cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0101805.10fu
title: SH0101805.10FU

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: 10.13145/bacdive110106.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive110107.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0101806.10fu
title: SH0101806.10FU

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: 10.13145/bacdive110107.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0101807.10fu
title: SH0101807.10FU

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: 10.13145/bacdive110108.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive110108.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0101808.10fu
title: SH0101808.10FU

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: 10.13145/bacdive110109.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive110109.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0101809.10fu
title: SH0101809.10FU

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: 10.13145/bacdive110110.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive110110.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0101810.10fu
title: SH0101810.10FU

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: 10.13145/bacdive110111.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive110111.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0101811.10fu
title: SH0101811.10FU

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.tnm6jn
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 "Geometry POLYGON((30.64328 -25.60377,32.20417 -25.60377,32.20417 -22.19485,30.64328 -22.19485,30.64328 -25.60377))",
 "HasGeospatialIssue is false",
 "Month is September",
 "OccurrenceStatus is Present",
 "TaxonKey is Loxodonta africana (Blumenbach, 1797)",
 "Year is 2022"
 ]
}

 The dataset includes 43 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033531-241126133413365/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.27880455
title: Associations between SPS and Exercise

description: This study examined associations between sensory processing sensitivity, exercise behavior, and preferences for exercise intensity.
DOI: 10.6084/m9.figshare.27880455.v1
title: Associations between SPS and Exercise_Cleaned.csv

description: This study examined associations between sensory processing sensitivity, exercise behavior, and preferences for exercise intensity.
DOI: 10.6084/m9.figshare.27880455.v2
title: Associations between SPS and Exercise

description: This study examined associations between sensory processing sensitivity, exercise behavior, and preferences for exercise intensity.
DOI: 10.15468/dl.6sg6hx
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-5.47703 36.1175,-5.4823 36.11497,-5.49008 36.11531,-5.49555 36.11274,-5.49243 36.11217,-5.48895 36.11472,-5.48694 36.11404,-5.48173 36.11451,-5.47703 36.1175))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 12 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033532-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dsgjnf
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eurystyles ochyrana (Szlach., Mytnik & Rutk.) F.Barros & L.R.S.Guim."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033534-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25921/2rzd-5a94
title: EK60 Water Column Sonar Data Collected During SH1905_Leg_1
DOI: 10.15468/dl.b8b8ug
title: Occurrence Download

description: A dataset containing 595 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "TaxonKey is Synsepalum dulcificum (Schumach. & Thonn.) Daniell"
 ]
}

 The dataset includes 595 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033533-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48366/r789725
title: Hyperspectral Sensing for Natural Resource Exploration and Global Agriculture: Insights from DESIS, PRISMA, and Hyperion

description: This collection of studies examines the diverse applications of hyperspectral remote sensing for natural resource exploration and agricultural monitoring. Topics include coal-bed methane exploration, oil and gas microseepage detection, and the comparison of new-generation hyperspectral sensors like DESIS and PRISMA with traditional multispectral data for global agriculture studies. The research presents advanced spectral techniques, such as Z-score distance for classification and endmember extraction from Hyperion, offering valuable tools for researchers, remote sensing professionals, and students.
DOI: 10.15468/dl.6n8fdx
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((-72.61488 5.07936,-72.45756 5.07925,-72.45742 5.23961,-72.61479 5.23973,-72.61488 5.07936)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Myrmecophaga Linnaeus, 1758"
 ]
}

 The dataset includes 64 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033535-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11262280
title: Bilateral integration in somatosensory cortex is controlled by behavioral relevance

description: Sensory perception naturally requires processing stimuli from both sides of the body. Yet, how neurons bind stimulus features across the hemispheres to create a unified perceptual experience remains unknown. To address this question, we performed large-scale recordings from neurons in both somatosensory cortices (S1) while mice shared information between their hemispheres and discriminated between two categories of bilateral stimuli. When expert mice touched stimuli associated with reward, they moved their whiskers with greater bilateral symmetry. During this period, synchronous spiking and enhanced spike-field coupling emerged between the hemispheres. This coordinated activity was absent in stimulus-matched naïve animals, indicating that interhemispheric (IH) binding was controlled by a goal-directed, internal process. In S1 neurons, the addition of ipsilateral touch primarily facilitated the contralateral, principal whisker response. This facilitation primarily emerged for reward-associated stimuli and was lost on trials where expert mice failed to respond. Taken together, these results reveal a novel state-dependent logic underlying bilateral integration in S1, where stimulus binding and facilitation are controlled by behavioral relevance.
DOI: 10.5281/zenodo.14449281
title: I-Seed_DS1 – CHARACTERIZATION OF BIOMECHANICS AND MATERIALS OF  NATURAL SEEDS MODEL

description: Dataset I-Seed_DS1 focus on bioengineering investigations of plant seed models, to define useful specifications for the design of the artificial systems in terms of multi-functional materials and morphological computation.


Task 3.1. Erodium cicutarium seeds: from natural features to robotic specifics.


Task 3.2. Samara seeds: from natural features to robotic specifics
DOI: 10.5281/zenodo.8096920
title: I-Seed_DS1 – CHARACTERIZATION OF BIOMECHANICS AND MATERIALS OF  NATURAL SEEDS MODEL

description: Dataset I-Seed_DS1 focus on bioengineering investigations of plant seed models, to define useful specifications for the design of the artificial systems in terms of multi-functional materials and morphological computation.


Task 3.1. Erodium cicutarium seeds: from natural features to robotic specifics.


Task 3.2. Samara seeds: from natural features to robotic specifics
DOI: 10.5281/zenodo.8096921
title: I-Seed_DS1 – CHARACTERIZATION OF BIOMECHANICS AND MATERIALS OF NATURAL SEEDS MODEL

description: Dataset I-Seed_DS1 focus on bioengineering investigations of plant seed models, to define useful specifications for the design of the artificial systems in terms of multi-functional materials and morphological computation. Task 3.1. Erodium cicutarium seeds: from natural features to robotic specifics. Task 3.2. Samara seeds: from natural features to robotic specifics
DOI: 10.15468/dl.y2qa9k
title: Occurrence Download

description: A dataset containing 1818 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "TaxonKey is Digitaria exilis (Kippist) Stapf"
 ]
}

 The dataset includes 1818 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033536-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cy53rj
title: Occurrence Download

description: A dataset containing 21216 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Elanus leucurus (Vieillot, 1818)"
 ]
}

 The dataset includes 21216 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033538-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9ws4w9
title: Occurrence Download

description: A dataset containing 51318 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Empidonax difficilis S.F.Baird, 1858"
 ]
}

 The dataset includes 51318 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033539-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25810/psk5-4485
title: FIRED Comoros Nov 2000 - July 2024

description: This is event-level polygons for the fire event delineation (FIRED) product for COMOROS from November 2000  to August 2024. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v061/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. Firedpy (https://github.com/earthlab/firedpy) is an algorithm that converts these rasters into events by stacking the entire time series into a spatial-temporal data cube, then uses an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. This particular dataset was created using a spatial parameter of 1 pixels and 5 days. Daily polygons are included and the event identification numbers are the same for both files, but the event-level product has only single polygons for each entire event, while the daily product has separate polygons for each date per event. See the associated paper for more details on the methods and more:

Balch, J.K.; St. Denis, L.A.; Mahood, A.L.; Mietkiewicz, N.P.; Williams, T.M.; McGlinchy, J.; Cook, M.C. FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019). Remote Sens. 2020, 12, 3498. https://doi.org/10.3390/rs12213498
DOI: 10.5281/zenodo.14447161
title: Digital Twin App Dataset

description: This project contains a dataset generated by the Digital Twin App for the Unitree Go1 robot, developed as part of the Real-time Digital Twins demonstration. 

The data is provided in ROS bag format and includes a variety of ROS topics, each containing specific types of data necessary for different aspects of robotic control and navigation.
DOI: 10.5281/zenodo.14447162
title: Digital Twin App Dataset

description: This project contains a dataset generated by the Digital Twin App for the Unitree Go1 robot, developed as part of the Real-time Digital Twins demonstration. 

The data is provided in ROS bag format and includes a variety of ROS topics, each containing specific types of data necessary for different aspects of robotic control and navigation.
DOI: 10.5281/zenodo.14447543
title: DLT Network Transactions Dataset

description: This project provides a dataset of all transactions occurring within the DLT network of the DESIRE6G platform, encompassing both Service Federation and Multi-Agent System (MAS) Security. The dataset helps for identifying any anomalies, understanding network behaviour, and ensuring the integrity of the data.The dataset was generated by monitoring a private Ethereum-based blockchain network using the Geth framework with a PoA (Proof-of-Authority) consensus algorithm. Data collection was automated with a Docker container that captures detailed transaction information in real-time, including interactions with smart contracts, and exports the results to a CSV file.The dataset includes the following attributes:

- **blockNumber**: The number of the block containing the transaction.
- **timestamp**: The timestamp of the block containing the transaction.
- **transactionHash**: The hash of the transaction.
- **from**: The address of the sender.
- **to**: The address of the recipient.
- **value**: The value transferred in the transaction (in Ether).
- **gas**: The gas provided for the transaction.
- **gasPrice**: The price of gas for the transaction (in Gwei).
- **nonce**: The number of transactions made by the sender prior to this one.
- **status**: The status of the transaction (1 for success, 0 for failure).
- **contractAddress**: The address of the contract, if the transaction created a contract; otherwise `None`.
- **contractName**: The name of the smart contract, if the transaction interacts with a known contract; otherwise `None`.
- **functionName**: The name of the function called in the smart contract, if applicable; otherwise `None`.