cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.bg4kvc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Broussonetia papyrifera (L.) L'Hér. ex Vent.",
 "Country is Gambia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081688-250525065834625/datasets/export for details.
DOI: 10.17632/br5dyxm7c6
title: Hybrid Prophet-XGBoost Forecasting for Urban Air Quality with Real-Time Data Integration For Chennai

description: This research aims to forecast short-term urban air quality by integrating meteorological variables and pollutant concentration data into a hybrid machine learning framework. The hypothesis is that using both historical pollutant data and weather features enhances predictive accuracy across different pollutant types.

Historic pollutant data (2022–2024) was collected from the WAQI (World Air Quality Index) historic dashboard, cleaned, and imputed for missing or anomalous values. This dataset includes daily values for PM₂.₅, PM₁₀, NO₂, SO₂, and O₃ from six key monitoring stations in Chennai. Supplementary weather and CAMS air quality data were sourced using the Open-Meteo APIs:

https://api.open-meteo.com/v1/forecast for daily weather

https://air-quality-api.open-meteo.com/v1/air-quality for CAMS-based pollutant history

These datasets were combined and processed to ensure daily granularity, using linear interpolation for imputation and z-score-based outlier capping.

The air quality forecast was generated for a 7-day horizon using a hybrid approach: Prophet (for seasonality), XGBoost (for lag-based learning), and ETS (for fallback modeling). AQI was computed based on Indian CPCB sub-index breakpoints, identifying both the AQI level and dominant pollutant each day.

To evaluate performance, back-testing was done on actual vs. predicted pollutant values. Results show high model accuracy, particularly for gaseous pollutants. Based on MAPE and sMAPE:

O₃: 95.22% accuracy 

SO₂: 93.04% accuracy 

PM₁₀: 80.28% accuracy

PM₂.₅: 76.78% accuracy

NO₂: 65.74% accuracy

The model successfully captured pollutant dynamics and generated reliable AQI forecasts, suitable for environmental monitoring and early warning applications.
DOI: 10.17632/br5dyxm7c6.1
title: Hybrid Prophet-XGBoost Forecasting for Urban Air Quality with Real-Time Data Integration For Chennai

description: This research aims to forecast short-term urban air quality by integrating meteorological variables and pollutant concentration data into a hybrid machine learning framework. The hypothesis is that using both historical pollutant data and weather features enhances predictive accuracy across different pollutant types.

Historic pollutant data (2022–2024) was collected from the WAQI (World Air Quality Index) historic dashboard, cleaned, and imputed for missing or anomalous values. This dataset includes daily values for PM₂.₅, PM₁₀, NO₂, SO₂, and O₃ from six key monitoring stations in Chennai. Supplementary weather and CAMS air quality data were sourced using the Open-Meteo APIs:

https://api.open-meteo.com/v1/forecast for daily weather

https://air-quality-api.open-meteo.com/v1/air-quality for CAMS-based pollutant history

These datasets were combined and processed to ensure daily granularity, using linear interpolation for imputation and z-score-based outlier capping.

The air quality forecast was generated for a 7-day horizon using a hybrid approach: Prophet (for seasonality), XGBoost (for lag-based learning), and ETS (for fallback modeling). AQI was computed based on Indian CPCB sub-index breakpoints, identifying both the AQI level and dominant pollutant each day.

To evaluate performance, back-testing was done on actual vs. predicted pollutant values. Results show high model accuracy, particularly for gaseous pollutants. Based on MAPE and sMAPE:

O₃: 95.22% accuracy 

SO₂: 93.04% accuracy 

PM₁₀: 80.28% accuracy

PM₂.₅: 76.78% accuracy

NO₂: 65.74% accuracy

The model successfully captured pollutant dynamics and generated reliable AQI forecasts, suitable for environmental monitoring and early warning applications.
DOI: 10.15468/dl.nbp5n5
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 28eb1a3f-1c15-4a95-931a-4af90ecb574d",
 "TaxonKey is Anolis cooki Grant, 1931"
 ]
}

 The dataset includes 37 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081690-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/jxy85cr3th
title: Steam Games Metadata and Player Reviews (2020–2024)

description: This dataset presents a comprehensive and structured collection of video game metadata and user reviews from the Steam platform, covering the period between January 2020 and December 2024. It was compiled to support research into how various game attributes influence user satisfaction, engagement, and review behavior. The central research hypothesis behind this work suggests that specific characteristics of video games, such as genre, pricing, and supported platform, are closely associated with trends in user sentiment and review volume. Understanding these patterns can contribute to predictive models of game reception and improve design and marketing strategies for future releases.

To explore this hypothesis, data was gathered in two phases. In the first phase, metadata for all games listed on Steam during the target period was collected using the official Steam API. Each game was identified by its unique AppID and evaluated to ensure data completeness. The scraper retrieved details including the game title, release date, genres, supported languages, age restrictions, and pricing information. Games that were unreleased or launched before 2020 were excluded from the dataset. This resulted in a refined metadata file, stored as games.json, containing detailed information on 23,107 Steam games released from 2020 onward.

In the second phase, a dedicated script was used to collect user reviews for each game in the metadata file. The review collection process filtered out games with fewer than 25 reviews to avoid bias due to insufficient data. For the remaining games, reviews were gathered in all available languages to ensure a culturally diverse and inclusive dataset. Reviews were saved in individual CSV files named using the game’s AppID and the number of reviews it contains. Each file includes structured rows with fields such as review text, language, rating, and vote counts. This resulted in over 31 million reviews across more than 23,000 games, forming a robust basis for textual and quantitative analysis.

The data reveals several meaningful trends. Free-to-play games tend to attract higher review volumes, although not necessarily higher user ratings. Games within specific genres, such as role-playing, simulation, and survival, often have longer and more detailed reviews, indicating deeper user engagement.

By releasing both the metadata and reviews together, this dataset offers a multidimensional view of the Steam game landscape from 2020 to 2024. It captures user engagement in digital gaming during and after the COVID-19 period and provides a foundation for future research in user behavior, content personalization, and the evolving dynamics of online platforms.
DOI: 10.17632/jxy85cr3th.2
title: Steam Games Metadata and Player Reviews (2020–2024)

description: This dataset presents a comprehensive and structured collection of video game metadata and user reviews from the Steam platform, covering the period between January 2020 and December 2024. It was compiled to support research into how various game attributes influence user satisfaction, engagement, and review behavior. The central research hypothesis behind this work suggests that specific characteristics of video games, such as genre, pricing, and supported platform, are closely associated with trends in user sentiment and review volume. Understanding these patterns can contribute to predictive models of game reception and improve design and marketing strategies for future releases.

To explore this hypothesis, data was gathered in two phases. In the first phase, metadata for all games listed on Steam during the target period was collected using the official Steam API. Each game was identified by its unique AppID and evaluated to ensure data completeness. The scraper retrieved details including the game title, release date, genres, supported languages, age restrictions, and pricing information. Games that were unreleased or launched before 2020 were excluded from the dataset. This resulted in a refined metadata file, stored as games.json, containing detailed information on 23,107 Steam games released from 2020 onward.

In the second phase, a dedicated script was used to collect user reviews for each game in the metadata file. The review collection process filtered out games with fewer than 25 reviews to avoid bias due to insufficient data. For the remaining games, reviews were gathered in all available languages to ensure a culturally diverse and inclusive dataset. Reviews were saved in individual CSV files named using the game’s AppID and the number of reviews it contains. Each file includes structured rows with fields such as review text, language, rating, and vote counts. This resulted in over 31 million reviews across more than 23,000 games, forming a robust basis for textual and quantitative analysis.

The data reveals several meaningful trends. Free-to-play games tend to attract higher review volumes, although not necessarily higher user ratings. Games within specific genres, such as role-playing, simulation, and survival, often have longer and more detailed reviews, indicating deeper user engagement.

By releasing both the metadata and reviews together, this dataset offers a multidimensional view of the Steam game landscape from 2020 to 2024. It captures user engagement in digital gaming during and after the COVID-19 period and provides a foundation for future research in user behavior, content personalization, and the evolving dynamics of online platforms.
DOI: 10.17632/skvrd2s9gg.2
title: A dataset of medicinal plant leaves from Bangladesh

description: This dataset contains a collection of 1,094 original JPG images of medicinal leaves, captured in natural conditions from the rural jungle area of Guadanga village, Phulpur, Mymensingh, Bangladesh. The images are organized into six folders, each representing a distinct and commonly found medicinal plant species:

• Centella Asiatica

• Coccinia Grandis

• Eclipta Prostrata

• Mikania Micrantha

• Murraya Koenigii

• Stephania Japonica

The original leaf images were captured using two high-resolution smartphone cameras — Google Pixel 5 and Google Pixel 6a — to ensure clear and detailed visuals suitable for a variety of machine learning and image processing tasks. All images are unprocessed, making the dataset ideal for researchers who wish to work with real-world, raw image data.

To support the development of deeper and more robust deep learning models, this dataset also includes 2,188 augmented JPG images, generated from the original set using standard image augmentation techniques. These augmentations help improve generalization and model performance on complex leaf classification tasks.

Dataset Summary:
Total Images:

Original: 1,094 JPG images

Augmented: 2,188 JPG images

Plant Classes: 6 distinct medicinal plant species

Image Format: JPG

Image Organization: Organized into 6 folders named after plant species

Capture Devices: Google Pixel 5 and Google Pixel 6a

Source Location: Jungle of Guadanga, Phulpur, Mymensingh, Bangladesh

Purpose: Suitable for tasks such as medicinal plant classification, leaf recognition, image segmentation, and deep learning-based botanical analysis.

This dataset provides a rich and realistic foundation for researchers and practitioners working in domains such as plant pathology, botany, herbal medicine identification, and AI-driven agriculture.
DOI: 10.17632/nbpsdhphy3
title: Crossings between Biomphalaria glabrata populations

description: Pairing and mass crossbreeding were performed between pigmented low susceptibility and albino susceptible snails. Adult F1 and F2 snails were individually challenged with SmLE miracidia. Snail-parasite compatibility was assessed using several parameters, and reproductive biology was evaluated in both unchallenged and infected snails. The files present part of the raw data obtained from these crossings.
DOI: 10.17632/nbpsdhphy3.2
title: Crossings between Biomphalaria glabrata populations

description: Pairing and mass crossbreeding were performed between pigmented low susceptibility and albino susceptible snails. Adult F1 and F2 snails were individually challenged with SmLE miracidia. Snail-parasite compatibility was assessed using several parameters, and reproductive biology was evaluated in both unchallenged and infected snails. The files present part of the raw data obtained from these crossings.
DOI: 10.15468/dl.xuyf24
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Broussonetia papyrifera (L.) L'Hér. ex Vent.",
 "Country is Guinea-Bissau",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081693-250525065834625/datasets/export for details.
DOI: 10.17632/phkpzcv8yp
title: Reanalyzed Data for Canine Lab Exercise

description: Data to accompany the paper "Decision Milestones in a Canine Lab Exercise: How Critical Thinking Goes Astray" in the Journal of Statistics and Data Science Education.
DOI: 10.17632/phkpzcv8yp.1
title: Reanalyzed Data for Canine Lab Exercise

description: Data to accompany the paper "Decision Milestones in a Canine Lab Exercise: How Critical Thinking Goes Astray" in the Journal of Statistics and Data Science Education.
DOI: 10.15468/dl.kgmfg7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Broussonetia papyrifera (L.) L'Hér. ex Vent.",
 "Country is Guinea",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081692-250525065834625/datasets/export for details.
DOI: 10.17632/93jw86jpv2
title: Norm data for the SOT protocol

description: Normative data for the SOT protocol in a regional sample of healthy female and male adults.
DOI: 10.17632/93jw86jpv2.1
title: Norm data for the SOT protocol

description: Normative data for the SOT protocol in a regional sample of healthy female and male adults.
DOI: 10.17632/rzxn2fpt8g
title: Sow social behaviour across seasons

description: Data related to the publication Seddaiu, P., Turner, S. P., & Camerlink, I. (2024). Cross-seasonal and diurnal variation in physical contact between sub-adult pigs. Applied Animal Behaviour Science, 278, 106379. https://doi.org/10.1016/j.applanim.2024.106379
DOI: 10.17632/rzxn2fpt8g.1
title: Sow social behaviour across seasons

description: Data related to the publication Seddaiu, P., Turner, S. P., & Camerlink, I. (2024). Cross-seasonal and diurnal variation in physical contact between sub-adult pigs. Applied Animal Behaviour Science, 278, 106379. https://doi.org/10.1016/j.applanim.2024.106379
DOI: 10.15468/dl.rjrp4t
title: Occurrence Download

description: A dataset containing 735 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhus schiedeana Schltdl."
 ]
}

 The dataset includes 735 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081695-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x72rpe
title: Occurrence Download

description: A dataset containing 210 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Broussonetia papyrifera (L.) L'Hér. ex Vent.",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 210 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081694-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q74y38
title: Occurrence Download

description: A dataset containing 11181 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhus trilobata Nutt."
 ]
}

 The dataset includes 11181 records from 245 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081696-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/8dvp9jybfz
title: Pre-Bloom Application of Petroleum Spray Oil for the Control of Green Apple Aphid, Aphis pomi DeGeer in Apple Orchards [Data]

description: The green apple aphid (Aphis pomi DeGeer) is a key early-season pest in apple orchards. Petroleum spray oils (PSOs), are routinely applied at the delayed dormant stage for managing pests like San José scale and European red mite. However, their impact on A. pomi has not been thoroughly evaluated. This study evaluated the ovicidal and larvicidal efficacy of PSOs (2% v/v) applied at the delayed dormant/green tip stage in apple orchards in Jammu and Kashmir, India. Laboratory and field assays demonstrated substantial suppression of egg hatch, with cumulative hatch reduced to 9.90 ± 0.57% (laboratory assay) and 9.62 ± 0.71% (field evaluation) in treated shoots compared to 46.91 ± 0.68% and 53.25 ± 3.25% in controls, respectively. Survival analyses revealed significantly higher mortality risk for treated eggs. Direct toxicity trials on nymphs showed mortality rates of 69.9 ± 1.95% in field conditions and &gt;99% in lab dip assays by 5 days after treatment. Residual toxicity assays indicated cumulative mortality reaching 64.07 ± 2.74 % by 2 days post-exposure, confirming efficacy even after drying. Field trials further revealed that PSO significantly reduced bud infestation by A. pomi (5.22 ± 0.54%) compared to the untreated control (19.04 ± 2.34%), with enhanced suppression observed when combined with imidacloprid (0.29 ± 0.14%). These findings underscore the potential of PSO as both a standalone and synergistic agent in aphid management, particularly when integrated with systemic insecticides. This is the first detailed report on the ovicidal and larvicidal activity of PSOs against A. pomi, supporting its inclusion in sustainable, early-season integrated pest management programs.
DOI: 10.17632/8dvp9jybfz.1
title: Pre-Bloom Application of Petroleum Spray Oil for the Control of Green Apple Aphid, Aphis pomi DeGeer in Apple Orchards [Data]

description: The green apple aphid (Aphis pomi DeGeer) is a key early-season pest in apple orchards. Petroleum spray oils (PSOs), are routinely applied at the delayed dormant stage for managing pests like San José scale and European red mite. However, their impact on A. pomi has not been thoroughly evaluated. This study evaluated the ovicidal and larvicidal efficacy of PSOs (2% v/v) applied at the delayed dormant/green tip stage in apple orchards in Jammu and Kashmir, India. Laboratory and field assays demonstrated substantial suppression of egg hatch, with cumulative hatch reduced to 9.90 ± 0.57% (laboratory assay) and 9.62 ± 0.71% (field evaluation) in treated shoots compared to 46.91 ± 0.68% and 53.25 ± 3.25% in controls, respectively. Survival analyses revealed significantly higher mortality risk for treated eggs. Direct toxicity trials on nymphs showed mortality rates of 69.9 ± 1.95% in field conditions and &gt;99% in lab dip assays by 5 days after treatment. Residual toxicity assays indicated cumulative mortality reaching 64.07 ± 2.74 % by 2 days post-exposure, confirming efficacy even after drying. Field trials further revealed that PSO significantly reduced bud infestation by A. pomi (5.22 ± 0.54%) compared to the untreated control (19.04 ± 2.34%), with enhanced suppression observed when combined with imidacloprid (0.29 ± 0.14%). These findings underscore the potential of PSO as both a standalone and synergistic agent in aphid management, particularly when integrated with systemic insecticides. This is the first detailed report on the ovicidal and larvicidal activity of PSOs against A. pomi, supporting its inclusion in sustainable, early-season integrated pest management programs.
DOI: 10.15468/dl.8eg6uj
title: Occurrence Download

description: A dataset containing 7541 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Material citation, Specimen, Occurrence evidence)",
 "Continent is one of (North America, South America)",
 "TaxonKey is Chaenopsidae"
 ]
}

 The dataset includes 7541 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081697-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/shtzxp8pjc
title: Population Pharmacokinetics and Dosing Regimen Optimization of Ceftazidime in Plasma and Cerebrospinal Fluid of Neonatal Sepsis Patients

description: The study included 69 neonates with sepsis.Based on plasma and cerebrospinal CSF concentration data collected from neonates with sepsis, statistical and graphical methods were employed to evaluate the stability and predictive performance of the model.The pharmacokinetic/pharmacodynamic (PK/PD) target for clinical efficacy was defined as the duration of free drug concentration above the minimum inhibitory concentration (MIC) for ≥70% of the dosing interval (70% fT&gt;MIC). Monte Carlo simulations were performed to identify optimal dosing regimens achieving a target attainment probability (PTA) ≥90%.Demographic and laboratory parameters were documented, including sex, body weight, height, body surface area (BSA), gestational age(GA), postnatal age(PNA), postmenstrual age(PMA), and biochemical markers such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), direct bilirubin (DBIL), γ-glutamyl transferase (γ-GT), albumin, globulin, uric acid (UA), blood urea nitrogen (BUN), serum cystatin C (Cys-C), and serum creatinine (SCr). Estimated glomerular filtration rate (eGFR) was calculated using the modified Schwartz formula, where eGFR (mL/min/1.73 m²) = (k × height) / SCr, with k = 0.33 for preterm infants and k = 0.45 for term infants. plasma creatinine was measured using the Roche cobas 8000 c702 enzymatic assay. Additionally, CSF analysis included protein, glucose, and chloride levels.