cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.925205
title: Bulk and diatom-bound nitrogen isotope ratios, opal, TOC, and TN from ODP Hole 178-1098B

description: Intense seasonal productivity and carbon drawdown on the West Antarctic Peninsula (WAP) is driven by upwelling of nutrient-rich Circumpolar Deep Water (CDW) and subsequent stratification. CDW influence on the WAP is thought to have varied dramatically during the mid-Holocene, 5-7 ka. Here, we use diatom-bound nitrogen isotopes (δ15NDB), a nutrient utilization proxy, from ODP Site 1098 in Palmer Deep to study variations in the presence of CDW on sub-millennial timescales in the mid-Holocene. CDW intrusion is synchronous with atmospheric warming over Antarctica, suggesting that stronger and/or more southerly Southern Hemisphere westerlies enhanced CDW intrusion onto the WAP shelf. Our results also suggest that bulk sedimentary nitrogen isotopes (δ15Nbulk) do not track the same processes as δ15NDB at this site and that this cannot be explained by changes in diatom assemblages.
DOI: 10.1594/pangaea.922169
title: Sedimentological, biogeochemical and hydrochemical characteristics of core PG2411 from Polar Fox Lagoon
DOI: 10.1594/pangaea.724308
title: (Table A b) Flux of planktic foraminiferal species in sediment trap series L1/K276-22 at 2000 m water depth
DOI: 10.1594/pangaea.724294
title: (Table A a) Relative contributions of planktic foraminiferal species in sediment trap series L1/K276-22 at 2000 m water depth
DOI: 10.1594/pangaea.922166
title: Sedimentological, biogeochemical and hydrochemical characteristics of core PG2410 from Uomullyakh Lagoon
DOI: 10.1594/pangaea.974854
title: High-Resolution Orthomosaics and Digital Elevation Models of Biogenic Structures in the German Wadden Sea

description: This dataset contains high-resolution (5 cm/pixel) orthomosaics and digital elevation models (DEMs) from unoccupied aerial vehicle (UAV) surveys of biogenic structures in the German Wadden Sea. Two Pacific oyster reefs (Kaiserbalje, Nordland) and one blue mussel bed (Nordstrand) were monitored between 2020 and 2022. The data, processed via structure from motion (SfM) and georeferenced, are provided as raster files (*.tiff), ready for GIS analysis. The Random Forest (RF) classification shapefiles support the mapping of biogenic structures. This dataset facilitates research on biogenic structure growth, sediment dynamics, and geomorphological processes in intertidal environments
description: Data Collection: This dataset was collected using UAV surveys with a DJI Phantom 4 Pro equipped with an RGB camera. Flights were conducted at a maximum altitude of 40 m, achieving a ground sampling distance (GSD) of 1.2 cm/pixel. Surveys were performed in 2020 and 2022 at three sites in the German Wadden Sea: two Pacific oyster reefs (Kaiserbalje and Nordland) and one blue mussel bed (Nordstrand). Each survey occurred around low tide and incorporated ground control and check points, whose coordinates were measured using a Stonex S900A dGPS in Real-Time Kinematic (RTK) mode, with horizontal and vertical accuracies of 0.008 m and 0.015 m, respectively.Data Processing: The UAV imagery was processed into georeferenced digital elevation models (DEMs) and orthomosaics (.tiff) using Structure from Motion (SfM) photogrammetry. These datasets are ready for GIS analysis. A Random Forest (RF) machine learning algorithm was applied for classification, using structural and spectral features as training data, resulting in shapefiles that map biogenic structures.
DOI: 10.1594/pangaea.982721
title: Basic measurements of radiation at station Langley Research Center (2025-04)
DOI: 10.1594/pangaea.982722
title: Basic measurements of radiation at station Granite Island (2025-04)
DOI: 10.5281/zenodo.15742629
title: AUTOMOTIVE INDUSTRY – A KEY SECTOR FOR EMPLOYMENT IN UZBEKISTAN
DOI: 10.5281/zenodo.15742630
title: AUTOMOTIVE INDUSTRY – A KEY SECTOR FOR EMPLOYMENT IN UZBEKISTAN
DOI: 10.15468/dl.3pqffb
title: Occurrence Download

description: A dataset containing 1623 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chanodichthys erythropterus (Basilewsky, 1855)"
 ]
}

 The dataset includes 1623 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069307-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9npp4e
title: Occurrence Download

description: A dataset containing 25700 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scincella Mittleman, 1950",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 25700 records from 149 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069308-250525065834625/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.29410397
title: Realistic coupling enables flexible macroscopic traveling waves in the mouse cortex.

description: This repository contains the file for the manuscript: Realistic coupling enables flexible macroscopic traveling waves in the mouse cortex.Authors: Guanhua Sun, James Hazelden, Ruby Kim, and Daniel B Forger (corresponding author at forger@umich.edu).<br>6/25/2025 - First upload: We have uploaded all the data that is related to the manuscript. The code will be uploaded later.
DOI: 10.6084/m9.figshare.29410397.v1
title: Realistic coupling enables flexible macroscopic traveling waves in the mouse cortex.

description: This repository contains the file for the manuscript: Realistic coupling enables flexible macroscopic traveling waves in the mouse cortex.Authors: Guanhua Sun, James Hazelden, Ruby Kim, and Daniel B Forger (corresponding author at forger@umich.edu).<br>6/25/2025 - First upload: We have uploaded all the data that is related to the manuscript. The code will be uploaded later.
DOI: 10.15468/dl.jjf4tu
title: Occurrence Download

description: A dataset containing 2457 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sula nebouxii excisa Todd, 1948"
 ]
}

 The dataset includes 2457 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069309-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15742635
title: THE ROLE OF COMMUNICATION IN PARENT-ADOLESCENT RELATIONSHIPS
DOI: 10.5281/zenodo.15742636
title: THE ROLE OF COMMUNICATION IN PARENT-ADOLESCENT RELATIONSHIPS
DOI: 10.5281/zenodo.7779573
title: SOUND-BASED DRONE FAULT CLASSIFICATION USING MULTI-TASK LEARNING

description: arxiv : https://arxiv.org/abs/2304.11708


Accepted at 29th International Congress on Sound and Vibration (ICSV29). 


The drone has been used for various purposes including military applications, aerial photography, and pesticide spraying. However, the drone is vulnerable to external disturbances, and malfunction in propellers and motors can easily occur. To improve the safety of drone operations, early detection of mechanical faults should be made in real-time. In this paper, we propose a sound-based deep neural network (DNN) fault classifier and drone sound dataset. The dataset was constructed by collecting the operating sounds of drones from microphones mounted on three different drones in an anechoic chamber. The dataset includes various operating conditions of drones, such as flight directions (front, back, right, left, clockwise, counter clockwise) and faults on propellers and motors. The drone sounds were then mixed with noises recorded in five different spots on the university campus, with a signal-to-noise ratio (SNR) varying from 10 dB to 15 dB. Using the acquired dataset, we train a DNN classifier, 1DCNN-ResNet, that classifies the types of mechanical faults and their locations from short-time input waveforms. We employ multitask learning (MTL) and incorporate the direction classification task as an auxiliary task to make the classifier learn more general audio features. The test over unseen data reveals that the proposed multitask model can successfully classify faults in drones and outperforms single-task models even with less training data. 


 


please reorganize the file directory like below


drone


ㄴA


ㄴB


ㄴC


 


For each drone type A, B, and C have 54000*2 files. (Here, *2 means stereo channel, you can find mic1 and mic2 in subdirectory) They are divided into train, valid, and test by a 6:2:2 ratio. For each file, recording information is labeled below.


{model_type}_{maneuvering_direction}_{fault}_{drone_file_index}_{background}_{background_file_index}_{SNR}


model_type: A, B, C


maneuvering_direction: F(Front), B(Back), R(Right), L(Left), C(Clockwise), CC(Counter-clockwise)


fault: N (Normal), MF1~4 (Moter Failure), PC1~4 (Propeller Cut) -> 1~4 means each motor/propeller of the quadcopter.


 
description: Contact lasscap@kaist.ac.kr, if you have any questions.
DOI: 10.5281/zenodo.7779574
title: SOUND-BASED DRONE FAULT CLASSIFICATION USING MULTI-TASK LEARNING

description: arxiv : https://arxiv.org/abs/2304.11708


Accepted at 29th International Congress on Sound and Vibration (ICSV29). 


The drone has been used for various purposes including military applications, aerial photography, and pesticide spraying. However, the drone is vulnerable to external disturbances, and malfunction in propellers and motors can easily occur. To improve the safety of drone operations, early detection of mechanical faults should be made in real-time. In this paper, we propose a sound-based deep neural network (DNN) fault classifier and drone sound dataset. The dataset was constructed by collecting the operating sounds of drones from microphones mounted on three different drones in an anechoic chamber. The dataset includes various operating conditions of drones, such as flight directions (front, back, right, left, clockwise, counter clockwise) and faults on propellers and motors. The drone sounds were then mixed with noises recorded in five different spots on the university campus, with a signal-to-noise ratio (SNR) varying from 10 dB to 15 dB. Using the acquired dataset, we train a DNN classifier, 1DCNN-ResNet, that classifies the types of mechanical faults and their locations from short-time input waveforms. We employ multitask learning (MTL) and incorporate the direction classification task as an auxiliary task to make the classifier learn more general audio features. The test over unseen data reveals that the proposed multitask model can successfully classify faults in drones and outperforms single-task models even with less training data. 


 


please reorganize the file directory like below


drone


ㄴA


ㄴB


ㄴC


 


For each drone type A, B, and C have 54000*2 files. (Here, *2 means stereo channel, you can find mic1 and mic2 in subdirectory) They are divided into train, valid, and test by a 6:2:2 ratio. For each file, recording information is labeled below.


{model_type}_{maneuvering_direction}_{fault}_{drone_file_index}_{background}_{background_file_index}_{SNR}


model_type: A, B, C


maneuvering_direction: F(Front), B(Back), R(Right), L(Left), C(Clockwise), CC(Counter-clockwise)


fault: N (Normal), MF1~4 (Moter Failure), PC1~4 (Propeller Cut) -> 1~4 means each motor/propeller of the quadcopter.


 
description: Contact lasscap@kaist.ac.kr, if you have any questions.
DOI: 10.15468/dl.mufqbc
title: Occurrence Download

description: A dataset containing 150 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Peru",
 "Geometry POLYGON((-73.10294 -16.40112,-72.56071 -16.67339,-71.76028 -17.17978,-71.36007 -17.66018,-70.3918 -18.34774,-69.74629 -18.09022,-69.78502 -17.77086,-69.38481 -17.37702,-69.60428 -17.3154,-70.15942 -16.80939,-70.7662 -15.6442,-71.63118 -15.33316,-73.10089 -15.49919,-73.56933 -16.27533,-73.10294 -16.40112))",
 "HasGeospatialIssue is false",
 "TaxonKey is Xenodacnis parina Cabanis, 1873"
 ]
}

 The dataset includes 150 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069310-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15742443
title: ProteinRAG-dataset
DOI: 10.5281/zenodo.15742444
title: ProteinRAG-dataset
DOI: 10.15468/dl.frxppv
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Spondylurus anegadae Hedges & Conn, 2012",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069311-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15742641
title: TA'LIM JARAYONIDA INTERFAOL USULLARDAN FOYDALANISHNING TALABA O'ZLASHTIRISHIDAGI O'RNI
DOI: 10.5281/zenodo.15742642
title: TA'LIM JARAYONIDA INTERFAOL USULLARDAN FOYDALANISHNING TALABA O'ZLASHTIRISHIDAGI O'RNI
DOI: 10.15468/dl.d4y88w
title: Occurrence Download

description: A dataset containing 205 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chanodichthys mongolicus (Basilewsky, 1855)"
 ]
}

 The dataset includes 205 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069313-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d3j3s2
title: Occurrence Download

description: A dataset containing 818 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhinoderma darwinii Duméril & Bibron, 1841"
 ]
}

 The dataset includes 818 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069312-250525065834625/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.29410454.v1
title: The retention of nanoparticles in solid tumours

description: Source data for the manuscript: The retention of nanoparticles in solid tumours
DOI: 10.15468/dl.5nzejp
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Luxembourg",
 "DatasetKey is A global database for the distributions of crop wild relatives"
 ]
}

 The dataset includes 34 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069314-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j8xynv
title: Occurrence Download

description: A dataset containing 13317352 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Australia",
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((150.14704 -36.69008,149.76852 -36.11122,145.11275 -34.72315,139.20786 -32.61269,139.0943 -36.87198,139.88919 -38.2224,141.59252 -38.75569,143.48512 -39.10903,144.69638 -38.84419,146.66467 -39.40212,147.08104 -38.84419,148.51941 -38.13313,150.18489 -38.01394,150.14704 -36.69008))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 13317352 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069305-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ujgfqn
title: Occurrence Download

description: A dataset containing 332 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is New Zealand",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mustela erminea Linnaeus, 1758",
 "Year 2000-2025"
 ]
}

 The dataset includes 332 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069315-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7289/v5h70crk
title: Effects of ocean acidification on growth and otolith condition of juvenile scup, Stenotomus chrysops from laboratory experiment studies from 2011-08-24 to 2011-10-19 (NCEI Accession 0117506)

description: This dataset contains laboratory experiment data that were collected to examine the effects of elevated levels of CO2 on the growth, survival, otolith (ear bone) condition and the skeleton of juvenile scup, Stenotomus chrysops, a species that supports both commercial and recreational fisheries. Increasing amounts of atmospheric carbon dioxide from human industrial activities are causing changes in global ocean carbon chemistry resulting in a reduction in pH, a process termed ocean acidification. Studies have demonstrated adverse effects on calcifying organisms, particularly some invertebrates, corals, sea urchins, pteropods, and coccolithophores. It is important to determine which species are sensitive to elevated levels of CO2 because of the potential impacts to ecosystems, marine resources, biodiversity, food webs, populations and effects on human communities and economies. There have been few studies examining the effects of ocean acidification on marine fish, particularly the juvenile stages of species that support important fisheries. These data demonstrated that elevated levels of pCO2 (&gt;1300 micro-atm) had no statistically significant effect on growth, survival, or otolith condition after 8 weeks of rearing. There was a trend towards a greater gain in weight and length in scup exposed to the mid-level (1726 micro-atm) and the high level (2614 micro-atm) treatments of pCO2 when compared to the fish in the control (1205 micro-atm) treatments, but these differences were not statistically significant. X-ray analysis of the fish revealed a slightly higher incidence of hyper-ossification in the vertebrae of a few scup from the highest treatments compared to fish from the control treatments. The study's results show that juvenile scup are tolerant to increases in levels of environmental pCO2, possibly due to conditions this species encounters in their naturally variable environment.
DOI: 10.3334/cdiac/otg.32oc20080510
title: Temperature, salinity and other variables collected from discrete sample and profile observations using CTD, bottle and other instruments from the OCEANUS in the North Atlantic Ocean from 2008-05-10 to 2008-05-23 (NCEI Accession 0117673)

description: This dataset includes chemical, discrete sample, physical and profile data collected from OCEANUS in the North Atlantic Ocean from 2008-05-10 to 2008-05-23 and retrieved during cruise Line W. These data include CHLOROFLUOROCARBON-11 (CFC-11), CHLOROFLUOROCARBON-113 (CFC-113), CHLOROFLUOROCARBON-12 (CFC-12), DISSOLVED OXYGEN, HYDROSTATIC PRESSURE, Potential temperature (theta), SALINITY, SULFUR HEXAFLUORIDE (SF6) and WATER TEMPERATURE. The instruments used to collect these data include CTD and bottle. These data were collected by John M. Toole of Woods Hole Oceanographic Institution (WHOI) as part of the GLODAPv2_32OC20080510 dataset.

The International CLIVAR Global Ocean Carbon and Repeat Hydrography Program carries out a systematic and global re-occupation of select WOCE/JGOFS hydrographic sections to quantify changes in storage and transport of heat, fresh water, carbon dioxide (CO2), and related parameters.
DOI: 10.3334/cdiac/otg.32oc19830501
title: Temperature, salinity and other variables collected from discrete sample and profile observations using CTD, bottle and other instruments from the OCEANUS in the North Atlantic Ocean from 1983-05-01 to 1983-05-17 (NCEI Accession 0117691)

description: This dataset includes chemical, discrete sample, physical and profile data collected from OCEANUS in the North Atlantic Ocean from 1983-05-01 to 1983-05-17 and retrieved during cruise 32OC19830501. These data include DISSOLVED OXYGEN, HYDROSTATIC PRESSURE, NITRATE, NITRITE, PHOSPHATE, Potential temperature (theta), SALINITY, SILICATE and WATER TEMPERATURE. The instruments used to collect these data include CTD and bottle. These data were collected by Michael S. McCartney of Woods Hole Oceanographic Institution (WHOI) as part of the GLODAPv2_32OC19830501 dataset.
DOI: 10.15468/dl.4rw9kt
title: Occurrence Download

description: A dataset containing 5703 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nitrosalsola vermiculata (L.) Theodorova"
 ]
}

 The dataset includes 5703 records from 130 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008316-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rcu7v2
title: Occurrence Download

description: A dataset containing 7852272 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pterocles alchata (Linnaeus, 1766), Pterocles exustus Temminck, 1825, Fulica americana Gmelin, 1789, Gallinula chloropus (Linnaeus, 1758), Gallirallus australis (Sparrman, 1786), Porphyrio alleni Thomson, 1842, Porphyrio flavirostris (Gmelin, 1789), Porphyrio porphyrio (Linnaeus, 1758), Rhea americana (Linnaeus, 1758), Raia americana DeKay, 1842, Rhea pennata d'Orbigny, 1834)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7852272 records from 1488 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0366652-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.epmesf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.404815 -32.41864, 149.404815 -32.420886, 149.407061 -32.420886, 149.407061 -32.41864, 149.404815 -32.41864))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0066333-240626123714530/datasets/export for details.
DOI: 10.15468/dl.zb9chh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((144.762749 -36.797949, 144.762749 -36.809178, 144.764994 -36.809178, 144.764994 -36.797949, 144.762749 -36.797949))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0066334-240626123714530/datasets/export for details.
DOI: 10.15468/dl.yjhqs8
title: Occurrence Download

description: A dataset containing 5999234 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anser albifrons (Scopoli, 1769), Anser anser (Linnaeus, 1758), Anser brachyrhynchus Baillon, 1834, Anser brachyrhyncus Baillon, Anser brachyrhynchos, Anser erythropus (Linnaeus, 1758), Anser fabalis (Latham, 1787), Anser fabilis (Latham, 1787), Anser indicus (Latham, 1790), Aythya ferina (Linnaeus, 1758), Athya ferina (Linnaeus, 1758), Aythya nyroca (Güldenstädt, 1770))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5999234 records from 1060 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0364265-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.