cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/nida.the.2006.275
title: ความสามารถในการแข่งขันของดิสเคาท์สโตร์และร้านโชวห่วยในเขตเทศบาลนครขอนแก่น
DOI: 10.14457/nida.the.1993.44
title: ประสิทธิผลการนำนโยบายป้องปรามทุจริตเลือกตั้งขององค์กรกลางไปปฏิบัติการ : วิจัยปฏิบัติการเรื่องการนำระบบข่าวสารข้อมูลด้านกว้างและด้านลึกเพื่อแจ้งเตือนผู้ที่อยู่ในข่ายเบาะแสละเมิดกฎหมายเลือกตั้งในเขตเลือกตั้ง ค จังหวัดนครศรีธรรมราช
DOI: 10.6084/m9.figshare.24026367
title: Rare detection of noncanonical proteins in yeast mass spectrometry studies

description: Data files for performing analyses in manuscript "Rare detection of noncanonical proteins in yeast mass spectrometry studies."
DOI: 10.6084/m9.figshare.24039429
title: Diameter at Breast Height (DBH) data of temperate zone trees from different woodland types.

description: Diameter at Breast Height (DBH) data of temperate zone trees, from different woodland types (semi-natural forest, wood-pasture, plantation)From semi-natural forests and wood-pastures, data is collected for Oak (Quercus), Hornbeam (Carpinus) and Beech (Fagus) trees.From plantations (two, approximatelly 10 and 15 years old plantations), data is collected for Poplar (Populus)) trees.
DOI: 10.6084/m9.figshare.24026367.v1
title: Rare detection of noncanonical proteins in yeast mass spectrometry studies

description: Data files for performing analyses in manuscript "Rare detection of noncanonical proteins in yeast mass spectrometry studies."
DOI: 10.6084/m9.figshare.24026367.v2
title: Rare detection of noncanonical proteins in yeast mass spectrometry studies

description: Data files for performing analyses in manuscript "Rare detection of noncanonical proteins in yeast mass spectrometry studies."
DOI: 10.5281/zenodo.8287690
title: amazona_xantholora_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8287689
title: amazona_xantholora_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23607693
title: patient63.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607729
title: patient33.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607681
title: patient48.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607738
title: patient68.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607732
title: patient67.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.5281/zenodo.8287714
title: mareca_sibilatrix_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8287713
title: mareca_sibilatrix_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.34740/kaggle/dsv/6374618
title: Balochi Language to English Translation Dataset
DOI: 10.5281/zenodo.8287718
title: mareca_sibilatrix_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8287717
title: mareca_sibilatrix_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23607756
title: patient31.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.20372232
title: Anaulus and Asterionellopsis

description: Molecular dataset composed of alignments and bayesian phylogenetic trees used to identify species of <i>Anaulus </i>and <i>Asterionellopsis </i>(diatoms) from Brazil in the manuscript: <b>Surf-diatoms from sandy beaches on the Eastern Coast of South America (Brazil</b><b>): the identification of </b><i><b>Anaulus </b></i><b>E</b><b>hrenberg and </b><i><b>Asterionellopsis </b></i><b>Round </b>published in <b>Botanica Marina. </b>DOI:10.1515/bot-2022-0067- Sequences deposited in Genbank were edited, aligned with the ClustalW algorithm in the MEGA-X Program.- These alignments were used to built the bayesian phylogenetic trees, the best-ﬁt model for each data matrix was estimated using the Akaike Information Criterion by the software JModeltest 2 and trees were built using the software MrBayes 3.2.3.- The alignments are in two formats (<b>.FAS</b> and <b>.NEXUS</b>) and were used as input to the Automatic Barcode Gap Discovery models for primary species delimitation (ABGD) and Assemble Species by Automatic Partitioning (ASAP).- The trees are in two formats: <b>.TRE</b> and <b>.NEXUS</b>. Trees composed of all sequences were used to understand the phylogenetic relationship between strains. While, trees composed only of haplotypes were used as input to the Poisson Tree Processes (PTP).<b>Funding</b><b>: </b>This work was supported by Brazilian funding agencies: CNPq Proc. 203883/2017-9; the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001; Brazilian Long-Term Ecological Research: CNPq/CAPES/FAPERGS/BC – Fundo Newton/PELD nº 15/2016More details on alignments and trees in the file README_MolecularData
DOI: 10.6084/m9.figshare.20372232.v3
title: Anaulus and Asterionellopsis

description: Molecular dataset composed of alignments and bayesian phylogenetic trees used to identify species of <i>Anaulus </i>and <i>Asterionellopsis </i>(diatoms) from Brazil in the manuscript: <b>Surf-diatoms from sandy beaches on the Eastern Coast of South America (Brazil</b><b>): the identification of </b><i><b>Anaulus </b></i><b>E</b><b>hrenberg and </b><i><b>Asterionellopsis </b></i><b>Round </b>published in <b>Botanica Marina. </b>DOI:10.1515/bot-2022-0067- Sequences deposited in Genbank were edited, aligned with the ClustalW algorithm in the MEGA-X Program.- These alignments were used to built the bayesian phylogenetic trees, the best-ﬁt model for each data matrix was estimated using the Akaike Information Criterion by the software JModeltest 2 and trees were built using the software MrBayes 3.2.3.- The alignments are in two formats (<b>.FAS</b> and <b>.NEXUS</b>) and were used as input to the Automatic Barcode Gap Discovery models for primary species delimitation (ABGD) and Assemble Species by Automatic Partitioning (ASAP).- The trees are in two formats: <b>.TRE</b> and <b>.NEXUS</b>. Trees composed of all sequences were used to understand the phylogenetic relationship between strains. While, trees composed only of haplotypes were used as input to the Poisson Tree Processes (PTP).<b>Funding</b><b>: </b>This work was supported by Brazilian funding agencies: CNPq Proc. 203883/2017-9; the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001; Brazilian Long-Term Ecological Research: CNPq/CAPES/FAPERGS/BC – Fundo Newton/PELD nº 15/2016More details on alignments and trees in the file README_MolecularData
DOI: 10.5281/zenodo.7016688
title: Remote sensing of the light-obscuring smoke properties in real-scale fires using a photometric measurement method

description: This data set complements the article https://doi.org/10.1007/s10694-023-01470-z. The data set contains the raw image data of three representative experiments and the corresponding input configuration data files for the LEDSA simulations. The data set contains: - The processed LEDSA simulation data of all experiments, mainly consisting of the measured and normalized intensities of all LEDs and the computed extinction coefficients according to the applied layer discretization (ledsa_simulations.zip). - The recorded measurement data of all experiments from three MIREX devices (MIREX.zip). - An exemplary data set consisting of the LEDSA raw data as RAW image files from three representative experiments in shortened form, containing every third image (image_data_{...}.zip). - LEDSA Input and Config files for analysis and simulation of the provided exemplary image data (ledsa_simulations_short.zip). - Python scripts for reading and post-processing the LESDA simulation data (postprocessing_tools.zip) - Juptyter Lab Python scripts that have been used to create the plots in the associated paper (data_analysis.zip). - The figures from the associated paper (figures.zip). Notes In order to run the Python scripts in Juptyer Labs properly, the given directory structure must be maintained, resulting when all archives are unpacked on the same hierarchical level. The authors gratefully acknowledge the financial support of the German Federal Ministry of Education and Research. The extensive LEDSA computations were performed largely on the high-performance computer system funded as part of the CoBra project with the grant number 13N15497.
DOI: 10.5281/zenodo.7016689
title: Remote sensing of the light-obscuring smoke properties in real-scale fires using a photometric measurement method

description: This data set complements the article https://doi.org/10.1007/s10694-023-01470-z. The data set contains the raw image data of three representative experiments and the corresponding input configuration data files for the LEDSA simulations. The data set contains: - The processed LEDSA simulation data of all experiments, mainly consisting of the measured and normalized intensities of all LEDs and the computed extinction coefficients according to the applied layer discretization (ledsa_simulations.zip). - The recorded measurement data of all experiments from three MIREX devices (MIREX.zip). - An exemplary data set consisting of the LEDSA raw data as RAW image files from three representative experiments in shortened form, containing every third image (image_data_{...}.zip). - LEDSA Input and Config files for analysis and simulation of the provided exemplary image data (ledsa_simulations_short.zip). - Python scripts for reading and post-processing the LESDA simulation data (postprocessing_tools.zip) - Juptyter Lab Python scripts that have been used to create the plots in the associated paper (data_analysis.zip). - The figures from the associated paper (figures.zip). Notes In order to run the Python scripts in Juptyer Labs properly, the given directory structure must be maintained, resulting when all archives are unpacked on the same hierarchical level. The authors gratefully acknowledge the financial support of the German Federal Ministry of Education and Research. The extensive LEDSA computations were performed largely on the high-performance computer system funded as part of the CoBra project with the grant number 13N15497.
DOI: 10.6084/m9.figshare.23607759
title: patient41.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607753
title: patient39.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607735
title: patient42.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607771
title: patient45.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607600
title: patient28.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.5517/ccdc.csd.cc2dzvs1
title: CCDC 2234194: Experimental Crystal Structure Determination

description: Related Article: Manas Jyoti Sarma, K. A. Sudarshana, Srihari Pabbaraja, Goverdhan Mehta|2023|J.Org.Chem.|88|12131|doi:10.1021/acs.joc.3c01279
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzvt2
title: CCDC 2234195: Experimental Crystal Structure Determination

description: Related Article: Manas Jyoti Sarma, K. A. Sudarshana, Srihari Pabbaraja, Goverdhan Mehta|2023|J.Org.Chem.|88|12131|doi:10.1021/acs.joc.3c01279
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzvv3
title: CCDC 2234196: Experimental Crystal Structure Determination

description: Related Article: Manas Jyoti Sarma, K. A. Sudarshana, Srihari Pabbaraja, Goverdhan Mehta|2023|J.Org.Chem.|88|12131|doi:10.1021/acs.joc.3c01279
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzvw4
title: CCDC 2234197: Experimental Crystal Structure Determination

description: Related Article: Manas Jyoti Sarma, K. A. Sudarshana, Srihari Pabbaraja, Goverdhan Mehta|2023|J.Org.Chem.|88|12131|doi:10.1021/acs.joc.3c01279
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzvy6
title: CCDC 2234199: Experimental Crystal Structure Determination

description: Related Article: Manas Jyoti Sarma, K. A. Sudarshana, Srihari Pabbaraja, Goverdhan Mehta|2023|J.Org.Chem.|88|12131|doi:10.1021/acs.joc.3c01279
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzvz7
title: CCDC 2234200: Experimental Crystal Structure Determination

description: Related Article: Manas Jyoti Sarma, K. A. Sudarshana, Srihari Pabbaraja, Goverdhan Mehta|2023|J.Org.Chem.|88|12131|doi:10.1021/acs.joc.3c01279
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzw09
title: CCDC 2234201: Experimental Crystal Structure Determination

description: Related Article: Manas Jyoti Sarma, K. A. Sudarshana, Srihari Pabbaraja, Goverdhan Mehta|2023|J.Org.Chem.|88|12131|doi:10.1021/acs.joc.3c01279
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.23607747
title: patient44.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607762
title: patient36.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607768
title: patient43.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607774
title: patient47.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.23607777
title: patient46.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.3761562.v2690
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: 10.5519/qd.ygk9sduv
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (9089 records)
DOI: 10.5281/zenodo.8287774
title: Bar graphs of DEMIX database tile classifications

description: The DEMIX database (Guth, 2023a) contains statistics from 6 test 1 arc second DEMs (ALOS, ASTER, CopDEM, FABDEM, NASADEM, and SRTM) compared to high resolution reference DEMs. The database contains 236 DEMIX tiles (Guth and others, 2023) and forms the basis for the ranking of global DEMs in Bielski and others (2023). A K-means clustering of the database using MICRODEM (Guth, 2023b, 2023c), and an additional set of 4 land cover and landform classifications (Table 1) for the 236 DEMIX tiles computed the percentage of each DEMIX tile in each classification category. Guth (2023d) has the raw data for the percentages of each category for each of the 236 tiles along with the K-means cluster assignments. This data set contains 3 figures for each of the 5 classification databases in Guth (2023d): Bar graph of the category percentages for each of the test areas. A composite version of these graphs is in Bielski and others (2023). Bar graph of the category percentages for each of the 236 test tiles. These graphs are too large to include on a single page with readable legends. Legend for the classification References: Bielski, C.; López-Vázquez, C.; Grohmann, C.H.; Guth. P.L.; and the TMSG DEMIX Working Group, 2023. DEMIX Method Ranks COPDEM, and FABDEM as Top 1” Global DEMs: https://arxiv.org/abs/2302.08425v3 Guth, P. L., 2023a. DEMIX GIS Database Version 2 (2.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8062008 Guth, P.L., 2023b. GIT-MICRODEM [Delphi source code, archived installation versions]. URL: https://github.com/prof-pguth/git_microdem Guth, P.L., 2023c, MICRODEM: Open-source GIS with a focus on Geomorphometry [download latest Win64 executable and CHM help file] URL: https://microdem.org/ Guth, P.L., 2023d, K-means clustering of the DEMIX data set (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8283791 Guth, Peter L., Peter Strobl, Kevin Gross, & Serge Riazanoff. (2023). DEMIX 10k Tile Data Set (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7504791
DOI: 10.5281/zenodo.8287773
title: Bar graphs of DEMIX database tile classifications

description: The DEMIX database (Guth, 2023a) contains statistics from 6 test 1 arc second DEMs (ALOS, ASTER, CopDEM, FABDEM, NASADEM, and SRTM) compared to high resolution reference DEMs. The database contains 236 DEMIX tiles (Guth and others, 2023) and forms the basis for the ranking of global DEMs in Bielski and others (2023). A K-means clustering of the database using MICRODEM (Guth, 2023b, 2023c), and an additional set of 4 land cover and landform classifications (Table 1) for the 236 DEMIX tiles computed the percentage of each DEMIX tile in each classification category. Guth (2023d) has the raw data for the percentages of each category for each of the 236 tiles along with the K-means cluster assignments. This data set contains 3 figures for each of the 5 classification databases in Guth (2023d): Bar graph of the category percentages for each of the test areas. A composite version of these graphs is in Bielski and others (2023). Bar graph of the category percentages for each of the 236 test tiles. These graphs are too large to include on a single page with readable legends. Legend for the classification References: Bielski, C.; López-Vázquez, C.; Grohmann, C.H.; Guth. P.L.; and the TMSG DEMIX Working Group, 2023. DEMIX Method Ranks COPDEM, and FABDEM as Top 1” Global DEMs: https://arxiv.org/abs/2302.08425v3 Guth, P. L., 2023a. DEMIX GIS Database Version 2 (2.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8062008 Guth, P.L., 2023b. GIT-MICRODEM [Delphi source code, archived installation versions]. URL: https://github.com/prof-pguth/git_microdem Guth, P.L., 2023c, MICRODEM: Open-source GIS with a focus on Geomorphometry [download latest Win64 executable and CHM help file] URL: https://microdem.org/ Guth, P.L., 2023d, K-means clustering of the DEMIX data set (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8283791 Guth, Peter L., Peter Strobl, Kevin Gross, & Serge Riazanoff. (2023). DEMIX 10k Tile Data Set (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7504791
DOI: 10.6084/m9.figshare.24039501
title: Event camera recordings of the wrists of subjects from which heart rates can be estimated

description: Event camera data from a Prophesee EVK4 event camera (Prophesee, Paris, France https://www.prophesee.ai/event-camera-evk4/) used to record the wrists of 25 subjects of mixed ages, genders and skin tones, all with resting heart rate and most also with elevated heart rate along with ground truth measurements of heart rate from an Apple Watch. Data is used to estimate HR from event stream data and compare to ground truth
DOI: 10.5281/zenodo.8287697
title: Dataset of experiment of wire-harness manufacturing framework validation

description: Dataset created during the validation experiments of the wire harness manufacturing framework developed within the REMODEL European project.
DOI: 10.5281/zenodo.8287698
title: Dataset of experiment of wire-harness manufacturing framework validation

description: Dataset created during the validation experiments of the wire harness manufacturing framework developed within the REMODEL European project.
DOI: 10.5281/zenodo.8287801
title: Genetic networks datasets: ten books by Gustave Roud, "En mer" by Bernard Comment

description: In genetic criticism, scholarly editing, authorial philology and, more generally, for the study of authorial manuscripts and writing processes it is essential to order and classify the textual witnesses and their relationships. The two datasets documents so-called ‘genetic networks’, representations of the genetic entities (witnesses, publications, dossiers) and of their relationships, modelled according to the GENO 1.0 ontology. The datasets contain genetic networks of the works of two Swiss authors: the main publications of Gustave Roud (1897-1976) and the short story “En mer” by Bernard Comment (1960).
DOI: 10.5281/zenodo.8287800
title: Genetic networks datasets: ten books by Gustave Roud, "En mer" by Bernard Comment

description: In genetic criticism, scholarly editing, authorial philology and, more generally, for the study of authorial manuscripts and writing processes it is essential to order and classify the textual witnesses and their relationships. The two datasets documents so-called ‘genetic networks’, representations of the genetic entities (witnesses, publications, dossiers) and of their relationships, modelled according to the GENO 1.0 ontology. The datasets contain genetic networks of the works of two Swiss authors: the main publications of Gustave Roud (1897-1976) and the short story “En mer” by Bernard Comment (1960).