cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/bvp4vrn9gc.1
title: Operational Data of an Energy Community Under P2P Trading and Flexibility Market Models

description: This dataset contains the annual input data used in the study “Statistical Analysis of an Energy Community's Operations in P2P Energy Trading and Flexibility Markets”. It includes hourly electricity demand, PV generation, thermal profiles, and DER configurations for 55 users in a low-voltage distribution network. The data supports the replication of optimization models analyzing peer-to-peer trading and flexibility services provision.
DOI: 10.17632/5hcgnft876.1
title: Comparative Evaluation of Antioxidant Activities, antimicrobial activity and Phytochemical Contents of Carica papaya Grown With and Without Fertilizers

description: This project investigates the comparative antioxidant and antibacterial potential of Carica papaya fruits cultivated with and without the use of fertilizers. The growing interest in organic farming and natural therapeutics highlights the need to understand how cultivation practices influence the bioactive profile of medicinal fruits. In this study, papaya fruits were subjected to solvent extraction using acetone, methanol, and ethyl acetate to obtain phytochemical-rich extracts. The research focused on quantifying total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activities through assays such as DPPH radical scavenging, ferric reducing antioxidant power (FRAP), and total antioxidant capacity (TAC). Additionally, the antibacterial efficacy of the extracts was evaluated against Escherichia coli and Staphylococcus aureus using the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) methods. Sterility checks were conducted to ensure extract purity before microbiological testing. The project aims to establish a correlation between organic cultivation practices and the enhancement of bioactive compounds in Carica papaya, thereby supporting its application in the development of natural antioxidant and antimicrobial formulations.
DOI: 10.17632/czxznncsv2.1
title: General happiness index from 2018 to 2024 in Hong Kong SAR: Dataset of repeated cross-sectional surveys

description: The dataset encompassed 10,070 responses gathered for the General Happiness Index survey from 2018 to 2024 in Hong Kong SAR, China. The self-reported questionnaire included demographic data (e.g., age range, sex, marital status, parental status, educational attainment, monthly income, religious affiliation), individual happiness, mental capital, values, social well-being (assessed by social well-being scale), satisfaction with external environmental factors, physical and mental health status, and the Patient Health Questionnaire-9 (PHQ-9). Data collection was conducted through online and/or in-person interviews, subject upon social conditions and infectious outbreaks. 
Data verification was conducted, and additional recording and computations (i.e., mean of mental capital and mean of satisfaction with external environmental factors) were implemented and added to enhance interpretability. Nonetheless, the original raw data was preserved. The statement of items with their response formats was described and explained. Some items about satisfaction with external environmental factors were encrypted because of their relative political sensitivity. Nevertheless, the complete dataset can be acquired upon a reasonable request. “.” was used to indicate a missing value.
DOI: 10.17632/czxznncsv2.2
title: General happiness index from 2018 to 2024 in Hong Kong SAR: Dataset of repeated cross-sectional surveys

description: The dataset encompassed 10,070 responses gathered for the General Happiness Index survey from 2018 to 2024 in Hong Kong SAR, China. The self-reported questionnaire included demographic data (e.g., age range, sex, marital status, parental status, educational attainment, monthly income, religious affiliation), individual happiness, mental capital, values, social well-being (assessed by social well-being scale), satisfaction with external environmental factors, physical and mental health status, and the Patient Health Questionnaire-9 (PHQ-9). Data collection was conducted through online and/or in-person interviews, subject upon social conditions and infectious outbreaks. 
Data verification was conducted, and additional recording and computations (i.e., mean of mental capital and mean of satisfaction with external environmental factors) were implemented and added to enhance interpretability. Nonetheless, the original raw data was preserved. The statement of items with their response formats was described and explained. Some items about satisfaction with external environmental factors were encrypted because of their relative political sensitivity. Nevertheless, the complete dataset can be acquired upon a reasonable request. A “.” was used to indicate a missing value. The items' comparison was tabulated and summarized in the word file below.
DOI: 10.15468/dl.6agfdr
title: Occurrence Download

description: A dataset containing 84862 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amazona ochrocephala (Gmelin, 1788)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 84862 records from 279 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012213-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/k3x83vc928.1
title: Education and Shadow Economy: A Panel Cointegration Analysis

description: Data on the determinants of shadow economy
DOI: 10.17632/k3x83vc928.2
title: Education and Shadow Economy

description: Data on the determinants of shadow economy
DOI: 10.17632/3xwncsb5c6.1
title: Three-dimensional susceptibility model of the Manica greenstone belt, Mozambique, an integrated analysis with in-situ petrophysics and geochemistry data

description: Air Magnetic data (residuals and regional anomalies)
Topography
Pseudogravity data
Petrophysical data
Geochemical data
DOI: 10.17632/hhmsdbz9d6.1
title: onion production and marketing
DOI: 10.15468/dl.mxa9m3
title: Occurrence Download

description: A dataset containing 18795 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pieris napi (Linnaeus, 1758)",
 "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 18795 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012221-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/zg8y839mwf
title: Disparities in Physician Consultation Times for Acne and Rosacea Based on Sex, Age, Race, Disease Severity and Insurance: Analysis of NAMCS Data

description: Research Protocol of Disparities in Physician Consultation Times for Acne and Rosacea Based on Sex, Age, Race, Disease Severity and Insurance: Analysis of NAMCS Data
DOI: 10.17632/zg8y839mwf.1
title: Disparities in Physician Consultation Times for Acne and Rosacea Based on Sex, Age, Race, Disease Severity and Insurance: Analysis of NAMCS Data

description: Research Protocol of Disparities in Physician Consultation Times for Acne and Rosacea Based on Sex, Age, Race, Disease Severity and Insurance: Analysis of NAMCS Data
DOI: 10.1184/r1/28710647
title: Facebook Posts and Ads Linking To Pink Slime News Articles

description: Using the CrowdTangle API, each of the pink slime news domains was input and searched for public Facebook Page and Group posts from 2019-2024. Since the maximum number of posts possible to return is 1,000, I created a recursive function to halve the timeframe until fewer than 1,000 posts were available and then add in the posts from all the remaining time frames. Each row is a different post from a public Facebook Page or Group linking to a known pink slime website.<br>Ads were collected via facebook.com/ads/library using the United States location and “Issues, elections or politics” ad category. Each of the ad purchasers listed above was a separate keyword that generated its own csv via the ad library. These csv's were then uploaded into a Python dataframe and concatenated into a single dataframe. Each row represents a different ad that ran on Meta's platforms and was paid for by a pink slime news parent organization.
DOI: 10.1184/r1/28710647.v1
title: Facebook Posts and Ads Linking To Pink Slime News Articles

description: Using the CrowdTangle API, each of the pink slime news domains was input and searched for public Facebook Page and Group posts from 2019-2024. Since the maximum number of posts possible to return is 1,000, I created a recursive function to halve the timeframe until fewer than 1,000 posts were available and then add in the posts from all the remaining time frames. Each row is a different post from a public Facebook Page or Group linking to a known pink slime website.<br>Ads were collected via facebook.com/ads/library using the United States location and “Issues, elections or politics” ad category. Each of the ad purchasers listed above was a separate keyword that generated its own csv via the ad library. These csv's were then uploaded into a Python dataframe and concatenated into a single dataframe. Each row represents a different ad that ran on Meta's platforms and was paid for by a pink slime news parent organization.
DOI: 10.17632/f4gr6rgkwr.1
title: Good and bad Classification and identification of Omelette

description: Dataset Description: Good and Bad Omelette Classification

This dataset is created for the binary classification task of identifying whether an omelette sample is of good or bad quality. The primary objective is to develop a machine learning model that can accurately classify an omelette image or sample based on predefined quality parameters.

1. Dataset Size and Structure:
The dataset consists of 2000 samples, equally divided into two classes:

1000 Good Omelettes

1000 Bad Omelettes


Each sample in the dataset represents one omelette and is accompanied by a corresponding label:

1 or "Good" for high-quality omelettes

0 or "Bad" for low-quality omelettes


2. Data Type:
The dataset may include:

Images: High-resolution photos of omelettes under consistent lighting conditions. Each image is labeled accordingly.

Optional Metadata (if available):

Texture metrics (e.g., crispiness, fluffiness)

Color balance (golden brown vs burnt or undercooked)

Shape regularity

Ingredients used

Cooking time and temperature



3. Quality Criteria (Labeling Guidelines):

 i) Good Omelette Characteristics:

 Evenly cooked (not burnt or undercooked)

 Appealing golden-brown color

 Balanced texture (not rubbery or overly crispy)

 Well-shaped and visually appealing

 Includes expected ingredients (e.g., eggs, milk, seasoning, optional vegetables)


 ii) Bad Omelette Characteristics:

 Undercooked or overcooked (burnt)

 Pale or overly dark in color

 Irregular shape, torn or folded poorly

 Displeasing texture (e.g., too runny or rubbery)

 Missing or wrong ingredients



4. Purpose of the Dataset:

 The dataset is intended for:

 Training and evaluating computer vision or quality assessment models

 Image classification tasks in food quality control

 Benchmarking performance of different ML algorithms in binary classification


5. Applications:

 i) Automated food quality inspection in restaurants or food delivery services

 ii) Educational tools for culinary training

 iii) Quality assurance in pre-packaged meal production


6. upload pictures:
upload proper bad 1000 pictures and good 1000 pictures.

7. Ethics and Bias Consideration:
 
 Care has been taken to ensure diversity in sample acquisition—different cooking styles, lighting, and plating are considered to avoid bias.
DOI: 10.17632/wrzzd94m4h.1
title: (DATASET) Innovative Capacity: Constructs and Determinants - G7 Countries

description: This dataset presents 21 innovation determinants data collected mainly from: (1) Global Innovation Index Reports published by the World Intellectual Property Organization; (2) Global Competitiveness Index 4.0 published by the World Economic Forum; (3) World Intellectual Property Organization (WIPO) and (4) World Bank, corresponding to Canada, France, Germany, Italy, Japan, United Kingdom and United States (G7) published from 2007 to 2022. 
These variables are (1) Intellectual Property Protection; (2) Imports of goods and services(% GDP); (3) High-tech imports (%); (4) Expenditure on education; (5) Gross domestic expenditures on research and development (GERD); (6) University–industry R&D collaboration; (7) GERD performed by business enterprise; (8) gross expenditure on R&D, % GDP; (9) university-industry R&D collaboration; (10) Full time researches (per million population); (11) Research institutions prominence; (12) State of cluster development and depth; (13) Scientific publications; (14) Patent applications; (15) Patents applications by origin; (16) Utility models by origin (Domestic res utility model ap/bn GDP PPP$); (17) High-tech exports ($); (18) ICT services exports (%); (19) Trademark application class count by origin; (20) Gross domestic product million PPP; and (21) Increase of GDP (%).
DOI: 10.17632/4rjdzrfd3r.1
title: Data for Xu et al. "A Cross-scale Characterization of Porous Rocks Altered by Flow and Dissolution"

description: Video data for 3D wormholes and subsamples.
DOI: 10.17632/c8fgj6f7bz
title: Evaluation of rsmA gene-delated strains by proteomic analyses

description: Normalized Spectral Abundance Factor (NSAF) data from three independent biological replicates were processed and stadistically evaluated to determine significant differences betwenn strains. Proteome analyses were performed in RStudio and included the evaluation of normality and homoscedasticity to assess the distribution of the NSAF data for triplicates of each identified protein. Differentially Abundant Proteins (DAPs) were identified based on the statistically significant differences in the NSAF values between conditions, defined by a Log2 Fold Change &gt; 1.0 and p &lt; 0.05 (determined using an unpaired t-test or Mann-Whitney U test, as appropriate). Additionally, proteins exclusively detected in the rsmA mutant strain were labeled in the tables as ON. In contrast, those identified only in the corresponding wild-type strain were labeled as OFF, suggesting negative and positive regulation by RsmA, respectively.
DOI: 10.17632/c8fgj6f7bz.1
title: Evaluation of rsmA gene-delated strains by proteomic analyses

description: Normalized Spectral Abundance Factor (NSAF) data from three independent biological replicates were processed and stadistically evaluated to determine significant differences betwenn strains. Proteome analyses were performed in RStudio and included the evaluation of normality and homoscedasticity to assess the distribution of the NSAF data for triplicates of each identified protein. Differentially Abundant Proteins (DAPs) were identified based on the statistically significant differences in the NSAF values between conditions, defined by a Log2 Fold Change &gt; 1.0 and p &lt; 0.05 (determined using an unpaired t-test or Mann-Whitney U test, as appropriate). Additionally, proteins exclusively detected in the rsmA mutant strain were labeled in the tables as ON. In contrast, those identified only in the corresponding wild-type strain were labeled as OFF, suggesting negative and positive regulation by RsmA, respectively.
DOI: 10.17632/gr87pgn56d.1
title: RNAseq FPKM, and analysis for mouse tracheal RNA from Gli1 heterozygous and homozygous mutants, uninjured and injured with SO2

description: This file contains RNAseq FPKM from mouse tracheas (Gli1+/- uninjured, Gli1+/- SO2 injury plus 12 hours, Gli1+/- SO2 injury plus 24 hours, Gli1-/- SO2 injury plus 12 hours, and Gli1-/- SO2 injury plus 24 hours); and the analysis steps to obtain top 300 Gli1, SO2 injury induced and suppressed genes.
DOI: 10.17632/gr87pgn56d.2
title: RNAseq FPKM, and analysis for mouse tracheal RNA from Gli1 heterozygous and homozygous mutants, uninjured and injured with SO2

description: This file contains RNAseq FPKM from mouse tracheas (Gli1+/- uninjured, Gli1+/- SO2 injury plus 12 hours, Gli1+/- SO2 injury plus 24 hours, Gli1-/- SO2 injury plus 12 hours, and Gli1-/- SO2 injury plus 24 hours); and the analysis steps to obtain top 300 Gli1, SO2 injury induced and suppressed genes.
DOI: 10.17632/fpvrf8kpck.1
title: Supplimentary Information: Explaining global variation in life-cycle greenhouse gas (GHG) emissions from soybeans and soybean meal: a systematic review

description: This is a supplementary information for the publication "Explaining global variation in life-cycle greenhouse gas (GHG) emissions from soybeans and soybean meal: a systematic review". See manuscript for details.
DOI: 10.17632/mjf39pyh5j.1
title: plant disease

description: This dataset has been made using the popular PlantVillage , PlantDoc and other datasets
DOI: 10.17632/67dxw92m4w.1
title: Components of the Earth's magnetic field and rock-magnetic characteristics preserved in the core Cz-07 (Lake Cuitzeo, Mexico)

description: The database contains three files that support the information from the ancient geomagnetic field recovered from the Cz-07 core of Lake Cuitzeo, located in Michoacán state, Mexico.

1. Magnetic Parameters.xls contains the measurements of χ, κ, NRM, SIRM, and ARM; as well as the interparametric relations obtained from these data: SIRM/k, ARM/k , ARM/SIRM, κFD %, S-300 and HIRM.
2. ChNRM.JR6 contains the raw data used for the determination of the inclination values of the ancient geomagnetic field. The file can be opened in Remasoft application from Chadima and Hrouda (2006) for data analysis.
3. Pseudo_Thellier.txt contains the raw data used for paleointensity determinations. The file is in the pTh format described on paleointensity.org (Beguin et al., 2019). On this website the data can be analyzed.
DOI: 10.17632/67dxw92m4w.2
title: Inclination of the Earth's magnetic field and rock-magnetic characteristics preserved in the core Cz-07 (Lake Cuitzeo, Mexico)

description: The database contains two files that support the information from the ancient geomagnetic field recovered from the Cz-07 core of Lake Cuitzeo, located in Michoacán state, Mexico.

1. Magnetic Parameters.xls contains the measurements of χ, κ, NRM, SIRM, and ARM; as well as the interparametric relations obtained from these data: SIRM/k, ARM/k , ARM/SIRM, κFD %, S-300 and HIRM.
2. ChNRM.JR6 contains the raw data used for the determination of the inclination values of the ancient geomagnetic field. The file can be opened in Remasoft application from Chadima and Hrouda (2006) for data analysis.
DOI: 10.17632/dwky3hnt6j.1
title: Raw data and MATLAB codes for Xu et al., 2025, GRL

description: This dataset includes the raw data, the compilation of published data, and the MATLAB codes of the Monte Carlo model used in Xu et al., 2025, GRL.
DOI: 10.15468/dl.3k98hf
title: Occurrence Download

description: A dataset containing 435511 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Cardellina canadensis (Linnaeus, 1766)",
 "Year is greater than or equal to 1950",
 {
 "or" : [
 "GadmGid is USA",
 "GadmGid is CAN",
 "GadmGid is MEX"
 ]
 }
 ]
}

 The dataset includes 435511 records from 87 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012216-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tu35fv
title: Occurrence Download

description: A dataset containing 42116 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Orthopsittaca manilata (Boddaert, 1783)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 42116 records from 108 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012223-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/1v5v-p774
title: "Zen-Ship"

description: "The dataset trained the CNN for Zen-Ship, an automated audio censoring application. The dataset contains spectral data for either explicit or non-explicit words."
DOI: 10.15468/dl.mbrzkr
title: Occurrence Download

description: A dataset containing 15383 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vulpes vulpes (Linnaeus, 1758)",
 "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 15383 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012225-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15330746
title: Dataset for paper "Sameness entices, but novelty enchants in fanfiction online"

description: Dataset for paper "Sameness entices, but novelty enchants in fanfiction online", a dataset of fanfiction collected from the platform Archive Of Our Own (AO3). Please refer to the paper for dataset details.

As authors on AO3 retain all rights for their works, we choose not to redistribute the fanfiction texts outside of AO3. Instead, for each fandom we analyze, we share the URLs of the works we collected in the fandom. Users can refer to this snippet for downloading contents from AO3 using the URLs. The dataset contains the following fields:

'URL'

We also share a derived dataset of metadata of the fanfiction, along with the LDA topic distribution from fitting an LDA model using the fanfiction, and the Jensen-Shannon divergence value between each fiction and the center (see paper for details). These fields can be used to reproduce results in the paper. The dataset contains the following fields:

'AdditionalTags'

'ArchiveWarnings'

'Author'

'Category'

'Chapters'

'Characters'

'Fandoms'

'Kudos'

'Language'

'Rating'

'Relationship'

'Title'

'Words'

'PublishDate'

'UpdateDate'

'CompleteDate'

'Comments'

'Hits'

'Bookmarks'

'URL'

'Dist': LDA topic distribution

'JSD': Jensen-Shannon divergence value

Additional code for analysis can be found in this Github repo.

Please direct questions about the dataset to the corresponding author of the paper.