cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/cbct6bbctb.1
title: Single-cell transcriptomics of the mouse retina and retinal organoids in X-linked retinoschisis

description: Retinas were harvested from Rs1 R102W point mutation mice at postnatal weeks 2 and 4 for single-cell transcriptomic analysis. Age-matched C57BL/6 mice served as controls, with a minimum of 10 retinas per group per time point.
Retinal organoids were differentiated from induced pluripotent stem cells (iPSCs), which were reprogrammed from urinary cells of a patient with an Rs1 R102W point mutation. Retinal organoids derived from normal iPSCs were used as controls. Organoids were collected at day 50 for single-cell transcriptomic analysis, with a minimum of 20 organoids per group.
DOI: 10.17632/y2hvk8sw79
title: AH-Rain

description: AH-Rain is a dataset first proposed in the paper "Spatiotemporal dynamic modeling for nowcasting rainfall prediction using a dual-dimensional masked autoencoder." The data was collected in Anhui Province, China, covering the region from 27° to 36° north latitude and 113° to 121° east longitude. The data has a temporal resolution of 6 minutes and a spatial resolution of 0.01° × 0.01°, with each radar echo image having a resolution of 800 × 900 pixels. Using an S-band radar, data are collected at nine elevation angles per volume scan. The composite reflectivity value represents the maximum value among the nine elevation angles at the same azimuth and range. The dataset is presented as continuous images taken at 6-minute intervals. Because the data are automatically collected and recorded by the radar, some time points may be missing, resulting in discontinuities. Researchers interested in this dataset are encouraged to perform data cleaning and partitioning on their own for further research. We kindly request that researchers who use this dataset acknowledge our work by citing the relevant publication.
DOI: 10.17632/y2hvk8sw79.1
title: AH-Rain

description: AH-Rain is a dataset first proposed in the paper "Spatiotemporal dynamic modeling for nowcasting rainfall prediction using a dual-dimensional masked autoencoder." The data was collected in Anhui Province, China, covering the region from 27° to 36° north latitude and 113° to 121° east longitude. The data has a temporal resolution of 6 minutes and a spatial resolution of 0.01° × 0.01°, with each radar echo image having a resolution of 800 × 900 pixels. Using an S-band radar, data are collected at nine elevation angles per volume scan. The composite reflectivity value represents the maximum value among the nine elevation angles at the same azimuth and range. The dataset is presented as continuous images taken at 6-minute intervals. Because the data are automatically collected and recorded by the radar, some time points may be missing, resulting in discontinuities. Researchers interested in this dataset are encouraged to perform data cleaning and partitioning on their own for further research. We kindly request that researchers who use this dataset acknowledge our work by citing the relevant publication.
DOI: 10.17632/6mwg5ddgwv
title: Raman spectroscopic investigation of sulfur speciation in aqueous fluids with multiple solutes

description: This file provides all the in situ Raman spectra and data that were presented in all the figures in this manuscript.
DOI: 10.17632/rmb9rkkj2d.5
title: Supplemental Material for Vrcan et al., Genome-wide analyses to identify genomic regions associated with udder morphology traits in dairy sheep

description: Supplementary Tables associated to research paper Vrcan et al., Genome-wide analyses to unravel genetic mechanisms governing udder morphology traits in dairy sheep.
DOI: 10.17632/6mwg5ddgwv.1
title: Raman spectroscopic investigation of sulfur speciation in aqueous fluids with multiple solutes

description: This file provides all the in situ Raman spectra and data that were presented in all the figures in this manuscript.
DOI: 10.17632/x8wj68wrfj
title: Arabic Paraphrasing Corpus for NLP Applications

description: The Arabic Paraphrasing dataset consists of 143 short-text records collected from journal articles. It is designed to support research in Arabic paraphrasing and text similarity detection. The dataset includes 100 paraphrased texts and 43 non-paraphrased texts, providing a balanced set of examples for evaluating paraphrase identification and generation models.
DOI: 10.17632/x8wj68wrfj.1
title: Arabic Paraphrasing Corpus for NLP Applications

description: The Arabic Paraphrasing dataset consists of 143 short-text records collected from journal articles. It is designed to support research in Arabic paraphrasing and text similarity detection. The dataset includes 100 paraphrased texts and 43 non-paraphrased texts, providing a balanced set of examples for evaluating paraphrase identification and generation models.
DOI: 10.17632/nzyw9csjs8
title: Collection of transcription factor binding sites of 18 central flowering genes predicted by PWM in A. thaliana genome

description: Based on PWM, we identified transcription factor binding sites in the Arabidopsis thaliana genome. This dataset contains all possible TFs of genes specifically responsible for flowering - including floral development and signaling - which were queried from the EPD (Eukaryotic Promoter Database) with cut-off (p-value) values ​​of 0.00001 and 0.0001.
We examined the promoter of 18 genes responsible for central flowering in positions -5000 to +1000.
DOI: 10.17632/nzyw9csjs8.3
title: Collection of transcription factor binding sites of 18 central flowering genes predicted by PWM in A. thaliana genome

description: Based on PWM, we identified transcription factor binding sites in the Arabidopsis thaliana genome. This dataset contains all possible TFs of genes specifically responsible for flowering - including floral development and signaling - which were queried from the EPD (Eukaryotic Promoter Database) with cut-off (p-value) values ​​of 0.00001 and 0.0001.
We examined the promoter of 18 genes responsible for central flowering in positions -5000 to +1000.
DOI: 10.6084/m9.figshare.30032545
title: Supplementary Material for: Statistical Analysis Plan for a Randomized Controlled Trial of Intensive Blood Pressure Control on Cardiovascular risk Reduction in Patients with Atrial Fibrillation

description: Introduction:
Elevated blood pressure (BP) is a key modifiable risk factor for cardiovascular (CV) complications in patients with atrial fibrillation (AF). While current guidelines recommend modest BP targets, the optimal target in AF patients remains uncertain. The Cardiovascular Risk Reduction in Atrial Fibrillation Trial (CRAFT) is a multicenter, prospective, randomized, open-label, blinded-endpoint trial that evaluates whether intensive home systolic BP control (&lt;120 mmHg) is superior to standard BP control (&lt;135 mmHg) in reducing major CV events. The primary outcome is a hierarchical composite of time to CV death, stroke, myocardial infarction, and heart failure hospitalization. A total sample of 1,675 participants provides 80% power to detect a win ratio of 1.50 between groups after a mean of 3 years of follow-up.
Methods:
This statistical analysis plan (SAP) was developed by the trial statistician and principal investigators, in collaboration with the steering committee and international experts. The SAP specifies the planned analyses of baseline characteristics, patients’ intervention, primary and secondary outcomes, subgroup effects, and safety outcomes. Analyses will be conducted on an intention-to-treat (ITT) analysis using the win-ratio method for the primary endpoint, and Cox proportional hazards and Poisson regression for secondary analyses. Sensitivity analyses and strategies for handling missing data are also described.
Discussion:
A pre-defined SAP was established for the CRAFT trial to ensure a transparent and verifiable analysis. The SAP was finalized prospectively, independent of treatment assignment, with the goal of preserving internal validity and minimizing analytical bias.
Keywords: Statistical analysis plan, atrial fibrillation, clinical trial, hypertension, blood pressure
Trial registration: ClinicalTrials.gov (NCT04347330)
DOI: 10.6084/m9.figshare.30032545.v2
title: Supplementary Material for: Statistical Analysis Plan for a Randomized Controlled Trial of Intensive Blood Pressure Control on Cardiovascular risk Reduction in Patients with Atrial Fibrillation

description: Introduction:
Elevated blood pressure (BP) is a key modifiable risk factor for cardiovascular (CV) complications in patients with atrial fibrillation (AF). While current guidelines recommend modest BP targets, the optimal target in AF patients remains uncertain. The Cardiovascular Risk Reduction in Atrial Fibrillation Trial (CRAFT) is a multicenter, prospective, randomized, open-label, blinded-endpoint trial that evaluates whether intensive home systolic BP control (&lt;120 mmHg) is superior to standard BP control (&lt;135 mmHg) in reducing major CV events. The primary outcome is a hierarchical composite of time to CV death, stroke, myocardial infarction, and heart failure hospitalization. A total sample of 1,675 participants provides 80% power to detect a win ratio of 1.50 between groups after a mean of 3 years of follow-up.
Methods:
This statistical analysis plan (SAP) was developed by the trial statistician and principal investigators, in collaboration with the steering committee and international experts. The SAP specifies the planned analyses of baseline characteristics, patients’ intervention, primary and secondary outcomes, subgroup effects, and safety outcomes. Analyses will be conducted on an intention-to-treat (ITT) analysis using the win-ratio method for the primary endpoint, and Cox proportional hazards and Poisson regression for secondary analyses. Sensitivity analyses and strategies for handling missing data are also described.
Discussion:
A pre-defined SAP was established for the CRAFT trial to ensure a transparent and verifiable analysis. The SAP was finalized prospectively, independent of treatment assignment, with the goal of preserving internal validity and minimizing analytical bias.
Keywords: Statistical analysis plan, atrial fibrillation, clinical trial, hypertension, blood pressure
Trial registration: ClinicalTrials.gov (NCT04347330)
DOI: 10.6084/m9.figshare.30032545.v1
title: Supplementary Material for: Statistical Analysis Plan for a Randomized Controlled Trial of Intensive Blood Pressure Control on Cardiovascular risk Reduction in Patients with Atrial Fibrillation

description: Introduction:
Elevated blood pressure (BP) is a key modifiable risk factor for cardiovascular (CV) complications in patients with atrial fibrillation (AF). While current guidelines recommend modest BP targets, the optimal target in AF patients remains uncertain. The Cardiovascular Risk Reduction in Atrial Fibrillation Trial (CRAFT) is a multicenter, prospective, randomized, open-label, blinded-endpoint trial that evaluates whether intensive home systolic BP control (&lt;120 mmHg) is superior to standard BP control (&lt;135 mmHg) in reducing major CV events. The primary outcome is a hierarchical composite of time to CV death, stroke, myocardial infarction, and heart failure hospitalization. A total sample of 1,675 participants provides 80% power to detect a win ratio of 1.50 between groups after a mean of 3 years of follow-up.
Methods:
This statistical analysis plan (SAP) was developed by the trial statistician and principal investigators, in collaboration with the steering committee and international experts. The SAP specifies the planned analyses of baseline characteristics, patients’ intervention, primary and secondary outcomes, subgroup effects, and safety outcomes. Analyses will be conducted on an intention-to-treat (ITT) analysis using the win-ratio method for the primary endpoint, and Cox proportional hazards and Poisson regression for secondary analyses. Sensitivity analyses and strategies for handling missing data are also described.
Discussion:
A pre-defined SAP was established for the CRAFT trial to ensure a transparent and verifiable analysis. The SAP was finalized prospectively, independent of treatment assignment, with the goal of preserving internal validity and minimizing analytical bias.
Keywords: Statistical analysis plan, atrial fibrillation, clinical trial, hypertension, blood pressure
Trial registration: ClinicalTrials.gov (NCT04347330)
DOI: 10.17632/9pvcj9n9fs
title: unique_user_influencers

description: This file contains user-aggregated metrics describing the engagement, influence, and activity patterns of Twitter accounts that posted about Cyclone Phailin (October 2013).
Each row corresponds to a unique Twitter user and summarizes their overall participation in the event discourse.


All personal identifiers (e.g., screen_name, username, user_id) have been removed or pseudonymized (user_anon_id).
No tweet text or private metadata are included.
DOI: 10.17632/9pvcj9n9fs.1
title: unique_user_influencers

description: This file contains user-aggregated metrics describing the engagement, influence, and activity patterns of Twitter accounts that posted about Cyclone Phailin (October 2013).
Each row corresponds to a unique Twitter user and summarizes their overall participation in the event discourse.


All personal identifiers (e.g., screen_name, username, user_id) have been removed or pseudonymized (user_anon_id).
No tweet text or private metadata are included.
DOI: 10.17632/p5sjx7d8cs
title: Phailin_annotated

description: This data contains 1,500 manually annotated tweet records from the Cyclone Phailin dataset, representing a multilingual (predominantly English) subset of Twitter posts collected during 9–13 October 2013.
Each record corresponds to a single tweet and includes anonymized metadata, derived variables, and human-assigned categorical labels.

This dataset is designed for supervised machine learning and communication analysis, particularly for identifying informative content, tweet categories, and user types during natural disasters.
All direct personal identifiers (e.g., screen_name, username, user_id, profile text, precise location) have been removed or pseudonymized (user_anon_id).
Mentions and URLs in tweet text were stripped, while hashtags were retained; a cleaned tokenized version of the tweet is provided as tokenized_text.
DOI: 10.17632/p5sjx7d8cs.1
title: Phailin_annotated

description: This data contains 1,500 manually annotated tweet records from the Cyclone Phailin dataset, representing a multilingual (predominantly English) subset of Twitter posts collected during 9–13 October 2013.
Each record corresponds to a single tweet and includes anonymized metadata, derived variables, and human-assigned categorical labels.

This dataset is designed for supervised machine learning and communication analysis, particularly for identifying informative content, tweet categories, and user types during natural disasters.
All direct personal identifiers (e.g., screen_name, username, user_id, profile text, precise location) have been removed or pseudonymized (user_anon_id).
Mentions and URLs in tweet text were stripped, while hashtags were retained; a cleaned tokenized version of the tweet is provided as tokenized_text.
DOI: 10.17632/tmh5jvfbz9
title: Phailin_Raw_2013

description: phailin_raw_2013.csv contains 58,262 tweets related to Cyclone Phailin, one of the most severe cyclones to strike India in October 2013.
The dataset spans the period 9–13 October 2013, covering the cyclone’s formation, landfall, and immediate aftermath.

Tweets were collected using the Twitter Academic API (via the Tweepy library) with event-specific hashtags and keywords such as #Phailin, #CyclonePhailin, and OrissaPhailin.
This dataset captures multilingual communication (primarily English and Indian regional languages) posted by citizens, media, NGOs, and government agencies during the disaster.

The file contains raw tweet-level metadata (tweet ID, timestamps, language, retweet counts, and user information) along with derived variables to support further aggregation and analysis.
DOI: 10.17632/tmh5jvfbz9.1
title: Phailin_Raw_2013

description: phailin_raw_2013.csv contains 58,262 tweets related to Cyclone Phailin, one of the most severe cyclones to strike India in October 2013.
The dataset spans the period 9–13 October 2013, covering the cyclone’s formation, landfall, and immediate aftermath.

Tweets were collected using the Twitter Academic API (via the Tweepy library) with event-specific hashtags and keywords such as #Phailin, #CyclonePhailin, and OrissaPhailin.
This dataset captures multilingual communication (primarily English and Indian regional languages) posted by citizens, media, NGOs, and government agencies during the disaster.

The file contains raw tweet-level metadata (tweet ID, timestamps, language, retweet counts, and user information) along with derived variables to support further aggregation and analysis.
DOI: 10.17632/3h3bwg3vx4
title: How do free trade agreements affect firms’ export values? Insights into the mechanisms of export costs and export stability

description: This archive contains the synthetic replication datasets (main.dta and robust.dta) and all Stata do-files necessary to reproduce the results presented in the paper. Each do-file corresponds to a specific table or figure, covering descriptive analyses, baseline estimations, and robustness checks. All output files are automatically generated, ensuring complete reproducibility as detailed in the accompanying README file.
DOI: 10.17632/3h3bwg3vx4.1
title: How do free trade agreements affect firms’ export values? Insights into the mechanisms of export costs and export stability

description: This archive contains the synthetic replication datasets (main.dta and robust.dta) and all Stata do-files necessary to reproduce the results presented in the paper. Each do-file corresponds to a specific table or figure, covering descriptive analyses, baseline estimations, and robustness checks. All output files are automatically generated, ensuring complete reproducibility as detailed in the accompanying README file.
DOI: 10.17632/3skbpssh33.1
title: Research data
DOI: 10.17632/nnjvz3b3tv
title: Life Cycle Assessment of Greenhouse Gas and PM2.5 Emissions from Semi-prefabricated Housing Construction

description: LCI dataset of Semi-prefabricated Housing Construction
DOI: 10.17632/nnjvz3b3tv.1
title: Life Cycle Assessment of Greenhouse Gas and PM2.5 Emissions from Semi-prefabricated Housing Construction

description: LCI dataset of Semi-prefabricated Housing Construction
DOI: 10.17632/j987ggwbpr
title: Conferences Abstract

description: Data used for the manuscript: Who gets the spotlight? Disparities in seabird research attention at scientific conferences. It consists of a readme file, several .csv files and an R script to reproduce the different tables and figures.
DOI: 10.17632/j987ggwbpr.1
title: Conferences Abstract

description: Data used for the manuscript: Who gets the spotlight? Disparities in seabird research attention at scientific conferences. It consists of a readme file, several .csv files and an R script to reproduce the different tables and figures.
DOI: 10.17632/rbw88g8z33
title: Aniline Containing Natural Products

description: Aniline containing natural products for network analysis
DOI: 10.17632/rbw88g8z33.1
title: Aniline Containing Natural Products

description: Aniline containing natural products for network analysis
DOI: 10.17632/n4p64ffv73
title: Water table depth monitoring extracted peatland, Latvia

description: This dataset contains continuous groundwater pressure and water table depth (WTD) monitoring data from the Kaigu peatland in Central Latvia, recorded between June 2023 and May 2025. The site represents a degraded, previously extracted peatland section characterized by diverse surface moisture and vegetation types according to the Greenhouse Gas Emission Site Types (GEST). The dataset included (1) raw absolute pressure data (cm H2O) from six monitoring wells, (2) barometric pressure data from the reference logger, (3) metadata on coordinates, installation elevations and installation data.
DOI: 10.17632/n4p64ffv73.1
title: Water table depth monitoring extracted peatland, Latvia

description: This dataset contains continuous groundwater pressure and water table depth (WTD) monitoring data from the Kaigu peatland in Central Latvia, recorded between June 2023 and May 2025. The site represents a degraded, previously extracted peatland section characterized by diverse surface moisture and vegetation types according to the Greenhouse Gas Emission Site Types (GEST). The dataset included (1) raw absolute pressure data (cm H2O) from six monitoring wells, (2) barometric pressure data from the reference logger, (3) metadata on coordinates, installation elevations and installation data.
DOI: 10.15468/dl.uxewmx
title: Occurrence Download

description: A dataset containing 4751 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-55.28282 3.94432,-52.89779 3.94432,-52.89779 6.02322,-55.28282 6.02322,-55.28282 3.94432))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Siluriformes"
 ]
}

 The dataset includes 4751 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013087-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2vr4pw
title: Occurrence Download

description: A dataset containing 262 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Mimosa galeottii)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 262 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013086-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/xv25yjbzkm
title: Diabetes Risk Prediction Dataset: Demographics, Lifestyle, and Clinical Indicators

description: 📄 Dataset Description

This dataset contains demographic, lifestyle, and clinical health indicators collected for the purpose of predicting diabetes risk using machine learning techniques. The data integrates both behavioral and physiological variables to provide a comprehensive view of factors influencing diabetes onset.

📄Content

1. Demographics: Gender, Age
2. Lifestyle Factors: Physical Activity, Smoking Status, Alcohol Intake, Family History, Hypertension
3. Clinical Measurements: Glucose, Blood Pressure, Skin Thickness, Insulin, BMI, Cholesterol, Diabetes Pedigree Function
4. Target Variable: Outcome (Diabetic / Non-diabetic)

📄Objective

The primary goal of this dataset is to support the development and evaluation of classification models that can predict whether an individual is diabetic or non-diabetic based on measurable risk factors.

📄Potential Use Cases

1. Building and testing machine learning models for diabetes prediction.
2. Exploring correlations between lifestyle choices and diabetes prevalence.
3. Conducting data analysis in healthcare research and medical decision support systems.
4. Developing early risk assessment tools for clinical practice.

📄Format

File type: CSV
Rows: Each row represents an individual record.
Columns: Attributes include demographic, lifestyle, clinical features, and diabetes outcome.

📄Notes

All values are anonymized.

The dataset is intended for educational, research, and analytical purposes only.

Users should validate models against external datasets before applying in clinical settings.