cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7627292
title: Confocal data of Oncelytris esquamatus, holotype, NIGP200820

description: This dataset contains the raw confocal laser scanning microscopy (CLSM) slices for the holotype of <em>Oncelytris esquamatus</em> (NIGP200820) from mid-Cretaceous Burmese amber. This dataset is associated with the publication "<em>Oncelytris esquamatus</em> gen. et sp. nov. from mid-Cretaceous amber of northern Myanmar (Coleoptera: Lucanidae)" (DOI:10.11646/zootaxa.5284.1.10). Confocal images were obtained with a Zeiss LSM710 confocal laser scanning microscope, using the 488 nm (Argon) or 561 nm (DPSS 561-10) laser excitation line. The original CZI files are provided, which could be opened by the ZEISS ZEN software.
DOI: 10.5281/zenodo.6717396
title: Confocal data of Alloterocucus atratus, holotype, NIGP180056

description: This dataset contains the raw confocal laser scanning microscopy (CLSM) slices for the holotype of <em>Alloterocucus atratus</em> (NIGP180056) from mid-Cretaceous Burmese amber. This dataset is associated with the publication "An enigmatic beetle with affinity to Lamingtoniidae in mid-Cretaceous amber from northern Myanmar (Coleoptera: Cucujoidea)" (DOI:10.3389/fevo.2022.972343). Confocal images were obtained with a Zeiss LSM710 confocal laser scanning microscope, using the 488 nm (Argon) laser excitation line. The original CZI files are provided, which could be opened by the ZEISS ZEN software.
DOI: 10.5281/zenodo.6717395
title: Confocal data of Alloterocucus atratus, holotype, NIGP180056

description: This dataset contains the raw confocal laser scanning microscopy (CLSM) slices for the holotype of <em>Alloterocucus atratus</em> (NIGP180056) from mid-Cretaceous Burmese amber. This dataset is associated with the publication "An enigmatic beetle with affinity to Lamingtoniidae in mid-Cretaceous amber from northern Myanmar (Coleoptera: Cucujoidea)" (DOI:10.3389/fevo.2022.972343). Confocal images were obtained with a Zeiss LSM710 confocal laser scanning microscope, using the 488 nm (Argon) laser excitation line. The original CZI files are provided, which could be opened by the ZEISS ZEN software.
DOI: 10.34740/kaggle/dsv/5684976
title: Balochi Language to English Translation Dataset
DOI: 10.5281/zenodo.7935019
title: Edited Abalone Age dataset

description: Categorical data has been one-hot encoded which makes it ready for running experiments with e.g. KNN.
DOI: 10.5281/zenodo.7935018
title: Edited Abalone Age dataset

description: Categorical data has been one-hot encoded which makes it ready for running experiments with e.g. KNN.
DOI: 10.5281/zenodo.7856060
title: Predicting Pulsed Laser Deposition SrTiO3 Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction - sample untreated_162nm

description: RHEED intensity image dataset of sample <strong>untreated_162nm</strong> in work "Predicting Pulsed Laser Deposition SrTiO<sub>3 </sub>Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction."
DOI: 10.5281/zenodo.7856059
title: Predicting Pulsed Laser Deposition SrTiO3 Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction - sample untreated_162nm

description: RHEED intensity image dataset of sample <strong>untreated_162nm</strong> in work "Predicting Pulsed Laser Deposition SrTiO<sub>3 </sub>Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction."
DOI: 10.6084/m9.figshare.22811183
title: Supplementary Data: <strong>A diminutive new basilosaurid whale reveals the trajectory of the cetacean life histories during the Eocene</strong>

description: We have included three supplementary files to accompany our publication in Communications Biology titled <strong>[A diminutive new basilosaurid whale reveals the trajectory of the cetacean life histories during the Eocene]</strong>. These files provide additional information and data related to our phylogenetic analysis and ancestral state reconstructions. <strong>Supplementary Data 1</strong> and <strong>2</strong> are Nexus files that contain the archaeocete-dominated and pelagicete-dominated matrices of Tutcetus rayanensis used in our phylogenetic analysis, respectively. These files can be used to reproduce our analysis and provide additional insight into the evolutionary relationships of Tutcetus rayanensis. <strong>Supplementary Data 3</strong> is a zip file that contains the results from the ancestral state reconstructions (ASRs) on the allcompat trees derived from Bayesian tip-dating analyses. The ASRs provide information on the probable evolutionary history of various morphological and ecological traits in Tutcetus rayanensis and can be used to test hypotheses about the factors that drove the evolution of these traits. We hope that these supplementary files will be helpful to researchers interested in our study and provide a valuable resource for further research in this field.
DOI: 10.7303/syn21241740
title: RNAseq_Harmonization
DOI: 10.5281/zenodo.6350341
title: Datos de las especies de árboles descubiertas en Costa Rica entre 2000 y 2021

description: Véase la versión definitiva: https://doi.org/10.5281/zenodo.7935038 (CC BY 4.0)
DOI: 10.5281/zenodo.6350340
title: Datos de las especies de árboles descubiertas en Costa Rica entre 2000 y 2021

description: Véase la versión definitiva: https://doi.org/10.5281/zenodo.7935038 (CC BY 4.0)
DOI: 10.5281/zenodo.7552276
title: Datos de las nuevas especies de árboles descubiertas en Costa Rica entre 2000 y 2022

description: Véase la versión definitiva: https://doi.org/10.5281/zenodo.7935038 (CC BY 4.0)
DOI: 10.5281/zenodo.7552275
title: Datos de las nuevas especies de árboles descubiertas en Costa Rica entre 2000 y 2022

description: Véase la versión definitiva: https://doi.org/10.5281/zenodo.7935038 (CC BY 4.0)
DOI: 10.25345/c5r786008
title: MassIVE MSV000091940 - Diazobutanone-assisted isobaric labeling of phospholipids and sulfated glycolipids enables multiplexed quantitative lipidomics using LC-MS/MS
title: This Diazo-assisted method features remarkable performances, including labeling efficiency, detection sensitivity, quantitative accuracy, and broad applicability to various biological samples.
DOI: 10.5281/zenodo.7934927
title: Indus River Shapefile

description: This file contains Indus river shapefile made by referring Google hybrid satellite data in Qgis 3.28.1.
DOI: 10.5281/zenodo.7934928
title: Indus River Shapefile

description: This file contains Indus river shapefile made by referring Google hybrid satellite data in Qgis 3.28.1.
DOI: 10.5281/zenodo.7933483
title: CountryTable_1.9

description: Headcount data under the 1.9$ international extreme poverty line. isInterpolated - For the years for which census or national estimates are not available, the population figures are interpolated or extrapolated. 0 - No / 1 - Yes <br> useMicroData - Microdata are unit-level data obtained from sample surveys, censuses, and administrative systems. They provide information about characteristics of individual people or entities such as households, business enterprises, facilities, farms or even geographical areas such as villages or towns. They allow in-depth understanding of socio-economic issues by studying relationships and interactions among phenomena. Microdata are thus key to designing projects and formulating policies, targeting interventions and monitoring and measuring the impact and results of projects, interventions and policies. 0 - No / 1 - Yes CountryCode - The country code table includes the WITS System country names for statistical purposes and both the International Standards Organization (ISO) 3-digit alphabetic codes and the United Nations Statistics Division (UNSD) 3-digit equivalent numeric codes. The names and codes are used in all of the three databases. CountryName - The name of the country RegionCode - East Asia and Pacific ,Europe and Central Asia ,Latin America and Caribbean ,Middle East and North Africa ,North America ,South Asia ,Sub-Saharan Africa<br> <br> RequestYear - The year the data is related to. DataYear - When requested the data<br> <br> PPP (Purchasing Power Parity) - Purchasing power parity is a measurement of the price of specific goods in different countries and is used to compare the absolute purchasing power of the countries' currencies.<br> <br> PovertyLine - The 1.9$ <br> <br> PovGap - Poverty Gap Index<br> <br> PovGapSqr - The Poverty Gap Squared
DOI: 10.5281/zenodo.7933482
title: CountryTable_1.9

description: Headcount data under the 1.9$ international extreme poverty line. isInterpolated - For the years for which census or national estimates are not available, the population figures are interpolated or extrapolated. 0 - No / 1 - Yes <br> useMicroData - Microdata are unit-level data obtained from sample surveys, censuses, and administrative systems. They provide information about characteristics of individual people or entities such as households, business enterprises, facilities, farms or even geographical areas such as villages or towns. They allow in-depth understanding of socio-economic issues by studying relationships and interactions among phenomena. Microdata are thus key to designing projects and formulating policies, targeting interventions and monitoring and measuring the impact and results of projects, interventions and policies. 0 - No / 1 - Yes CountryCode - The country code table includes the WITS System country names for statistical purposes and both the International Standards Organization (ISO) 3-digit alphabetic codes and the United Nations Statistics Division (UNSD) 3-digit equivalent numeric codes. The names and codes are used in all of the three databases. CountryName - The name of the country RegionCode - East Asia and Pacific ,Europe and Central Asia ,Latin America and Caribbean ,Middle East and North Africa ,North America ,South Asia ,Sub-Saharan Africa<br> <br> RequestYear - The year the data is related to. DataYear - When requested the data<br> <br> PPP (Purchasing Power Parity) - Purchasing power parity is a measurement of the price of specific goods in different countries and is used to compare the absolute purchasing power of the countries' currencies.<br> <br> PovertyLine - The 1.9$ <br> <br> PovGap - Poverty Gap Index<br> <br> PovGapSqr - The Poverty Gap Squared
DOI: 10.5281/zenodo.7935056
title: Data World Bank Indicators

description: The Dataset consist of the indicators which are used to select datasets using the library:<br> import world_bank_data as wb # https://github.com/mwouts/world_bank_data<br> method wb.get_series<br> <br> indicators_education.csv<br> indicators_gender.csv<br> indicators_health.csv<br> indicators_worlddevelopment.csv<br> <br> The files are combined together in the corresponding csv files:<br> wb_education.csv', <br> wb_gender.csv', <br> wb_health.csv', <br> wb_worlddev.csv'<br> <br> <br> <br> They have the following licenses:<br> https://datacatalog.worldbank.org/public-licenses#cc-by
DOI: 10.5281/zenodo.7935055
title: Data World Bank Indicators

description: The Dataset consist of the indicators which are used to select datasets using the library:<br> import world_bank_data as wb # https://github.com/mwouts/world_bank_data<br> method wb.get_series<br> <br> indicators_education.csv<br> indicators_gender.csv<br> indicators_health.csv<br> indicators_worlddevelopment.csv<br> <br> The files are combined together in the corresponding csv files:<br> wb_education.csv', <br> wb_gender.csv', <br> wb_health.csv', <br> wb_worlddev.csv'<br> <br> <br> <br> They have the following licenses:<br> https://datacatalog.worldbank.org/public-licenses#cc-by
DOI: 10.5281/zenodo.7935060
title: Extreme Poverty Headcount Change

description: We classify countries into 5 categories based on the change of the extreme poverty headcount between 1990 and 2015. A country is defined as poor if more than 10% of its population is living in extreme poverty. The categories are: <strong>Rich Countries (R)</strong>: Countries that have a value of extreme poverty headcount below 10% in 1990 and in 2015 <strong>Emerging Countries 1 (E_R1)</strong>: Countries that have a value of extreme poverty headcount above 10% in 1990 and below 10% in 2015 with a decrease in this value of 50% or more (head count in 2015 is half or less than half of what it was in 1990) <strong>Emerging Countries 2 (E_R2)</strong>: Countries that have a value of extreme poverty headcount above 10% in 1990 and still above 10% in 2015 with a decrease in this value of more than 50% (head count is lower in 2015 but still above 10%) <strong>Non-emerging countries (NE)</strong>: Countries where the head count in 1990 was more than 10% and still more than 10% in 2015 with a reduction of less than 50% <strong>Countries going into extreme poverty (B)</strong>: Countries with less than 10% head count in 1990 and more than 10% in 2015
DOI: 10.5281/zenodo.7935059
title: Extreme Poverty Headcount Change

description: We classify countries into 5 categories based on the change of the extreme poverty headcount between 1990 and 2015. A country is defined as poor if more than 10% of its population is living in extreme poverty. The categories are: <strong>Rich Countries (R)</strong>: Countries that have a value of extreme poverty headcount below 10% in 1990 and in 2015 <strong>Emerging Countries 1 (E_R1)</strong>: Countries that have a value of extreme poverty headcount above 10% in 1990 and below 10% in 2015 with a decrease in this value of 50% or more (head count in 2015 is half or less than half of what it was in 1990) <strong>Emerging Countries 2 (E_R2)</strong>: Countries that have a value of extreme poverty headcount above 10% in 1990 and still above 10% in 2015 with a decrease in this value of more than 50% (head count is lower in 2015 but still above 10%) <strong>Non-emerging countries (NE)</strong>: Countries where the head count in 1990 was more than 10% and still more than 10% in 2015 with a reduction of less than 50% <strong>Countries going into extreme poverty (B)</strong>: Countries with less than 10% head count in 1990 and more than 10% in 2015
DOI: 10.18113/d3t88n
title: Eddy covariance flux tower data for Indianapolis, IN (INFLUX project)

description: As part of the Indianapolis Flux (INFLUX) experiment, the accuracy and biases of simulated meteorological fields were assessed for the city of Indianapolis, IN. A variety of meteorological observations were collected, including eddy covariance data. The flux tower, located east of downtown Indianapolis,utilizes a sonic anemometer (Campbell Scientific; CSAT-3), and a high-frequency open-path infrared water vapor and CO2 sensor (LI-COR Environmental; LI-7500). The flux instrumentation is mounted on a communications tower at a height of 30 meters.
DOI: 10.25919/debv-rs70
title: Parkes observations for project P1054 semester 2023APRS_02

description: With this proposal we ask time to continue our timing follow-up campaign of pulsars discovered with the MeerKAT telescope. Twenty sources have been discovered in targeted observations of Fermi unidentified point sources, one in association with a Supernova Remnant, 13 in the Magellanic Clouds, 71 in Globular Clusters and 74 in a survey of the Galactic plane. A large fraction of the new discoveries are recycled pulsars (including at least one double neutron star system and several 'spider' binaries), or young pulsars. Timing observations have an essential role in exploiting the full potential of any pulsar discovery, allowing the precise measurement of rotational, astrometric and orbital parameters which, in turn, give us powerful tools to improve our understanding of the physics in extreme environments as well as of the population of neutron stars as a whole. The UWL receiver of the Parkes telescope is a sensitive, versatile instrument that is allowing us to successfully time these new sources, in the bright-end of TRAPUM discoveries.
DOI: 10.34740/kaggle/dsv/5685262
title: #ChatGPT 1000 Daily 🐦 Tweets
DOI: 10.25345/c5mg7g56h
title: MassIVE MSV000091941 - Diazobutanone-assisted isobaric labeling of phospholipids and sulfated glycolipids enables multiplexed quantitative lipidomics using LC-MS/MS
title: This Diazo-assisted method features remarkable performances, including labeling efficiency, detection sensitivity, quantitative accuracy, and broad applicability to various biological samples.
DOI: 10.6084/m9.figshare.3761562.v2586
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: 10.5517/ccdc.csd.cc2dd4qp
title: CCDC 2216212: Experimental Crystal Structure Determination

description: Related Article: Thomas L. Morrison, Indrani Bhowmick, Matthew P. Shores|2023|Cryst.Growth Des.|23|3186|doi:10.1021/acs.cgd.2c01347
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.cc2dd4rq
title: CCDC 2216213: Experimental Crystal Structure Determination

description: Related Article: Thomas L. Morrison, Indrani Bhowmick, Matthew P. Shores|2023|Cryst.Growth Des.|23|3186|doi:10.1021/acs.cgd.2c01347
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.cc2dd4sr
title: CCDC 2216214: Experimental Crystal Structure Determination

description: Related Article: Thomas L. Morrison, Indrani Bhowmick, Matthew P. Shores|2023|Cryst.Growth Des.|23|3186|doi:10.1021/acs.cgd.2c01347
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.cc2dd4ts
title: CCDC 2216215: Experimental Crystal Structure Determination

description: Related Article: Thomas L. Morrison, Indrani Bhowmick, Matthew P. Shores|2023|Cryst.Growth Des.|23|3186|doi:10.1021/acs.cgd.2c01347
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.cc2djqym
title: CCDC 2220621: Experimental Crystal Structure Determination

description: Related Article: Priyank Kumar Sharma, Akanksha Babbar, Dibyendu Mallick, Soumyajit Das|2023|J.Org.Chem.|88|5473|doi:10.1021/acs.joc.2c03103
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.22439257
title: Datasets underlying Li et al 2023 Nature Communications: Breakdown of self-incompatibility due to genetic interaction between a specific S-allele and an unlinked modifier

description: To understand the different datasets and the cross-links between them, we have provided a list with the meaning of each column name. <br> We hope this information facilitates understanding our data, and allows re-analysis from scratch or with the help of the R-code provided. However, should anything be unclear, please do not hesitate to contact us in case any queries arise: health and personal circumstances permitting, we will do our best to help and then update the documentation.
DOI: 10.6084/m9.figshare.22439257.v1
title: Datasets underlying Li et al 2023 Nature Communications: Breakdown of self-incompatibility due to genetic interaction between a specific S-allele and an unlinked modifier

description: To understand the different datasets and the cross-links between them, we have provided a list with the meaning of each column name. <br> We hope this information facilitates understanding our data, and allows re-analysis from scratch or with the help of the R-code provided. However, should anything be unclear, please do not hesitate to contact us in case any queries arise: health and personal circumstances permitting, we will do our best to help and then update the documentation.
DOI: 10.6084/m9.figshare.22439257.v2
title: Datasets underlying Li et al 2023 Nature Communications: Breakdown of self-incompatibility due to genetic interaction between a specific S-allele and an unlinked modifier

description: To understand the different datasets and the cross-links between them, we have provided a list with the meaning of each column name. <br> We hope this information facilitates understanding our data, and allows re-analysis from scratch or with the help of the R-code provided. However, should anything be unclear, please do not hesitate to contact us in case any queries arise: health and personal circumstances permitting, we will do our best to help and then update the documentation.
DOI: 10.5281/zenodo.7933488
title: Sound stimuli: Considerations for the perceptual evaluation of steady-state and time-varying sounds using psychoacoustic metrics

description: The current dataset provides all the sound stimuli (wav files) to recreate the figures from the study with the title "Considerations for the perceptual evaluation of steady-state and time-varying sounds using psychoacoustic metrics" by the same authors. There are three datasets: <strong>dataset 1</strong> for fly-by aircraft sounds (directory <em>1-Aircraft-fly-by</em>), <strong>dataset 2</strong> for pass-by train sounds (directory <em>2-Train-pass-by</em>), and <strong>dataset 3</strong> for sounds from a resonating tube called hummer (directory <em>3-Hummer-resonances</em>). A brief description of the datasets is included. The reproduction of figures requires the installation of the sound quality analysis toolbox (SQAT) for MATLAB. <strong>Use these data</strong>:<br> Download all these data, locate them in a local directory of your computer. If you have MATLAB and you downloaded a local copy of the <strong>SQAT toolbox</strong> (open access at: https://github.com/ggrecow/SQAT) you can recreate the figures of our paper. After downloading and initialising the toolbox (type 'startup_SQAT;', without quotation marks in MATLAB), run the script <strong>copy_sounds_for_pub_Osses2023c_to_SQAT.m</strong>. This last step is not required but recommended. Subsequently, you can run the toolbox script pub_Osses2023c_Forum_Acusticum_SQAT.m and follow the instructions on screen.
description: Author AO received funding from French National Research Agency (ANR, project: 17-EURE-0017). Author GFG received funding from the Deutsche Forschungsgemeinschaft (DFG, EXC 2163/1, project: 390881007).