cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc25y5my
title: CCDC 2024040: Experimental Crystal Structure Determination

description: Related Article: Ross F. Koby, Alicia M. Doerr, Nicholas R. Rightmire, Nathan D. Schley, William W. Brennessel, Brian K. Long, Timothy P. Hanusa|2021|Chem.-Eur.J.|27|8195|doi:10.1002/chem.202100589
DOI: 10.5517/ccdc.csd.cc270mfb
title: CCDC 2056181: Experimental Crystal Structure Determination

description: Related Article: Liaokuo Gong, Fuquan Huang, Zhizhuan Zhang, Yu Zhong, Jiance Jin, Kezhao Du, Xiaoying Huang|2021|Chem.Eng.Journal|424|130544|doi:10.1016/j.cej.2021.130544
DOI: 10.5517/ccdc.csd.cc2760n4
title: CCDC 2061365: Experimental Crystal Structure Determination

description: Related Article: Zeki KARTAL, Onur ŞAHİN|2021|J.Mol.Struct.|1243|130720|doi:10.1016/j.molstruc.2021.130720
DOI: 10.6084/m9.figshare.14774709
title: Association of dopamine D2 receptor (DRD2) C939T and a lack of association of Tumor Factor-β (TNF-β) +A252G polymorphisms with susceptibility to Migraine in A Northern Iranian population

description: Two single nucleotide polymorphisms (SNPs) in TNF and <i>DRD2</i> genes (<i>TNF-β +A252G</i> and <i>DRD2 C939T</i>) were genotyped by PCR restriction fragment length polymorphism (PCR-RFLP). The forward and reverse primer sequences for the two SNPs are listed in table 1. Finally, to ensure the reliability of the PCR–RFLP results, the PCR products were sequenced by the Sanger sequencing method, and sequences of the PCR products were analyzed by the Codon Code Aligner software.
DOI: 10.6084/m9.figshare.14774709.v2
title: Association of dopamine D2 receptor (DRD2) C939T and a lack of association of Tumor Factor-β (TNF-β) +A252G polymorphisms with susceptibility to Migraine in A Northern Iranian population

description: Two single nucleotide polymorphisms (SNPs) in TNF and <i>DRD2</i> genes (<i>TNF-β +A252G</i> and <i>DRD2 C939T</i>) were genotyped by PCR restriction fragment length polymorphism (PCR-RFLP). The forward and reverse primer sequences for the two SNPs are listed in table 1. Finally, to ensure the reliability of the PCR–RFLP results, the PCR products were sequenced by the Sanger sequencing method, and sequences of the PCR products were analyzed by the Codon Code Aligner software.
DOI: 10.6084/m9.figshare.14774709.v1
title: Association of dopamine D2 receptor (DRD2) C939T and a lack of association of Tumor Factor-β (TNF-β) +A252G polymorphisms with susceptibility to Migraine in A Northern Iranian population

description: Two single nucleotide polymorphisms (SNPs) in TNF and <i>DRD2</i> genes (<i>TNF-β +A252G</i> and <i>DRD2 C939T</i>) were genotyped by PCR restriction fragment length polymorphism (PCR-RFLP). The forward and reverse primer sequences for the two SNPs are listed in table 1. Finally, to ensure the reliability of the PCR–RFLP results, the PCR products were sequenced by the Sanger sequencing method, and sequences of the PCR products were analyzed by the Codon Code Aligner software.
DOI: 10.6084/m9.figshare.14774757
title: Fate and stability of dissolved organic carbon in topsoils and subsoils under beech forests _ Data

description: Raw and processed data and R script for the BGC paper "Fate and stability of dissolved organic carbon in topsoils and subsoils under beech forests"<br>
DOI: 10.6084/m9.figshare.14774757.v1
title: Fate and stability of dissolved organic carbon in topsoils and subsoils under beech forests _ Data

description: Raw and processed data and R script for the BGC paper "Fate and stability of dissolved organic carbon in topsoils and subsoils under beech forests"<br>
DOI: 10.34740/kaggle/dsv/2327130
title: Credit Risk dataset
DOI: 10.5517/ccdc.csd.cc27bf12
title: CCDC 2065593: Experimental Crystal Structure Determination

description: Related Article: Alejandro Cabrera-García, Vincent Blay, Rubén Blay-Roger, Ángel G. Ravelo, Javier González-Platas, M. Carmen Arévalo, Joaquín Sanchiz, Pedro Martín-Zarza|2021|Chem.Eng.Journal|420|130342|doi:10.1016/j.cej.2021.130342
DOI: 10.5517/ccdc.csd.cc27n2vv
title: CCDC 2074887: Experimental Crystal Structure Determination

description: Related Article: Mazarine Laurent, Stéphane Bostyn, Mathieu Marchivie, Yves Robin, Sylvain Routier, Frédéric Buron|2021|RSC Advances|11|19363|doi:10.1039/D1RA03092B
DOI: 10.5517/ccdc.csd.cc254fpg
title: CCDC 2000265: Experimental Crystal Structure Determination

description: Related Article: Shou-Kun Zhang, Antonio Del Vecchio, Rositha Kuniyil, Antonis M. Messinis, Zhipeng Lin, Lutz Ackermann|2021|Cell Press: Chem|7|1379|doi:10.1016/j.chempr.2021.04.009
DOI: 10.6084/m9.figshare.14774763
title: KDDTrain+

description: The full NSL-KDD train set including attack-type labels and difficulty level in CSV format
DOI: 10.6084/m9.figshare.14774754.v1
title: MiniPlaces

description: The MiniPlaces dataset contains 100 classes randomly chosen from Places dataset with 600 images of size 84×84 pixels per class. It is split into 64 base classes, 16 validation classes and 20 novel classes.
DOI: 10.6084/m9.figshare.14774754
title: MiniPlaces

description: The MiniPlaces dataset contains 100 classes randomly chosen from Places dataset with 600 images of size 84×84 pixels per class. It is split into 64 base classes, 16 validation classes and 20 novel classes.
DOI: 10.6084/m9.figshare.14774748
title: Dados_CPI_Pandemia

description: Dados referentes a CPI da Pandemia.
DOI: 10.6084/m9.figshare.14774748.v1
title: Dados_CPI_Pandemia

description: Dados referentes a CPI da Pandemia.
DOI: 10.5281/zenodo.4937322
title: Dataset of Tropical cyclone risk assessment in Guangdong

description: The dataset uses multi-source datasets (TC, remote sensing, meteorological, vector, and socioeconomic data) from various domestic and international data platforms and institutions .The TC best track data was obtained at the Japan Meteorological Agency (JMA) (http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/besttrack.html) and Japan typhoon Digital Center (http://agora.ex.nii.ac.jp/digital-typhoon ).Tropical cyclone information for past tropical cyclones includes the position, central pressure, moving velocity, duration time ,moving distance and intensity of each TC from 1951-2018 for every six hour. Remote sensing data include digital elevation model (DEM), normalized difference vegetation index (NDVI), land use, and land cover. Meteorological data include the wind speed and total precipitation.Total precipitation and wind speed is in the period of 2010-2018 , collected respectively from China Meterological Administration(http://data.cma.cn),.Socioeconomic data include the population density, GDP, and historical disaster loss.The data of population density, GDP and vegetation index were obtained from spatial grid datasets of the Chinese population, GDP and vegetation index based on 1km spatial resolution.Land use and cover data was from multi period land use and cover remote sensing datasets in China (CNLUCC), and all these datasets is available at Resource and Environment data Cloud Platform provided by Institute of geography, resources and environment, Chinese Academy of Sciences(http://www.resdc.cn). DEM data was deprived from Aster GDEM v2 at 30 m resolution, available at United States Geological Survey (USGS Earth Explorer site in Center for Earth Observation.The indicator of Slope is calculated from the DEM data..Vector data include road networks, railway networks, water networks, coastlines and point of interest (POI) data such as the medical, public, and educational infrastructure and charitable organizations in the cities of Guangdong.The Indicator of coastline,river density ,railway were deprived from 1: 1 million National basic geographic information dataset (2017 version)in National Basic Geographic Information Center.
DOI: 10.5281/zenodo.4937321
title: Dataset of Tropical cyclone risk assessment in Guangdong

description: The dataset uses multi-source datasets (TC, remote sensing, meteorological, vector, and socioeconomic data) from various domestic and international data platforms and institutions .The TC best track data was obtained at the Japan Meteorological Agency (JMA) (http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/besttrack.html) and Japan typhoon Digital Center (http://agora.ex.nii.ac.jp/digital-typhoon ).Tropical cyclone information for past tropical cyclones includes the position, central pressure, moving velocity, duration time ,moving distance and intensity of each TC from 1951-2018 for every six hour. Remote sensing data include digital elevation model (DEM), normalized difference vegetation index (NDVI), land use, and land cover. Meteorological data include the wind speed and total precipitation.Total precipitation and wind speed is in the period of 2010-2018 , collected respectively from China Meterological Administration(http://data.cma.cn),.Socioeconomic data include the population density, GDP, and historical disaster loss.The data of population density, GDP and vegetation index were obtained from spatial grid datasets of the Chinese population, GDP and vegetation index based on 1km spatial resolution.Land use and cover data was from multi period land use and cover remote sensing datasets in China (CNLUCC), and all these datasets is available at Resource and Environment data Cloud Platform provided by Institute of geography, resources and environment, Chinese Academy of Sciences(http://www.resdc.cn). DEM data was deprived from Aster GDEM v2 at 30 m resolution, available at United States Geological Survey (USGS Earth Explorer site in Center for Earth Observation.The indicator of Slope is calculated from the DEM data..Vector data include road networks, railway networks, water networks, coastlines and point of interest (POI) data such as the medical, public, and educational infrastructure and charitable organizations in the cities of Guangdong.The Indicator of coastline,river density ,railway were deprived from 1: 1 million National basic geographic information dataset (2017 version)in National Basic Geographic Information Center.
DOI: 10.5281/zenodo.4934761
title: ForManuscriptsubmittoJGRas2020JD033940

description: This data was the updated to plot figures and tables in Paper # 2020JD033940 submitted to JGR on 12nd, 6, October.
DOI: 10.6084/m9.figshare.14774770.v1
title: test

description: Test
DOI: 10.21227/dfvb-re49
title: 8 years of hourly heat and electricity demand for a residential building

description: The heating and electricity consumption data are the results of an energy audit program aggregated for multiple load profiles of a residential customer. These profiles include HVAC systems loads, convenience power, elevator, etc. The datasets are gathered between December 2010 and November 2018 with a one-hour timestep resolution, thereby containing 140,160 measurements, half of which is for heat or electricity. In addition to the historical energy consumption values, a concatenation of weather variables is also available. The weather variables are air pressure, temperature, and humidity plus wind speed, cloudiness percentage, and solar irradiation at the predetermined location.
DOI: 10.5281/zenodo.4927421
title: Data set for Probing Vibrational Symmetry Effects and Nuclear Spin Economy Principles in Molecular Spin Qubits

description: One file with the description of the data for the publication Probing Vibrational Symmetry Effects and Nuclear Spin Economy Principles in Molecular Spin Qubits Inorg. Chem. 2021, 60, 140−151 https://doi.org/10.1021/acs.inorgchem.0c02573 One zip file with data in ascii format used to generate the figures of the manuscript
DOI: 10.5281/zenodo.4927420
title: Data set for Probing Vibrational Symmetry Effects and Nuclear Spin Economy Principles in Molecular Spin Qubits

description: One file with the description of the data for the publication Probing Vibrational Symmetry Effects and Nuclear Spin Economy Principles in Molecular Spin Qubits Inorg. Chem. 2021, 60, 140−151 https://doi.org/10.1021/acs.inorgchem.0c02573 One zip file with data in ascii format used to generate the figures of the manuscript
DOI: 10.5281/zenodo.4896516
title: Unveiling process insights from refactoring practices

description: Dataset for experiment replication
DOI: 10.5281/zenodo.4896515
title: Unveiling process insights from refactoring practices

description: Dataset for experiment replication
DOI: 10.18112/openneuro.ds003688.v1.0.6
title: Open multimodal iEEG-fMRI dataset from naturalistic stimulation with a short audiovisual film
DOI: 10.5281/zenodo.4924099
title: Threatened by the Worst but Hoping for the Best: Unraveling the Relationship Between Threat , Hope, and Public Opinion during Conflict

description: Dataset, Codebook, and Codes for the article: <strong>Threatened by the Worst but Hoping for the Best: Unraveling the Relationship Between Threat, Hope, and Public Opinion during Conflict.</strong> <strong>Political Behavior</strong>
DOI: 10.5281/zenodo.4924098
title: Threatened by the Worst but Hoping for the Best: Unraveling the Relationship Between Threat , Hope, and Public Opinion during Conflict

description: Dataset, Codebook, and Codes for the article: <strong>Threatened by the Worst but Hoping for the Best: Unraveling the Relationship Between Threat, Hope, and Public Opinion during Conflict.</strong> <strong>Political Behavior</strong>
DOI: 10.5281/zenodo.4937947
title: Raw data and figures for "Increasing Sensitivity and Versatility in NMR Supersequences with New HSQC-based Modules"

description: Datasets, pulse programmes, processing scripts, and figures for the publication "Increasing Sensitivity and Versatility in NMR Supersequences with New HSQC-based Modules" (J. Magn. Reson., accepted, 2021). Please see the README.txt file for more information. If you are only interested in pulse programmes and processing scripts, then this dataset will likely be too big for your liking (it is ca. 9 GB because there is a lot of 2D data). You can download the pulse programmes and processing scripts from the Bruker User Library https://www.bruker.com/en/services/bruker-user-library.html.
DOI: 10.5519/qd.pfp26x8p
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.14766102.v10
title: antspyt1w helper data

description: downloadable cloud data for testing and processing
DOI: 10.21227/05e7-xs69
title: DeepDarts Dataset

description: The accompanying dataset for the CVSports 2021 paper: DeepDarts: Modeling Keypoints as Objects for Automatic Scoring in Darts using a Single CameraPaper Abstract:Existing multi-camera solutions for automatic scorekeeping in steel-tip darts are very expensive and thus inaccessible to most players. Motivated to develop a more accessible low-cost solution, we present a new approach to keypoint detection and apply it to predict dart scores from a single image taken from any camera angle. This problem involves detecting multiple keypoints that may be of the same class and positioned in close proximity to one another. The widely adopted framework for regressing keypoints using heatmaps is not well-suited for this task. To address this issue, we instead propose to model keypoints as objects. We develop a deep convolutional neural network around this idea and use it to predict dart locations and dartboard calibration points within an overall pipeline for automatic dart scoring, which we call DeepDarts. Additionally, we propose several task-specific data augmentation strategies to improve the generalization of our method. As a proof of concept, two datasets comprising 16k images originating from two different dartboard setups were manually collected and annotated to evaluate the system. In the primary dataset containing 15k images captured from a face-on view of the dartboard using a smartphone, DeepDarts predicted the total score correctly in 94.7% of the test images. In a second more challenging dataset containing limited training data (830 images) and various camera angles, we utilize transfer learning and extensive data augmentation to achieve a test accuracy of 84.0%. Because DeepDarts relies only on single images, it has the potential to be deployed on edge devices, giving anyone with a smartphone access to an automatic dart scoring system for steel-tip darts. The code and datasets are available.
DOI: 10.34740/kaggle/dsv/2327569
title: Vietnam SARS-CoV-2 | COVID-19 Data
DOI: 10.6084/m9.figshare.14766102.v11
title: antspyt1w helper data

description: downloadable cloud data for testing and processing
DOI: 10.25573/data.14774802
title: (mg) No 6. MAG04 Phylogenomic Analysis (metagenome) Output

description: Files generated from the pangenomic (<b>01_MAG04_PAN</b>/) and phylogenomic (<b>02_MAG04_PHYLOGENOMICS</b>) analyses of MAG04. You can use the anvi'o commands described in the workflow to visualize the data.
DOI: 10.25573/data.14774802.v1
title: (mg) No 6. MAG04 Phylogenomic Analysis (metagenome) Output

description: Files generated from the pangenomic (<b>01_MAG04_PAN</b>/) and phylogenomic (<b>02_MAG04_PHYLOGENOMICS</b>) analyses of MAG04. You can use the anvi'o commands described in the workflow to visualize the data.
DOI: 10.34740/kaggle/dsv/2327705
title: Printed Digits Dataset
DOI: 10.34740/kaggle/dsv/2327131
title: Credit Risk Analysis
DOI: 10.5281/zenodo.4932159
title: Single Cell RNA Sequencing of Human Dura Reveals Cellular Meningeal Landscape and Insights into Meningioma Immune Response

description: Single-cell RNA-sequencing data (feature-barcode matrices) of human dura generated using the 5' Gene Expression Solution (10x Genomics).
DOI: 10.5281/zenodo.4939043
title: Single Cell RNA Sequencing of Human Dura Reveals Cellular Meningeal Landscape and Insights into Meningioma Immune Response

description: Placeholder text
DOI: 10.5281/zenodo.4938736
title: Raw data and figures for "Increasing Sensitivity and Versatility in NMR Supersequences with New HSQC-based Modules"

description: Datasets, pulse programmes, processing scripts, and figures for the publication "Increasing Sensitivity and Versatility in NMR Supersequences with New HSQC-based Modules" (J. Magn. Reson., accepted, 2021). Please see the README.txt file for more information. If you are only interested in pulse programmes and processing scripts, then this dataset will likely be too big for your liking (it is ca. 9 GB because there is a lot of 2D data). You can download the pulse programmes and processing scripts from the Bruker User Library https://www.bruker.com/en/services/bruker-user-library.html. <strong>Changelog</strong> v1.0.1: some quality of life improvements to the Python NUS script to stop it from being accidentally used on old pulse programmes.
DOI: 10.3886/e111705v1-88900
title: Data and Code for: State of American Entrepreneurship

description: Assessing the state of American entrepreneurship requires not simply counting the quantity but also the initial quality of new ventures. Combining comprehensive business registries and predictive analytics, we present estimates of entrepreneurial quantity and quality from 1988-2014. Rather than a secular pattern of declining business dynamism, our quality-adjusted measures follow a cyclical pattern sensitive to economic and capital market conditions. Consistent with the role of investment cycles as a driver of high-growth entrepreneurship, our results highlight the role of economic and institutional conditions as a driver of both initial entrepreneurial quality and the scaling of new ventures over time.
description: All business who are legally registered in any of 32 US states between 1988 and 2014.
description: other; For more information, please refer to...<br><br>The State of American Entrepreneurship: New Estimates of the Quality and Quantity of Entrepreneurship for 32 US States, 1988-2014By Jorge Guzman and Scott Stern<br>
DOI: 10.5281/zenodo.3938047
title: jsnagai/Automated-Stomata-Classification-and-Detection-in-Microscope-Images-of-Maize-Cultivars: This is a release

description: This is a initial relese
DOI: 10.5281/zenodo.3938046
title: jsnagai/Automated-Stomata-Classification-and-Detection-in-Microscope-Images-of-Maize-Cultivars: This is a release

description: This is a initial relese
DOI: 10.6084/m9.figshare.12831926
title: Genomic insights into the sessile life and biofouling of barnacles (Crustacea: Cirripedia)

description: Members of the infraclass Cirripedia, commonly called barnacles, are unique among the subphylum Crustacea in that they exhibit a biphasic life cycle with a planktonic larval stage and a sessile adult stage. Understanding their unique sessile life and mechanisms of attachment are hampered by the lack of genomic resources. Here, we present a 746 Mb genome assembly of <i>Lepas anserifera</i> – the first sequenced stalked barnacle genome. We estimate that Cirripedia first arose ~495 million years ago (MYA) and further diversified since Mesozoic. A demographic analysis revealed remarkable population changes of the barnacle in relation to sea-level fluctuations in the last 2 MYA. Comparative genomic analyses revealed the expansion of a number of developmental related genes families in barnacle genomes, such as Br-C, PCP20 and Lola, which are potentially important for the evolution of metamorphosis, cuticle development and central nervous system. Phylogenetic analysis and tissue expression profiling showed the possible roles of gene duplication, functional diversification and co-option in shaping the genomic evolution of barnacles. Overall, our study provides not only a valuable draft genome for comparative genomic analysis of crustacean evolution, but also facilitates studies of biofouling control.<br>Draft genome assembly and annotation of the stalked barnacle Lepas anserifera:<br>Genome sequences - Lepas_v1.0_gna.fasta.gzGenome annotation - Lepas_v1.0.gff.zipPredicted transcript sequences - Lepas_v1.0.transcrtip.fasta.zipPredicted protein sequences - Lepas_v1.0.proteins.fasta.zip
DOI: 10.5519/qd.g9tur9gr
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (110 records)
DOI: 10.6084/m9.figshare.14384819.v2
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the radial artery on the forearm (between elbow and wrist, about in the middle with a slightly changing position regularly to avoid skin damage due to continuous skin obstruction and warmth), by being attached with a velcro to the interior of a cotton sports wrist band. See the works of Dr. Antonio Martinez Nicolas for more details on wrist skin temperature rhythm and WTIO.<br>The procedure is described in: https://pubmed.ncbi.nlm.nih.gov/18761026/<br>This dataset can be used alone or in combination with ibutton-left-nondominant-upper-arm-cotton-sports-wristband-dorsal-interior-5min and ibutton-left-nondominant-upper-arm-cotton-sports-wristband-ventral-exterior-5min to regress dorsal skin temperature and ambient temperature respectively.<br>Each file contains the whole history up to the timestamp in the filename. Hence, to study the longest period, use only the latest file, do not concatenate with previous ones.<br>
DOI: 10.6084/m9.figshare.14456312.v1
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-ventral-exterior-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the ventral side of the forearm, by being attached with a velcro to the exterior of a cotton sports wrist band.<br>This dataset is meant to capture ambient temperature. It is placed just beside the main skin sensor but on the exterior of the cotton wristband instead of the interior, so that this sensor reflects the ambient temperature at the exact site where the main skin sensor is. This should be used in combination with the ibutton-left-nondominant-upper-arm-cotton-sports-wristband-5min dataset (main skin sensor, placed on the radial artery).<br>Each file contains the whole history up to the timestamp in the filename. Hence, to study the longest period, use only the latest file, do not concatenate with previous ones.