cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18679964
title: Dataset: Air Quality Dataset for Luanda (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Luanda covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Luanda, compare Luanda with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18679965
title: Dataset: Air Quality Dataset for Luanda (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Luanda covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Luanda, compare Luanda with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.7807/immo:red:hk:suf:v7.2
title: RWI Real Estate Data - Hauskauf - suf
title: RWI Real Estate Data - Houses for Sale - suf

description: ImmobilienScout24 ist die größte Immobilien-Internetplattform in Deutschland. Auf der Website werden sowohl Immobilien zur privaten als auch zur gewerblichen Nutzung angeboten. Die Daten umfassen jedoch nur Wohnimmobilien. Der Datensatz umfasst die meisten auf der Plattform erhobenen Merkmale wie z.B. Preis, Größe und Ausstattung der Wohneinheit, aber auch generierte Informationen wie die Dauer der Inseratverfügbarkeit.
description: ImmobilienScout24 is the largest real estate internet platform in Germany. Properties for private as well as commercial use are offered on the website. However, the data only cover residential properties. The dataset covers most characteristics collected on the platform like price, size and characteristics of the housing unit but also automatically generated items like the duration of the advertisement spell.
description: RWI-GEO-RED
description: RWI-GEO-RED
description: Computer-based observation
description: alle Häuser zum Verkauf auf der Webseite ImmobilienScout24
description: all houses for sale at ImmobilienScout24
description: full sample
DOI: 10.15468/dl.uu68uu
title: Occurrence Download

description: A dataset containing 462225 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Eswatini"
 ]
}

 The dataset includes 462225 records from 321 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026995-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17617/3.muv1mf
title: Experimental Sodalis infection eliminates ancient insect symbiont

description: Many insects benefit from ancient nutrient-supplementing endosymbionts. While symbiont losses and replacements occur on evolutionary timescales, their dynamics remain enigmatic due to the lack of experimentally tractable systems. Here, we report on the experimental establishment of the culturable bacterium Sodalis praecaptivus in a grain pest beetle (Oryzaephilus surinamensis) and its effect on the native symbiont Shikimatogenerans silvanidophilus, which produces the tyrosine precursor prephenate. Injection of Sodalis into female beetles led to systemic intracellular infection and efficient transovarial vertical transmission but reduced host survival and reproduction. Interestingly, Sodalis also invaded the host’s bacteriomes, causing irregular morphology and rapid loss of Shikimatogenerans within three beetle generations. Transcriptomics revealed a strong upregulation of host immune effectors upon Sodalis infection, but little reaction from Shikimatogenerans, indicating that the ancient symbiont is incapable of responding adaptively to the introduced competitor. The rapid elimination of the native symbiont in O. surinamensis showcases the fragility of ancient beneficial symbioses and experimentally recapitulates a crucial step towards a functional symbiont replacement.
DOI: 10.5281/zenodo.18679977
title: Dataset: Air Quality Dataset for Osaka (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Osaka covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Osaka, compare Osaka with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18679978
title: Dataset: Air Quality Dataset for Osaka (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Osaka covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Osaka, compare Osaka with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.15468/dl.yjmnte
title: Occurrence Download

description: A dataset containing 1 records in GBIF matching the query:
SELECT
 COUNT(*)
FROM
 occurrence
WHERE
 CAST(occurrence.specieskey AS INTEGER) = 1423395
 AND occurrence.countrycode = 'SE'
 AND occurrence."month" IN (10, 11)

 The dataset's 1 records were derived from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027005-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18679957
title: DENTAL CALCULUS AND ITS EFFECT ON PERIODONTAL TISSUES

description: Dental calculus, commonly known as tartar, is a mineralized form of dental plaque that plays a significant role in the development and progression of periodontal diseases. Its presence on tooth surfaces creates a favorable environment for bacterial accumulation, leading to inflammation of periodontal tissues. This article examines the formation of dental calculus, its impact on periodontal structures, and the clinical consequences associated with its accumulation. The study also discusses preventive and therapeutic strategies aimed at minimizing periodontal damage. The findings confirm that dental calculus is a critical etiological factor in periodontal disease and requires early detection and professional management.
DOI: 10.5281/zenodo.18679956
title: DENTAL CALCULUS AND ITS EFFECT ON PERIODONTAL TISSUES

description: Dental calculus, commonly known as tartar, is a mineralized form of dental plaque that plays a significant role in the development and progression of periodontal diseases. Its presence on tooth surfaces creates a favorable environment for bacterial accumulation, leading to inflammation of periodontal tissues. This article examines the formation of dental calculus, its impact on periodontal structures, and the clinical consequences associated with its accumulation. The study also discusses preventive and therapeutic strategies aimed at minimizing periodontal damage. The findings confirm that dental calculus is a critical etiological factor in periodontal disease and requires early detection and professional management.
DOI: 10.21227/s8ff-a919
title: "PQA_MG_KEDU25"

description: "The current global initiatives for rural electrification have promoted the application of renewable energy-based minigrids. These minigrids are highly influenced by weather dynamics, which impacts power quality and service delivery. Maintaining a high-quality power supply enhances the security and sustainability of the power system. This study provides an in-depth analysis of power quality in autonomous minigrids, with a critical focus on evaluating key power quality attributes, including power factor, harmonic distortion, frequency stability, voltage stability, dips, swells, and interruptions. The study was carried out on eleven selected autonomous minigrids in different remote parts of Kenya. Questionnaires were used to collect data at all eleven visited sites. Minigrid data logging was performed at six of the eleven selected sites using a power quality analyzer (Fluke 1777) for one week at each site. Local and international power quality standards were used to collect and evaluate data. Novel fuzzy power quality indices were applied to compare the overall performance of individual minigrids. The study recorded the highest average power factor at Ndeda Island (0.89) and very poor average power factors at Illauti (0.61) and Remba Island (0.51). The frequency variation records of Locheromoit (0.52), Ndeda (0.59), and Remba (1.2) were outside the EN50160:2010 and IEEE519-2022 thresholds. Substantial interruptions were observed at Hadado (1.2 hrs\/week) and Illaut (2.59 hrs\/week). The Wasini minigrid recorded the highest total power quality index (0.94) of all the sites. These results demonstrate the critical role of power quality indices in identifying serious power quality issues prevalent in minigrids."
DOI: 10.5281/zenodo.18679985
title: Dataset: Air Quality Dataset for Linyi (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Linyi covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Linyi, compare Linyi with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18679986
title: Dataset: Air Quality Dataset for Linyi (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Linyi covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Linyi, compare Linyi with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18679993
title: Dataset: Air Quality Dataset for Baoding (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Baoding covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Baoding, compare Baoding with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18679994
title: Dataset: Air Quality Dataset for Baoding (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Baoding covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Baoding, compare Baoding with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.15468/dl.3wg785
title: Occurrence Download

description: A dataset containing 87 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)"
 ]
 }
 },
 "Year is greater than or equal to 1900",
 "TaxonKey is Sorghum virgatum"
 ]
}

 The dataset includes 87 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027029-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x5zfzr
title: Occurrence Download

description: A dataset containing 3995 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anabacerthia ruficaudata",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2026",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3995 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027027-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jejzw8
title: Occurrence Download

description: A dataset containing 1829 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((120.85292 20.47542,126.95829 22.57619,132.66977 32.02967,130.569 35.18083,130.50335 39.11978,125.77661 38.26634,122.03461 40.03887,116.78268 41.0236,102.66811 38.39764,98.92611 34.13044,100.50169 22.051,110.34906 18.70289,120.85292 20.47542))",
 "TaxonKey is Paulownia tomentosa"
 ]
}

 The dataset includes 1829 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027034-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zafj7s
title: Occurrence Download

description: A dataset containing 281 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((5.020921373829479 49.9998833305303, 5.0205552436840835 50.00251648889372, 5.019399063938768 50.00505300405723, 5.017497155800599 50.00739537636429, 5.014922533872124 50.009453555126434, 5.011774111625154 50.011148404492886, 5.0081729044604675 50.012414750870256, 5.0042573756154525 50.01320389382525, 5.000178104309623 50.013485483015614, 4.996091982671263 50.01324868819644, 4.992156166954211 50.012502616780864, 4.988522018471583 50.01127596270153, 4.98532927008866 50.00961590024113, 4.982700645011353 50.007586265872064, 4.9807371363967805 50.005265098781, 4.979514129825397 50.002741635550585, 4.979078517095288 50.00011287545348, 4.979446910600715 49.997479849173686, 4.980605024413213 49.99494373490096, 4.982508242881555 49.99260197125985, 4.9850833519172735 49.99054451627505, 4.9882313638908204 49.98885039560872, 4.991831325861763 49.987584671916274, 4.995744964162135 49.986795950832885, 4.999821987390734 49.98651451847465, 5.00390584566873 49.986751181210195, 5.007839727318452 49.98749685173493, 5.011472565471035 49.98872289714825, 5.01466482674704 49.99038223583131, 5.017293862098103 49.992411141500256, 5.019258615906567 49.994731685906444, 5.02048351302247 49.99725472726531, 5.020921373829479 49.9998833305303))",
 "KingdomKey is one of (Animalia, Fungi, Plantae)",
 "Year is one of (2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026)"
 ]
}

 The dataset includes 281 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027025-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ffu5ex
title: Occurrence Download

description: A dataset containing 48725 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hydrobia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 48725 records from 218 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027032-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18680000
title: Dataset: Air Quality Dataset for Kaohsiung (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Kaohsiung covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Kaohsiung, compare Kaohsiung with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18680001
title: Dataset: Air Quality Dataset for Kaohsiung (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Kaohsiung covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Kaohsiung, compare Kaohsiung with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.7807/immo:red:hm:suf:v6.2
title: RWI Real Estate Data - Hausmiete - suf
title: RWI Real Estate Data - Houses for Rent - suf

description: ImmobilienScout24 ist die größte Immobilien-Internetplattform in Deutschland. Auf der Website werden sowohl Immobilien zur privaten als auch zur gewerblichen Nutzung angeboten. Die Daten umfassen jedoch nur Wohnimmobilien. Der Datensatz umfasst die meisten auf der Plattform erhobenen Merkmale wie z.B. Preis, Größe und Ausstattung der Wohneinheit, aber auch generierte Informationen wie die Dauer der Inseratverfügbarkeit.
description: ImmobilienScout24 is the largest real estate internet platform in Germany. Properties for private as well as commercial use are offered on the website. However, the data only cover residential properties. The dataset covers most characteristics collected on the platform like price, size and characteristics of the housing unit but also automatically generated items like the duration of the advertisement spell.
description: RWI-GEO-RED
description: RWI-GEO-RED
description: Computer-based observation
description: alle Häuser zur Miete auf der Webseite ImmobilienScout24
description: all houses for rent at ImmobilienScout24
description: full sample
DOI: 10.15468/dl.g28qpa
title: Occurrence Download

description: A dataset containing 12315 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aira caryophyllea",
 "Continent is Europe",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 100",
 "Year is greater than or equal to 1970",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Material citation"
 ]
 }
 }
 ]
}

 The dataset includes 12315 records from 163 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027030-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.20351/29he20260111
title: ATMESHET Cruise, RV Hespérides
title: 29HE20260111

description: TEMPORAL ANALYSIS AND SPATIAL MODELING OF ACTIVE TECTONIC AND VOLCANIC PROCESSES USING GNSS TIME SERIES AND SEISMOGEODETICS IN THE SOUTH SHETLAND ISLANDS AND ANTARCTIC PENINSULA (ATMESHET) SUMMARY This project proposes the establishment of a network of seismic geodetic stations integrated with cGNSS stations and MEMS accelerometers, along with tide gauges in their vicinity. This configuration enables the acquisition of unified topocentric series, 3D accelerations, and instantaneous sea level data. Its key feature lies in transitioning from episodic observations to continuous cGNSS observations at the vertices of the Antarctic Geodetic Network in Spanish (RGAE Network). The ability to generate time series conceptually alters the temporal analysis of geodynamic evolution. The analytical study and statistical analysis provide precise information regarding the detection, behavior, and forecast of tectonic and/or volcanic geodynamic processes in the Shetland Islands region of the South, Bransfield Sea, and Antarctic Peninsula (SHETPENANT). The establishment of more precise 3D geodynamic models will facilitate a detailed study of the subduction process of the Phoenix microplate. The temporal analysis of the obtained series will reveal the pre-seismic, co-seismic, and post-seismic phases of the geodynamic process. Their assessment will yield crucial insights into the nature of the process. The instantaneous sea level data will enable correlation with the process's magnitude, establishing a pattern for tsunami generation in the region. GNSS time series will offer ionospheric and tropospheric models, showing their temporal evolution and variation with geodynamic activity. This involves calculating parameters such as total electron content (TEC) and precipitable water vapor (PWV). A comprehensive review of the 3D series on the geodynamic mechanism of Deception Island will be conducted. GNSS processing will be performed using various scientific software (such as Bernese and GIPSY) and different constellations, including multi-constellation approaches. Particular emphasis will be placed on evaluating the performance of the Galileo system and its contribution to determining deformation parameters for geodynamic applications. The exploration will extend to kinematic techniques and methods for processing GNSS observations. This project comprises several components: Design and development of multiparameter GNSS Network, MEMS accelerometer, and tide gauge in the South Shetland Islands, Bransfield Sea, and Antarctic Peninsula (SHETPENANT). Review and analysis of GNSS processing techniques to evaluate the performance of both GPS and Galileo systems. Methodological actions for temporal analysis of tectonic and/or volcanic geodynamical processes in the SHETPENANT region. Spatial modeling to represent this geodynamical activity. Application to other regions with significant tectonic and/or volcanic processes: the Mexican Volcanic Belt and Popocatépetl volcano in Mexico, and the subduction of the Cocos plate and Concepción volcano in Nicaragua.