cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14968157
title: Dataset of "Rayleigh wave sensitivity to fluid saturation changes in volcano hydrothermal systems"

description: This dataset supports the research study "Rayleigh wave sensitivity to fluid saturation changes in volcano hydrothermal systems" by G. A. Castromán, M. Rosas-Carbajal, N. D. Barbosa, M.J. Heap, C. Caudron, A. Burtin and F. I. Zyserman.

We provide with commented octave codes for estimating the phase velocity of Rayleigh waves in a layered subsurface model representative of a volcano hydrothermal system. The codes reproduce all the figures of the article.

In doubt, contact at: gcastroman@fcaglp.unlp.edu.ar
DOI: 10.5281/zenodo.14968158
title: Dataset of "Rayleigh wave sensitivity to fluid saturation changes in volcano hydrothermal systems"

description: This dataset supports the research study "Rayleigh wave sensitivity to fluid saturation changes in volcano hydrothermal systems" by G. A. Castromán, M. Rosas-Carbajal, N. D. Barbosa, M.J. Heap, C. Caudron, A. Burtin and F. I. Zyserman.

We provide with commented octave codes for estimating the phase velocity of Rayleigh waves in a layered subsurface model representative of a volcano hydrothermal system. The codes reproduce all the figures of the article.

In doubt, contact at: gcastroman@fcaglp.unlp.edu.ar
DOI: 10.15468/dl.96fr2d
title: Occurrence Download

description: A dataset containing 2242 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "TaxonKey is Meles meles (Linnaeus, 1758)"
 ]
}

 The dataset includes 2242 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007304-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/10945498
title: Balochi Language to English Translation Dataset
DOI: 10.5281/zenodo.14983912
title: DiJetGAN tuples

description: A Generative-Adversarial Network (GAN) based on convolutional neural networks is used to simulate the production of pairs of jets at the LHC. The GAN is trained on events generated using MADGRAPH5, PYTHIA8, and DELPHES3 fast detector simulation. We demonstrate that a number of kinematic distributions both at Monte Carlo truth level and after the detector simulation can be reproduced by the generator network.
DOI: 10.5281/zenodo.14983913
title: DiJetGAN tuples

description: A Generative-Adversarial Network (GAN) based on convolutional neural networks is used to simulate the production of pairs of jets at the LHC. The GAN is trained on events generated using MADGRAPH5, PYTHIA8, and DELPHES3 fast detector simulation. We demonstrate that a number of kinematic distributions both at Monte Carlo truth level and after the detector simulation can be reproduced by the generator network.
DOI: 10.15468/dl.wu87qh
title: Occurrence Download

description: A dataset containing 132982 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Côte d’Ivoire",
 "GadmGid is CIV",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (EX, EW, CR, EN, VU, NT, LC, DD, NE)",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae",
 "Year 1954-2025"
 ]
}

 The dataset includes 132982 records from 106 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007302-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.78kebe
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((-94.48215 37.18079,-94.4814 37.18077,-94.48135 37.18167,-94.4821 37.1817,-94.48213 37.18117,-94.48215 37.18083,-94.48215 37.18079))",
 "Geometry POLYGON((-94.48122 37.18034,-94.48218 37.17995,-94.4822 37.17994,-94.48223 37.17943,-94.48223 37.17939,-94.48208 37.17954,-94.48193 37.17968,-94.48178 37.17973,-94.4817 37.17975,-94.48156 37.17977,-94.48138 37.17972,-94.48107 37.17968,-94.48087 37.17964,-94.48061 37.17957,-94.48038 37.1795,-94.48018 37.17945,-94.47998 37.17938,-94.47985 37.17933,-94.47972 37.17926,-94.47959 37.17919,-94.4795 37.17917,-94.47938 37.17918,-94.4793 37.17922,-94.47921 37.17924,-94.47913 37.17925,-94.47906 37.17927,-94.47903 37.17933,-94.47903 37.17942,-94.47906 37.17953,-94.47909 37.17965,-94.47912 37.17972,-94.47911 37.17982,-94.47905 37.1799,-94.47899 37.17998,-94.47891 37.18005,-94.47887 37.18015,-94.4788 37.18029,-94.47873 37.18039,-94.4787 37.18042,-94.47865 37.18047,-94.47861 37.18061,-94.47856 37.18071,-94.4806 37.18075,-94.48068 37.18069,-94.48093 37.1805,-94.48122 37.18034))",
 "Geometry POLYGON((-94.48213 37.18117,-94.4821 37.1817,-94.4821 37.18172,-94.48282 37.18175,-94.48285 37.1812,-94.48213 37.18117))",
 "Geometry POLYGON((-94.48217 37.18055,-94.48215 37.18079,-94.48215 37.18083,-94.48287 37.18086,-94.48295 37.17946,-94.48223 37.17943,-94.48217 37.18055))",
 "Geometry POLYGON((-94.48093 37.1805,-94.48068 37.18069,-94.4806 37.18075,-94.4814 37.18077,-94.4814 37.18077,-94.48215 37.18079,-94.48217 37.18055,-94.4822 37.17994,-94.48218 37.17995,-94.48122 37.18034,-94.48093 37.1805))",
 "Geometry POLYGON((-94.48287 37.18086,-94.48215 37.18083,-94.48213 37.18117,-94.48285 37.1812,-94.48287 37.18086))",
 "Geometry POLYGON((-94.482 37.18348,-94.48198 37.18398,-94.48191 37.18512,-94.48645 37.18526,-94.4883 37.18531,-94.48837 37.18363,-94.48848 37.18363,-94.49095 37.18369,-94.49101 37.18204,-94.49108 37.18022,-94.49005 37.18019,-94.48892 37.18015,-94.48755 37.18011,-94.48669 37.18008,-94.48678 37.17827,-94.48344 37.17816,-94.4823 37.17812,-94.48229 37.17835,-94.48223 37.17939,-94.48223 37.17943,-94.48295 37.17946,-94.48287 37.18086,-94.48285 37.1812,-94.48282 37.18175,-94.48282 37.18177,-94.48272 37.1835,-94.482 37.18348))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007306-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2n5fxr
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-105.48074334190986 20.520283104591254,-105.37088006065986 20.520283104591254,-105.37088006065986 20.630146385841254,-105.48074334190986 20.630146385841254,-105.48074334190986 20.520283104591254))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Obelia Péron & Lesueur, 1810"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007307-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/fqqe-g413
title: BRURIIoT: A Dataset for Network Anomaly Detection in IIoT with an Enhanced Feature Engineering Approach

description: This paper presents an enhanced methodology for network anomaly detection in Industrial IoT (IIoT) systems using advanced data aggregation and Mutual Information (MI)-based feature selection. The focus is on transforming raw network traffic into meaningful, aggregated forms that capture crucial temporal and statistical patterns. A refined set of 150 features including unique IP counts, TCP acknowledgment patterns, and ICMP sequence ratios was identified using MI to enhance detection accuracy. The approach is experimented with our BRURIIoT dataset comprising over 59 million network packets condensed into 3 million records. Unlike existing datasets with limited attack diversity or missing key features, BRURIIoT preserves nuanced attack behaviors in real-world IIoT devices. SHapley Additive exPlanations (SHAP) analysis demonstrated the importance of aggregated features in model predictions. Machine learning classifiers, including Support Vector Machine (SVM), Gradient Boost, XGBoost, CatBoost, KNN, AdaBoost, Random Forest, Extra Trees, and a custom DNN model are trained on the aggregated data achieved outstanding performance with an accuracy of 99.52%, precision of 98.20% and recall of 98.13%, F1-score of 98.17%. These results were validated using K-fold cross-validation to verify their robustness and reliability. The outcome of this work presents an enabling framework for scaling IIoT cyberattack detection via the application of advanced aggregation and feature engineering towards developing interpretable, scalable, and effective cybersecurity solutions. The findings address the urgent need for robust anomaly detection techniques for modern IIoT environments.
DOI: 10.15468/dl.jqb9b7
title: Occurrence Download

description: A dataset containing 1244870 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is RU-BIRDS.RU, Birds observations database from Russia and neighboring regions. Zoological Museum of M.V. Lomonosov Moscow State University."
 ]
}

 The dataset includes 1244870 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007305-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8tpu7d
title: Occurrence Download

description: A dataset containing 10877 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ameiva ameiva (Linnaeus, 1758))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 10877 records from 174 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007257-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14983931
title: Dataset for "Span Definition for Two-Way Slab Deflection Control Provisions"

description: Code use for first submission for peer review.
DOI: 10.5281/zenodo.14983930
title: Dataset for "Span Definition for Two-Way Slab Deflection Control Provisions"

description: Code use for first submission for peer review.
DOI: 10.5281/zenodo.14983894
title: Raw Data and Generated Synthetic Weather Year Datasets

description: This dataset contains both the raw data and the generated synthetic weather years used in the paper submitted to Progress in Energy. The data covers 11 regions analyzed in this study: Austria (AT), Belgium (BE), Denmark (DK), the Czech Republic (CZ), France (FR), Germany (DE), Italy (IT), Luxembourg (LU), the Netherlands (NL), Poland (PL), and Switzerland (CH).



demand_generation_all.csv: This file includes the raw data, adjusted data, and residual load used in the study. The adjusted demand and renewable generation time series have been specifically designed to align with our system setup. These adjustments are based on renewable capacity values and demand values derived from the FlexMex scenario 2D. A detailed description of FlexMex is available at https://zenodo.org/records/5802178. The dataset includes the following columns: 



Timestamps: Defined by the columns 'year', 'month', 'day', and 'hour'.

Raw demand time series: 'country code+ _demand'

Raw renewable generation time series:



Solar PV:  'country code + _solar'.

Wind onshore:  'country code + _wind_onshore'.

Wind offshore:  'country code + _wind_offshore'.



Adjusted demand time series: 'country code + _demand_aj'

Adjusted renewable generation time series:



Solar PV:  'country code + _solar_aj'.

Wind onshore:  'country code + _wind_onshore_aj'.

Wind offshore:  'country code + _wind_offshore_aj'.



Residual Load time series: 'country code + _r_load_aj'.



'TMY.csv': Time series of the typical meteorological year.

'ELY.csv': Time series of the extreme low residual load year.

'EHY.csv': Time series of the extreme high residual load year.

'TMY_1D.csv': Time series of the typical meteorological year with a one-day extreme event.

'TMY_1W.csv': Time series of the typical meteorological year with a one-week extreme event.

'TMY_2W.csv': Time series of the typical meteorological year wth a two-week extreme event.

'EHY_1D.csv': Time series of the extreme high residual load year with a one-day extreme event.

'EHY_2W.csv': Time series of the extreme high residual load year with a two-week extreme event..
DOI: 10.5281/zenodo.14983895
title: Raw Data and Generated Synthetic Weather Year Datasets

description: This dataset contains both the raw data and the generated synthetic weather years used in the paper submitted to Progress in Energy. The data covers 11 regions analyzed in this study: Austria (AT), Belgium (BE), Denmark (DK), the Czech Republic (CZ), France (FR), Germany (DE), Italy (IT), Luxembourg (LU), the Netherlands (NL), Poland (PL), and Switzerland (CH).



demand_generation_all.csv: This file includes the raw data, adjusted data, and residual load used in the study. The adjusted demand and renewable generation time series have been specifically designed to align with our system setup. These adjustments are based on renewable capacity values and demand values derived from the FlexMex scenario 2D. A detailed description of FlexMex is available at https://zenodo.org/records/5802178. The dataset includes the following columns: 



Timestamps: Defined by the columns 'year', 'month', 'day', and 'hour'.

Raw demand time series: 'country code+ _demand'

Raw renewable generation time series:



Solar PV:  'country code + _solar'.

Wind onshore:  'country code + _wind_onshore'.

Wind offshore:  'country code + _wind_offshore'.



Adjusted demand time series: 'country code + _demand_aj'

Adjusted renewable generation time series:



Solar PV:  'country code + _solar_aj'.

Wind onshore:  'country code + _wind_onshore_aj'.

Wind offshore:  'country code + _wind_offshore_aj'.



Residual Load time series: 'country code + _r_load_aj'.



'TMY.csv': Time series of the typical meteorological year.

'ELY.csv': Time series of the extreme low residual load year.

'EHY.csv': Time series of the extreme high residual load year.

'TMY_1D.csv': Time series of the typical meteorological year with a one-day extreme event.

'TMY_1W.csv': Time series of the typical meteorological year with a one-week extreme event.

'TMY_2W.csv': Time series of the typical meteorological year wth a two-week extreme event.

'EHY_1D.csv': Time series of the extreme high residual load year with a one-day extreme event.

'EHY_2W.csv': Time series of the extreme high residual load year with a two-week extreme event..
DOI: 10.25376/hra.28550435
title: 1-s2.0-S0753332223016438-main-2.pdf

description: We studied how the mitophagy regulates the vascular function in animal treated with ethanol
DOI: 10.25376/hra.28550435.v1
title: 1-s2.0-S0753332223016438-main-2.pdf

description: We studied how the mitophagy regulates the vascular function in animal treated with ethanol
DOI: 10.15468/dl.quhb7w
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-105.32327263878486 20.566059471778754,-105.21340935753486 20.566059471778754,-105.21340935753486 20.675922753028754,-105.32327263878486 20.675922753028754,-105.32327263878486 20.566059471778754))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Obelia Péron & Lesueur, 1810"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007258-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8aek4g
title: Occurrence Download

description: A dataset containing 77742 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fagus grandifolia Ehrh."
 ]
}

 The dataset includes 77742 records from 328 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007301-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ebaqut
title: Occurrence Download

description: A dataset containing 2410 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cynomys mexicanus Merriam, 1892"
 ]
}

 The dataset includes 2410 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007309-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.824sw3
title: Occurrence Download

description: A dataset containing 40608 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anaphalis margaritacea (L.) Benth.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 40608 records from 398 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007308-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p14scuyu
title: Temperature data collected using Onset HOBO U-22 loggers deployed at intertidal sites on five Boston Harbor Islands, 2023

description: This dataset contains air and water temperature data recorded at multiple shoreline sites on five islands within Boston Harbor, MA USA over the period April - August, 2023. This data was collected using Onset HOBO U-22 temperature loggers that were deployed across 5 islands: Gallops, Georges, Lovell, Peddocks, and Thompson Island. The dataset contains the island name, site designation, date, and time for the temperature data recorded.
DOI: 10.15468/dl.qyyqdy
title: Occurrence Download

description: A dataset containing 7310 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "TaxonKey is Selasphorus rufus (J.F.Gmelin, 1788)",
 "Year 2010-2024"
 ]
}

 The dataset includes 7310 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007312-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mqa3pr
title: Occurrence Download

description: A dataset containing 48843 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Andropogon gayanus Kunth)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 48843 records from 187 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007310-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.enwpr3
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Coronula diadema (Linnaeus, 1767)"
 ]
}

 The dataset includes 4 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007261-250227182400228/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.28548758
title: BreastSwinFedNetX

description: The datasets used in this study were collected from the Kaggle platform. Below are their available links:1. BreakHis: https://www.kaggle.com/datasets/ambarish/breakhis2. Breast Ultrasound Images Dataset (BUSI): https://www.kaggle.com/datasets/sabahesaraki/breast-ultrasound-images-dataset3. CBIS-DDSM: https://www.kaggle.com/datasets/seanbaek19/cbis-ddsm-40964. INbreast: https://www.kaggle.com/datasets/eoussama/breast-cancer-mammograms/data5. Combined Dataset: https://www.kaggle.com/datasets/rezaullhaque/combined-dataset/data<br>The total data size is 26 GB.
DOI: 10.15468/dl.gbpfhk
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Coronula reginae Darwin, 1854"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007314-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.57ytw9
title: Occurrence Download

description: A dataset containing 25564 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "Geometry POLYGON((-129.54198 23.017,-54.9745 23.017,-54.9745 46.22423,-129.54198 46.22423,-129.54198 23.017))",
 "TaxonKey is Lycorma delicatula (White, 1845)"
 ]
}

 The dataset includes 25564 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007262-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ufkj82
title: Occurrence Download

description: A dataset containing 38126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is one of (United States of America, Canada, Mexico)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Bombus pensylvanicus (De Geer, 1773)",
 "Year 1900-2025"
 ]
}

 The dataset includes 38126 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007316-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n32rr3
title: Occurrence Download

description: A dataset containing 24522 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "OccurrenceStatus is Present",
 "TaxonKey is Rosaceae"
 ]
}

 The dataset includes 24522 records from 257 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007375-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25318/3310090801-eng
title: Level of impact interest rates have on the business or organization, fourth quarter of 2024

description: Level of impact interest rates have on the business or organization, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, fourth quarter of 2024.
DOI: 10.15468/dl.e56jtv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Squalus vulipinis (Bonnaterre, 1788)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007377-241126133413365/datasets/export for details.
DOI: 10.15468/dl.grvbkv
title: Occurrence Download

description: A dataset containing 325867 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lactuca serriola L."
 ]
}

 The dataset includes 325867 records from 2578 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007358-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.