parentheses in the titles of the scholarly publications indexed by PubMed between 1947 and 2019. Each abbreviation is extracted thanks to the parenthetic level count algorithm and is assigned to the title, PMID and year of publication of each corresponding research paper. Then, every acronym is allocated its length and the number of upper and lower case letters it involves. Finally, the entities including one or no upper case letter, less than three characters, eight characters or more, or a high rate of non-alphanumeric characters are semi-automatically eliminated to ensure the consistency of the research database.
description: To cite the work: Turki, H., Hadj Taieb, M. A., & Ben Aouicha, M. (2020). Enhancing filter-based parenthetic abbreviation extraction methods. Journal of the American Medical Informatics Association. doi:10.1093/jamia/ocaa314.
DOI: 10.5281/zenodo.4288593
title: Options

description: Dataset for the paper entitled <strong>Does Introduction of Index Options Affect Stock Market Volatility? A Panel Data Evaluation Approach</strong>
DOI: 10.5281/zenodo.4288592
title: Options

description: Dataset for the paper entitled <strong>Does Introduction of Index Options Affect Stock Market Volatility? A Panel Data Evaluation Approach</strong>
DOI: 10.5281/zenodo.4286065
title: Broadband Dielectric Spectroscopy Study of Biobased Poly(alkylene 2,5-furanoate)s' Molecular Dynamics

description: <strong>Related publication:</strong><br> Soccio, M.; Martínez-Tong, D.E.; Guidotti, G.; Robles-Hernández, B.; Munari, A.; Lotti, N.; Alegria, A. Broadband Dielectric Spectroscopy Study of Biobased Poly(alkylene 2,5-furanoate)s’ Molecular Dynamics. <em>Polymers</em> 2020, <em>12</em>, 1355.<br> 10.3390/polym12061355 <strong>EUSMI proposal codes:</strong><br> E171100040, E171100043
DOI: 10.6084/m9.figshare.13277081
title: MHC-sexual selection-St Kilda Soay sheep

description: data for "An investigation of MHC-dependent sexual selection in a free-living population of sheep"
DOI: 10.5281/zenodo.4286064
title: Broadband Dielectric Spectroscopy Study of Biobased Poly(alkylene 2,5-furanoate)s' Molecular Dynamics

description: <strong>Related publication:</strong><br> Soccio, M.; Martínez-Tong, D.E.; Guidotti, G.; Robles-Hernández, B.; Munari, A.; Lotti, N.; Alegria, A. Broadband Dielectric Spectroscopy Study of Biobased Poly(alkylene 2,5-furanoate)s’ Molecular Dynamics. <em>Polymers</em> 2020, <em>12</em>, 1355.<br> 10.3390/polym12061355 <strong>EUSMI proposal codes:</strong><br> E171100040, E171100043
DOI: 10.5517/ccdc.csd.cc25g9zy
title: CCDC 2009760: Experimental Crystal Structure Determination

description: Related Article: Zhen-Lin Qiu, Chun Tang, Xin-Rong Wang, Yang-Yang Ju, Ke-Shan Chu, Ze-Ying Deng, Hao Hou, Yu-Min Liu, Yuan-Zhi Tan|2020|Angew.Chem.,Int.Ed.|59|20868|doi:10.1002/anie.202008505
DOI: 10.5517/ccdc.csd.cc25gb00
title: CCDC 2009761: Experimental Crystal Structure Determination

description: Related Article: Zhen-Lin Qiu, Chun Tang, Xin-Rong Wang, Yang-Yang Ju, Ke-Shan Chu, Ze-Ying Deng, Hao Hou, Yu-Min Liu, Yuan-Zhi Tan|2020|Angew.Chem.,Int.Ed.|59|20868|doi:10.1002/anie.202008505
DOI: 10.5517/ccdc.csd.cc25gb11
title: CCDC 2009762: Experimental Crystal Structure Determination

description: Related Article: Zhen-Lin Qiu, Chun Tang, Xin-Rong Wang, Yang-Yang Ju, Ke-Shan Chu, Ze-Ying Deng, Hao Hou, Yu-Min Liu, Yuan-Zhi Tan|2020|Angew.Chem.,Int.Ed.|59|20868|doi:10.1002/anie.202008505
DOI: 10.5517/ccdc.csd.cc25r1zz
title: CCDC 2018161: Experimental Crystal Structure Determination

description: Related Article: Zhen-Lin Qiu, Chun Tang, Xin-Rong Wang, Yang-Yang Ju, Ke-Shan Chu, Ze-Ying Deng, Hao Hou, Yu-Min Liu, Yuan-Zhi Tan|2020|Angew.Chem.,Int.Ed.|59|20868|doi:10.1002/anie.202008505
DOI: 10.17028/rd.lboro.13280489.v1
title: Supplementary information files for Cryopreservation of mesenchymal stem cells using medical grade ice nucleation inducer

description: Supplementary files for article Cryopreservation of mesenchymal stem cells using medical grade ice nucleation inducer. Mesenchymal stem cells (MSCs) can differentiate into multiple different tissue lineages and have favourable immunogenic potential making them an attractive prospect for regenerative medicine. As an essential part of the manufacturing process, preservation of these cells whilst maintaining potential is of critical importance. An uncontrolled area of storage remains the rate of change of temperature during freezing and thawing. Controlled-rate freezers attempted to rectify this; however, the change of phase from liquid to solid introduces two extreme phenomena; a rapid rise and a rapid fall in temperature in addition to the intended cooling rate (normally -1 °C/min) as a part of the supercooling event in cryopreservation. Nucleation events are well known to initiate the freezing transition although their active use in the form of ice nucleation devices (IND) are in their infancy in cryopreservation. This study sought to better understand the effects of ice nucleation and its active instigation with the use of an IND in both a standard cryotube with MSCs in suspension and a high-throughput adhered MSC 96-well plate set-up. A potential threshold nucleation temperature for best recovery of dental pulp MSCs may occur around -10 °C and for larger volume cell storage, IND and fast thaw creates the most stable process. For adhered cells, an IND with a slow thaw enables greatest metabolic activity post-thaw. This demonstrates a necessity for a medical grade IND to be used in future regenerative medicine manufacturing with the parameters discussed in this study to create stable products for clinical cellular therapies.
DOI: 10.17028/rd.lboro.13280489
title: Supplementary information files for Cryopreservation of mesenchymal stem cells using medical grade ice nucleation inducer

description: Supplementary files for article Cryopreservation of mesenchymal stem cells using medical grade ice nucleation inducer. Mesenchymal stem cells (MSCs) can differentiate into multiple different tissue lineages and have favourable immunogenic potential making them an attractive prospect for regenerative medicine. As an essential part of the manufacturing process, preservation of these cells whilst maintaining potential is of critical importance. An uncontrolled area of storage remains the rate of change of temperature during freezing and thawing. Controlled-rate freezers attempted to rectify this; however, the change of phase from liquid to solid introduces two extreme phenomena; a rapid rise and a rapid fall in temperature in addition to the intended cooling rate (normally -1 °C/min) as a part of the supercooling event in cryopreservation. Nucleation events are well known to initiate the freezing transition although their active use in the form of ice nucleation devices (IND) are in their infancy in cryopreservation. This study sought to better understand the effects of ice nucleation and its active instigation with the use of an IND in both a standard cryotube with MSCs in suspension and a high-throughput adhered MSC 96-well plate set-up. A potential threshold nucleation temperature for best recovery of dental pulp MSCs may occur around -10 °C and for larger volume cell storage, IND and fast thaw creates the most stable process. For adhered cells, an IND with a slow thaw enables greatest metabolic activity post-thaw. This demonstrates a necessity for a medical grade IND to be used in future regenerative medicine manufacturing with the parameters discussed in this study to create stable products for clinical cellular therapies.
DOI: 10.6084/m9.figshare.13280459
title: Eco-evolutionary consequences of climate change and size-selective fishing

description: This archive contains the model code and input for the simulation experiments, as well as their output data, published in: Ayllón, Nicola, Elvira, Almodóvar, in press. Climate change will render size-selective harvest of cold-water fish species unsustainable in Mediterranean freshwaters. Journal of Applied Ecology.<br><br>The archive consists of:<br><br>- One zip file containing the NetLogo code and all files needed to run the simulations: NetLogo extensions required by the software (six folders), input files to define the stream reach and perform the hydraulic modelling (two text files and two csv files), input files defining the temperature and flow time series for each of the three environmental scenarios simulated (three text files), one input file defining the setup of fishing scenarios (one text file), and a file defining the values of parameters that are not set up in the softwares’s interface (one nls file).<br><br>- One RData file containing the outputs of each simulation experiment performed. Outputs are divided into two data frames, one including population outputs and the other the phenotypic traits outputs. <br>
DOI: 10.6084/m9.figshare.13280459.v1
title: Eco-evolutionary consequences of climate change and size-selective fishing

description: This archive contains the model code and input for the simulation experiments, as well as their output data, published in: Ayllón, Nicola, Elvira, Almodóvar, in press. Climate change will render size-selective harvest of cold-water fish species unsustainable in Mediterranean freshwaters. Journal of Applied Ecology.<br><br>The archive consists of:<br><br>- One zip file containing the NetLogo code and all files needed to run the simulations: NetLogo extensions required by the software (six folders), input files to define the stream reach and perform the hydraulic modelling (two text files and two csv files), input files defining the temperature and flow time series for each of the three environmental scenarios simulated (three text files), one input file defining the setup of fishing scenarios (one text file), and a file defining the values of parameters that are not set up in the softwares’s interface (one nls file).<br><br>- One RData file containing the outputs of each simulation experiment performed. Outputs are divided into two data frames, one including population outputs and the other the phenotypic traits outputs. <br>