cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17626222
title: Underwater images collected by a Paddle in Le-Morne, Mauritius - 2018-01-21

description: This dataset was collected by a Paddle in Le-Morne, Mauritius - 2018-01-21. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
DOI: 10.5281/zenodo.15749940
title: ToCA Theoretical Extension: Recursive Derivation of the Regulation Coefficient k (v1.0.3a)
DOI: 10.5281/zenodo.15749941
title: ToCA Theoretical Extension: Recursive Derivation of the Regulation Coefficient k (v1.0.3a)
DOI: 10.15468/dl.exux78
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (India, Thailand, Myanmar)",
 "TaxonKey is Dendrobium chrysotoxum"
 ]
}

 The dataset includes 62 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038355-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cmytgj
title: Occurrence Download

description: A dataset containing 147 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Michelia macclurei"
 ]
}

 The dataset includes 147 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038356-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4snk4q
title: Occurrence Download

description: A dataset containing 194 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A checklist of Acari type specimens deposited in the Jalal Afshar Zoological Museum, Karaj, Iran"
 ]
}

 The dataset includes 194 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038357-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30632846
title: Multivariate zero-inflated generalised poisson data generation methods for simulating counts of adverse events

description: Counts of maximum-grade adverse events collected in clinical trials are important measures of treatment toxicity and tolerability. Analyzing the frequencies and correlations of adverse event counts by type, treatment cycle, and grade provides deeper insight into toxicity profiles. A prerequisite for developing such inferential methods is the ability to generate multivariate count data with specified event rates and correlation structures. In this article, we present three methods for simulating multivariate count data with zero-inflated generalised Poisson (ZIGP) distributions. The methods accommodate arbitrarily specified pairwise correlations within the feasible range for the target distribution. We develop them under the Normal-to-Anything (NORTA) and Sample-Iterate (SI) simulation frameworks. Simulation studies show strong performance in reproducing desired rates, scales, zero-inflation, and correlation matrices. We apply the methods to simulate AE counts based on the NCCTG N9741 multicenter randomised phase III colorectal cancer trial. We also illustrate broader applicability by simulating hospital visit counts using data from the National Medical Expenditure Survey.
DOI: 10.6084/m9.figshare.30632846.v1
title: Multivariate zero-inflated generalised poisson data generation methods for simulating counts of adverse events

description: Counts of maximum-grade adverse events collected in clinical trials are important measures of treatment toxicity and tolerability. Analyzing the frequencies and correlations of adverse event counts by type, treatment cycle, and grade provides deeper insight into toxicity profiles. A prerequisite for developing such inferential methods is the ability to generate multivariate count data with specified event rates and correlation structures. In this article, we present three methods for simulating multivariate count data with zero-inflated generalised Poisson (ZIGP) distributions. The methods accommodate arbitrarily specified pairwise correlations within the feasible range for the target distribution. We develop them under the Normal-to-Anything (NORTA) and Sample-Iterate (SI) simulation frameworks. Simulation studies show strong performance in reproducing desired rates, scales, zero-inflation, and correlation matrices. We apply the methods to simulate AE counts based on the NCCTG N9741 multicenter randomised phase III colorectal cancer trial. We also illustrate broader applicability by simulating hospital visit counts using data from the National Medical Expenditure Survey.
DOI: 10.6084/m9.figshare.30478925.v2
title: <b>A 1-km resolution dataset of affordability-constrained accessibility to elderly care facilities in China (v1)</b>

description: This dataset provides a 1-km resolution assessment of accessibility to elderly care services across China, integrating both spatial accessibility and economic affordability dimensions. Accessibility was measured using improved spatial interaction models that account for facility capacity, service competition, and transportation networks, while affordability was incorporated through the ratio of per capita disposable income to care service costs. The dataset captures multi-dimensional disparities in elderly care resource allocation, offering a valuable foundation for aging policy research, spatial equity analysis, and urban–rural planning.
DOI: 10.34740/kaggle/dsv/13760283
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.17619938
title: SU2-Geometric-Phase-Visualization-Code

description: SU2-Geometric-Phase-Visualization-Code

This repository contains the code and demonstration videos used in the paper “Visualized Geometric Phase of Caustic Geometric Beams.”

It includes:- Code for geometric-phase extraction and data fitting  - Demonstration videos showing the evolution of feature lines (feature lines) with the geometric phase    (Note: The parameters (p, q) shown in the videos correspond to (s, t) in the main manuscript.)
DOI: 10.5281/zenodo.17619939
title: SU2-Geometric-Phase-Visualization-Code

description: SU2-Geometric-Phase-Visualization-Code

This repository contains the code and demonstration videos used in the paper “Visualized Geometric Phase of Caustic Geometric Beams.”

It includes:- Code for geometric-phase extraction and data fitting  - Demonstration videos showing the evolution of feature lines (feature lines) with the geometric phase    (Note: The parameters (p, q) shown in the videos correspond to (s, t) in the main manuscript.)
DOI: 10.21227/1706-bd45
title: "Valid Malformed Archives"

description: "These malformed archives samples were all able to successfully bypass the malicious attachment detection of the email providers we tested: 91 are single-attribute-modified samples and 70 are structurally modified samples. We also provide the effective samples for two combination of attributes."
DOI: 10.15468/dl.hp3dt2
title: Occurrence Download

description: A dataset containing 4117857 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "DatasetKey is EOD – eBird Observation Dataset"
 ]
}

 The dataset includes 4117857 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038339-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uxjk9g
title: Occurrence Download

description: A dataset containing 282 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Schima superba",
 "Year 1985-2025"
 ]
}

 The dataset includes 282 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038358-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15747809
title: ToCA  Theory of Cosmic Architecture

description: The Theory of Cosmic Architecture (ToCA) is a pioneering framework that unifies physical, biological, and cognitive systems through a principle of universal tension balance. It proposes that the universe operates as a self-regulating architecture, where emergent phenomena—such as galactic dynamics, consciousness, and ecological stability—arise from regulated interactions within layered arrays. ToCA challenges traditional views by suggesting that dark matter and dark energy may be illusions of this regulatory system, offering a holistic alternative that integrates existing scientific models and invites interdisciplinary exploration.
DOI: 10.5281/zenodo.15747810
title: ToCA  Theory of Cosmic Architecture

description: The Theory of Cosmic Architecture (ToCA) is a pioneering framework that unifies physical, biological, and cognitive systems through a principle of universal tension balance. It proposes that the universe operates as a self-regulating architecture, where emergent phenomena—such as galactic dynamics, consciousness, and ecological stability—arise from regulated interactions within layered arrays. ToCA challenges traditional views by suggesting that dark matter and dark energy may be illusions of this regulatory system, offering a holistic alternative that integrates existing scientific models and invites interdisciplinary exploration.
DOI: 10.5281/zenodo.17626227
title: Underwater images collected by a Kite surf in Le-Morne, Mauritius - 2018-03-10

description: This dataset was collected by a Kite surf in Le-Morne, Mauritius - 2018-03-10. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            
                
                                       
                
                
 GPS information: 

                GPX file from Garmin watch.
            
                    
                

                
            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
DOI: 10.5281/zenodo.17626526
title: Underwater images collected by a Kite surf in Le-Morne, Mauritius - 2018-03-10

description: This dataset was collected by a Kite surf in Le-Morne, Mauritius - 2018-03-10. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            
                
                                       
                
                
 GPS information: 

                GPX file from Garmin watch.
            
                    
                

                
            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
DOI: 10.15468/dl.sta6ys
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Updated checklist of semi-terrestrial and estuarine crabs (Crustacea: Decapoda: Brachyura) of Barbados, West Indies"
 ]
}

 The dataset includes 45 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038359-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30625283
title: <b>Rotavirus and its association with other etiological agents</b>

description: Results and demographic data from patients aged 0-5 years with gastrointestinal infection and suspected rotavirus infection. These samples were processed at the Central Epidemiology Laboratory (LCE) of the Instituto Mexicano del Seguro Social (IMSS). The samples were received between June 2023 and October 2025. 642 samples were processed for rotavirus detection tests, and 321 of these samples were also processed for molecular detection of 18 other etiological agents (4 viruses, 11 bacteria, 1 protozoan, and 2 parasites).
DOI: 10.6084/m9.figshare.30625283.v2
title: <b>Rotavirus and its association with other etiological agents</b>

description: Results and demographic data from patients aged 0-5 years with gastrointestinal infection and suspected rotavirus infection. These samples were processed at the Central Epidemiology Laboratory (LCE) of the Instituto Mexicano del Seguro Social (IMSS). The samples were received between June 2023 and October 2025. 642 samples were processed for rotavirus detection tests, and 321 of these samples were also processed for molecular detection of 18 other etiological agents (4 viruses, 11 bacteria, 1 protozoan, and 2 parasites).
DOI: 10.6084/m9.figshare.30625283.v1
title: <b>Rotavirus and its association with other etiological agents</b>

description: Results and demographic data from patients aged 0-5 years with gastrointestinal infection and suspected rotavirus infection. These samples were processed at the Central Epidemiology Laboratory (LCE) of the Instituto Mexicano del Seguro Social (IMSS). The samples were received between June 2023 and October 2025. 642 samples were processed for rotavirus detection tests, and 321 of these samples were also processed for molecular detection of 18 other etiological agents (4 viruses, 11 bacteria, 1 protozoan, and 2 parasites).
DOI: 10.5281/zenodo.17626527
title: The Fun Factor: Unlocking Place Love Through Exceptional Tourist Experiences

description: This study illustrates the psychological mechanisms of tourists’ behavioral outcome. Destinations strive to offer a wide range of venues with rich experiential attributes that evoke positive emotions. Fun holds the key to unlocking positive outcomes. This study explored the mediating role of fun between service excellence and place love and examine how expectation congruence moderates the mediating effect between service excellence and fun. As such, this paper should be of interest to a broad readership including destination marketers who may be interested in understanding factors contributing to the fun in marketing their destinations.
DOI: 10.5281/zenodo.17626528
title: The Fun Factor: Unlocking Place Love Through Exceptional Tourist Experiences

description: This study illustrates the psychological mechanisms of tourists’ behavioral outcome. Destinations strive to offer a wide range of venues with rich experiential attributes that evoke positive emotions. Fun holds the key to unlocking positive outcomes. This study explored the mediating role of fun between service excellence and place love and examine how expectation congruence moderates the mediating effect between service excellence and fun. As such, this paper should be of interest to a broad readership including destination marketers who may be interested in understanding factors contributing to the fun in marketing their destinations.
DOI: 10.15468/dl.4fjxqm
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Lao People’s Democratic Republic, Viet Nam, Belgium, unknown or invalid, United States of America, Guadeloupe)",
 "TaxonKey is Dendrobium chrysotoxum"
 ]
}

 The dataset includes 40 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038360-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fsugeu
title: Occurrence Download

description: A dataset containing 2595386 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (Asia, Europe)",
 "OccurrenceStatus is Present",
 "TaxonKey is Mareca penelope"
 ]
}

 The dataset includes 2595386 records from 1200 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038347-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15572713
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250602f Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250602f Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.15572714
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250602f Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250602f Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract