cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14498691
title: ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech

description:  

This is the Zenodo repository for the ASVspoof 5 database. ASVspoof 5 is the fifth edition in a series of challenges which promote the study of speech spoofing and deepfake attacks, and the design of detection solutions. Compared to previous challenges, the ASVspoof~5 database is built from crowdsourced data collected from around 2,000 speakers in diverse acoustic conditions.  More than 20 attacks, also crowdsourced, are generated and optionally tested using surrogate detection models, while seven adversarial attacks are incorporated for the first time.



Please check README.txt and LICENSE.txt before downloading the database.

Database paper (to be submitted): https://arxiv.org/abs/2502.08857



Please consider citing the reference listed at the bottom of this page.



It is highly recommended to follow the rules and instructions in the ASVspoof 5 challenge evaluation plan (phase 2, https://www.asvspoof.org/), if you want to produce results comparable with the literature. 

Latest work using the ASVspoof 5 database can be found in the Automatic Speaker Verification Spoofing Countermeasures Workshop proceeding: https://www.isca-archive.org/asvspoof_2024/index.html

If you are interested in creating spoofed data for research purpose using the ASVspoof 5 protocol, please send request to info@asvspoof.org
DOI: 10.15468/dl.rbq5u5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Caranx muroadsi Temminck & Schlegel, 1844",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001260-250213122211068/datasets/export for details.
DOI: 10.15468/dl.w6rk88
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Platessa cornuta Temminck & Schlegel, 1846",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001261-250213122211068/datasets/export for details.
DOI: 10.15468/dl.5s6jne
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Solanum stenotomum Juz. & Bukasov"
 ]
}

 The dataset includes 23 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001262-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28415222
title: Zotero

description: Zotero como usar
DOI: 10.15468/dl.2c7xma
title: Occurrence Download

description: A dataset containing 88 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Haliotis gigantea Gmelin, 1791",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 88 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001264-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kv7dwp
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Xiphias gladius Linnaeus, 1758",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001265-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28415192
title: Figshare1 Data on the QT interval

description: Data on the QT interval in rat given doxorubicin
DOI: 10.15468/dl.6jg6gg
title: Occurrence Download

description: A dataset containing 26905 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Solanum tuberosum L."
 ]
}

 The dataset includes 26905 records from 507 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001266-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m9k5h3
title: Occurrence Download

description: A dataset containing 3632 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Yarwun Port Curtis Sediment Bacterial 16S rRNA (V6) 454 sequence",
 "Country is Australia"
 ]
}

 The dataset includes 3632 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001267-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bbm7um
title: Occurrence Download

description: A dataset containing 4208 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Type locality distributions from the World Register of Marine Species",
 "Country is Australia"
 ]
}

 The dataset includes 4208 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001268-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.25w2g7
title: Occurrence Download

description: A dataset listing the 1435 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Geometry POLYGON((-90.00896 20.96347,-89.92744 20.73056,-89.58388 20.66068,-89.36843 20.78296,-89.45578 21.05664,-89.60135 21.14399,-89.88668 21.12652,-90.00896 20.96347))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Insecta"
 ]
}

 The dataset's 1435 records were derived from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001263-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ruueev
title: Occurrence Download

description: A dataset containing 743 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Girella punctata Gray, 1835",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 743 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001269-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bemfwv
title: Occurrence Download

description: A dataset containing 398074 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Geometry POLYGON((-88.76 35.67,-70.04 35.67,-70.04 39.75,-88.76 39.75,-88.76 35.67))",
 "HasCoordinate is true",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Fungi"
 ]
}

 The dataset includes 398074 records from 175 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001256-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2t39d6
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Solanum stenotomum Juz. & Bukasov"
 ]
}

 The dataset includes 23 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001270-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ned7sz
title: Occurrence Download

description: A dataset containing 54 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyperoglyphe japonica (Döderlein, 1884)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 54 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001271-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14851410
title: Spatial Estimation of Soil Organic Matter and Total Nitrogen by Fusing Field Vis-NIR Spectroscopy and Multi-spectral Remote Sensing Data

description: original data and the main code for the study
DOI: 10.5281/zenodo.14851409
title: Spatial Estimation of Soil Organic Matter and Total Nitrogen by Fusing Field Vis-NIR Spectroscopy and Multi-spectral Remote Sensing Data

description: original data and the main code for the study. 

(1) Remote Sensing Data Processing

First, the GaoFen-1 (GF-1) remote sensing data is clipped in ArcGIS to match the extent of the study area. Then, the clipped remote sensing data is processed using the ‘Remote sensing processing.R’ script in R, where spectral indices (such as NDVI, EVI, etc.) and the coefficient of variation (CV) are calculated to provide input data for subsequent modeling analysis.

(2) Field Spectral Data Processing

The field vis-NIR spectral data is standardized through Direct Standardization (DS) transformation, which is carried out using the 'PLS_Workspace Browse' tool in MATLAB. The DS transformation aims to eliminate environmental influences on the spectral data, thereby improving the comparability and consistency of the data. The transformed spectral data undergoes Principal Component Analysis (PCA) to extract principal components, which are then spatially interpolated in ArcGIS to generate a distribution map of the spectral principal components across the study area.

(3) Modeling Analysis

After the preprocessing of both remote sensing and field spectral data, modeling analysis is conducted using the ‘modelling.R’ script in R. This script integrates the preprocessed remote sensing data (spectral indices and coefficient of variation) and field spectral data (principal components). Machine learning algorithms,including Partial Least Squares Regression (PLSR) and Random Forest (RF), are employed to construct soil property prediction models and assess the model's performance (by ‘Accuracy. R’ script).
DOI: 10.5281/zenodo.14868248
title: Spatial Estimation of Soil Organic Matter and Total Nitrogen by Fusing Field Vis-NIR Spectroscopy and Multi-spectral Remote Sensing Data

description: original data and the main code for the study. 

(1) Remote Sensing Data Processing

First, the GaoFen-1 (GF-1) remote sensing data is clipped in ArcGIS to match the extent of the study area. Then, the clipped remote sensing data is processed using the ‘Remote sensing processing.R’ script in R, where spectral indices (such as NDVI, EVI, etc.) and the coefficient of variation (CV) are calculated to provide input data for subsequent modeling analysis.

(2) Field Spectral Data Processing

The field vis-NIR spectral data is standardized through Direct Standardization (DS) transformation, which is carried out using the 'PLS_Workspace Browse' tool in MATLAB. The DS transformation aims to eliminate environmental influences on the spectral data, thereby improving the comparability and consistency of the data. The transformed spectral data undergoes Principal Component Analysis (PCA) to extract principal components, which are then spatially interpolated in ArcGIS to generate a distribution map of the spectral principal components across the study area.

(3) Modeling Analysis

After the preprocessing of both remote sensing and field spectral data, modeling analysis is conducted using the ‘modelling.R’ script in R. This script integrates the preprocessed remote sensing data (spectral indices and coefficient of variation) and field spectral data (principal components). Machine learning algorithms,including Partial Least Squares Regression (PLSR) and Random Forest (RF), are employed to construct soil property prediction models and assess the model's performance (by ‘Accuracy. R’ script).
DOI: 10.15468/dl.3ycp9c
title: Occurrence Download

description: A dataset containing 30647 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aphelandra R.Br."
 ]
}

 The dataset includes 30647 records from 547 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001272-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28307321
title: Prediction of Olympic medals based on GA-BP and logistic regression model

description: Predicting the number and distribution of medals in the future Olympic Games has become a noticeable topic. However, it is not easy to predict the number of Olympic medals. We need to comprehensively consider historical data, athletes' performance, host country effect and other factors from multiple dimensions. This paper adopts GA-BP algorithm model, which is an optimization algorithm combining genetic algorithm (GA) and back propagation neural network (BPNN). It uses the global search ability of genetic algorithm to optimize the weight and bias parameters of BP neural network, so as to improve the training efficiency and prediction performance of neural network. By estimating the number of gold medals and total medals of each country in the Olympic Games, and verifying the accuracy of the model, the medal list of the 2028 Los Angeles Olympic Games is finally predicted. Based on the synthetic control model, this paper selects two countries, Estonia and China, as the research object. By constructing a virtual control group and two experimental groups, the change of the number of medals in different periods and the change of the number of medals with or without coaches in the same period were analyzed, and the difference between the actual medal growth and the synthetic control group (no coach effect team) was compared. The results show that the number of medals won by Estonia and China with a head coach is higher than that without a head coach. Under the guidance of excellent coaches, Estonia won 1 gold medal and 2 bronze medals in 1992, indicating that the great head coach effect has a significant role in promoting the performance of athletes. This paper explores the valuable opinions of the Olympic committee decision-making, reveals the key factors behind the distribution of medals, optimizes the allocation of national strategic resources, and predicts the performance of countries in the future Olympic Games. This research will help to improve the accuracy of the model more comprehensively, better understand the medal trend of the Olympic Games, and provide a scientific basis for the NOC to achieve better results in the future Olympic Games.
DOI: 10.15468/dl.cndrjn
title: Occurrence Download

description: A dataset containing 4389 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is (Table AT3) Planktonic foraminiferal stratigraphy of ODP Hole 182-1128B",
 "Country is Australia"
 ]
}

 The dataset includes 4389 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001275-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.26zpvf
title: Occurrence Download

description: A dataset containing 3501 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Birda - Global Observation Dataset",
 "Country is Australia"
 ]
}

 The dataset includes 3501 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001274-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jhxqq7
title: Occurrence Download

description: A dataset containing 3237 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Algae (S)",
 "Country is Australia"
 ]
}

 The dataset includes 3237 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001273-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d8xmnt
title: Occurrence Download

description: A dataset containing 26905 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Solanum tuberosum L."
 ]
}

 The dataset includes 26905 records from 507 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001276-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.929c87
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calliandra strigillosa"
 ]
}

 The dataset includes 5 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038150-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/ku6aak
title: DMNS Herp Collection (Arctos)

description: The Denver Museum of Nature & Science Amphibian and Reptile Collection is a small, but growing collection of approximately 1000 specimens primarily from the western US. The bulk of specimens are fluid-preserved, with some skeletal preparations, and associated frozen tissues. The collection grows primarily as a result of incidental bycatch from invertebrate surveys and salvage activities.
DOI: 10.25919/4jwj-eb24
title: Parkes observations for project P1219 semester 2025APRS_15

description: Magnetic fields are fundamental in regulating star formation and the evolution of molecular clouds. Zeeman splitting offers a unique method to directly measure line-of-sight magnetic field strengths in interstellar environments, from the diffuse ISM to dense cores. Observations of HI and OH absorption toward pulsars provide an unprecedented opportunity to measure magnetic fields with high precision, benefiting from pulsars' small angular sizes and reliable Stokes V spectra unaffected by instrumental effects. Our recent tentative Zeeman splitting detections in OH absorption toward PSR J1644-4559 with Parkes reveal magnetic field strengths that suggest magnetically subcritical states, where magnetic pressure counteracts gravity. This challenges conventional theories of subcritical cold neutral medium (CNM) transitioning to supercritical star-forming molecular clouds, emphasizing the need for detailed investigation. We propose a continuation of Zeeman splitting studies through high-sensitivity OH and HI absorption observations of pulsars PSR J1644-4559, J1721-3532, and J1852+0031 using Parkes. By employing an innovative phase-resolved spectral technique and extending integration times, we aim to enhance Zeeman detection sensitivity and study magnetic field transitions in the CNM and quiescent molecular clouds. This work will refine our understanding of subcritical-to-supercritical transitions in star formation, establish pulsar absorption as a robust probe of interstellar magnetic fields, and advance observational techniques critical to star formation studies.
DOI: 10.15468/jijwox
title: DMNS Parasite Collection (Arctos)

description: The Denver Museum of Nature & Science Parasite Collection houses approximately 6,000 specimens or specimen lots of ectoparasites and endoparasites. Parasite specimens are linked to DMNS bird and mammal hosts, primarily collected since 2006, with a focus on the Rocky Mountain and Great Plains regions. The collection is largely fluid, with some specimens mounted on slides.
DOI: 10.15468/bqvk9g
title: DMNS Mammal Collection (Arctos)

description: The Denver Museum of Nature & Science Mammal Collection currently consists of approximately 21,000 specimens, which includes 20,000+ cataloged specimens. The collection spans 1870 to the present, is worldwide in coverage, and includes specimens from the three major extant mammalian lineages (monotremes, marsupials, and placentals) distributed across 21 orders, 266 genera, and 381 species. The collection’s primary strength is its focus on the southern Rocky Mountains and Great Plains. Approximately 82% of the collection is from the western United States, with specimens from Colorado (73%) representing the largest percentage. Small mammals, such as shrews, rodents, lagomorphs, and bats, constitute the majority (84%) of specimens in the collection. The composition of the collection is primarily study skins and skeletal material, with a growing wet collection. High-quality specimen data, frozen tissues, and parasites are associated with most of the specimens archived since 2006.
DOI: 10.15468/udo5wb
title: DMNS Egg Collection (Arctos)

description: The Denver Museum of Nature & Science Egg/Nest Collection houses approximately 7,000 catalogued specimens focused primarily on the United States. The bulk of the collection was acquired as a donation of the William C. Bradbury private collection and covers the late 19th and early 20th centuries.
DOI: 10.15468/lyw1fq
title: DMNS Marine Invertebrate Collection (Arctos)

description: The Denver Museum of Nature & Science Marine Invertebrate Collection dates to the early 1900s. It is a diverse collection of worldwide specimens, the largest portion being marine shells. It also has specimens of echinoderms, corals, sponges, crustaceans, and other invertebrates. Despite its name, it includes a substantial collection of land and freshwater snail shells. The collection contains nearly 50,000 lots, of which more than half are databased in Arctos with more being added to the database each week. More than half of the databased lots are geolocated, and over 1,000 specimen records have images. 

Specimens in the collection represent nearly 6,000 species in over 450 families. Specimens come from over 150 countries with the majority from the United States and most of those from Florida and Hawaii. All specimens have been donated to the Museum by shell collectors, including many self-collected specimens.
DOI: 10.15468/t3bsxx
title: DMNS Bird Collection (Arctos)

description: he Denver Museum of Nature & Science bird collection contains approximately 53,000 specimens from around the world (1842 to the present), with a focus on the Rocky Mountain and Great Plains regions. The collection is worldwide in scope (six out of seven continents represented) with excellent taxonomic coverage of class Aves (205 out of ~224 families represented). Ordinal representation is excellent; however, more than half of the birds in the collection belong to Passeriformes. The collection includes study skins, skeletal material (~5,000, most with associated skin), taxidermy mounts, frozen tissue samples (~12,000), and associated parasites (ecto- and endoparasites). Growth of the collection continues primarily through salvage activities. The 7,000 egg sets/nests are curated separately - this collection is also global in scope with a focus on North America and Europe.