cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0183148.10fu
title: SH0183148.10FU

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/sh0183149.10fu
title: SH0183149.10FU

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/sh0183150.10fu
title: SH0183150.10FU

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/sh0183151.10fu
title: SH0183151.10FU

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: 10.34740/kaggle/dsv/9889145
title: WallStreetBets 2022
DOI: 10.15468/dl.jpqg2a
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Ilex sapiiformis Reissek"
 ]
}

 The dataset includes 7 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011429-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6dyq24
title: Occurrence Download

description: A dataset containing 3545 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-78.09012 36.99311,-69.35613 36.99311,-69.35613 46.34479,-78.09012 46.34479,-78.09012 36.99311))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Ambystoma jeffersonianum (Green, 1827)"
 ]
}

 The dataset includes 3545 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011430-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wukrbu
title: Occurrence Download

description: A dataset listing the 476 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-78.94799 43.37669,-77.79186 43.37669,-77.79186 43.83978,-78.94799 43.83978,-78.94799 43.37669))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia"
 ]
}

 The dataset's 476 records were derived from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011427-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.unnqjc
title: Occurrence Download

description: A dataset containing 29969 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-133.56581 54.52019,-133.53286 52.77411,-131.64402 51.09392,-129.40377 52.13718,-131.56715 54.49822,-133.56581 54.52019))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae",
 "Year 1970-2024"
 ]
}

 The dataset includes 29969 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011431-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v3wfux
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "OccurrenceStatus is Present",
 "TaxonKey is Leontopithecus caissara Lorini & Persson, 1990"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011433-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3sqss8
title: Occurrence Download

description: A dataset containing 218 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Handroanthus spongiosus (Rizzini) S.O.Grose"
 ]
}

 The dataset includes 218 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011436-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3sjw3e
title: Occurrence Download

description: A dataset containing 7027 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-78.05311 -0.7724,-78.10614 -1.01734,-77.38014 -1.17138,-77.10869 -0.95674,-77.38646 -0.78123,-78.03038 -0.63477,-78.05311 -0.7724))",
 "TaxonKey is Amphibia"
 ]
}

 The dataset includes 7027 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011437-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ge7qch
title: Occurrence Download

description: A dataset containing 30417 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-78.3429 -0.15417,-78.35091 -0.74936,-77.78241 -1.41394,-77.08847 -1.11768,-76.30912 -0.56786,-76.33848 -0.2289,-77.32067 0.00597,-77.94522 -0.02606,-78.3429 -0.15417))",
 "OccurrenceStatus is Present",
 "TaxonKey is Amphibia"
 ]
}

 The dataset includes 30417 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011435-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.atwff8
title: Occurrence Download

description: A dataset containing 40848 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.32631 -0.83053,-76.20124 -0.29045,-77.00057 0.0336,-77.98893 -0.04201,-78.29137 -0.49568,-78.24817 -1.20319,-76.17424 -1.17619,-75.59635 -1.34361,-75.2723 -0.97095,-75.32631 -0.83053))",
 "OccurrenceStatus is Present",
 "TaxonKey is Amphibia"
 ]
}

 The dataset includes 40848 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011434-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57996/cran.ceres-2630
title: Dataset "Impact of Carbon Sources in Airport De-icing Compounds on the Growth of Sphaerotilus natans"

description: Airport de-icer contaminated surface runoff discharges have been implicated in the growth of undesirable river biofilms (URBs, formerly 'sewage fungus'), in this research we sought to establish a definitive link between de-icer contaminated discharges and the growth of the characteristic URB taxon, S. natans. The dataset uploaded here is the raw optical density data from the high-throughput optical density instrument (BioScreen C MBR) used to monitor microbial growth.
DOI: 10.57996/cran.ceres-2614
title: Dataset "Aviation Product Named Entity Recognition (ApNER)"

description: In order to verify the proposed model, this study used the aircraft design standard documents and airworthiness standard documents published by the European Aviation Safety Agency (EASA) and the US Electronic Federal Regulations (eCFR), as well as the open source aircraft design dataset AircraftVerse [38] as the corpus to construct a named entity recognition dataset for aviation products (ApNER).
DOI: 10.57996/cran.ceres-2601
title: Dataset "Development and optimisation of rapid analysis of weathered slag using portable XRF - Supplementary information and code"

description: pXRF is widely used for rapid measurement of heavy metals in soils, however, thorough evaluation of common pre-processing methods and their effectiveness is limited. This study addresses processing methods using samples collected at a high heterogenetic post-metallurgical site containing,; basic oxygen steelmaking (BOS) slag and soil; the former being an important source of potentially toxic and valuable elements. Impact of pre-treatment processes, including sieving, drying, grinding, sample vessel, and ignition on the accuracy of pXRF measurements of samples were compared against ICP-MS. Of the twelve elements detected, four showed qualitative (Cr and Fe r² ≥0.60, RSD ≤ 30%) or quantitative (Mn and Ca r² ≥0.70, RSD ≤ 20%) measurements for raw samples. This improved to six elements after pre-processing (Sr qualitative, and Pb, Cr, Mn, Ca, Fe quantitative). Sieving and grinding improved precision (average RSD fell by 7.17% and 8.37% respectively), while drying and grinding enhanced accuracy (average r2 increased by 0.03 and 0.10 respectively). This study provides the first evidence that organic matter does not significantly impact pXRF accuracy. The two distinct matrices (BOS slag and soil) on- site resulted in a bimodal concentration distribution and a negative correlation for Ti. Importantly, this research proposes that not all common pre-processing steps are necessary to generate high-quality data, thereby increasing the speed and reducing the cost of data collection. Further analysis is required to develop a methodology to generate high-quality data across all elements of interest with BOS slag, or other relevant high heterogeneity samples. The supplementary information for this study includes : the full unprocessed dataset. all code used to for statistical analysis and graph generation
DOI: 10.57996/cran.ceres-2671
title: Data relating to "Li-S cell partial charge-discharge"

description: This data file includes partial charge and discharge measurements of a 19 Ah Li-S cell subject to MLTB duty cycle.
DOI: 10.57996/cran.ceres-2642
title: Dataset "Sapper - MSc Thesis - Survey Data"

description: Using a mixed-methods approach, this research explores how the PPP model has influenced the sustainability of RWS delivery in Rwanda. Survey was collected from 318 respondents, 12 semi-structured interviews, two focus group discussions, and 78 site visits of assets across two PPP managed systems in Rwanda and supplemented by secondary data from institutions.
DOI: 10.57996/cran.ceres-2641
title: Dataset relating to "Permeability measurements for the Investigation of a practical approach to the measurement of magnetic permeability of ferrofluids"

description: Ferrofluids are colloids of magnetic particles in a fluid. Ferrofluids have wide range of application in engineering and medicine. Their relative magnetic permeability is one of the important parameters that needs to be measured. This dataset contains the measurements observed in the process of using an existing technique to measure magnetic permeability with a solenoid and LCR meter to identify experimental factors relevant to the accuracy of measurement.
DOI: 10.57996/cran.ceres-2586
title: Dataset for "Application of Spatial Offset Raman Spectroscopy (SORS) and Machine Learning for Sugar Syrup Adulteration Detection in UK Honey"

description: Honey authentication is a complex process which traditionally requires costly and time-consuming analytical techniques not readily available to the producers. The aim of this study was to develop non-invasive sensor methods coupled with multivariate data analysis for de-tecting the type and percentage of exogenous sugar adulteration in UK honeys. For this purpose, we employed through-container Spatial Offset Raman Spectroscopy (SORS) on 17 different types of natural honeys produced in the UK over the course of a season and the same honey samples spiked with rice and sugar beet syrups at levels 10%, 20%, 30%, 50% w/w. The data acquired were used to construct prediction models for 14 types of honey with similar Raman fingerprint using different algorithms, namely PLS-DA, XGBoost and Random Forest with the aim to detect the level of adulteration per type of sugar syrup. The best performing algorithm for classification was Random Forest with only 1% of the pure honeys misclassified as adulterated and &lt; 3.5% of adulterated honey samples misclassified as pure. Random Forest was further employed to create a classification model which successfully classified samples according to the type of adulterant (rice or sugar beet) and the adulteration level. In addition, we collected SORS spectra from 27 samples of heather honey (24 Calluna vulgaris and 3 Erica Cinerea) produced in the UK and cor-responding subsamples spiked with high fructose sugar cane syrup and performed exploratory data analysis with PCA and classification with Random Forest which both showed a clear sepa-ration between pure and adulterated samples at medium (40%) and high (60%) adulteration levels and a 90% success at low adulteration levels (20%). The results of this study demonstrate the potential of SORS in combination with machine learning to be applied for the authentication of honey samples and the detection of exogenous sugars in the form of sugar syrups. A major advantage of the SORS technique is that it is a rapid, non-invasive method deployable in field with potential application at all stages of the supply chain.
DOI: 10.57996/cran.ceres-2604
title: Dataset "AR SUS & QUIS Hololens"

description: AR system usability and user experience in flight operations
DOI: 10.15468/dl.msb84z
title: Occurrence Download

description: A dataset containing 223968 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Apis mellifera Linnaeus, 1758",
 "Country is United States of America",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 223968 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011432-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57996/cran.ceres-2599
title: Dataset "Martlewetal2023_Data"

description: The intensification of arable agriculture has resulted in an increase in vehicle wheel load and the intensity of field operations, which has increased the risk and incidence of degradation in physical properties of the uncultivated subsoil layer. Biopores generated by the long-term, repeated use of specific cover crops within an arable rotation has been suggested as an approach to improve subsoil physical properties. Therefore, this paper aimed to determine the impact of long-term repeated cover cropping and the interaction of rotation treatments with different cultivation approaches on subsoil physical properties. Data was collected at the NIAB ‘Sustainable Trial for Arable Rotations’ long-term, rotation and cultivation field experiment established in 2006. Rotation treatments comprised a brassica cover crop alternated annually with winter wheat (ALTCC) compared to continuous winter wheat (CWW). Cultivation treatments comprised PLOUGH (250 mm depth), and non-inversion cultivation at 250 mm (DEEP) and 100 mm (SHALLOW) depths. Penetration resistance and volumetric soil moisture were collected at bi-monthly intervals during the 2018/19 growing season. Undisturbed soil cores were collected for laboratory analyses of soil water retention, water stable aggregates, root morphology digital scanning and biomass, and X-ray computed tomography (CT). Results showed that treatment ALTCC combined with SHALLOW, resulted in lower penetration resistance and increased moisture in the subsoil. This increased subsoil moisture persisted later into the season compared to the control. SHALLOW increased subsoil water retention, improved subsoil root morphology and increased subsoil porosity. Benefits from treatment ALTCC were not observed where combined with higher intensity, deeper cultivation. Overall, the combination of treatments ALTCC with SHALLOW, produced significant benefits to subsoil physical properties.
DOI: 10.57996/cran.ceres-2663
title: Data "Geophysics data (ERT) for water loss from sand dams"

description: The data includes all raw and processed geophysical data from two fieldtrips in Kenya. LS toolbox was used to process the raw data. Res2DInv was used following LS toolbox. Information regarding parameterisation is available in chapter 5 of the thesis (link to be attached when available) and in the published paper (link to be attached when available). The data includes coordinates for each electrode used in each geophysics profile in excel and in Google Earth, as well as DAT files of the raw data collected with the Terrameter for each profile.
DOI: 10.57996/cran.ceres-2594
title: Dataset "Effect of temperature, relative humidity and incubation time on the mycotoxin production by Fusarium spp. responsible for dry rot in potato tubers"

description: Potato is the fourth most consumed crop around the world. More than half of the potato crop is stored for three to nine months at cold temperatures (3- 10°C) for the fresh and seed market. One of the main causes of fresh potato waste in the retail supply chain is the appearance of fungal and bacterial rots during storage, around 3-5% of the potato crop is lost every year. Dry rot is a fungal disease that mainly affects the potato crop during storage and is responsible for a large volume of waste and associated economic losses. It is produced by Fusarium spp., such as Fusarium sambucinum and F. oxysporum. Understanding the ecophysiology of these fungi is a key point to mitigate their occurrence under commercial storage conditions. Therefore, this work aimed to elucidate the effect of three different temperatures (5, 10 and 15°C) and two different water activities (aw; 0.97, 0.99) on the ecophysiology and mycotoxin accumulation of F. sambucinum and F. oxysporum in a potato-based semi-synthetic medium. The mycotoxin accumulation was then studied in vivo, in potato tubers stored for 40 days at 8.5°C. Results showed that higher temperatures and aw enhanced fungal growth, lag time and mycotoxin accumulation in vitro. Six different mycotoxins (r-2, HT-2, diacetoxyscirpenol, 15-acetoxyscirpenol, neosolaniol and beau-vericin) were detected in vitro and in vivo. Due to the long period of time that potato tubers spend in storage, the fluctuations of environmental factors, such as temperature and relative humidity, could promote the development of fungal rots, as well as mycotoxin accumulation. This could result in important food and economical losses for the potato market, as well as a threat to the food safety of potato tubers
DOI: 10.57996/cran.ceres-2598
title: Dataset for "Characterisation and anaerobic digestion of fat, oil and grease (FOG) waste from wastewater treatment plants"

description: Data set for Figure 3 and Figure 4
DOI: 10.57996/cran.ceres-2582
title: Data used to validate the DF-IBM algorithm against previous experimental and numerical data

description: Results and data related to the paper "An improved implicit direct-forcing immersed boundary method (DF-IBM) around arbitrarily moving rigid structures".