cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17256865
title: Filter Pore Size of seawater eDNA samples: Shotgun Sequencing - Part 1/2

description: Data related to the publication "Filter pore size influences taxonomic composition of retained eDNA from seawater samples – evidence from shotgun sequencing". Raw sequencing files could be found in ENA/NCBI under the BioProject PRJEB104040.

This dataset contains:




 
Number of files
Decompressed Weight


Paired-reads in fasta format 
15
53 GB


Raw Blast results
15
810 GB


md5 hashes 
1
-
DOI: 10.5281/zenodo.18491930
title: Vernacular Cataloguing

description: “Vernacular” the word refers to exact script as it in original. Vernacular cataloguing comes as in original script, e.g. title, author’s name etc. Users can find their searching without translation. No transliteration is needed in Vernacular Cataloguing.

It preserves authenticity, cultural heritage. Vernacular Cataloguing comes in native languages. It saves accurate data. Users who do not comfortable in international language can find stuffs through their native languages. 

Vernacular Cataloguing saves cultural languages. It brings users and increasing accessibility. 

A library should have facility of Vernacular cataloguing. 

In a library members should be careful about making catalogue. No spelling should be incorrect. Training should be proper. They should be more careful about accuracy.
DOI: 10.5281/zenodo.18491931
title: Vernacular Cataloguing

description: “Vernacular” the word refers to exact script as it in original. Vernacular cataloguing comes as in original script, e.g. title, author’s name etc. Users can find their searching without translation. No transliteration is needed in Vernacular Cataloguing.

It preserves authenticity, cultural heritage. Vernacular Cataloguing comes in native languages. It saves accurate data. Users who do not comfortable in international language can find stuffs through their native languages. 

Vernacular Cataloguing saves cultural languages. It brings users and increasing accessibility. 

A library should have facility of Vernacular cataloguing. 

In a library members should be careful about making catalogue. No spelling should be incorrect. Training should be proper. They should be more careful about accuracy.
DOI: 10.5281/zenodo.18491981
title: Dynamic hydroxyl bridge mechanism for selective ozone evolution on Ni-Sb-SnO2
DOI: 10.5281/zenodo.18491980
title: Dynamic hydroxyl bridge mechanism for selective ozone evolution on Ni-Sb-SnO2
DOI: 10.34740/kaggle/dsv/14739466
title: Public Opinion on Climate Change (Updated Daily)
DOI: 10.5281/zenodo.18491991
title: KAJIAN LINGKUNGAN PROYEK PEMBANGUNAN PERUMAHAN PERUMAHAN SUBSIDI GRIYA SITRAH 2 PALOPO
DOI: 10.5281/zenodo.18491990
title: KAJIAN LINGKUNGAN PROYEK PEMBANGUNAN PERUMAHAN PERUMAHAN SUBSIDI GRIYA SITRAH 2 PALOPO
DOI: 10.21227/yr3h-9f31
title: "Literature-based evidence map of fucoidan from Undaria pinnatifida sporophyll (2025\u20132026)"

description: "This study reviews the anti-inflammatory and antioxidant activities of fucoidan derived from the sporophyll of Undaria pinnatifida and examines how marine and aquaculture environmental factors may influence its composition and functionality. Evidence from human trials, preclinical studies, and observational reports was categorized by evidence strength. Anti-inflammatory effects are supported by relatively more human evidence, whereas antioxidant activity has been reported mainly in in vitro and animal studies. Environmental conditions\u2014especially harvest season and sporophyll maturity\u2014are consistently associated with variations in fucoidan yield, degree of sulfation, molecular weight, and sugar composition, which may contribute to differences in biological activity. These findings highlight the need for standardized harvesting conditions and structural profiling of fucoidan to improve consistency in research and industrial applications."
DOI: 10.5281/zenodo.18491766
title: C29823 BItFROST

description: 3D model of antler pick in the collection of the Museum of Cultural History, University of Oslo

View 3D model on BItFROST

View artefact on the Unimus portal

Documented for study by Mieko Matsumoto
DOI: 10.5281/zenodo.18491767
title: C29823 BItFROST

description: 3D model of antler pick in the collection of the Museum of Cultural History, University of Oslo

View 3D model on BItFROST

View artefact on the Unimus portal

Documented for study by Mieko Matsumoto
DOI: 10.5281/zenodo.18491978
title: Zenodo, Polarization Test Data for DoT/DoFP Polarization Imaging

description: DoT data are used for testing reconstruction accuracy, while DoFP data are employed for subjective testing.
DOI: 10.5281/zenodo.18491979
title: Zenodo, Polarization Test Data for DoT/DoFP Polarization Imaging

description: DoT data are used for testing reconstruction accuracy, while DoFP data are employed for subjective testing.
DOI: 10.5281/zenodo.14793397
title: URBANE Valladolid Living Lab In-home vs in-trunk delivery

description: At home vs in-trunk delivery data for several urban scenarios carried out within the Valladolid LL as part of the URBANE project
DOI: 10.5281/zenodo.14793398
title: URBANE Valladolid Living Lab In-home vs in-trunk delivery

description: At home vs in-trunk delivery data for several urban scenarios carried out within the Valladolid LL as part of the URBANE project
DOI: 10.6084/m9.figshare.28498622
title: Critical Soil Moisture Estimates and Regime Properties

description: This repository provides the datasets, processing workflows, and analysis codes used to estimate critical soil moisture thresholds (θ*) at the global scale and to characterize hydrological regime dynamics and land–atmosphere interactions. The framework derives θ* using three independent proxy pathways that represent complementary physical processes governing land surface feedbacks: diurnal soil temperature range (dTsoil), evaporative fraction (EF), and the temporal rate of soil moisture drying (dθ/dt). In addition to θ* estimates, the repository includes a suite of derived regime diagnostics designed to quantify hydrological stability and transition behavior. These include persistence (γ), defined as the fraction of time spent in the water-limited regime; tipping potential (τ), representing the probability of regime switching; and binary regime classification accuracy (π), which measures the level of agreement among independent critical threshold estimation methods. The persistence (γ) and tipping potential (τ) metrics are computed separately for EF-, dTsoil-, and dθ/dt-based thresholds, whereas the classification accuracy (π) metric is evaluated between dTsoil–EF and dTsoil–dθ/dt method pairs to assess cross-proxy consistency. The repository further provides estimates of land–atmosphere coupling strength (Ω), a diagnostic metric that describes the sensitivity of surface energy partitioning to soil moisture variability and enables the identification of regions with strong soil moisture–atmosphere feedbacks (“coupling hotspots”). The Ω metric is derived consistently across all three methods.<b>References</b>: For detailed methodological descriptions, definitions of θ* thresholds, and full explanations of derived regime metrics, users are referred to the original article: https://doi.org/10.1029/2025EF006194. See the latest version of this repository at: https://doi.org/10.6084/m9.figshare.28498622<b>Connect</b>: For questions, technical clarifications, or collaboration inquiries, please contact the repository author at: sandipan.paul.ess@gmail.com | https://sites.google.com/view/sandipan-paul?usp=sharing
DOI: 10.6084/m9.figshare.28498622.v3
title: Critical Soil Moisture Estimates and Regime Properties

description: This repository provides the datasets, processing workflows, and analysis codes used to estimate critical soil moisture thresholds (θ*) at the global scale and to characterize hydrological regime dynamics and land–atmosphere interactions. The framework derives θ* using three independent proxy pathways that represent complementary physical processes governing land surface feedbacks: diurnal soil temperature range (dTsoil), evaporative fraction (EF), and the temporal rate of soil moisture drying (dθ/dt). In addition to θ* estimates, the repository includes a suite of derived regime diagnostics designed to quantify hydrological stability and transition behavior. These include persistence (γ), defined as the fraction of time spent in the water-limited regime; tipping potential (τ), representing the probability of regime switching; and binary regime classification accuracy (π), which measures the level of agreement among independent critical threshold estimation methods. The persistence (γ) and tipping potential (τ) metrics are computed separately for EF-, dTsoil-, and dθ/dt-based thresholds, whereas the classification accuracy (π) metric is evaluated between dTsoil–EF and dTsoil–dθ/dt method pairs to assess cross-proxy consistency. The repository further provides estimates of land–atmosphere coupling strength (Ω), a diagnostic metric that describes the sensitivity of surface energy partitioning to soil moisture variability and enables the identification of regions with strong soil moisture–atmosphere feedbacks (“coupling hotspots”). The Ω metric is derived consistently across all three methods.<b>References</b>: For detailed methodological descriptions, definitions of θ* thresholds, and full explanations of derived regime metrics, users are referred to the original article: https://doi.org/10.1029/2025EF006194. See the latest version of this repository at: https://doi.org/10.6084/m9.figshare.28498622<b>Connect</b>: For questions, technical clarifications, or collaboration inquiries, please contact the repository author at: sandipan.paul.ess@gmail.com | https://sites.google.com/view/sandipan-paul?usp=sharing
DOI: 10.6084/m9.figshare.28498622.v2
title: Critical Soil Moisture Estimates and Regime Properties

description: This repository provides the datasets, processing workflows, and analysis codes used to estimate critical soil moisture thresholds (θ*) at the global scale and to characterize hydrological regime dynamics and land–atmosphere interactions. The framework derives θ* using three independent proxy pathways that represent complementary physical processes governing land surface feedbacks: diurnal soil temperature range (dTsoil), evaporative fraction (EF), and the temporal rate of soil moisture drying (dθ/dt). In addition to θ* estimates, the repository includes a suite of derived regime diagnostics designed to quantify hydrological stability and transition behavior. These include persistence (γ), defined as the fraction of time spent in the water-limited regime; tipping potential (τ), representing the probability of regime switching; and binary regime classification accuracy (π), which measures the level of agreement among independent critical threshold estimation methods. The persistence (γ) and tipping potential (τ) metrics are computed separately for EF-, dTsoil-, and dθ/dt-based thresholds, whereas the classification accuracy (π) metric is evaluated between dTsoil–EF and dTsoil–dθ/dt method pairs to assess cross-proxy consistency. The repository further provides estimates of land–atmosphere coupling strength (Ω), a diagnostic metric that describes the sensitivity of surface energy partitioning to soil moisture variability and enables the identification of regions with strong soil moisture–atmosphere feedbacks (“coupling hotspots”). The Ω metric is derived consistently across all three methods.For detailed methodological descriptions, definitions of θ* thresholds, and full explanations of derived regime metrics, users are referred to the original article: https://doi.org/10.1029/2025EF006194For questions, technical clarifications, or collaboration inquiries, please contact the repository author at: sandipan.paul.ess@gmail.com | https://sites.google.com/view/sandipan-paul?usp=sharing
DOI: 10.5281/zenodo.15592496
title: Repro-RAxML-NG Benchmark Dataset

description: See https://github.com/stelzch/reproducible-reduce-benchmark for details and usage.

data.tar.lzma

The dataset compilation in data.tar.lzma is adapted from the RAxML-NG paper, previously published under https://figshare.com/s/6123932e0a43280095ef

Please cite the original studies listed in Table 3 of the RAxML-NG paper supplement when (re-)using the datasets.

Changes made to the data:



The num_pe file contains the recommended number of MPI ranks as given by raxml-ng --parse

The time.s file contains a runtime estimate in minutes.

Rearranged file hierarchy


results.tar.lzma

Contains the log files from our reproducible RAxML-NG executions.

benchmark-supermuc.tar.gz

Binaries, log files and intermediate files from Repro-RAxML-NG executions on the SuperMUC-NG. Additionally, results from isolated benchmarks of our reduce algorithm ReproRed.

evaluation.tar.lzma

Input data, RAxML-NG log files and results of non-reproducible tree searches on TreeBASE datasets with varying thread count and varying random seed.

evaluation-revision.tar.lzma

Additional files produced during revision. Quartet-distances of ML trees.
DOI: 10.5281/zenodo.18491488
title: Repro-RAxML-NG Benchmark Dataset

description: See https://github.com/stelzch/reproducible-reduce-benchmark for details and usage.

data.tar.lzma

The dataset compilation in data.tar.lzma is adapted from the RAxML-NG paper, previously published under https://figshare.com/s/6123932e0a43280095ef

Please cite the original studies listed in Table 3 of the RAxML-NG paper supplement when (re-)using the datasets.

Changes made to the data:



The num_pe file contains the recommended number of MPI ranks as given by raxml-ng --parse

The time.s file contains a runtime estimate in minutes.

Rearranged file hierarchy


results.tar.lzma

Contains the log files from our reproducible RAxML-NG executions.

benchmark-supermuc.tar.gz

Binaries, log files and intermediate files from Repro-RAxML-NG executions on the SuperMUC-NG. Additionally, results from isolated benchmarks of our reduce algorithm ReproRed.

evaluation.tar.lzma

Input data, RAxML-NG log files and results of non-reproducible tree searches on TreeBASE datasets with varying thread count and varying random seed.

evaluation-revision.tar.lzma

Additional files produced during revision. Quartet-distances of ML trees.
DOI: 10.5281/zenodo.18492022
title: R-programming

description: R is a powerful, open-source programming language and software environment primarily used for statistical computing, data analysis, and graphical representation. Developed by Ross Ihaka and Robert Gentleman in the early 1990s, R has become one of the most popular tools among statisticians, data scientists, researchers, and academicians. Its flexibility, extensive package ecosystem, and strong data visualization capabilities make it suitable for a wide range of applications.
DOI: 10.5281/zenodo.18492023
title: R-programming

description: R is a powerful, open-source programming language and software environment primarily used for statistical computing, data analysis, and graphical representation. Developed by Ross Ihaka and Robert Gentleman in the early 1990s, R has become one of the most popular tools among statisticians, data scientists, researchers, and academicians. Its flexibility, extensive package ecosystem, and strong data visualization capabilities make it suitable for a wide range of applications.
DOI: 10.5281/zenodo.18478466
title: A Multi-Regional Single-Cell Atlas of the Huntington's Disease Brain

description: Single-cell atlas of multiple brain regions in HD patients.
DOI: 10.5281/zenodo.18478467
title: A Multi-Regional Single-Cell Atlas of the Huntington's Disease Brain

description: Single-cell atlas of multiple brain regions in HD patients.
DOI: 10.5281/zenodo.18492069
title: KAJIAN LINGKUNGAN PROYEK PEMBANGUNAN INFRASTRUKTUR JALAN DI SIDRAP - ANABUANA
DOI: 10.5281/zenodo.18492070
title: KAJIAN LINGKUNGAN PROYEK PEMBANGUNAN INFRASTRUKTUR JALAN DI SIDRAP - ANABUANA
DOI: 10.5281/zenodo.18492012
title: Bone Frac Dataset

description: About Dataset

Upper-Extremity Bone Fracture Segmentation & Detection (X-ray)

A comprehensive dataset of upper-extremity X-ray images was prepared for automated bone fracture localization and classification in computer vision research. The primary goal of this dataset is to support the development and benchmarking of algorithms for fracture detection and pixel-level fracture segmentation on radiographs.

The dataset includes X-ray images grouped into multiple fracture-related categories covering common anatomical regions of the upper limb. The provided classes (as defined in data.yaml) are:





Elbow Positive




Fingers Positive




Shoulder Fracture




Wrist Positive




Humerus




Forearm Fracture




Humerus Fracture



Each image is annotated with pixel-level segmentation masks (polygon-based), enabling precise localization of fracture regions. These mask annotations can also be used to derive bounding boxes, making the dataset suitable for both instance segmentation and object detection pipelines (e.g., Ultralytics/YOLO segmentation training and evaluation).

Dataset Highlights





Total images: 3,715





Train: 3,316 | Validation: 257 | Test: 142






Total annotated instances: 4,294




Annotation format: YOLO segmentation labels (normalized polygon coordinates)




Application scenarios: fracture region localization, multi-class fracture recognition, detection-to-segmentation cascades, and clinical decision-support prototypes.



By providing diverse fracture categories across upper-extremity regions, this dataset aims to facilitate robust model development for real-world radiographic fracture analysis, accelerating research in computer-aided diagnosis and improving clinical workflow efficiency.
DOI: 10.5281/zenodo.18492013
title: Bone Frac Dataset

description: About Dataset

Upper-Extremity Bone Fracture Segmentation & Detection (X-ray)

A comprehensive dataset of upper-extremity X-ray images was prepared for automated bone fracture localization and classification in computer vision research. The primary goal of this dataset is to support the development and benchmarking of algorithms for fracture detection and pixel-level fracture segmentation on radiographs.

The dataset includes X-ray images grouped into multiple fracture-related categories covering common anatomical regions of the upper limb. The provided classes (as defined in data.yaml) are:





Elbow Positive




Fingers Positive




Shoulder Fracture




Wrist Positive




Humerus




Forearm Fracture




Humerus Fracture



Each image is annotated with pixel-level segmentation masks (polygon-based), enabling precise localization of fracture regions. These mask annotations can also be used to derive bounding boxes, making the dataset suitable for both instance segmentation and object detection pipelines (e.g., Ultralytics/YOLO segmentation training and evaluation).

Dataset Highlights





Total images: 3,715





Train: 3,316 | Validation: 257 | Test: 142






Total annotated instances: 4,294




Annotation format: YOLO segmentation labels (normalized polygon coordinates)




Application scenarios: fracture region localization, multi-class fracture recognition, detection-to-segmentation cascades, and clinical decision-support prototypes.



By providing diverse fracture categories across upper-extremity regions, this dataset aims to facilitate robust model development for real-world radiographic fracture analysis, accelerating research in computer-aided diagnosis and improving clinical workflow efficiency.
DOI: 10.48544/b9b2234a-9b1d-49af-9766-f0e9a91369c6
title: Transformative regions for sustainability; the Utrecht case
DOI: 10.5281/zenodo.18492097
title: Linux

description: Linux is a free and open-source operating system based on the Unixarchitecture. It is widely used in servers, desktops, mobile devices, embedded systems, and supercomputers. Linux is known for its stability, security, flexibility, and community-driven development.
DOI: 10.5281/zenodo.18492098
title: Linux

description: Linux is a free and open-source operating system based on the Unixarchitecture. It is widely used in servers, desktops, mobile devices, embedded systems, and supercomputers. Linux is known for its stability, security, flexibility, and community-driven development.
DOI: 10.60964/bndu-z7qy-jp81
title: fMRI, MRS, pupillometry and behavioural data acquired after noradrenaline manipulation during learning: data and code

description: In humans, we apply a double-blind pharmacological manipulation immediately before  participants learn a novel cognitive map (day 1). On the same day (day 1), functional Magnetic Resonance Imaging (fMRI), Magnetic Resonance Spectroscopy, behavioural and pupillometry data are acquired, while additional behavioural measures of memory are acquired on day 5. Data include: group level neuroimaging data,  pupillometry data, behavioural data. Code includes: Matlab code for executing the task in PsychToolobox, Matlab code for data analysis.
DOI: 10.57760/sciencedb.36879
title: THE LOD OF UNTD-LIBS
title: THE LOD OF UNTD-LIBS

description: These data represent the raw spectral data used for the calibration curve.
description: These data represent the raw spectral data used for the calibration curve.