cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.29196
title: Technological Approach to Invasive Species: The Role of Remote Sensing and Predictive Modeling
title: Technological Approach to Invasive Species: The Role of Remote Sensing and Predictive Modeling

description: The dataset provides a global compilation of case studies on invasive species monitoring using remote sensing between 2016 to 2024. It documents species across continents, their study areas, techniques applied, datasets and sensors used, research objectives, ecological impacts, and accuracy assessments. The data reflects diverse methodologies, including UAV imagery, multispectral, hyperspectral, LiDAR, and time-series satellite analysis. It highlights both the potential of advanced machine learning and deep learning methods for scalable detection and the ecological risks posed by invasive plants. References to peer-reviewed studies ensure reliability, making this dataset a valuable resource for ecological monitoring and management strategies.
description: The dataset provides a global compilation of case studies on invasive species monitoring using remote sensing between 2016 to 2024. It documents species across continents, their study areas, techniques applied, datasets and sensors used, research objectives, ecological impacts, and accuracy assessments. The data reflects diverse methodologies, including UAV imagery, multispectral, hyperspectral, LiDAR, and time-series satellite analysis. It highlights both the potential of advanced machine learning and deep learning methods for scalable detection and the ecological risks posed by invasive plants. References to peer-reviewed studies ensure reliability, making this dataset a valuable resource for ecological monitoring and management strategies.
DOI: 10.34894/ychauu
title: Experimental investigation of an axial bidirectional impulse turbine in a (thermo)acoustic flow

description: In this study the experimental data for the investigation of a axial bidirectional impulse turbine in a (thermo)acoustic field is stored.
DOI: 10.5281/zenodo.16918660
title: Supplementary materials for the article 'Multi-scale in-silico modelling to unveil structural requirements for DNA-PK inhibitors as radiosensitizers and MolSHAP based design of novel ligands' authored by Soumya Mitra, Rakesh Kumar Dolai, Nilanjan Ghosh Subhash C Mandal and Amit Kumar Halder
DOI: 10.5281/zenodo.16918661
title: Supplementary materials for the article 'Multi-scale in-silico modelling to unveil structural requirements for DNA-PK inhibitors as radiosensitizers and MolSHAP based design of novel ligands' authored by Soumya Mitra, Rakesh Kumar Dolai, Nilanjan Ghosh Subhash C Mandal and Amit Kumar Halder
DOI: 10.15468/dl.zy3syt
title: Occurrence Download

description: A dataset containing 14393 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Helenium amarum"
 ]
}

 The dataset includes 14393 records from 116 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027968-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bgmx3m
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Heptapterus multiradiatus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027970-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15156637
title: Multi-Organ Gynaecological Magnetic Resonance Imaging for Brachytherapy-based Oncology

description: This dataset introduces a Multi-Organ Gynaecological Magnetic Resonance Imaging for Brachytherapy-based Oncology (MOGaMBO) dataset, a novel magnetic resonance imaging dataset aimed to advance research in applications of computational intelligence in brachytherapy diagnosis and organ segmentation for cervical cancer treatment. The dataset comprises high-resolution T2-weighted 3D MR scans from 94 patients with locally advanced cervical cancer (stages IB2–IVA), adhering to FIGO guidelines for interstitial and intra-cavitary brachytherapy. The imaging was performed using a 1.5T GE Signa Explorer scanner, with acquisition parameters TR and TE set to optimal values for soft-tissue contrast at 2600ms and 155ms, respectively, combined with a pixel resolution of 0.5 × 0.5 mm² and 30–50 slices per scan. To ensure dosimetric consistency, bladder volume was standardized via Foley catheterization during imaging. The critical organs-at-risk—urinary bladder, rectum, sigmoid colon, and femoral heads, were manually contoured by expert radiation oncologists using the open-source ITK-SNAP platform, ensuring precise region-of-interest annotations. The dataset underwent rigorous deidentification to protect patient privacy, removing all demographic and identifiable information. MOGaMBO provides a standardized, privacy-compliant resource for developing and validating medical image segmentation or representation learning algorithms, and brachytherapy-related research tools. This dataset addresses a critical gap in accessible, multi-organ imaging resources for the gynaecological brachytherapy dataset, with applications in treatment planning, and AI-driven clinical research.

 

If you use this dataset, then cite the following work in the appropriate format

BibTex:

@misc{manna2025,      title={Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation},       author={Siladittya Manna and Suresh Das and Sayantari Ghosh and Saumik Bhattacharya},      year={2025},      eprint={2503.23507},      archivePrefix={arXiv},      primaryClass={cs.CV},      url={https://arxiv.org/abs/2503.23507}, }

 

MLA:

Manna, Siladittya, et al. "Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation." arXiv preprint arXiv:2503.23507 (2025).

 

APA:

Manna, S., Das, S., Ghosh, S., & Bhattacharya, S. (2025). Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation. arXiv preprint arXiv:2503.23507.

 

Chicago:

Manna, Siladittya, Suresh Das, Sayantari Ghosh, and Saumik Bhattacharya. "Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation." arXiv preprint arXiv:2503.23507 (2025).

 

Harvard:

Manna, S., Das, S., Ghosh, S. and Bhattacharya, S., 2025. Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation. arXiv preprint arXiv:2503.23507.
DOI: 10.5281/zenodo.16918589
title: Multi-Organ Gynaecological Magnetic Resonance Imaging for Brachytherapy-based Oncology

description: This dataset introduces a Multi-Organ Gynaecological Magnetic Resonance Imaging for Brachytherapy-based Oncology (MOGaMBO) dataset, a novel magnetic resonance imaging dataset aimed to advance research in applications of computational intelligence in brachytherapy diagnosis and organ segmentation for cervical cancer treatment. The dataset comprises high-resolution T2-weighted 3D MR scans from 94 patients with locally advanced cervical cancer (stages IB2–IVA), adhering to FIGO guidelines for interstitial and intra-cavitary brachytherapy. The imaging was performed using a 1.5T GE Signa Explorer scanner, with acquisition parameters TR and TE set to optimal values for soft-tissue contrast at 2600ms and 155ms, respectively, combined with a pixel resolution of 0.5 × 0.5 mm² and 30–50 slices per scan. To ensure dosimetric consistency, bladder volume was standardized via Foley catheterization during imaging. The critical organs-at-risk—urinary bladder, rectum, sigmoid colon, and femoral heads, were manually contoured by expert radiation oncologists using the open-source ITK-SNAP platform, ensuring precise region-of-interest annotations. The dataset underwent rigorous deidentification to protect patient privacy, removing all demographic and identifiable information. MOGaMBO provides a standardized, privacy-compliant resource for developing and validating medical image segmentation or representation learning algorithms, and brachytherapy-related research tools. This dataset addresses a critical gap in accessible, multi-organ imaging resources for the gynaecological brachytherapy dataset, with applications in treatment planning, and AI-driven clinical research.

 

If you use this dataset, then cite the following work in the appropriate format

BibTex:

@misc{manna2025,      title={Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation},       author={Siladittya Manna and Suresh Das and Sayantari Ghosh and Saumik Bhattacharya},      year={2025},      eprint={2503.23507},      archivePrefix={arXiv},      primaryClass={cs.CV},      url={https://arxiv.org/abs/2503.23507}, }

 

MLA:

Manna, Siladittya, et al. "Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation." arXiv preprint arXiv:2503.23507 (2025).

 

APA:

Manna, S., Das, S., Ghosh, S., & Bhattacharya, S. (2025). Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation. arXiv preprint arXiv:2503.23507.

 

Chicago:

Manna, Siladittya, Suresh Das, Sayantari Ghosh, and Saumik Bhattacharya. "Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation." arXiv preprint arXiv:2503.23507 (2025).

 

Harvard:

Manna, S., Das, S., Ghosh, S. and Bhattacharya, S., 2025. Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation. arXiv preprint arXiv:2503.23507.
DOI: 10.15468/dl.gvuhj2
title: Occurrence Download

description: A dataset containing 35448 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Tragopogon porrifolius"
 ]
}

 The dataset includes 35448 records from 653 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027969-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k3gagv
title: Occurrence Download

description: A dataset containing 122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Oreolalax popei"
 ]
}

 The dataset includes 122 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027971-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e9sb9r
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Panicum maximum",
 "Country is Djibouti",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027973-250811113504898/datasets/export for details.
DOI: 10.15468/dl.z86e9s
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Panicum maximum",
 "Country is Czechia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027972-250811113504898/datasets/export for details.
DOI: 10.15468/dl.nvcvxk
title: Occurrence Download

description: A dataset containing 6697 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Coregonus albula",
 "Year 2013-2018"
 ]
}

 The dataset includes 6697 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027974-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5kw57x2m
title: MassIVE MSV000098900 - DIA proteomics of Solanum lasiocarpum fruit
title: Mature fruit of Solanum lasiocarpum was analyzed by short-gradient DIA LC-MS/MS. We provide Thermo RAW files and a custom FASTA (predicted from transcriptome by TransDecoder) for community re-analysis. A descriptive HTML report is included as supplement. LC: Easy-nLC 1200; MS: Q Exactive HF-X Orbitrap; DIA; ~16-min gradient.
DOI: 10.18167/dvn1/6pyg2o
title: KEOPS - LEAP4FNSSA - Output

description: The Long-term EU-AU Research and Innovation Partnership for Food and Nutrition Security and Sustainable Agriculture (LEAP4FNSSA) is a Coordination and Support Action (CSA). The main objective of the project is to provide a tool for European and African institutions to engage in a Sustainable Partnership Platform for research and innovation on Food and Nutrition Security, and Sustainable Agriculture (FNSSA). Work Package 3 (WP3) of the project aims to provide the core information system for the partnership platform. These data are the results of three virtual workshop sessions organized on 23rd and 24th of November 2020 (1st and 2nd sessions), and 9th of December 2020 (3rd session). Topic of data: Evaluation of KEOPS output Data description: (1) Type of results and visualisations to propose for the KEOPS platform, (2) 7 contributions (WP1 + HLPD members) + 9 contributions (WP3 members)
DOI: 10.6084/m9.figshare.26878867.v4
title: AirRC Dataset

description: <b>Associated Publication</b><br>[Your Paper Title] (Manuscript under review / Journal, DOI if available)
DOI: 10.15468/dl.v529uz
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Austrolebias univentripinnis)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027975-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3926nh
title: Occurrence Download

description: A dataset containing 239037 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prunus serotina",
 "BasisOfRecord is one of (Human Observation)"
 ]
}

 The dataset includes 239037 records from 415 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027930-250811113504898/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.27095374
title: Data and Code for Curveira-Santos et al. "Imbalanced recovery and depleted baselines of a protected mammal community in post-conflict Angola"

description: Multi-species detection data and R code used to fit the dynamic community occupancy model described in Curveira-Santos et al. "Imbalanced recovery and depleted baselines of a protected mammal community in post-conflict Angola".<br>Data collection and model formulation details are reported in the main article and supplementary material.<br><br><b><i>i.</i></b><b><i> </i></b><b>Data:</b> “Data.rdata”<br><br>Species detection and covariate data from camera-trap surveys conducted conducted in Bicuar National Park, Angola, between 2017 and 2023. The data file contains the following objects:"K": Two-dimensional effort array with number of 3-day sampling occasion per camera-site and yearly-season;"Yaug": Three-dimensional detection array with number of 3-day sampling occasions where at least one individual was detected, per species (zero-augmented), camera-site, and yearly-season;"season_list": Primary survey periods identifier (yearly-seasonal);"species_list": Species identifier (scientific names);"covariates": Site-specific (rows) covariate values (columns) for mean above-ground vegetation biomass (bmass), time since last fire (tsfire), distance to nearest human access (dhuma), distance to nearest waterhole (dwater), camera target feature (trail), camera height (height), and vegetation biomass at site (sbmass).<b><i>ii.</i></b><b> </b><b>Model Code:</b> “DCOM.R”<br><br>JAGS code written for program R to implement the dynamic community occupancy model.<br><br>
DOI: 10.6084/m9.figshare.27095374.v1
title: Data and Code for Curveira-Santos et al. "Imbalanced recovery and depleted baselines of a protected mammal community in post-conflict Angola"

description: Multi-species detection data and R code used to fit the dynamic community occupancy model described in Curveira-Santos et al. "Imbalanced recovery and depleted baselines of a protected mammal community in post-conflict Angola".<br>Data collection and model formulation details are reported in the main article and supplementary material.<br><br><b><i>i.</i></b><b><i> </i></b><b>Data:</b> “Data.rdata”<br><br>Species detection and covariate data from camera-trap surveys conducted conducted in Bicuar National Park, Angola, between 2017 and 2023. The data file contains the following objects:"K": Two-dimensional effort array with number of 3-day sampling occasion per camera-site and yearly-season;"Yaug": Three-dimensional detection array with number of 3-day sampling occasions where at least one individual was detected, per species (zero-augmented), camera-site, and yearly-season;"season_list": Primary survey periods identifier (yearly-seasonal);"species_list": Species identifier (scientific names);"covariates": Site-specific (rows) covariate values (columns) for mean above-ground vegetation biomass (bmass), time since last fire (tsfire), distance to nearest human access (dhuma), distance to nearest waterhole (dwater), camera target feature (trail), camera height (height), and vegetation biomass at site (sbmass).<b><i>ii.</i></b><b> </b><b>Model Code:</b> “DCOM.R”<br><br>JAGS code written for program R to implement the dynamic community occupancy model.<br><br>
DOI: 10.5281/zenodo.16918475
title: Genome-wide prediction of readthrough using TransStop

description: We applied the TransStop model to predict readthrough efficacy of eight drugs, on all potential premature termination codons in the human genome.
DOI: 10.5281/zenodo.16918476
title: Genome-wide prediction of readthrough using TransStop

description: We applied the TransStop model to predict readthrough efficacy of eight drugs, on all potential premature termination codons in the human genome.
DOI: 10.6084/m9.figshare.29958188
title: 3D PCA (60% Variance Clouds)

description: 3D PCA of SMARCB1 Variants with 60% Variance annotations as probability cloud.
DOI: 10.6084/m9.figshare.29958188.v1
title: 3D PCA (60% Variance Clouds)

description: 3D PCA of SMARCB1 Variants with 60% Variance annotations as probability cloud.
DOI: 10.5281/zenodo.16918680
title: Manually curated dataset of bias-testing prompt templates for LangBiTe
DOI: 10.5281/zenodo.16918681
title: Manually curated dataset of bias-testing prompt templates for LangBiTe
DOI: 10.15468/dl.kx3xaf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Panicum maximum",
 "Country is Dominica",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027976-250811113504898/datasets/export for details.
DOI: 10.18167/dvn1/6tlmd3
title: Source Data to study Genome assemblies of Musa wild banana ancestors and draw figures.

description: Source data associated with the paper "Unravelling genomic drivers of speciation in Musa through genome assemblies of wild banana ancestors" (includes sequence data and data and configuration files for figures and artworks generation). multiple types of data are present : raw Image files from cytological studies. Image files generated for chromosome scale assembly studies. Sequence file of genome assemblies. Multifasta gene alignments that allows plylogenetic analysis within the Musaceae family. Multifasta files of non redundant repeat sequences identified in genome assemblies that allows for repeated fraction genome analysis. tabulated, text and conf files for artwork and figures generation. Sequence file of genome assemblies.
DOI: 10.15468/dl.gme3w9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Panicum maximum",
 "Country is Dominican Republic",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027978-250811113504898/datasets/export for details.
DOI: 10.15468/dl.8bgkm9
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bujurquina pardus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027979-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16918659
title: AI, Mental Health, and Criminal Justice Reform
title: AI, Mental Health, and Criminal Justice Reform: Visionary Proposals for Public Safety
title: Democratic Sentencing and the Open Brain: Innovative Approaches to Crime and Society

description: This portfolio presents two visionary and original proposals developed independently by Mariarosaria Ottaiano (Naples, Italy; London, UK):

 



The Open Brain – a framework for ethically redirecting AI-driven eye-tracking and behavioural analytics away from commercial exploitation and toward public health and safety. The concept explores how everyday digital devices could act as “open brains,” enabling early detection of mental-health vulnerabilities, radicalisation risks, and criminal tendencies, while safeguarding human rights and ensuring transparency.

Democratic Sentencing for Organized Crime – a novel legal model that reframes organized crime as both a psychological pathology and a societal danger. The proposal envisions sentencing determined transparently by citizen panels within strict legal frameworks, reducing corruption, weakening mafia power, and restoring justice as a shared social responsibility.


Together, these papers bridge AI, psychology, law, and human rights, combining feasible near-term research opportunities with long-term visionary thinking. This work is intended to inspire academic debate, policy innovation, and interdisciplinary collaboration. 

 

If you would like to extend this work with me or explore collaboration, I would be glad to hear from you. 

m.r.o.27@icloud.com
DOI: 10.15468/dl.7d7zeh
title: Occurrence Download

description: A dataset containing 501372 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is one of (Asia, Oceania, Europe, North America, South America)",
 "TaxonKey is Impatiens glandulifera",
 "Year 1849-2025"
 ]
}

 The dataset includes 501372 records from 832 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027942-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.