cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.zhbglx
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Heliconius sapho (Drury, 1782)"
 ]
}

 The dataset includes 96 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017196-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g2guwe
title: Occurrence Download

description: A dataset containing 370 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Meconopsis racemosa Maxim."
 ]
}

 The dataset includes 370 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008908-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.br4nux
title: Occurrence Download

description: A dataset containing 732 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tragopogon angustifolius Bellardi ex Willd.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 732 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079180-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.znvutj
title: Occurrence Download

description: A dataset containing 7577391 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON((-108.479 16.69922,-95.8667 16.69922,-97.32788 25.70801,-97.6355 25.72998,-108.479 26.23535,-108.479 16.69922))"
 ]
}

 The dataset includes 7577391 records from 1316 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006704-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2a23t3
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is one of (China, Chinese Taipei)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Athetis lepigone"
 ]
}

 The dataset includes 20 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063884-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vr684t
title: Occurrence Download

description: A dataset containing 1529 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Phalcoboenus d'Orbigny, 1834"
 ]
}

 The dataset includes 1529 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013083-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14013976
title: DYNAMIC PRICING IN FINANCIAL TECHNOLOGY: EVALUATING MACHINE LEARNING SOLUTIONS FOR MARKET ADAPTABILITY

description: The rapid advancement of technology has transformed the financial services sector, leading to the rise of fintech companies that leverage cutting-edge tools such as artificial intelligence (AI) and machine learning (ML) to offer innovative solutions. One area where fintech is particularly impactful is dynamic pricing, which involves adjusting prices in real-time based on market conditions, user behavior, and external factors. The ability to optimize pricing in response to fluctuating conditions is critical for maximizing profitability, improving customer satisfaction, and maintaining competitiveness. In this context, machine learning algorithms provide a powerful framework for making data-driven pricing decisions by learning from historical data and predicting future trends.
DOI: 10.15468/dl.a8nj59
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Glaucium leptopodum (Kar. & Kir.) Maxim."
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013084-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14013975
title: DYNAMIC PRICING IN FINANCIAL TECHNOLOGY: EVALUATING MACHINE LEARNING SOLUTIONS FOR MARKET ADAPTABILITY

description: The rapid advancement of technology has transformed the financial services sector, leading to the rise of fintech companies that leverage cutting-edge tools such as artificial intelligence (AI) and machine learning (ML) to offer innovative solutions. One area where fintech is particularly impactful is dynamic pricing, which involves adjusting prices in real-time based on market conditions, user behavior, and external factors. The ability to optimize pricing in response to fluctuating conditions is critical for maximizing profitability, improving customer satisfaction, and maintaining competitiveness. In this context, machine learning algorithms provide a powerful framework for making data-driven pricing decisions by learning from historical data and predicting future trends.
DOI: 10.5281/zenodo.14015364
title: DYNAMIC PRICING IN FINANCIAL TECHNOLOGY: EVALUATING MACHINE LEARNING SOLUTIONS FOR MARKET ADAPTABILITY

description: The rapid advancement of technology has transformed the financial services sector, leading to the rise of fintech companies that leverage cutting-edge tools such as artificial intelligence (AI) and machine learning (ML) to offer innovative solutions. One area where fintech is particularly impactful is dynamic pricing, which involves adjusting prices in real-time based on market conditions, user behavior, and external factors. The ability to optimize pricing in response to fluctuating conditions is critical for maximizing profitability, improving customer satisfaction, and maintaining competitiveness. In this context, machine learning algorithms provide a powerful framework for making data-driven pricing decisions by learning from historical data and predicting future trends.
DOI: 10.15468/dl.e3t9zj
title: Occurrence Download

description: A dataset containing 2856 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Astyanax lacustris (Lütken, 1875), Astronotus ocellatus (Agassiz, 1831), Apistogramma commbrae (Regan, 1906), Aphyocharax dentatus Eigenmann & Kennedy, 1903, Ageneiosus inermis (Linnaeus, 1766))"
 ]
}

 The dataset includes 2856 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013085-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5067/zbxsa1len453
title: MiCASA Daily NPP Rh FIRE FUEL ATMC Fluxes 0.1 degree x 0.1 degree
DOI: 10.5067/as9u6awvty69
title: MiCASA 3-Hourly NEE Fluxes 0.1 degree x 0.1 degree
DOI: 10.5067/ucfeaaidiueq
title: MiCASA Monthly NPP Rh FIRE FUEL ATMC Fluxes
DOI: 10.15468/dl.6f98cx
title: Occurrence Download

description: A dataset containing 8528 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Bixa L."
 ]
}

 The dataset includes 8528 records from 406 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013086-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.963310
title: Marine heat flow data at station HF2214 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963313
title: Marine heat flow data at station HF2216 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963317
title: Marine heat flow data at station HF2219 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963275
title: Summarized list of all heat flow determinations on RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963318
title: Marine heat flow data at station HF2220 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963303
title: Marine heat flow data at station HF2211 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963306
title: Marine heat flow data at station HF2212 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963309
title: Marine heat flow data at station HF2213 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963314
title: Marine heat flow data at station HF2217 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963316
title: Marine heat flow data at station HF2218 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963297
title: Marine heat flow data at station HF2210 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963312
title: Marine heat flow data at station HF2215 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963319
title: Marine heat flow data at station HF2221 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.963320
title: Marine heat flow data at station HF2222 sampled during RV METEOR cruise M183

description: Heat flow data, sampled during M183 within the RIFLOR project. Locations are along the Mid Atlantic ridge between 57° 29'N and 58° 18'N, mainly within the denominated Squid Pond. We used the 6 m Bremen heat probe with 21 channels. In-situ temperatures and thermal conductivities were derived using MHFRED, according to the inversion method of Villinger and Davis (2007).
DOI: 10.1594/pangaea.971603
title: Oxygen and Argon concentrations in surface waters during the MOSAiC expedition in the Arctic Ocean, core parameters

description: Throughout the MOSAiC drift expedition on the RV POLARSTERN (Oct 2019 – Oct 2020), we used membrane-inlet mass spectrometry (MIMS) to continuously measure abundances of oxygen (represented by m/z 32) and argon (represented by m/z 40) in underway sampled surface waters (11m depth) of the Arctic Ocean. The instrument was regularly calibrated (i.e., measuring water equilibrated with pure nitrogen and reference air, respectively), enabling baseline corrections of obtained raw signals as well as the calculation of the gasses' individual concentrations. These data allow to distinguish the physical and biological contribution to oxygen supersaturation (O2phys, O2bio; Eveleth et al. 2014), and to reconstruct net community productivity of the transected waters (e.g., Ulfsbo et al. 2015). Alongside our data, we re-publish interpolated underway data from the ship's thermosalinograph and other sensors which we required in order to calculate theoretical saturation concentrations in the environment. Timespans in which bottle experiments were conducted with the instrument are presented as raw reads without calculated concentration and ratio data: Due to the pump-supported sample intake, these assessments required different calibrations and will be separately published in high resolution elsewhere.
description: NaN values appear when 'delta O2:Ar as determined from concentrations' cannot be calculated (at the timepoint where 0% Argon was calibrated)
DOI: 10.15468/dl.kp8b2c
title: Occurrence Download

description: A dataset containing 2856 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Astyanax lacustris (Lütken, 1875), Astronotus ocellatus (Agassiz, 1831), Apistogramma commbrae (Regan, 1906), Aphyocharax dentatus Eigenmann & Kennedy, 1903, Ageneiosus inermis (Linnaeus, 1766))"
 ]
}

 The dataset includes 2856 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013087-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.961920
title: Zooplankton abundance and biomass in Sørfjorden, Norway, on G.O. Sars in December 2019 sampled with a Hydrobios Multinet Mammoth

description: Vertically stratified samples were collected during the ICES Broadband Acoustics course Sørfjorden, Norway, on G.O. Sars in December 2019. The goal was to obtain mesozooplankton diversity and abundance date to compare with a hydracoustic dataset collected with a TS probe. The used Hydrobios Multinet Mammoth had a 1m2net opening, eight nets (#9 was in the surface and discarded) nets, 300µm mesh, oblique haul during darkness in the at 2kn. Scanned on Epson V750 flatbed scanner at 2400dpi, processed using Zooprocess and uploaded to https://ecotaxa.obs-vlfr.fr/prj/6145 Exported data were used to estimate individual biomass according to Lehette & Hernandez-Leon (2006) and aggregated to depth layers. Data: GOSars_examples.zip contains example images.
DOI: 10.15468/dl.tuyzru
title: Occurrence Download

description: A dataset containing 3372 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Barringtonia racemosa (L.) Spreng."
 ]
}

 The dataset includes 3372 records from 118 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013088-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.972613
title: 2D multichannel seismic reflection raw data (GI Gun) of RV SONNE cruise SO182 in 2005 to the Transkei Basin, seismic reflection profile AWI-20050001

description: Seismic reflection data collected in the Transkei Basin during cruise SO182 with RV Sonne in 2005. 3 GI-guns were used a seismic source, the data were recorded with a 2250 m (active length) long digital streamer. The data are unprocessed. No gain, filter or mute have been applied. The data are in SEGY format. See cruise report (Uenzelmann-Neben, 2005) or ReadMe file for more information on acquisition parameters.
DOI: 10.1594/pangaea.972638
title: 2D multichannel seismic reflection raw data (GI Gun) of RV SONNE cruise SO182 in 2005 to the Transkei Basin, seismic reflection profile AWI-20050017

description: Seismic reflection data collected in the Transkei Basin during cruise SO182 with RV Sonne in 2005. 3 GI-guns were used a seismic source, the data were recorded with a 2250 m (active length) long digital streamer. The data are unprocessed. No gain, filter or mute have been applied. The data are in SEGY format. See cruise report (Uenzelmann-Neben, 2005) or ReadMe file for more information on acquisition parameters.
DOI: 10.1594/pangaea.972637
title: 2D multichannel seismic reflection raw data (GI Gun) of RV SONNE cruise SO182 in 2005 to the Transkei Basin, seismic reflection profile AWI-20050002

description: Seismic reflection data collected in the Transkei Basin during cruise SO182 with RV Sonne in 2005. 3 GI-guns were used a seismic source, the data were recorded with a 2250 m (active length) long digital streamer. The data are unprocessed. No gain, filter or mute have been applied. The data are in SEGY format. See cruise report (Uenzelmann-Neben, 2005) or ReadMe file for more information on acquisition parameters.
DOI: 10.1594/pangaea.972640
title: 2D multichannel seismic reflection raw data (GI Gun) of RV SONNE cruise SO182 in 2005 to the Transkei Basin, seismic reflection profile AWI-20050003

description: Seismic reflection data collected in the Transkei Basin during cruise SO182 with RV Sonne in 2005. 3 GI-guns were used a seismic source, the data were recorded with a 2250 m (active length) long digital streamer. The data are unprocessed. No gain, filter or mute have been applied. The data are in SEGY format. See cruise report (Uenzelmann-Neben, 2005) or ReadMe file for more information on acquisition parameters.
DOI: 10.1594/pangaea.972643
title: 2D multichannel seismic reflection raw data (GI Gun) of RV SONNE cruise SO182 in 2005 to the Transkei Basin, seismic reflection profile AWI-20050016

description: Seismic reflection data collected in the Transkei Basin during cruise SO182 with RV Sonne in 2005. 3 GI-guns were used a seismic source, the data were recorded with a 2250 m (active length) long digital streamer. The data are unprocessed. No gain, filter or mute have been applied. The data are in SEGY format. See cruise report (Uenzelmann-Neben, 2005) or ReadMe file for more information on acquisition parameters.
DOI: 10.1594/pangaea.972639
title: 2D multichannel seismic reflection raw data (GI Gun) of RV SONNE cruise SO182 in 2005 to the Transkei Basin, seismic reflection profile AWI-20050006

description: Seismic reflection data collected in the Transkei Basin during cruise SO182 with RV Sonne in 2005. 3 GI-guns were used a seismic source, the data were recorded with a 2250 m (active length) long digital streamer. The data are unprocessed. No gain, filter or mute have been applied. The data are in SEGY format. See cruise report (Uenzelmann-Neben, 2005) or ReadMe file for more information on acquisition parameters.
DOI: 10.1594/pangaea.972641
title: 2D multichannel seismic reflection raw data (GI Gun) of RV SONNE cruise SO182 in 2005 to the Transkei Basin, seismic reflection profile AWI-20050007

description: Seismic reflection data collected in the Transkei Basin during cruise SO182 with RV Sonne in 2005. 3 GI-guns were used a seismic source, the data were recorded with a 2250 m (active length) long digital streamer. The data are unprocessed. No gain, filter or mute have been applied. The data are in SEGY format. See cruise report (Uenzelmann-Neben, 2005) or ReadMe file for more information on acquisition parameters.
DOI: 10.1594/pangaea.972642
title: 2D multichannel seismic reflection raw data (GI Gun) of RV SONNE cruise SO182 in 2005 to the Transkei Basin, seismic reflection profile AWI-20050004

description: Seismic reflection data collected in the Transkei Basin during cruise SO182 with RV Sonne in 2005. 3 GI-guns were used a seismic source, the data were recorded with a 2250 m (active length) long digital streamer. The data are unprocessed. No gain, filter or mute have been applied. The data are in SEGY format. See cruise report (Uenzelmann-Neben, 2005) or ReadMe file for more information on acquisition parameters.