cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/tttdwht3mp
title: Innovación Sostenible a partir de Caracterización de Ladrillos Sostenibles PolyCal Block con Plástico Reciclado y Carbonato de Calcio

description: Este proyecto desarrolla un ladrillo sostenible innovador, el 'PolyCal Block', diseñado para capturar CO2 durante su proceso de fabricación. Al integrar plástico reciclado y carbonato de calcio, este ladrillo ecoamigable no solo mejora las propiedades mecánicas, sino que también aborda desafíos ambientales críticos, como la alta contribución de la industria de la construcción a las emisiones de CO2, (39% global) y la mitigación de la contaminación por plástico, las pruebas de laboratorio evaluaron la resistencia a la compresión, la durabilidad, la absorción de agua y el aislamiento térmico para asegurar el cumplimiento de los estándares de la industria, adicionalmente, el proyecto evaluó la viabilidad económica, enfocándose en los costos de producción y la disponibilidad de materiales, dirigido a sectores como la construcción ecológica, proyectos de vivienda gubernamentales y el ecoturismo, PolyCal Block promueve los principios de la economía circular al reutilizar los residuos plásticos y reducir la huella de carbono. A pesar de desafíos como la aceptación del mercado y la variabilidad de los recursos, el proyecto demuestra un potencial significativo para revolucionar las prácticas de construcción sostenible a nivel global.
DOI: 10.17632/tttdwht3mp.1
title: Innovación Sostenible a partir de Caracterización de Ladrillos Sostenibles PolyCal Block con Plástico Reciclado y Carbonato de Calcio

description: Este proyecto desarrolla un ladrillo sostenible innovador, el 'PolyCal Block', diseñado para capturar CO2 durante su proceso de fabricación. Al integrar plástico reciclado y carbonato de calcio, este ladrillo ecoamigable no solo mejora las propiedades mecánicas, sino que también aborda desafíos ambientales críticos, como la alta contribución de la industria de la construcción a las emisiones de CO2, (39% global) y la mitigación de la contaminación por plástico, las pruebas de laboratorio evaluaron la resistencia a la compresión, la durabilidad, la absorción de agua y el aislamiento térmico para asegurar el cumplimiento de los estándares de la industria, adicionalmente, el proyecto evaluó la viabilidad económica, enfocándose en los costos de producción y la disponibilidad de materiales, dirigido a sectores como la construcción ecológica, proyectos de vivienda gubernamentales y el ecoturismo, PolyCal Block promueve los principios de la economía circular al reutilizar los residuos plásticos y reducir la huella de carbono. A pesar de desafíos como la aceptación del mercado y la variabilidad de los recursos, el proyecto demuestra un potencial significativo para revolucionar las prácticas de construcción sostenible a nivel global.
DOI: 10.17632/z42mw4r3dx
title: Electrical Impedance and resistence measurment device

description: These files are the necesary to build a device that could measure the electrical resistence and the electrical impedance of a sample of variable sizes.
DOI: 10.17632/z42mw4r3dx.1
title: Electrical Impedance and resistence measurment device

description: These files are the necesary to build a device that could measure the electrical resistence and the electrical impedance of a sample of variable sizes.
DOI: 10.15468/dl.v4hc2s
title: Occurrence Download

description: A dataset containing 37380 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Zalophus californianus (Lesson, 1828)"
 ]
}

 The dataset includes 37380 records from 173 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033588-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q93kbs
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (India, China, Myanmar, Nepal, Bhutan, Bangladesh, Pakistan, Afghanistan)",
 "TaxonKey is Colotis protractus (Butler, 1876)"
 ]
}

 The dataset includes 12 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033589-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/zj847r2gt9
title: Generational Differences in Music Perception: Optimising Background Music for Grocery Retail Stores in Slovakia

description: Quantitative date: customer identification based on camera. Software analyzed visitors (day time, gender, generation...) based on face analysis. Questionaire - music preferences in retail store in Slovakia.
DOI: 10.17632/zj847r2gt9.1
title: Generational Differences in Music Perception: Optimising Background Music for Grocery Retail Stores in Slovakia

description: Quantitative date: customer identification based on camera. Software analyzed visitors (day time, gender, generation...) based on face analysis. Questionaire - music preferences in retail store in Slovakia.
DOI: 10.17632/3pbhfhnh2g.1
title: Evolution of recent volcanic ash deposits under native and planted temperate forests in Patagonia, Argentina

description: This dataset originates from a research entitled: "Evolution of recent volcanic ash deposits under native and planted temperate forests in Patagonia, Argentina" , this study investigates the initial evolution of volcanic ash deposited by the Chaitén volcano in the Andean-Patagonian Region of Argentina and how different vegetation types influence its transformation. The research is part of a broader project titled "Soil neoformation and edaphic changes associated with conifer plantation in areas affected by recent volcanic eruptions."

To conduct this study, four sampling sites were selected along a west-east transect, where pine ponderosa plantations border native Cordillera cypress forests. Fifteen years later of the eruption undisturbed soil profile samples were collected for micromorphological analyses, while disturbed ash samples underwent physical, chemical, and biological assessments. Additionally, two ash samples from the May 2008 eruption were preserved and utilized as reference materials.

The dataset provides a description of the micromorphological characteristics of the ash and soil under different vegetation (cypress forests and pine plantations). Data obtained from the physical-chemical and biological analyses of the ash at the time of fall and fifteen years after its deposition are also provided. These data contribute valuable insights into post-eruption soil formation processes and the role of vegetation in modifying volcanic deposits.

For accessibility, the dataset has been deposited in Mendelay Data repository, ensuring transparency and reproducibility for future research. Proper citation and linking within academic publications facilitate integration into broader studies on soil evolution and volcanic ash dynamics.
DOI: 10.17632/xnpkvnj33r.1
title: Datasets for mantle contributions to global tungsten recycling and mineralization

description: Datasets for mantle contributions to global tungsten recycling and mineralization
DOI: 10.17632/xnpkvnj33r
title: Datasets for mantle contributions to global tungsten recycling and mineralization

description: Datasets for mantle contributions to global tungsten recycling and mineralization
DOI: 10.17632/xnpkvnj33r.2
title: Datasets for mantle contributions to global tungsten recycling and mineralization

description: Datasets for mantle contributions to global tungsten recycling and mineralization
DOI: 10.15468/dl.cn8jjb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyperolius argus Peters, 1854",
 "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 ((20.2855 -34.7533,20.509 -34.5676,20.509 -32.9007,17.7723 -32.9007,17.8156 -33.0786,18.3471 -33.7176,18.3748 -33.8287,18.2181 -34.0492,18.3197 -34.3408,18.4452 -34.429,18.5435 -34.4213,18.5872 -34.3667,18.5363 -34.167,18.7345 -34.1508,18.7216 -34.3637,18.7808 -34.4521,19.0289 -34.4206,19.0831 -34.4835,19.2655 -34.5017,19.2032 -34.6157,19.2394 -34.6926,19.375 -34.6963,19.6091 -34.8524,19.8251 -34.8396,19.9798 -34.9064,20.1081 -34.8731,20.1517 -34.7847,20.2855 -34.7533))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033590-250525065834625/datasets/export for details.
DOI: 10.17632/8dg6p5mbms
title: CSR Disclosure and Financial Performance Data of Bangladeshi Banks (FY2022)

description: This dataset supports the research study titled “Corporate Social Responsibility Disclosure and Its Strategic Implications: A Comparative Study of Selected Commercial Banks in Bangladesh.” It contains structured financial and sustainability metrics for seven commercial banks in Bangladesh for the fiscal year 2022.

The data includes:

CSR Disclosure Index (CSRI) calculated using a 10-theme binary scoring method based on Bangladesh Bank’s SFD Circular No. 01.

Return on Equity (ROE) computed from annual financial reports as a measure of profitability.

Green Finance (%) representing the proportion of green loans disbursed relative to total loans, based on Bangladesh Bank disclosures.

This dataset enables correlation analysis between CSR transparency and two critical outcomes—profitability and environmental finance performance. It is intended for use in academic research, policy analysis, and financial sustainability evaluation in emerging markets.

Variables included:

Bank Name

CSR Disclosure Index (0–1 scale)

Return on Equity (%)

Green Finance (%)

Source Documents:

Audited Annual Reports (2022) of each bank

Bangladesh Bank Green Finance Reports

CSR guidelines from Bangladesh Bank (SFD Circular No. 01)

License: Creative Commons Attribution (CC BY 4.0)
DOI: 10.17632/8dg6p5mbms.1
title: CSR Disclosure and Financial Performance Data of Bangladeshi Banks (FY2022)

description: This dataset supports the research study titled “Corporate Social Responsibility Disclosure and Its Strategic Implications: A Comparative Study of Selected Commercial Banks in Bangladesh.” It contains structured financial and sustainability metrics for seven commercial banks in Bangladesh for the fiscal year 2022.

The data includes:

CSR Disclosure Index (CSRI) calculated using a 10-theme binary scoring method based on Bangladesh Bank’s SFD Circular No. 01.

Return on Equity (ROE) computed from annual financial reports as a measure of profitability.

Green Finance (%) representing the proportion of green loans disbursed relative to total loans, based on Bangladesh Bank disclosures.

This dataset enables correlation analysis between CSR transparency and two critical outcomes—profitability and environmental finance performance. It is intended for use in academic research, policy analysis, and financial sustainability evaluation in emerging markets.

Variables included:

Bank Name

CSR Disclosure Index (0–1 scale)

Return on Equity (%)

Green Finance (%)

Source Documents:

Audited Annual Reports (2022) of each bank

Bangladesh Bank Green Finance Reports

CSR guidelines from Bangladesh Bank (SFD Circular No. 01)

License: Creative Commons Attribution (CC BY 4.0)
DOI: 10.17632/fpc6ypbsts.1
title: Mother's own milk normalize immune system development in extremely preterm infants

description: The dataset is used to reproduce figures for the paper "Mother's own milk normalize immune system development in extremely preterm infants". The scripts are shared under https://github.com/Brodinlab/preterm_DHA.
DOI: 10.17632/fpc6ypbsts.2
title: Mother's own milk normalize immune system development in extremely preterm infants

description: The dataset is used to reproduce figures for the paper "Mother's own milk normalize immune system development in extremely preterm infants". The scripts are shared under https://github.com/Brodinlab/preterm_DHA.
DOI: 10.17632/fpc6ypbsts
title: Immune development differs between preterm newborns fed mothers' own milk and donor milk

description: The dataset is used to reproduce figures for the paper "Immune development differs between preterm newborns fed mothers' own milk and donor milk". The scripts are shared under https://github.com/Brodinlab/preterm_DHA.
DOI: 10.17632/fpc6ypbsts.3
title: Immune development differs between preterm newborns fed mothers' own milk and donor milk

description: The dataset is used to reproduce figures for the paper "Immune development differs between preterm newborns fed mothers' own milk and donor milk". The scripts are shared under https://github.com/Brodinlab/preterm_DHA.
DOI: 10.17632/w4jtfpw2sd
title: Arduino Smartwatch Code

description: Arduino Code for the Smartwatch Project
DOI: 10.17632/w4jtfpw2sd.1
title: Arduino Smartwatch Code

description: Arduino Code for the Smartwatch Project
DOI: 10.5281/zenodo.15559633
title: 2012 -London - L1#3

description: University of Reading Grimmond Urban Micromet Group

City: London

Year: 2012

Sites: RGS, NDT.NK, NGT

Data Levels: L1 #3
DOI: 10.5281/zenodo.15559634
title: 2012 -London - L1#3

description: University of Reading Grimmond Urban Micromet Group

City: London

Year: 2012

Sites: 

Data Levels: L1 #3
DOI: 10.5281/zenodo.15587853
title: 2012 -London - L1#3

description: University of Reading Grimmond Urban Micromet Group

City: London

Year: 2012

Sites: RGS, NDT

Data Levels: L1 #3
DOI: 10.5281/zenodo.15587868
title: 2012 -London - L1#3

description: University of Reading Grimmond Urban Micromet Group

City: London

Year: 2012

Sites: RGS, NDT.NK, NGT

Data Levels: L1 #3
DOI: 10.15468/dl.ceb9ke
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Lophuromys angolensis W.Verheyen, Dierckx & Hulselmans, 2000",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 31 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033591-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/9n53tbjcr8.1
title: Disparities in Acral Lentiginous Melanoma: Racial Factors Beyond Delayed Diagnosis (Supplemental Material)

description: Supplementary material for "Disparities in Acral Lentiginous Melanoma: Racial Factors Beyond Delayed Diagnosis".
DOI: 10.5281/zenodo.15537374
title: for testing

description: This project explores the intricate details of single cells in the human body, focusing on their structure, function, and behaviour. By studying individual cells, it aims to uncover how they contribute to overall 111 1111 health, disease progression, and human bio
DOI: 10.5281/zenodo.15537375
title: for testing

description: This project explores the intricate details of single cells in the human body, focusing on their structure, function, and behaviour. By studying individual cells, it aims to uncover how they contribute to overall 111 1111 health, disease progression, and human bio
DOI: 10.15468/dl.xz3jch
title: Occurrence Download

description: A dataset containing 650434 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is LACM Entomology Collection",
 "TaxonKey is one of (Animalia, Phoridae)"
 ]
}

 The dataset includes 650434 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033575-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6nsz26
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Zalophus californianus wollebaeki (Sivertsen, 1953)"
 ]
}

 The dataset includes 74 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033592-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/kss4fsggvm.1
title: High-Performance Liquid Chromatography Method Modification for the Simultaneous Analysis of Disodium Guanylate and Disodium Inosinate in Mushrooms (specifically Hericium erinaceus)

description: The data presents a modified method from existing methods for the simultaneous analysis of disodium guanylate (GMP) and disodium inosinate (IMP) in Hericium erinaceus mushrooms using high-performance liquid chromatography (HPLC).
DOI: 10.17632/f9n9s3p99t.1
title: MontadoDB: A Comprehensive Dataset of Pasture Parameters in the Sourthern Region of Portugal

description: This data comprises 705 samples, including collection date and day of the year (Date and DOY), sample region (Sample), geographical coordinates (Lat and Long), and the parameters collected from the laboratory: Pasture Measure Content, Crude Protein, Neutral Detergent Fiber, Fresh Weigth, Dry Matter (PMC (%), PB (g/100g), NDF (g/100g), Kg MS/ha), with its BoxCox transformation (PMC (%)_BoxCox, PB (g/100g)_BoxCox, NDF (g/100g)_BoxCox, Kg MS/ha_BoxCox) for data normalization.

Multispectral and weather data were collected for each sample coordinate. The spectral data comes from Google Earth Engine on four satellites (Landsat-8, Sentinel-2, Sentinel-3, and MODIS) and their respective collections and tiers. 

- Sentinel-2 Surface reflectance : B1, B2, B3, B4, B5, B6, B7, B8, B8A, B9, B11, B12
- Sentinel-2 Top-of-atmosphere: B1, B2, B3, B4, B5, B6, B7, B8, B8A, B9, B10, B11, B12
- Landsat-8 Surface reflectance tier 1: SR_B1, SR_B2, SR_B3, SR_B4, SR_B5, SR_B6, SR_B7
- Landsat-8 Top-of-atmosphere (tier 1 / 1 + realtime): B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11
- Landsat-8 Raw (tier 1 / 1 + realtime): B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11
- Sentinel-3: Oa02, Oa03, Oa04, Oa05, Oa06, Oa07, Oa08, Oa09, Oa11, Oa12, Oa13, Oa14, Oa15, Oa16, Oa17, Oa18, Oa19, Oa20, Oa21
- MODIS: NDVI, EVI

The spectral bands columns are preceded by a column that indicates the date of the collected image. Every column name highlights the type of satellite, its collection, and tier, e.g., Landsat-8_SR_1, which refers to the Landsat-8 satellite, surface reflectance collection, and tier 1. 

The weather data can be acquired from Open weather and Open Meteo APIs, fetching the following weather conditions: Maximum and Minimum Temperature acquired (TEMP_MAX (°C), TEMP_MIN (°C)), Average Solar Radiation (RAD_SOL (J/M2)), Average rainfall recorded during the day (RAIN (mm)), Average Wind Speed (WIND_SPD (km/h)), Average Estimated Soil Evapotranspiration (EVAPOT (mm)), Average Atmospheric Pressure (PRES_ATM (hPa)) and Average Relative Humidity (HUM_REL (%)).

The "dataset" folder includes eight files: "Experimental_data.csv", "Sentinel-2.csv", "Sentinel-3.csv", "Landsat-8.csv", "Modis.csv", "Complete_data.csv", "Weather_data.csv", and "Satellite_info.json". "Experimental_data.csv" and "Weather_data.csv" contain only samples and weather data, respectively. "Each satellite CSV includes Forage parameters, spectral bands, and weather data. The "Complete_data.csv" merges all the other files. "Satellite_info.json" contains auxiliary satellite data for GEE and dataset build.

The "scripts" folder contains two necessary modules, one for GEE functions - "multispectral_api.py", and another for Weather API calls - "weather_api.py", and a notebook Python file ("build_dataset.ipynb") that uses both modules to fetch the data and build the dataset.
DOI: 10.17632/f9n9s3p99t.2
title: MontadoDB: A Comprehensive Dataset of Pasture Parameters in the Sourthern Region of Portugal

description: This data comprises 705 samples, including collection date and day of the year (Date and DOY), sample region (Sample), geographical coordinates (Lat and Long), and the parameters collected from the laboratory: Pasture Measure Content, Crude Protein, Neutral Detergent Fiber, Fresh Weigth, Dry Matter (PMC (%), PB (g/100g), NDF (g/100g), Kg MS/ha), with its BoxCox transformation (PMC (%)_BoxCox, PB (g/100g)_BoxCox, NDF (g/100g)_BoxCox, Kg MS/ha_BoxCox) for data normalization.

Multispectral and weather data were collected for each sample coordinate. The spectral data comes from Google Earth Engine on four satellites (Landsat-8, Sentinel-2, Sentinel-3, and MODIS) and their respective collections and tiers. 

- Sentinel-2 Surface reflectance : B1, B2, B3, B4, B5, B6, B7, B8, B8A, B9, B11, B12
- Sentinel-2 Top-of-atmosphere: B1, B2, B3, B4, B5, B6, B7, B8, B8A, B9, B10, B11, B12
- Landsat-8 Surface reflectance tier 1: SR_B1, SR_B2, SR_B3, SR_B4, SR_B5, SR_B6, SR_B7
- Landsat-8 Top-of-atmosphere (tier 1 / 1 + realtime): B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11
- Landsat-8 Raw (tier 1 / 1 + realtime): B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11
- Sentinel-3: Oa02, Oa03, Oa04, Oa05, Oa06, Oa07, Oa08, Oa09, Oa11, Oa12, Oa13, Oa14, Oa15, Oa16, Oa17, Oa18, Oa19, Oa20, Oa21
- MODIS: NDVI, EVI

The spectral bands columns are preceded by a column that indicates the date of the collected image. Every column name highlights the type of satellite, its collection, and tier, e.g., Landsat-8_SR_1, which refers to the Landsat-8 satellite, surface reflectance collection, and tier 1. 

The weather data can be acquired from Open weather and Open Meteo APIs, fetching the following weather conditions: Maximum and Minimum Temperature acquired (TEMP_MAX (°C), TEMP_MIN (°C)), Average Solar Radiation (RAD_SOL (J/M2)), Average rainfall recorded during the day (RAIN (mm)), Average Wind Speed (WIND_SPD (km/h)), Average Estimated Soil Evapotranspiration (EVAPOT (mm)), Average Atmospheric Pressure (PRES_ATM (hPa)) and Average Relative Humidity (HUM_REL (%)).

The "dataset" folder includes eight files: "Experimental_data.csv", "Sentinel-2.csv", "Sentinel-3.csv", "Landsat-8.csv", "Modis.csv", "Complete_data.csv", "Weather_data.csv", and "Satellite_info.json". "Experimental_data.csv" and "Weather_data.csv" contain only samples and weather data, respectively. "Each satellite CSV includes Forage parameters, spectral bands, and weather data. The "Complete_data.csv" merges all the other files. "Satellite_info.json" contains auxiliary satellite data for GEE and dataset build.

The "scripts" folder contains two necessary modules, one for GEE functions - "multispectral_api.py", and another for Weather API calls - "weather_api.py", and a notebook Python file ("build_dataset.ipynb") that uses both modules to fetch the data and build the dataset.