cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17387611
title: TUD-HCMC Dataset for Floating Litter Detection and Flux Quanitification

description: Dataset

This dataset contains the data used for the publication:



Jia, T., Taormina, R., de Vries, R., Kapelan, Z., van Emmerik, T. H., Vriend, P., & Okkerman, I. (2025). A semi-supervised learning-based framework for quantifying litter fluxes in river systems. Water Research, 124833.


The TU Delft - Ho Chi Minh City (TUD-HCMC) dataset is for detecting floating litter and quantifying litter fluxes in rivers with wide cross-sections using computer vision techniques. The Data information.xlsx file shows the detailed information of the collected images. The images and annotations are stored in two folders (i.e., Thu Thiem 0909 and Binh Loi 1209) 

We conducted measurements at the Binh Loi and Thu Thiem bridges across the Saigon River in Ho Chi Minh City, Vietnam, over two days during the wet season in September 2023. We divided each bridge into five transects, and monitored floating litter at the center of each transect. The length of these transects was carefully selected to ensure that the bridge piers were not visible within the camera's field of view during sampling. All measurements were performed in the southernmost side of bridges during the ebb tide. On each measurement day, we conducted 4 or 6 rounds of measurements. During each round, we captured images (6016×4000 pixels) sequentially from the sampling point 1 to 5, using a handheld camera (Pentax K-series) over a period of 130 seconds. The camera was oriented nearly vertically with respect to the water surface, with a time-lapse recording (1 image/10 seconds). The observation area width for each sampling point is 7 m, and the ground sampling distance (GSD) of each image is 0.12 cm/pixel. Due to instability in the operation of the handheld camera, we only selected the images without heavy blur for measuring litter fluxes. Finally, we built the TUD-HCMC dataset, including 199 images and 309 images collected from the Thu Thiem and Binh Loi bridge, respectively. We annotated litter items in images using bounding boxes to indicate their locations. Since some items appear in multiple consecutive images, the number of annotated litter items exceeds the actual number of litter items in the rivers (see Data information.xlsx file).

Cite this dataset

If you use this dataset for a publication, please cite the paper. Here is a BibTeX entry:



@article{jia2025semi,
  title={A semi-supervised learning-based framework for quantifying litter fluxes in river systems},
  author={Jia, Tianlong and Taormina, Riccardo and de Vries, Rinze and Kapelan, Zoran and van Emmerik, Tim HM and Vriend, Paul and Okkerman, Imke},
  journal={Water Research},
  pages={124833},
  year={2025},
  publisher={Elsevier}
}
DOI: 10.5281/zenodo.17387612
title: TUD-HCMC Dataset for Floating Litter Detection and Flux Quanitification

description: Dataset

This dataset contains the data used for the publication:



Jia, T., Taormina, R., de Vries, R., Kapelan, Z., van Emmerik, T. H., Vriend, P., & Okkerman, I. (2025). A semi-supervised learning-based framework for quantifying litter fluxes in river systems. Water Research, 124833.


The TU Delft - Ho Chi Minh City (TUD-HCMC) dataset is for detecting floating litter and quantifying litter fluxes in rivers with wide cross-sections using computer vision techniques. The Data information.xlsx file shows the detailed information of the collected images. The images and annotations are stored in two folders (i.e., Thu Thiem 0909 and Binh Loi 1209) 

We conducted measurements at the Binh Loi and Thu Thiem bridges across the Saigon River in Ho Chi Minh City, Vietnam, over two days during the wet season in September 2023. We divided each bridge into five transects, and monitored floating litter at the center of each transect. The length of these transects was carefully selected to ensure that the bridge piers were not visible within the camera's field of view during sampling. All measurements were performed in the southernmost side of bridges during the ebb tide. On each measurement day, we conducted 4 or 6 rounds of measurements. During each round, we captured images (6016×4000 pixels) sequentially from the sampling point 1 to 5, using a handheld camera (Pentax K-series) over a period of 130 seconds. The camera was oriented nearly vertically with respect to the water surface, with a time-lapse recording (1 image/10 seconds). The observation area width for each sampling point is 7 m, and the ground sampling distance (GSD) of each image is 0.12 cm/pixel. Due to instability in the operation of the handheld camera, we only selected the images without heavy blur for measuring litter fluxes. Finally, we built the TUD-HCMC dataset, including 199 images and 309 images collected from the Thu Thiem and Binh Loi bridge, respectively. We annotated litter items in images using bounding boxes to indicate their locations. Since some items appear in multiple consecutive images, the number of annotated litter items exceeds the actual number of litter items in the rivers (see Data information.xlsx file).

Cite this dataset

If you use this dataset for a publication, please cite the paper. Here is a BibTeX entry:



@article{jia2025semi,
  title={A semi-supervised learning-based framework for quantifying litter fluxes in river systems},
  author={Jia, Tianlong and Taormina, Riccardo and de Vries, Rinze and Kapelan, Zoran and van Emmerik, Tim HM and Vriend, Paul and Okkerman, Imke},
  journal={Water Research},
  pages={124833},
  year={2025},
  publisher={Elsevier}
}
DOI: 10.15468/dl.wefje3
title: Occurrence Download

description: A dataset containing 682480 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((-41.83 -6.52,-41.83 -10.3,-32.9 -10.3,-32.9 -6.32,-41.83 -6.52))",
 "Geometry POLYGON((-33.2 -3.3,-33.2 -4.41,-31.1 -4.41,-31.1 -3.3,-33.2 -3.3))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 682480 records from 462 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006241-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17474016
title: Assessment of the Bacterial and Physico-chemical Quality of Reservoir Water in Ohodo Metropolis

description: Abstract: 

The safety of drinking water sources is a critical public health issue. This study assessed the bacteriological quality of water samples collected from eight selected reservoirs in Ohodo metropolis over a three-month period. Samples were analyzed for physico-chemical parameters (temperature, pH, electrical conductivity, turbidity) on-site and for microbial content in the laboratory. The membrane filtration technique was employed for bacterial isolation and the dilution method for total counts. Results showed that while physico-chemical properties of the water samples met WHO standards, microbial analysis indicated poor quality. Total bacterial counts were high, ranging from 1.0 x 10² to 1.1 x 10⁵ cfu/ml, with total coliform counts up to 11.03 cfu/100ml. Critically, several pathogenic bacteria were identified: Escherichia coli, Shigella spp., Staphylococcus aureus, Bacillus cereus, Salmonella typhi, Pseudomonas aeruginosa, Enterobacter spp., and Klebsiella pneumoniae. These findings confirm significant fecal contamination, rendering the water a direct threat to public health and increasing consumer risk for illnesses like diarrhea, typhoid fever, and cholera.

Keywords: Bacterial, Physico-chemical, Reservoir Water and Quality of water.
DOI: 10.5281/zenodo.17474017
title: Assessment of the Bacterial and Physico-chemical Quality of Reservoir Water in Ohodo Metropolis

description: Abstract: 

The safety of drinking water sources is a critical public health issue. This study assessed the bacteriological quality of water samples collected from eight selected reservoirs in Ohodo metropolis over a three-month period. Samples were analyzed for physico-chemical parameters (temperature, pH, electrical conductivity, turbidity) on-site and for microbial content in the laboratory. The membrane filtration technique was employed for bacterial isolation and the dilution method for total counts. Results showed that while physico-chemical properties of the water samples met WHO standards, microbial analysis indicated poor quality. Total bacterial counts were high, ranging from 1.0 x 10² to 1.1 x 10⁵ cfu/ml, with total coliform counts up to 11.03 cfu/100ml. Critically, several pathogenic bacteria were identified: Escherichia coli, Shigella spp., Staphylococcus aureus, Bacillus cereus, Salmonella typhi, Pseudomonas aeruginosa, Enterobacter spp., and Klebsiella pneumoniae. These findings confirm significant fecal contamination, rendering the water a direct threat to public health and increasing consumer risk for illnesses like diarrhea, typhoid fever, and cholera.

Keywords: Bacterial, Physico-chemical, Reservoir Water and Quality of water.
DOI: 10.6084/m9.figshare.30022813
title: Guía del Taller: "Uso Efectivo de Herramientas de IA Generativa"

description: <b>Guía del Taller:</b> <i>“Uso Efectivo de Herramientas de IA Generativa”.</i>Este documento forma parte del material para la Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b><br>Autores: Concepción González García (UCAM), Nina Pallarés Cerdá (UCAM).<br><b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.6084/m9.figshare.30022813.v1
title: Guía del Taller: "Uso Efectivo de Herramientas de IA Generativa"

description: <b>Guía del Taller:</b> <i>“Uso Efectivo de Herramientas de IA Generativa”.</i>Este documento forma parte del material para la Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp. </b><br>Autores: Concepción González García (UCAM), Nina Pallarés Cerdá (UCAM).<br><br>
DOI: 10.6084/m9.figshare.30022813.v2
title: Guía del Taller: "Uso Efectivo de Herramientas de IA Generativa"

description: <b>Guía del Taller:</b> <i>“Uso Efectivo de Herramientas de IA Generativa”.</i>Este documento forma parte del material para la Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b><br>Autores: Concepción González García (UCAM), Nina Pallarés Cerdá (UCAM).<br><b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.15468/dl.8ceb7s
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "StateProvince is one of (Karnataka, Maharashtra, Andhra Pradesh, Telangana)",
 "TaxonKey is Micrixalus kottigeharensis"
 ]
}

 The dataset includes 43 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006368-251025141854904/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.30022804
title: Instrumento de Evaluación de Competencias Digitales

description: <b>Instrumento de </b><b>Evaluación de Competencias Digitales</b><br>Este documento forma parte del material para la Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b><br>Autores: Concepción González García (UCAM), Nina Pallarés Cerdá (UCAM).<br><b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.6084/m9.figshare.30022804.v1
title: Instrumento de Evaluación de Competencias Digitales

description: <b>Instrumento de </b><b>Evaluación de Competencias Digitales</b><br>Este documento forma parte del material para la Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b><br>Autores: Concepción González García (UCAM), Nina Pallarés Cerdá (UCAM).<br><b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.6084/m9.figshare.30022798
title: Datos CSV

description: Base de datos para la a Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b>Autores: Concepción González García (UCAM),Nina Pallarés Cerdá (UCAM).<b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.6084/m9.figshare.30022798.v1
title: Datos CSV

description: Base de datos para la a Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b>Autores: Concepción González García (UCAM),Nina Pallarés Cerdá (UCAM).<b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.6084/m9.figshare.30022777
title: Manual docente para el diseño de las Autoevaluaciones en línea

description: <b>Manual Docente para el Diseño de las Autoevaluaciones en Línea</b><br>Este documento forma parte del material para la Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b><br>Autores: Concepción González García (UCAM), Nina Pallarés Cerdá (UCAM).<br><b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.6084/m9.figshare.30022777.v2
title: Manual docente para el diseño de las Autoevaluaciones en línea

description: <b>Manual Docente para el Diseño de las Autoevaluaciones en Línea</b><br>Este documento forma parte del material para la Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b><br>Autores: Concepción González García (UCAM), Nina Pallarés Cerdá (UCAM).<br><b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.6084/m9.figshare.30022777.v1
title: Manual docente para el diseño de las Autoevaluaciones en línea

description: <b>Manual Docente para el Diseño de las Autoevaluaciones en Línea</b><br>Este documento forma parte del material para la Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b><br>Autores: Concepción González García (UCAM), Nina Pallarés Cerdá (UCAM).
DOI: 10.6084/m9.figshare.30022663
title: Código de análisis (STATA)

description: Código de análisis para la a Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b>Autores: Concepción González García (UCAM),Nina Pallarés Cerdá (UCAM).<b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.6084/m9.figshare.30022663.v1
title: Código de análisis (STATA)

description: Código de análisis para la a Replicación del Estudio: <b>Impacto de la IA Generativa en Competencias Digitales Universitarias: Evidencia Experimental Basada en el Marco DigComp.</b>Autores: Concepción González García (UCAM),Nina Pallarés Cerdá (UCAM).<b>Artículo completo para </b><b>descargar</b><i>https://doi.org/10.5944/ried.45533</i>
DOI: 10.15468/dl.sevkyp
title: Occurrence Download

description: A dataset containing 213 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Cytinus ruber",
 "Year 1800-2025"
 ]
}

 The dataset includes 213 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006370-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mqvbrc
title: Occurrence Download

description: A dataset containing 489 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prunus subhirtella",
 "HasCoordinate is true"
 ]
}

 The dataset includes 489 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006369-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qgqxmj
title: Occurrence Download

description: A dataset containing 65479 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Liriodendron tulipifera",
 "HasCoordinate is true"
 ]
}

 The dataset includes 65479 records from 448 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006321-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15649644
title: Data for a publication "Influence of surface roughness on molecular flow through labyrinth seals for space applications"

description: This dataset contains simulation results, processed data, and MATLAB scripts used to analyze the influence of surface roughness on molecular flow through labyrinth seals for space applications. It includes synthetic surface roughness profiles, molecular flow simulations from COMSOL Multiphysics, and correction functions developed in MATLAB. The data support the manuscript “Influence of Surface Roughness on Molecular Flow through Labyrinth Seals for Space Applications” and enable reproduction and further development of the presented correction model.
DOI: 10.5281/zenodo.15649645
title: Data for a publication "Influence of surface roughness on molecular flow through labyrinth seals for space applications"

description: This dataset contains simulation results, processed data, and MATLAB scripts used to analyze the influence of surface roughness on molecular flow through labyrinth seals for space applications. It includes synthetic surface roughness profiles, molecular flow simulations from COMSOL Multiphysics, and correction functions developed in MATLAB. The data support the manuscript “Influence of Surface Roughness on Molecular Flow through Labyrinth Seals for Space Applications” and enable reproduction and further development of the presented correction model.
DOI: 10.17026/ar/xloe33
title: Plangebied Slotvalkensteinsedijk 5 te Poortugaal, gemeente Albrandswaard. Archeologisch vooronderzoek: proefsleuvenonderzoek. Plangebied Slotvalkensteinsedijk 5 te Poortugaal, gemeente Albrandswaard. Archeologisch vooronderzoek: proefsleuvenonderzoek.

description: &lt;p&gt;In opdracht van de gemeente Albrandswaard heeft RAAP van 5 augustus tot en met 6 augustus 2024 een archeologisch proefsleuvenonderzoek uitgevoerd in het kader van het project ‘Poortugaal- Slotvalkensteinsedijk 5’ in de gemeente Albrandswaard. Op deze locatie was sprake van een 19eeeuwse boerderij met een oorsprong in de 14e eeuw.&lt;br&gt;Het doel van het proefsleuvenonderzoek was het vaststellen van de archeologische waarde van het terrein. Hiertoe was het noodzakelijk inzicht te krijgen in de precieze aard en omvang van de vindplaats. In het verlengde daarvan is in kaart gebracht wat de consequenties zijn van de onderzoeksresultaten voor de verdere planvorming in het plangebied. Is de archeologische vindplaats behoudenswaardig, en, zo ja, kan deze behouden blijven of dient deze te worden opgegraven?&lt;br&gt;Tijdens het onderzoek zijn drie proefsleuven aangelegd met een totaal oppervlak van 238 m2. Dit komt neer op een dekkingsgraad van 8,6% van het totale plangebied. Dit onderzoek was beperkt tot een ontgravingsdiepte van 1 m -Mv, waarbij diepere waarnemingen door middel van boringen zijn vergaard.&lt;br&gt;Verspreid over de proefsleuven zijn verschillende archeologische resten aangetroffen. Deze sluiten overwegend aan bij de 19e- en 20e-eeuwse bebouwing en sloop, en zijn door een slechte conservering en lage informatiewaarde niet als behoudenswaardig bestempeld. Het vondstmateriaal bevatte daarbij een duidelijk oudere component, met een vroegste datering in de 14e eeuw. Hoewel dit materiaal uit geroerde contexten afkomstig is, is het een bevestiging van de lange gebruiksgeschiedenis van deze locatie. De aanwezigheid van oudere laatmiddeleeuwse of Nieuwe tijdse archeologische resten beneden 1 m -Mv kan dan ook niet worden uitgesloten.&lt;/p&gt;
DOI: 10.15468/dl.229gbx
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Populus italica",
 "HasCoordinate is true"
 ]
}

 The dataset includes 10 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006372-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z2k8nw
title: Occurrence Download

description: A dataset containing 328 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "StateProvince is one of (Karnataka, Maharashtra, Andhra Pradesh, Telangana)",
 "TaxonKey is one of (Aquila heliaca, Aquila heliaca adalberti, Aquila heliaca heliaca)"
 ]
}

 The dataset includes 328 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006374-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qc2xnt
title: Occurrence Download

description: A dataset containing 9423 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aspergillus flavus"
 ]
}

 The dataset includes 9423 records from 143 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006373-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bgqvbe
title: Occurrence Download

description: A dataset containing 137 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "StateProvince is one of (Karnataka, Maharashtra, Andhra Pradesh, Telangana)",
 "TaxonKey is one of (Melursus ursinus, Melursus ursinus inornatus, Melursus ursinus ursinus)"
 ]
}

 The dataset includes 137 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006375-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.96xd22
title: Occurrence Download

description: A dataset containing 137 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "StateProvince is one of (Karnataka, Maharashtra, Andhra Pradesh, Telangana)",
 "TaxonKey is Melursus ursinus"
 ]
}

 The dataset includes 137 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006376-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.