cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/pdcp9mjy3z
title: Comprehensive Deepfake Detection Dataset: Real and Synthetic Frames from Roop and Akool AI Technologies

description: This dataset is a cutting-edge resource for deepfake detection, containing 110,694 frames extracted from 480 videos. It features two primary categories: deepfake and real frames. The deepfake frames (106,948) were generated from 450 videos using advanced AI tools such as Roop Faceswapper and Akool AI, while the real frames (3,746) were derived from 30 authentic videos. The dataset is meticulously curated to ensure diversity, balance, and high-quality representation, making it an invaluable resource for training and evaluating deepfake detection models.

The dataset collection process was conducted with ethical approval from Daffodil International University, ensuring adherence to ethical standards for data collection and research in deepfake detection systems.

Key Features:
Total Videos: 480 (450 deepfake, 30 real).
Frame Distribution: 106,948 deepfake frames and 3,746 real frames.
Deepfake Generation Tools: Leveraged state-of-the-art technologies like Roop Face-Swapper and Akool AI for synthetic video creation.
Demographic Diversity: Includes frames from 15 males and 15 females, ensuring varied representation across facial features, lighting conditions, and environments.
Balanced Dataset: Carefully curated for fair model training and evaluation.
Applications: Ideal for developing scalable, real-time detection systems in cybersecurity, digital forensics, and media integrity verification.

This dataset offers an unparalleled opportunity to explore and enhance deepfake detection models, addressing the challenges posed by synthetic media with a diverse and high-quality benchmark.
DOI: 10.17632/pdcp9mjy3z.2
title: Comprehensive Deepfake Detection Dataset: Real and Synthetic Frames from Roop and Akool AI Technologies

description: This dataset is a cutting-edge resource for deepfake detection, containing 110,694 frames extracted from 480 videos. It features two primary categories: deepfake and real frames. The deepfake frames (106,948) were generated from 450 videos using advanced AI tools such as Roop Faceswapper and Akool AI, while the real frames (3,746) were derived from 30 authentic videos. The dataset is meticulously curated to ensure diversity, balance, and high-quality representation, making it an invaluable resource for training and evaluating deepfake detection models.

The dataset collection process was conducted with ethical approval from Daffodil International University, ensuring adherence to ethical standards for data collection and research in deepfake detection systems.

Key Features:
Total Videos: 480 (450 deepfake, 30 real).
Frame Distribution: 106,948 deepfake frames and 3,746 real frames.
Deepfake Generation Tools: Leveraged state-of-the-art technologies like Roop Face-Swapper and Akool AI for synthetic video creation.
Demographic Diversity: Includes frames from 15 males and 15 females, ensuring varied representation across facial features, lighting conditions, and environments.
Balanced Dataset: Carefully curated for fair model training and evaluation.
Applications: Ideal for developing scalable, real-time detection systems in cybersecurity, digital forensics, and media integrity verification.

This dataset offers an unparalleled opportunity to explore and enhance deepfake detection models, addressing the challenges posed by synthetic media with a diverse and high-quality benchmark.
DOI: 10.15468/dl.6946kg
title: Occurrence Download

description: A dataset containing 588 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (CAN.11.9_1, CAN.11.90_1, CAN.11.54_1, CAN.11.12_1, CAN.11.90.1_1, CAN.11.42_1)",
 "OccurrenceStatus is Present",
 "RecordedBy is one of (Alexandre Dumas, Masson, Pierre)",
 "TaxonKey is Poales"
 ]
}

 The dataset includes 588 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081616-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/yfd385sdhb
title: Data and code for: Giving in Dictator Games When the Recipient is a Charity: A Replication Study including an Extension on Gender Differences

description: Data and code for the review process.

The results replicate the findings of Livingston, J. A., & Rasulmukhamedov, R. (2023). On the Interpretation of Giving in Dictator Games When the Recipient is a Charity. Journal of Economic Behavior & Organization, 208, 275–285. doi:10.1016/j.jebo.2023.01.025.

All results can be reproduced using the dataset and Stata do file that are provided.
DOI: 10.17632/yfd385sdhb.1
title: Data and code for: Giving in Dictator Games When the Recipient is a Charity: A Replication Study including an Extension on Gender Differences

description: Data and code for the review process.

The results replicate the findings of Livingston, J. A., & Rasulmukhamedov, R. (2023). On the Interpretation of Giving in Dictator Games When the Recipient is a Charity. Journal of Economic Behavior & Organization, 208, 275–285. doi:10.1016/j.jebo.2023.01.025.

All results can be reproduced using the dataset and Stata do file that are provided.
DOI: 10.17632/n4dz34f5xm
title: A Novel Dual Pressure-Temperature Interpolation Model for Mathematically Exact Adsorption Equilibrium for Performance Simulation of Integrated Absorption-Adsorption Refrigeration System using the MIL-101(Cr)/water Pair

description: This Data is intended to reproduce the equilibrium plots for silica-gel/water and MIL-101(Cr)/water illustrated in Figure 4 in the manuscript based on the proposed higher-order pressure-temperature interpolation model.
DOI: 10.17632/n4dz34f5xm.3
title: A Novel Dual Pressure-Temperature Interpolation Model for Mathematically Exact Adsorption Equilibrium for Performance Simulation of Integrated Absorption-Adsorption Refrigeration System using the MIL-101(Cr)/water Pair

description: This Data is intended to reproduce the equilibrium plots for silica-gel/water and MIL-101(Cr)/water illustrated in Figure 4 in the manuscript based on the proposed higher-order pressure-temperature interpolation model.
DOI: 10.15468/dl.k2nuc9
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argemone mexicana L.",
 "Country is Botswana",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081619-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7rrjym
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argemone mexicana L.",
 "Country is Argentina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 21 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081618-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.md8wew
title: Occurrence Download

description: A dataset containing 581 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argemone mexicana L.",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 581 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081620-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/23263pm4zx.1
title: Regime-dependent volatility spillover asymmetry in Shanghai and Hong Kong stock markets with forecasting and portfolio inferences

description: This dataset include the data and code for the paper of "Regime-dependent volatility spillover asymmetry in Shanghai and Hong Kong stock markets with forecasting and portfolio inferences", Primary analyses were conducted using WinRATS 10 and OxMetrics 9. The regime-dependent spillover measures and BEKK-GARCH models were implemented exclusively through WinRATS scripting. Forecasting procedures and subsequent evaluations were performed interactively within the OxMetrics 9 environment.
DOI: 10.17632/jxy85cr3th.1
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 possibly vote counts depending on the API’s response format. 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 during a pivotal period in digital gaming and provides a foundation for future research in user behavior, content personalization, and the evolving dynamics of online platforms.
DOI: 10.17632/zztwrn36n8.1
title: Dataset of User Reviews from Low-Rated Applications on the Amazon Appstore

description: This dataset provides a comprehensive collection of 79,821 end-user reviews from 64 low-rated software applications on the Amazon Appstore. The dataset is specifically curated to focus on applications that exhibit significant user dissatisfaction, making it a valuable resource for studying the root causes of software failure and negative user reception. The applications span 14 distinct categories, offering a broad view of user feedback across different software domains.

The data was systematically collected using an automated web scraping tool. The selection criteria targeted applications with a user rating of 3 stars (out of 5) or lower and a minimum of 400 reviews to ensure the data reflects a broad consensus of user opinion. The dataset is provided in CSV format and contains three primary columns for each review: the user's rating ('Stars'), the 'Title_of_Review', and the full text of the 'Base_Review'.

This resource is intended for researchers, software developers, requirements engineers, and educators. It is particularly useful for studies in software quality assessment, user experience (UX) analysis, sentiment analysis, issue detection, and for training and validating machine learning and natural language processing (NLP) models. Its unique focus on negative feedback provides an unfiltered and concentrated source of data for understanding why software products fail to meet user expectations.
DOI: 10.15468/dl.xjh6mv
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argemone mexicana L.",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 37 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081622-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fmx35f
title: Occurrence Download

description: A dataset containing 70 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argemone mexicana L.",
 "Country is Cuba",
 "HasCoordinate is true"
 ]
}

 The dataset includes 70 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081623-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m6x4bh
title: Occurrence Download

description: A dataset containing 926 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Formica exsecta Nylander, 1846",
 "Geometry POLYGON((-8.00174339329464 54.1998526673513, 0.202120938926891 54.1998526673513, 0.202120938926891 61.2628565887411, -8.00174339329464 61.2628565887411, -8.00174339329464 54.1998526673513))",
 "CoordinateUncertaintyInMeters is 0,101",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 926 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081621-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wwcqcq
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argemone mexicana L.",
 "Country is Egypt",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081624-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/pvyk5gk92g
title: All About Coinbase Customer Service Support For Withdrawal, Reopen , Deposite issues

description: How to Contact Coinbase Support – Official Support Number 
To contact with Coinbase Tool Hub number, call (+1-857-240-9932) or (+1-857-240-9932). Support is 
available around the clock to help with 
How to Get in Touch with coinbase Customer Service Number Contact Support Fast 
For coinbase Phone Support (+1-857-240-9932), please contact our support team at (+1-857-240
9932) We can assist with installation, setup, and troubleshooting 
Can I get my money back from Coinbase? 
Yes, Coinbase help desk number (+1-857-240-9932), providing continuous access to trading, 
deposits, and withdrawals. Their automated help center and live chat support are available at all 
t
 imes (+1-857-240-9932) . While direct agent support may have specific hours, Coinbase ensures a 
seamless user experience (+1-857-240-9932) with round-the-clock assistance for urgent matters. 
To contact a live representative at Coinbase, call their 24/7 customer service hotline at 【(+1-857
240-9932) or 1-800-Coinbase. You can also use their website’s live chat or email for assistance. 
This is Coinbase’s main customer service hotline, available 24/7 for U.S. customers(+1-857-240-9932) 
It’s ideal for urgent issues like booking changes, cancellations, or refund inquiries. Have your booking 
reference number ready to expedite the process.
DOI: 10.17632/pvyk5gk92g.1
title: All About Coinbase Customer Service Support For Withdrawal, Reopen , Deposite issues

description: How to Contact Coinbase Support – Official Support Number 
To contact with Coinbase Tool Hub number, call (+1-857-240-9932) or (+1-857-240-9932). Support is 
available around the clock to help with 
How to Get in Touch with coinbase Customer Service Number Contact Support Fast 
For coinbase Phone Support (+1-857-240-9932), please contact our support team at (+1-857-240
9932) We can assist with installation, setup, and troubleshooting 
Can I get my money back from Coinbase? 
Yes, Coinbase help desk number (+1-857-240-9932), providing continuous access to trading, 
deposits, and withdrawals. Their automated help center and live chat support are available at all 
t
 imes (+1-857-240-9932) . While direct agent support may have specific hours, Coinbase ensures a 
seamless user experience (+1-857-240-9932) with round-the-clock assistance for urgent matters. 
To contact a live representative at Coinbase, call their 24/7 customer service hotline at 【(+1-857
240-9932) or 1-800-Coinbase. You can also use their website’s live chat or email for assistance. 
This is Coinbase’s main customer service hotline, available 24/7 for U.S. customers(+1-857-240-9932) 
It’s ideal for urgent issues like booking changes, cancellations, or refund inquiries. Have your booking 
reference number ready to expedite the process.
DOI: 10.5281/zenodo.15776867
title: Evaluation of Iron Detoxification in Thalassemic Patients in Ninevah Governorate
DOI: 10.5281/zenodo.15776868
title: Evaluation of Iron Detoxification in Thalassemic Patients in Ninevah Governorate
DOI: 10.17632/fsfpfjkh9y
title: Mercury and methylmercury concentration in tar contaminated sediments along the coast of Qatar

description: One of the pollutants that impacts the coastal environment of Qatar is the vast expanse of oil residue, ‘tarmats’ deposited on its beaches. The current study aimed to gauge the concentration levels of total mercury (THg), methylmercury (CH3-Hg), and total sulfur (TS) in tarmat contaminated sediments and test their presence in select coastal species. Seven biota species under three classes (Gastropoda, Bivalvia, and Crustacea) have been found on the tarmat of Ras Rakan and Umm-Tais islands. Layers of hard asphalt-like tarmats and sediments samples were collected from 34 sites, along the coast of Qatar. Moreover, the Biota Sediment Accumulation Factor (BSAF) was calculated for THg and CH3-Hg through sentinel species.
DOI: 10.17632/fsfpfjkh9y.1
title: Mercury and methylmercury concentration in tar contaminated sediments along the coast of Qatar

description: One of the pollutants that impacts the coastal environment of Qatar is the vast expanse of oil residue, ‘tarmats’ deposited on its beaches. The current study aimed to gauge the concentration levels of total mercury (THg), methylmercury (CH3-Hg), and total sulfur (TS) in tarmat contaminated sediments and test their presence in select coastal species. Seven biota species under three classes (Gastropoda, Bivalvia, and Crustacea) have been found on the tarmat of Ras Rakan and Umm-Tais islands. Layers of hard asphalt-like tarmats and sediments samples were collected from 34 sites, along the coast of Qatar. Moreover, the Biota Sediment Accumulation Factor (BSAF) was calculated for THg and CH3-Hg through sentinel species.
DOI: 10.5281/zenodo.15776800
title: Phase diagram of cell migration modes

description: Raw data for generating key figures of the manuscript: Substrate properties and actin polymerization speed dictate universal modes of cell migration: gripping, slipping, and stick-slip. https://doi.org/10.1101/2025.06.20.660727
DOI: 10.5281/zenodo.15776801
title: Phase diagram of cell migration modes

description: Raw data for generating key figures of the manuscript: Substrate properties and actin polymerization speed dictate universal modes of cell migration: gripping, slipping, and stick-slip. https://doi.org/10.1101/2025.06.20.660727
DOI: 10.17632/mnt66z9tks.1
title: The ARRIVE Essential 10 and The Recommended Set; Author Checklist (Insect Colonization)

description: This study investigated the impact of Rohypnol on insect colonization and decomposition patterns in a forensic context. The research hypothesis was that increasing concentrations of Rohypnol would reduce the abundance of insects attracted to decomposing remains and prolong the duration of decomposition stages, while not significantly altering the pattern of insect succession. To test this, four domestic pigs (Sus scrofa Linnaeus) were used—one as a control and three as experimental units receiving oral doses of Rohypnol at concentrations of 1 mg/250 ml, 2 mg/250 ml, and 3 mg/250 ml dissolved in vodka.

After euthanasia, the carcasses were placed in individual metal cages at the University of Nairobi’s Veterinary Farm, Upper Kabete, and left to decompose under natural conditions. Insect sampling was conducted over a 60-day period using aerial nets, pitfall traps, and forceps. Sampling frequency was three times daily for the first eight days, twice daily for the next eight days, and once daily thereafter until decomposition reached the dry remains stage. Samples included adult insects and maggots collected from the body surface, natural openings, and surrounding area. Maggots were either preserved in 75% ethanol or reared to adulthood for identification. Insects were identified using standard entomological keys and recorded by species and abundance.

The first dataset contains insect species occurrence, developmental stages, and temporal distribution across the five decomposition stages (fresh, bloated, active decay, advanced decay, and dry). The second dataset includes meteorological data—such as temperature and humidity—collected daily from the study site to provide context for environmental influences on decomposition and insect activity.

Key findings show that insect abundance decreased as Rohypnol concentration increased, but the composition and succession pattern of insect species remained consistent. Calliphoridae was the most dominant family across all carcasses. Decomposition was slower in Rohypnol-treated carcasses, indicating the drug’s potential to delay insect colonization or development. These data are useful for forensic scientists and entomologists investigating drug-related deaths, post-mortem interval estimation, and carrion ecology. Researchers can use this dataset to examine drug effects on decomposition dynamics, validate forensic models, and compare findings across different environmental or geographic contexts.
DOI: 10.15468/dl.dygeu9
title: Occurrence Download

description: A dataset containing 739 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argemone mexicana L.",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 739 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081626-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.78c56c
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argemone mexicana L.",
 "Country is Fiji",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081625-250525065834625/datasets/export for details.