cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15142976
title: TABLE 3 in New data on Dysderoidea (Arachnida: Araneae) of the Pamir Mountains, Tajikistan

description: TABLE 3. Altitudinal distribution of Segestria in Central Asia. *—doubtful altitude (see the discussion).
SpeciesS. nekhaevae Fomichev & Marusik,1300Fomichev & Marusik 20202020S. pamirica sp. n.2200–2500Present dataS. shtoppelae Fomichev & Marusik,1300Fomichev & Marusik 20202020S. turkestanica Dunin, 19861500 (in Kyrgyzstan)Dunin 1986; Fomichev & Marusik 20203000 (in Kazakhstan)*
description: Published as part of Fomichev, Alexander A., 2024, New data on Dysderoidea (Arachnida: Araneae) of the Pamir Mountains, Tajikistan, pp. 586 in Zootaxa 5496 (4) on page 586, DOI: 10.11646/zootaxa.5496.4.7, http://zenodo.org/record/13617738
DOI: 10.15468/dl.32ssk3
title: Occurrence Download

description: A dataset containing 17623 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is one of (Sceloporus grammicus Wiegmann, 1828, Sceloporus grammicus disparilis Stejneger, 1916)"
 ]
}

 The dataset includes 17623 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019398-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/k4wt-vy93
title: "A robustness evaluation dataset for joint recommendation and fraud detection."

description: "A dataset for evaluating recommender system robustness through joint training with fraud detection tasks."
DOI: 10.5281/zenodo.15589166
title: Semi-Recurrent Neural Networks In IllustrisTNG And N-Body Simulations

description: This is the official data repository for the MNRAS publication Modelling the galaxy-halo connection using semi-recurrent neural networks, and subsequent works Optimised neural network predictions of galaxy formation histories using semi-stochastic corrections and Evaluating the galaxy formation histories predicted by a neural network in pure dark matter simulations. For details on access and utilisation of the data and code, see documentation.pdf in the affiliated GitHub repository.
DOI: 10.5281/zenodo.7358459
title: Semi-Recurrent Neural Networks In IllustrisTNG And N-Body Simulations

description: This is the official data repository for the MNRAS publication Modelling the galaxy-halo connection using semi-recurrent neural networks, and subsequent works Optimised neural network predictions of galaxy formation histories using semi-stochastic corrections and Evaluating the galaxy formation histories predicted by a neural network in pure dark matter simulations. For details on access and utilisation of the data and code, see documentation.pdf in the affiliated GitHub repository.
DOI: 10.5281/zenodo.7358460
title: Semi-Recurrent Neural Networks In IllustrisTNG

description: This is the official data repository for the MNRAS publication Modelling the galaxy-halo connection using semi-recurrent neural networks. For details on access and utilisation of the data and code, see documentation.pdf in the affiliated GitHub repository.
DOI: 10.15468/dl.k8a5ad
title: Occurrence Download

description: A dataset containing 36448 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Streptomyces Waksman & Henrici, 1943"
 ]
}

 The dataset includes 36448 records from 425 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019399-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wmarmd
title: Occurrence Download

description: A dataset containing 12902 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "OccurrenceStatus is Present",
 "TaxonKey is Panthera leo"
 ]
}

 The dataset includes 12902 records from 109 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050057-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nd4z2f
title: Occurrence Download

description: A dataset listing the 463380 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "DatasetKey is EOD – eBird Observation Dataset",
 "Month is February",
 "OccurrenceStatus is Present",
 "Year 2023-2025"
 ]
}

 The dataset's 463380 records were derived from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025315-250811113504898/datasets/export for details.
DOI: 10.15468/dl.6zewu2
title: Occurrence Download

description: A dataset containing 268 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Galearis spathulata"
 ]
}

 The dataset includes 268 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025321-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17611/dp/21238317
title: Moment Tensor for February 15, 2023 MW 5.0 (GCMT) SOUTHERN BOLIVIA
DOI: 10.17611/dp/21238323
title: Moment Tensor for February 16, 2023 MW 5.7 (GCMT) VANUATU ISLANDS
DOI: 10.17611/dp/21238329
title: Moment Tensor for February 16, 2023 MW 5.5 (GCMT) HAITI REGION
DOI: 10.15468/dl.8s42ea
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Monocorophium sextonae",
 "Country is Netherlands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004555-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17611/dp/21238335
title: Moment Tensor for February 16, 2023 MW 4.8 (GCMT) ADRIATIC SEA
DOI: 10.15468/dl.67w947
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Abactochromis labrosus, Acanthocleithron chapini, Acanthopagrus berda, Acapoeta tanganicae, Acentrogobius audax, Acentrogobius nebulosus, Acentrogobius therezieni, Acipenser sturio, Afronandus sheljuzhkoi, Afronemacheilus abyssinicus, Agonostomus catalai, Agonostomus telfairii, Alburnus alburnus, Alcolapia alcalica, Alcolapia grahami, Alcolapia latilabris, Alcolapia ndalalani, Alestes ansorgii, Alestes baremoze, Alestes bouboni, Brycinus nurse, Alestes dentex, Alestes liebrechtsii, Alestes macrophthalmus, Alestes stuhlmannii, Alestopetersius bifasciatus, Alestopetersius brichardi, Alestopetersius caudalis, Alestopetersius compressus, Alestopetersius hilgendorfi, Alestopetersius leopoldianus, Alestopetersius nigropterus, Alestopetersius smykalai, Alestopetersius tumbensis, Allenbatrachus meridionalis, Alosa agone, Alosa algeriensis, Alosa alosa, Alosa fallax, Alticorpus geoffreyi, Alticorpus macrocleithrum, Alticorpus mentale, Alticorpus peterdaviesi, Alticorpus profundicola, Altolamprologus calvus, Altolamprologus compressiceps, Neolamprologus fasciatus, Amarginops platus, Ambassis ambassis, Ambassis dussumieri, Ambassis fontoynonti, Ambassis gymnocephalus, Ambassis natalensis, Ambassis urotaenia, Amphilius atesuensis, Amphilius athiensis, Amphilius brevis, Amphilius caudosignatus, Amphilius cryptobullatus, Amphilius dimonikensis, Amphilius grandis, Amphilius jacksonii, Amphilius kakrimensis, Amphilius korupi, Amphilius lamani, Amphilius lampei, Amphilius laticaudatus, Amphilius lentiginosus, Amphilius longirostris, Amphilius lujani, Amphilius maesii, Amphilius mamonekenensis, Amphilius natalensis, Amphilius opisthophthalmus, Amphilius platychir, Amphilius pulcher, Amphilius rheophilus, Amphilius uranoscopus, Amphilius zairensis, Anaecypris punica, Pseudophoxinus punicus, Ancharius fuscus, Ancharius griseus, Andersonia leptura, Anguilla anguilla, Anguilla bengalensis, Anguilla bicolor, Anguilla marmorata, Anguilla mossambica, Anomalochromis thomasi, Aphanius apodus)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((51.6287 10.9151,51.6417 11.0599,46.1382 11.0599,46.1382 2.0599,46.3452 2.0599,48.3339 4.1422,49.3495 5.6782,49.6723 6.54,51.2679 9.1793,51.3777 9.8638,51.776 10.0634,51.9157 10.4446,51.6287 10.9151))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004556-250827131500795/datasets/export for details.
DOI: 10.17611/dp/21238341
title: Moment Tensor for February 16, 2023 MW 5.1 (GCMT) LUZON, PHILIPPINES
DOI: 10.17611/dp/21238347
title: Moment Tensor for February 16, 2023 MW 4.9 (GCMT) JORDAN - SYRIA REGION
DOI: 10.17611/dp/21238353
title: Moment Tensor for February 16, 2023 MW 5.1 (GCMT) NEAR COAST OF GUATEMALA
DOI: 10.17611/dp/21238359
title: Moment Tensor for February 16, 2023 MW 4.8 (GCMT) TANZANIA
DOI: 10.17611/dp/21238365
title: Moment Tensor for February 16, 2023 MW 5.3 (GCMT) SOUTHERN MID-ATLANTIC RIDGE
DOI: 10.17611/dp/21238371
title: Moment Tensor for February 16, 2023 MW 4.9 (GCMT) CENTRAL MID-ATLANTIC RIDGE
DOI: 10.17611/dp/21238377
title: Moment Tensor for February 16, 2023 MW 5.2 (GCMT) JORDAN - SYRIA REGION
DOI: 10.17611/dp/21238383
title: Moment Tensor for February 16, 2023 MW 4.8 (GCMT) LUZON, PHILIPPINES
DOI: 10.25444/nhlbi.30002788
title: Data to accompany "Non-invasive pressure-volume loops using the elastance model and CMR: a porcine validation at transient pre-loads", European Heart Journal - Imaging Methods and Practice, 2024

description: Aims: Pressure-volume (PV) loops have utility in the evaluation of cardiac pathophysiology but require invasive measurements. Recently, a time-varying elastance model to derive PV loops non-invasively was proposed, using left ventricular (LV) volume by cardiovascular magnetic resonance (CMR) and brachial cuff pressure as inputs. Validation was performed using CMR and pressure measurements acquired on the same day, but not simultaneously, and without varying pre-loads. This study validates the non-invasive elastance model used to estimate PV loops at varying pre-loads, compared with simultaneous measurements of invasive pressure and volume from real-time CMR, acquired concurrent to an inferior vena cava (IVC) occlusion.Methods and results: We performed dynamic PV loop experiments under CMR guidance in 15 pigs (n = 7 naïve, n = 8 with ischaemic cardiomyopathy). Pre-load was altered by IVC occlusion, while simultaneously acquiring invasive LV pressures and volumes from real-time CMR. Pairing pressure and volume signals yielded invasive PV loops, and model-based PV loops were derived using real-time LV volumes. Haemodynamic parameters derived from invasive and model-based PV loops were compared. Across 15 pigs, 297 PV loops were recorded. Intra-class correlation coefficient (ICC) agreement was excellent between model-based and invasive parameters: stroke work (bias = 0.007 ± 0.03 J, ICC = 0.98), potential energy (bias = 0.02 ± 0.03 J, ICC = 0.99), ventricular energy efficiency (bias = -0.7 ± 2.7%, ICC = 0.98), contractility (bias = 0.04 ± 0.1 mmHg/mL, ICC = 0.97), and ventriculoarterial coupling (bias = 0.07 ± 0.15, ICC = 0.99). All haemodynamic parameters differed between naïve and cardiomyopathy animals (P &lt; 0.05). The invasive vs. model-based PV loop dice similarity coefficient was 0.88 ± 0.04.Conclusion: An elastance model-based estimation of PV loops and associated haemodynamic parameters provided accurate measurements at transient loading conditions compared with invasive PV loops.
DOI: 10.25444/nhlbi.30002788.v1
title: Data to accompany "Non-invasive pressure-volume loops using the elastance model and CMR: a porcine validation at transient pre-loads", European Heart Journal - Imaging Methods and Practice, 2024

description: Aims: Pressure-volume (PV) loops have utility in the evaluation of cardiac pathophysiology but require invasive measurements. Recently, a time-varying elastance model to derive PV loops non-invasively was proposed, using left ventricular (LV) volume by cardiovascular magnetic resonance (CMR) and brachial cuff pressure as inputs. Validation was performed using CMR and pressure measurements acquired on the same day, but not simultaneously, and without varying pre-loads. This study validates the non-invasive elastance model used to estimate PV loops at varying pre-loads, compared with simultaneous measurements of invasive pressure and volume from real-time CMR, acquired concurrent to an inferior vena cava (IVC) occlusion.Methods and results: We performed dynamic PV loop experiments under CMR guidance in 15 pigs (n = 7 naïve, n = 8 with ischaemic cardiomyopathy). Pre-load was altered by IVC occlusion, while simultaneously acquiring invasive LV pressures and volumes from real-time CMR. Pairing pressure and volume signals yielded invasive PV loops, and model-based PV loops were derived using real-time LV volumes. Haemodynamic parameters derived from invasive and model-based PV loops were compared. Across 15 pigs, 297 PV loops were recorded. Intra-class correlation coefficient (ICC) agreement was excellent between model-based and invasive parameters: stroke work (bias = 0.007 ± 0.03 J, ICC = 0.98), potential energy (bias = 0.02 ± 0.03 J, ICC = 0.99), ventricular energy efficiency (bias = -0.7 ± 2.7%, ICC = 0.98), contractility (bias = 0.04 ± 0.1 mmHg/mL, ICC = 0.97), and ventriculoarterial coupling (bias = 0.07 ± 0.15, ICC = 0.99). All haemodynamic parameters differed between naïve and cardiomyopathy animals (P &lt; 0.05). The invasive vs. model-based PV loop dice similarity coefficient was 0.88 ± 0.04.Conclusion: An elastance model-based estimation of PV loops and associated haemodynamic parameters provided accurate measurements at transient loading conditions compared with invasive PV loops.
DOI: 10.17611/dp/21238389
title: Moment Tensor for February 17, 2023 MW 5.3 (GCMT) RYUKYU ISLANDS, JAPAN
DOI: 10.17611/dp/21238395
title: Moment Tensor for February 17, 2023 MW 5.3 (GCMT) CENTRAL MID-ATLANTIC RIDGE
DOI: 10.17611/dp/21238401
title: Moment Tensor for February 17, 2023 MW 4.8 (GCMT) VANCOUVER ISLAND, CANADA REGION
DOI: 10.17611/dp/21238407
title: Moment Tensor for February 17, 2023 MW 6.2 (GCMT) TANIMBAR ISLANDS REG., INDONESIA
DOI: 10.17611/dp/21238413
title: Moment Tensor for February 18, 2023 MW 5.4 (GCMT) TONGA ISLANDS REGION
DOI: 10.17611/dp/21238419
title: Moment Tensor for February 18, 2023 MW 4.8 (GCMT) COSTA RICA
DOI: 10.17611/dp/21238425
title: Moment Tensor for February 18, 2023 MW 5.3 (GCMT) VANUATU ISLANDS
DOI: 10.17611/dp/21238431
title: Moment Tensor for February 18, 2023 MW 4.8 (GCMT) CRETE, GREECE
DOI: 10.17611/dp/21238437
title: Moment Tensor for February 18, 2023 MW 5.1 (GCMT) TURKEY
DOI: 10.17611/dp/21238443
title: Moment Tensor for February 18, 2023 MW 5.8 (GCMT) SOUTH SANDWICH ISLANDS REGION
DOI: 10.17611/dp/21238449
title: Moment Tensor for February 19, 2023 MW 5.3 (GCMT) OFF COAST OF NORTHERN CHILE
DOI: 10.17611/dp/21238455
title: Moment Tensor for February 19, 2023 MW 5.0 (GCMT) MINDANAO, PHILIPPINES
DOI: 10.17611/dp/21238461
title: Moment Tensor for February 19, 2023 MW 4.9 (GCMT) NEAR COAST OF NICARAGUA
DOI: 10.17611/dp/21238467
title: Moment Tensor for February 19, 2023 MW 4.7 (GCMT) TURKEY
DOI: 10.17611/dp/21238473
title: Moment Tensor for February 19, 2023 MW 4.8 (GCMT) MID-INDIAN RIDGE
DOI: 10.17611/dp/21238479
title: Moment Tensor for February 19, 2023 MW 4.9 (GCMT) SOUTH SANDWICH ISLANDS REGION
DOI: 10.17611/dp/21238485
title: Moment Tensor for February 19, 2023 MW 4.9 (GCMT) VANUATU ISLANDS REGION
DOI: 10.17611/dp/21238491
title: Moment Tensor for February 19, 2023 MW 4.8 (GCMT) NORTHERN MOLUCCA SEA
DOI: 10.17611/dp/21238497
title: Moment Tensor for February 19, 2023 MW 5.3 (GCMT) MID-INDIAN RIDGE
DOI: 10.17611/dp/21238503
title: Moment Tensor for February 19, 2023 MW 4.9 (GCMT) HOKKAIDO, JAPAN REGION
DOI: 10.17611/dp/21238509
title: Moment Tensor for February 19, 2023 MW 4.9 (GCMT) MID-INDIAN RIDGE
DOI: 10.17611/dp/21238515
title: Moment Tensor for February 19, 2023 MW 4.9 (GCMT) NORTHERN MOLUCCA SEA
DOI: 10.17611/dp/21238521
title: Moment Tensor for February 20, 2023 MW 4.8 (GCMT) TURKEY
DOI: 10.17611/dp/21238527
title: Moment Tensor for February 20, 2023 MW 5.0 (GCMT) OFF W COAST OF NORTHERN SUMATRA
DOI: 10.17611/dp/21238533
title: Moment Tensor for February 20, 2023 MW 4.9 (GCMT) PHILIPPINE ISLANDS REGION
DOI: 10.15468/dl.aef9dn
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Monocorophium sextonae",
 "Country is New Zealand",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004559-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17611/dp/21238539
title: Moment Tensor for February 20, 2023 MW 5.0 (GCMT) TONGA ISLANDS REGION
DOI: 10.17611/dp/21238545
title: Moment Tensor for February 20, 2023 MW 6.3 (GCMT) JORDAN - SYRIA REGION
DOI: 10.17611/dp/21238551
title: Moment Tensor for February 20, 2023 MW 5.2 (GCMT) SOUTH OF PANAMA
DOI: 10.17611/dp/21238557
title: Moment Tensor for February 21, 2023 MW 4.8 (GCMT) OFF COAST OF CENTRAL AMERICA
DOI: 10.17611/dp/21238563
title: Moment Tensor for February 21, 2023 MW 5.4 (GCMT) KODIAK ISLAND REGION, ALASKA
DOI: 10.17611/dp/21238569
title: Moment Tensor for February 21, 2023 MW 5.1 (GCMT) SOUTHERN IRAN
DOI: 10.17611/dp/21238575
title: Moment Tensor for February 21, 2023 MW 5.3 (GCMT) ICELAND
DOI: 10.17611/dp/21238581
title: Moment Tensor for February 21, 2023 MW 5.0 (GCMT) BANDA SEA
DOI: 10.17611/dp/21238587
title: Moment Tensor for February 21, 2023 MW 4.8 (GCMT) PACIFIC-ANTARCTIC RIDGE
DOI: 10.17611/dp/21238593
title: Moment Tensor for February 21, 2023 MW 5.0 (GCMT) GALAPAGOS TRIPLE JUNCTION REGION
DOI: 10.17611/dp/21238599
title: Moment Tensor for February 22, 2023 MW 4.8 (GCMT) BONIN ISLANDS, JAPAN REGION
DOI: 10.17611/dp/21238605
title: Moment Tensor for February 22, 2023 MW 5.1 (GCMT) SOUTHERN IRAN
DOI: 10.17611/dp/21238611
title: Moment Tensor for February 22, 2023 MW 4.9 (GCMT) WEST OF MACQUARIE ISLAND
DOI: 10.17611/dp/21238617
title: Moment Tensor for February 22, 2023 MW 5.7 (GCMT) BANDA SEA
DOI: 10.17611/dp/21238623
title: Moment Tensor for February 22, 2023 MW 4.8 (GCMT) SOUTHERN XINJIANG, CHINA
DOI: 10.17611/dp/21238629
title: Moment Tensor for February 23, 2023 MW 6.8 (GCMT) TAJIKISTAN-XINJIANG BORDER REG.
DOI: 10.17611/dp/21238635
title: Moment Tensor for February 23, 2023 MW 5.4 (GCMT) OFF COAST OF CENTRAL CHILE
DOI: 10.17611/dp/21238641
title: Moment Tensor for February 23, 2023 MW 5.3 (GCMT) SALTA PROVINCE, ARGENTINA
DOI: 10.17611/dp/21238647
title: Moment Tensor for February 23, 2023 MW 5.0 (GCMT) JORDAN - SYRIA REGION
DOI: 10.17611/dp/21238653
title: Moment Tensor for February 23, 2023 MW 5.3 (GCMT) CENTRAL EAST PACIFIC RISE
DOI: 10.17611/dp/21238659
title: Moment Tensor for February 23, 2023 MW 6.4 (GCMT) TALAUD ISLANDS, INDONESIA
DOI: 10.17611/dp/21238665
title: Moment Tensor for February 24, 2023 MW 4.8 (GCMT) LEEWARD ISLANDS
DOI: 10.17611/dp/21238671
title: Moment Tensor for February 24, 2023 MW 5.1 (GCMT) SOUTH OF MARIANA ISLANDS
DOI: 10.17611/dp/21238677
title: Moment Tensor for February 24, 2023 MW 4.7 (GCMT) TURKEY
DOI: 10.17611/dp/21238683
title: Moment Tensor for February 24, 2023 MW 5.0 (GCMT) NORTHERN MOLUCCA SEA
DOI: 10.17611/dp/21238689
title: Moment Tensor for February 24, 2023 MW 4.8 (GCMT) KENAI PENINSULA, ALASKA
DOI: 10.17611/dp/21238695
title: Moment Tensor for February 24, 2023 MW 4.8 (GCMT) SOUTH SANDWICH ISLANDS REGION
DOI: 10.17611/dp/21238701
title: Moment Tensor for February 25, 2023 MW 5.0 (GCMT) SOUTHERN MID-ATLANTIC RIDGE
DOI: 10.17611/dp/21238707
title: Moment Tensor for February 25, 2023 MW 4.9 (GCMT) OFF COAST OF MICHOACAN, MEXICO
DOI: 10.17611/dp/21238713
title: Moment Tensor for February 25, 2023 MW 4.9 (GCMT) NORTHWEST OF RYUKYU ISLANDS
DOI: 10.17611/dp/21238719
title: Moment Tensor for February 25, 2023 MW 5.3 (GCMT) TURKEY
DOI: 10.17611/dp/21238725
title: Moment Tensor for February 25, 2023 MW 6.1 (GCMT) HOKKAIDO, JAPAN REGION
DOI: 10.17611/dp/21238731
title: Moment Tensor for February 25, 2023 MW 5.0 (GCMT) SANTA CRUZ ISLANDS
DOI: 10.17611/dp/21238737
title: Moment Tensor for February 25, 2023 MW 6.3 (GCMT) NEW BRITAIN REGION, P.N.G.
DOI: 10.17611/dp/21238743
title: Moment Tensor for February 26, 2023 MW 4.9 (GCMT) SANTA CRUZ ISLANDS
DOI: 10.17611/dp/21238749
title: Moment Tensor for February 26, 2023 MW 4.9 (GCMT) NORTHERN MOLUCCA SEA
DOI: 10.15468/dl.mmug59
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "StateProvince is Arkansas",
 "TaxonKey is one of (Scaphinotus parisiana, Dryobius sexnotatus, Heterosternuta ouachita)"
 ]
}

 The dataset includes 11 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004561-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17611/dp/21238755
title: Moment Tensor for February 26, 2023 MW 5.1 (GCMT) BALLENY ISLANDS REGION
DOI: 10.17611/dp/21238761
title: Moment Tensor for February 26, 2023 MW 4.9 (GCMT) KERMADEC ISLANDS, NEW ZEALAND
DOI: 10.17611/dp/21238767
title: Moment Tensor for February 26, 2023 MW 5.0 (GCMT) KERMADEC ISLANDS, NEW ZEALAND
DOI: 10.17611/dp/21238773
title: Moment Tensor for February 26, 2023 MW 5.0 (GCMT) FLORES REGION, INDONESIA
DOI: 10.17611/dp/21238779
title: Moment Tensor for February 26, 2023 MW 4.9 (GCMT) OFF COAST OF MICHOACAN, MEXICO
DOI: 10.17611/dp/21238785
title: Moment Tensor for February 26, 2023 MW 4.9 (GCMT) KYRGYZSTAN-XINJIANG BORDER REG.
DOI: 10.17611/dp/21238791
title: Moment Tensor for February 27, 2023 MW 5.4 (GCMT) SULAWESI, INDONESIA
DOI: 10.17611/dp/21238797
title: Moment Tensor for February 27, 2023 MW 5.2 (GCMT) SOUTH OF KERMADEC ISLANDS
DOI: 10.17611/dp/21238803
title: Moment Tensor for February 27, 2023 MW 4.8 (GCMT) TURKEY
DOI: 10.17611/dp/21238809
title: Moment Tensor for February 27, 2023 MW 5.0 (GCMT) NEAR COAST OF NORTHERN PERU
DOI: 10.17611/dp/21238815
title: Moment Tensor for February 27, 2023 MW 4.8 (GCMT) NORTHERN MID-ATLANTIC RIDGE
DOI: 10.17611/dp/21238821
title: Moment Tensor for February 27, 2023 MW 4.9 (GCMT) NORTHERN MID-ATLANTIC RIDGE
DOI: 10.17611/dp/21238827
title: Moment Tensor for February 27, 2023 MW 5.3 (GCMT) TURKEY
DOI: 10.17611/dp/21238833
title: Moment Tensor for February 27, 2023 MW 5.1 (GCMT) SANTA CRUZ ISLANDS
DOI: 10.17611/dp/21238839
title: Moment Tensor for February 27, 2023 MW 5.2 (GCMT) OFF COAST OF CENTRAL AMERICA
DOI: 10.17611/dp/21238845
title: Moment Tensor for February 28, 2023 MW 4.9 (GCMT) TAJIKISTAN-XINJIANG BORDER REG.
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title: Moment Tensor for February 28, 2023 MW 5.2 (GCMT) SOUTHEAST OF HONSHU, JAPAN
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title: Moment Tensor for February 28, 2023 MW 5.4 (GCMT) CARLSBERG RIDGE
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title: Moment Tensor for February 28, 2023 MW 5.0 (GCMT) NORTHERN MOLUCCA SEA
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title: Moment Tensor for February 28, 2023 MW 5.0 (GCMT) SICHUAN, CHINA
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title: Moment Tensor for February 28, 2023 MW 5.3 (GCMT) SOUTHEAST OF EASTER ISLAND
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title: Moment Tensor for February 28, 2023 MW 5.4 (GCMT) NEAR COAST OF GUATEMALA