cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0034227.10fu
title: SH0034227.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0034228.10fu
title: SH0034228.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0034229.10fu
title: SH0034229.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0034230.10fu
title: SH0034230.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0034231.10fu
title: SH0034231.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0034232.10fu
title: SH0034232.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0034233.10fu
title: SH0034233.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0034234.10fu
title: SH0034234.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0034235.10fu
title: SH0034235.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.whf36s
title: Occurrence Download

description: A dataset containing 120990 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Colias croceus",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 5000",
 "Year is greater than or equal to 1970",
 "Country is one of (Italy, Switzerland, Germany, Austria, Slovenia, France)"
 ]
}

 The dataset includes 120990 records from 1571 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0075314-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/7gc9mxbb3b.2
title: Survey data on the attitudes of adolescents in Hong Kong towards the COVID-19 vaccination 

description: It is a novel data set on Hong Kong’s adolescents’ attitude towards the COVID-19 vaccination, excluding their parental opinions. This research used a cross-sectional questionnaire survey, which collects data from the population at a single point in time. Our questionnaire was designed in both English and Chinese for the adolescents’ convenience, using a self-designed, online questionnaire website, which was sent to 30 secondary schools across Hong Kong at the beginning of June 2021, to be completed by 31st June 2021. This gathered a total of 2609 surveys, excluding those which did not fit into the criteria. As the data has identified factors that affect vaccine hesitancy, government authorities can use the data to choose effective ways to promote the COVID-19 vaccination and to educate the general population about the benefits of receiving it.
DOI: 10.17632/yz4v8tb3tp.4
title: Dataset for Smile Detection from Face Images

description: This data is used in the second experimental evaluation of face smile detection in the paper titled "Smile detection using Hybrid Face Representaion" - O.A.Arigbabu et al. 2015. Download the main images from LFW website: http://vis-www.cs.umass.edu/lfw/ to select the samples we used for smile and non-smile, as in the list. Kindly cite: Arigbabu, Olasimbo Ayodeji, et al. "Smile detection using hybrid face representation." Journal of Ambient Intelligence and Humanized Computing (2016): 1-12. Huang GB, Mattar M, Berg T, Learned-Miller E (2007) Labeled faces in the wild: a database for studying face recognition in unconstrained environments. University of Massachusetts, Amherst, Technical Report
DOI: 10.17632/zwd7cc64x6.1
title: Data for: Were they all giants? Perspectives on late Holocene plate-boundary earthquakes at the northern end of the Cascadia subduction zone.

description: Radiocarbon ages on deposits associated with megathrust earthquakes at the Cascadia subduction zone
DOI: 10.17632/n9y9c7xrz3.1
title: Sound Datasets of a Rolling Element Bearing under Various Operating Conditions

description: Welcome to the FSTF Mechanical Laboratory at Sidi Mohamed Ben Abdellah University.

Within this repository, we present a comprehensive collection of ball-bearing test data encompassing both normal and faulty bearings across diffrent operating speeds. The experimental procedures were conducted utilizing a specialized test rig rotor system, with sound data meticulously measured at proximal and distal locations relative to the housing bearings. These web pages serve as a unique resource, meticulously documenting the precise test conditions of the motor and detailing the bearing fault status for each conducted experiment.

The datasets are bifurcated into two distinct categories: the first category entails recordings obtained using a stethoscope, denoted as datasets 1, while the second category comprises recordings conducted without a stethoscope under diffrent operating conditions, referred to as datasets 2. In both cases, bearings—specifically SKF model 6004, grooved ball bearings—were installed in a rotor system specified in Appendix A, as provided by the Gunt Company [1]. The defective bearings featured artificial damage in the inner race, outer race, and ball element, representing localized defects, as well as a bearing afflicted with a looseness defect due to prolonged operation.

Data acquisition procedures involved the recording of sound signals emanating from the bearings under diverse conditions, employing a mobile application named VibroTeak, developed by our team. This application facilitates the recording of sound signals in (.wav) format at a sampling rate of 44.1 kHz. Subsequently, the sound data was imported into Matlab using the "audioread" function for further processing. Figure 1 (Appendix A) illustrates the acquisition of acoustic signals utilizing a stethoscope connected to a smartphone via the jack input.

The datasets presented herein offer a novel avenue for researchers to delve into, assess, and propose innovative diagnostic algorithms tailored to this specific type of data.

References:
[1] Gunt, “PT 500.12 Roller bearing faults kit.” https://www.gunt.de/en/products/mechatronics/machinery-diagnosis/roller-bearing-faults-kit/052.50012/pt500-12/glct-1:pa-148:ca-77:pr-1030.
DOI: 10.17632/pp6ntt6549.3
title: Sourced datasets for “Enhanced Arctic sea ice melting controlled by larger heat discharge of Mid-Holocene rivers”

description: The datasets include age models, grain-size parameters, and rare earth elements in cores LV77-36-1 and LV77-41-1, as well as observational data. The age models and sedimentation rate data are shown in sheet1 (“Age model”). The grain sizes and rare earth elements are shown in sheet2 (“Core records”). And the observational data of Siberian river basin (85–180° E, 45–75° N) precipitation, Siberian river runoff and temperature, and East Siberian Arctic Shelf (85–180° E, 65–80° N) and pan-Arctic (0–360° E, 45–90° N) surface air temperature anomalies in May are shown in sheet3 (Observational data).
DOI: 10.17632/mrcf7f4tc2.1
title: Clinical Knowledge Graph

description: We have developed the Clinical Knowledge Graph (CKG), an open source platform currently comprised of more than 16 million nodes and 220 million relationships to represent relevant experimental data, public databases and the literature. The CKG incorporates the latest statistical and machine learning algorithms, drastically accelerating analysis and interpretation of typical proteomics workflows. We use several biomarker studies to illustrate how the CKG may support, enrich and accelerate clinical decision-making. Here, we are uploading a dump of CKG's database that can be used to easily create a Neo4 graph database harmonizing 9 ontologies, 26 relevant biomedical databases. Experimental studies included in the publication are also included as CKG reports. To get the full database up and running follow the installation instructions specified in CKG's documentation (https://github.com/MannLabs/CKG) and GitHub repository (https://github.com/MannLabs/CKG).
DOI: 10.17632/z2rbfzz3ng.1
title: Student Registration Dataset of Faculty of Information Technology at Isra University, Amman, Jordan

description: The dataset contains complete registration information that reflects the real scenario during the 2017/2018 second semester in faculty of information technology at Isra University. The dataset contains 89 courses, 143 sections, 24 instructors, 686 students, and 25 halls, 13 overlapping morning time periods and 3 evening time periods.
DOI: 10.17632/zmvvff35dx.1
title: SeqLengthPlot outputs on toxin candidates identified by DeTox in the single-end Transcriptome of Savalia savaglia

description: This dataset contains the output folder compiled by SeqLengthPlot applied to the toxin candidates identified by DeTox in the single-end of Savalia savaglia. 

The folder seq_length_DeTox_output_Ss_SE_candidate_toxins contains:
• seq_above99aa.fasta:
Retrieved FASTA file containing the toxin candidates with lengths of 100 aa and above, after splitting the input FASTA file based on the given threshold.

• seq_below100aa.fasta:
Retrieved FASTA file containing the toxin candidates with lengths below 100 aa, after splitting the input FASTA file based on the given threshold.

• seq_length_distribution_above99aa.png:
PNG image file showing a histogram of toxin candidate lengths of 100 aa and above on a linear scale.

• seq_length_distribution_above99_log.png:
PNG image file showing a histogram of toxin candidate lengths of 100 aa and above on a logarithmic scale.

• seq_length_distribution_below100aa.png:
PNG image file showing a histogram of toxin candidate lengths below 100 aa on a linear scale.

• seq_length_distribution_below100_log.png:
PNG image file showing a histogram of toxin candidate lengths below 100 aa on a logarithmic scale.

• seq_length_stats_by_threshold_100.txt:
Text file containing detailed statistics of the toxin candidate lengths in the input FASTA file, including the total number of sequences, the number of sequences 100 aa and above, the number of sequences below 100 aa, and the corresponding minimum and maximum lengths.
DOI: 10.17632/m3dbvfss5v.1
title: Dataset allowing for the identification of three new synthetic cannabimimetics featuring a norbornyl methyl side chain by spectrometric and spectroscopic techniques

description: Synthetic cannabimimetics are a diverse group of new psychoactive substances with varying potency and harm potential. Every year, new SCs appear on the drug market and reliable and correct identification of these new derivatives independent from the matrix relies on the availability of verified spectra. Three new synthetic cannabimimetics featuring a norbornyl methyl side chain and varying in the core structure element were identified in different seizures and forms. Cumyl-BC[2.2.1]HpMeGaClone and Cumyl-BC[2.2.1]HpMINACA were laced onto herbal blends whereas Cumyl-BC[2.2.1]HpMICA was seized as pure solid powder. The data collection process involves a comprehensive set of orthogonal analytical techniques aimed at the unambiguous identification of the respective end- and exo-isomers. Furthermore, the diversity of analytical techniques allows a greater number of laboratories working in the field of forensic chemistry to confidently identify the substances described in our original research article. Structure elucidation and analytical characterisation were performed within the EU-project ADEBAR plus using gas chromatography-mass spectrometry (GC-MS), gas chromatography-solid state infrared spectroscopy (GC-sIR), as well as solid and neat IR spectroscopy, Raman spectroscopy, liquid chromatography-electrospray ionisation-mass spectrometry (LC-ESI-MS), and high resolution (HR)-LC-ESI-MS, and nuclear magnetic resonance (NMR) spectroscopy. The raw analytical data files are included in this data repository alongside the individual spectra in a universally importable format. The use of the universal JCAMP format for storage of the spectra facilitates database maintenance and enables seamless integration of the verified spectra. The dataset enables other researchers worldwide to confidently identify these three new SCs.
DOI: 10.17632/rfkv3y4237.1
title: The spatial heterogeneity of urban green space distribution and configuration in Lilongwe City, Malawi

description: The present dataset is part of the article under consideration for publication titled “The Spatial Heterogeneity of Urban Green Space Distribution and Configuration in Lilongwe City, Malawi”. In this study, we used remote sensing data and landscape metrics to understand the distribution and configuration of urban green spaces in the city’s neighbourhoods and functional land uses and their relationships with urban form. The study results revealed that 20% of neighbourhoods fail to meet the World Health Organisation (WHO) recommended standard of 9 m2 of green space per person, with a predominant concentration of these undersupplied areas in high-density and quasi-residential zones. The study reveals the significant correlation of urban form metrics, namely building coverage, building density, building perimeter area ratio, road density, and the distribution and configuration of urban green spaces. We used the Normalised Difference Vegetation Index (NDVIS) as a proxy of green spaces. The NDVI was computed from a 10-metre-resolution Sentinel Level-2A imagery acquired on September 5, 2022 (Product ID: L2A_T36LXK_A028718_20220905T080208). A satellite image covering the entire city of Lilongwe city was obtained from the Copernicus Open Access Hub (https://scihub.copernicus.eu/). The acquired satellite image was clipped to extract study areas using the Lilongwe city boundary shapefile. We used the Microsoft building footprint and open street dataset to compute urban metrics. The population census data for the neighbourhoods was extracted from the 2018 Malawi Population and Housing Census report. The urban green space and urban form metrics were correlated to understand the impact of urban form on urban green spaces.
DOI: 10.17632/kky3y64d8n.1
title: Databases (Women´s empowerment)

description: Data base: data, tables and figures
DOI: 10.17632/8bk6h6bmkr.1
title: Raw Data from Clinical Trial NCT02692495

description: Laboratory data of internationally-recruited volunteers with idiopathic malodor that participated in the Internet-based self-selection trial registered as NCT02692495 at clinicaltrials.gov
DOI: 10.17632/2n3sc78mph.2
title: Sustainable Consumption Intention in Vietnam 

description: The survey was conducted in both direct and online form in November 2021 in Vietnam. The dataset was collected through 2 survey parts: the first part explores the respondents' demographic characteristics including gender, age, education level, marital status, and income, the second part explores respondents' consent to statements related to factors affecting sustainable consumption intention.