cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25318/4310002201-eng
title:  Mobility of immigrant taxfilers by census metropolitan areas and tax year

description: Immigrant mobility, by age and sex, knowledge of official languages at admission, pre-admission experience, immigrant admission category, admission year and tax year, for Canada, provinces and census metropolitan areas.
DOI: 10.3334/cdiac/00001_v2017
title: Global, Regional, and National Fossil-Fuel CO2 Emissions (1751 - 2014) (V. 2017)

description: Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). Further details on the contents and processing of the historical energy statistics are provided in Andres et al. (1999). The 1950 to present CO2 emission estimates are derived primarily from energy statistics published by the United Nations (2017), using the methods of Marland and Rotty (1984). The energy statistics were compiled primarily from annual questionnaires distributed by the U.N. Statistical Office and supplemented by official national statistical publications. As stated in the introduction of the Statistical Yearbook, "in a few cases, official sources are supplemented by other sources and estimates, where these have been subjected to professional scrutiny and debate and are consistent with other independent sources." Data from the U.S. Department of Interior's Geological Survey (USGS 2017) were used to estimate CO2 emitted during cement production. Values for emissions from gas flaring were derived primarily from U.N. data but were supplemented with data from the U.S. Department of Energy's Energy Information Administration (1994), Rotty (1974), and data provided by G. Marland. Greater details about these methods are provided in Marland and Rotty (1984), Boden et al. (1995), and Andres et al. (1999).
DOI: 10.34892/72x9-rt61
title: Global Distribution of Cold-water Corals

description: This dataset shows of the global distribution of cold-water corals. Occurrence records are given for the subclass Octocorallia (octocorals; also known as Alcyonaria) and four Orders (in Class Anthozoa): Scleractinia (reef-forming corals), Antipatharia (black corals), Zoanthidae (encrusting or button polyps), and Pennatulacea (sea pens). Occurrence records are also available for the order sub-Order Filifera (lace corals) in Class Hydrozoa.
DOI: 10.5067/0jrlvl8yv2y4
title: MERRA-2 tavgM_2d_flx_Nx: 2d,Monthly mean,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics V5.12.4
DOI: 10.5067/8s35xf81c28f
title: MERRA-2 tavgM_2d_lnd_Nx: 2d,Monthly mean,Time-Averaged,Single-Level,Assimilation,Land Surface Diagnostics V5.12.4
DOI: 10.5067/99ftcyyylaq0
title: Global Seasonal-Snow Classification, Version 1
DOI: 10.5281/zenodo.13891286
title: Enhanced Majorana stability in a three-site Kitaev chain

description: This repository contains all the raw data and the code used to generate the figures of the article "Enhanced Majorana stability in a three-site Kitaev chain".A "kitaev3_simulations.ipynb" notebook generates all the theory simulations and a "kitaev3_figures.ipynb" notebook generates all the figures. To be able to run them you can install anaconda, create a fresh environment and install the proplot, jupyterlab, xarray, netcdf4, tqdm python packages as in the following example:

conda create -n kitaev3 python=3.10
conda activate kitaev3
conda install proplot
conda install jupyterlab
conda install xarray netcdf4
conda install tqdm

Alternatively, you can install the environment from the env.yml file we provide and run the notebooks as follows:

conda env create -f env.yml
conda activate kitaev3
jupyter lab

In addition, in "raw_data > databases-and-notebooks" we share the entire QCoDeS databases from which the measurements shown in the manuscript are extracted. They contain the tuning of our device's quantum dots, the optimization of the tunneling barriers and much more. We include our measurement logs in PDF form for easy browsing.
DOI: 10.5281/zenodo.14614029
title: Formation and composition of the Earth's Hadean protocrust

description: This directory contains data and code to accompany the paper "Formation and composition of the Earth’s Hadean protocrust" by Simon Turner, Bernard Wood, Tim Johnson, Craig O’Neill and Bernard Bourdon, to be published in Nature, 2025.
DOI: 10.5281/zenodo.14760926
title: Dataset of "Ultrafast momentum-resolved visualization of the interplay between phonon-mediated scattering and plasmons in graphite"

description: UED_RAW_sorted: During the experiment, we scanned along the delay stage to vary the time delay between the pump and the probe. Each h5 file contains two diffraction patterns (pump on and pump off) of one second of exposure at a given delay.  We merged h5 file with the same delay with the home-made software 'data_explorer' in https://github.com/remiclaude/UED_interface and extract a pickle file containing the diffraction patterns along the delay for imgON (with the pump) and imgOFF (without the pump) and the metadata. - UED_PROCESSED: The jupyter notebook 'treat_pickle.ipynb' in https://github.com/remiclaude/UED_processing used the pickles files in folder 'RAW_sorted' and process them: removes hot pixel, shift images to keep the unscattered beam at the same position, and average the diffraction map along the symmetry axis.


 

The python files to process and create the figures shown in the publication are shown in the section "related work"
DOI: 10.5281/zenodo.14853285
title: Intersecting Identities in AI Imagery: A Text-to-Image Dataset on Transgender and Neurodivergent Representations

description: This dataset contains a set of images generated by a popular text-to-image AI model (DeepAI Image Generator) using prompts that reference transgender and neurodivergent identities—alone and in combination with terms like “cisgender” and “neurotypical.” The images highlight how AI-driven content generation can produce starkly different (and sometimes problematic) depictions based on the input prompt. In particular, the dataset demonstrates:



Varying levels of stylization and sexualization for transgender vs. cisgender prompts.

Surreal or medicalized depictions when the model interprets terms like “neurodivergent.”

Content filtering restrictions that block or label certain identity keywords (e.g., “transsexual,” “fag”) as unsafe.


Each image is labeled with the exact prompt that produced it, allowing researchers, practitioners, and educators to explore how generative AI systems respond differently to intersecting identities. By presenting these outputs in context, the dataset serves as a resource for studying algorithmic bias, prompting more inclusive data curation, and refining moderation policies to reduce harm to marginalized communities.

This analysis was developed with the assistance of ChatGPT 1.0.
DOI: 10.5281/zenodo.14861092
title: FaciaVox a Multimodal Biometric Dataset

description: The FaciaVox dataset is an extensive multimodal biometric resource designed to enable in-depth exploration of face-image and voice recording research areas in both masked and unmasked scenarios.

Features of the Dataset:

1. Multimodal Data: A total of 1,800 face images (JPG) and 6,000 audio recordings (WAV) were collected, enabling cross-domain analysis of visual and auditory biometrics.

2. Participants were categorized into four age groups for structured labeling:Label 1: Under 16 yearsLabel 2: 16 to less than 31 yearsLabel 3: 31 to less than 46 yearsLabel 4: 46 years and above

3. Sibling Data: Some participants are siblings, adding a challenging layer for speaker identification and facial recognition tasks due to genetic similarities in vocal and facial features. Sibling relationships are documented in the accompanying "FaciaVox List" data file.

4. Standardized Filenames: The dataset uses a consistent, intuitive naming convention for both facial images and voice recordings. Each filename includes:Type (F: Face Image, V: Voice Recording)Participant ID (e.g., sub001)Mask Type (e.g., a: unmasked, b: disposable mask, etc.)Zoom Level or Sentence ID (e.g., 1x, 3x, 5x for images or specific sentence identifier {01, 02, 03, ..., 10} for recordings)

5. Diverse Demographics: 19 different countries.

6. A challenging face recognition problem involving reflective mask shields and severe lighting conditions.

7. Each participant uttered 7 English statements and 3 Arabic statements, regardless of their native language. This adds a challenge for speaker identification. 

Research Applications

FaciaVox is a versatile dataset supporting a wide range of research domains, including but not limited to:•    Speaker Identification (SI) and Face Recognition (FR): Evaluating biometric systems under varying conditions.•    Impact of Masks on Biometrics: Investigating how different facial coverings affect recognition performance.•    Language Impact on SI: Exploring the effects of native and non-native speech on speaker identification.•    Age and Gender Estimation: Inferring demographic information from voice and facial features.•    Race and Ethnicity Matching: Studying biometrics across diverse populations.•    Synthetic Voice and Deepfake Detection: Detecting cloned or generated speech.•    Cross-Domain Biometric Fusion: Combining facial and vocal data for robust authentication.•    Speech Intelligibility: Assessing how masks influence speech clarity.•    Image Inpainting: Reconstructing occluded facial regions for improved recognition.

Researchers can use the facial images and voice recordings independently or in combination to explore multimodal biometric systems. The standardized filenames and accompanying metadata make it easy to align visual and auditory data for cross-domain analyses. Sibling relationships and demographic labels add depth for tasks such as familial voice recognition, demographic profiling, and model bias evaluation.
DOI: 10.5281/zenodo.14916067
title: Supplementary Data Tables to "Water abundance in the lunar farside mantle"
DOI: 10.5281/zenodo.4686669
title: Global soil respiration and its components dataset derived from the Random Forest method

description: We generated a globally gridded dataset of total soil respiration, heterotrophic soil respiration and autotrophic soil respiration during 1982-2012 using the Random Forest method, the spatial resolution of the dataset is 0.5 deg.
DOI: 10.5281/zenodo.6894273
title: Global Mangrove Watch (1996 - 2020) Version 3.0 Dataset

description: This study has used L-band Synthetic Aperture Radar (SAR) global mosaic datasets from the Japan Aerospace Exploration Agency (JAXA) for 11 epochs from 1996 to 2020 to develop a long-term time-series of global mangrove extent and change. The study used a map-to-image approach to change detection where the baseline map (GMW v2.5) was updated using thresholding and a contextual mangrove change mask. This approach was applied between all image-date pairs producing 10 maps for each epoch, which were summarised to produce the global mangrove time-series. The resulting mangrove extent maps had an estimated accuracy of 87.4 % (95th conf. int.: 86.2 - 88.6 %), although the accuracies of the individual gain and loss change classes were lower at 58.1 % (52.4 - 63.9 %) and 60.6 % (56.1 - 64.8 %), respectively. Sources of error included a mis-registration in the SAR mosaic datasets, which could only be partially corrected for, but also confusion in fragmented areas of mangroves, such as around aquaculture ponds. Overall, 152,604 km<sup>2</sup> (133,996 - 176,910) of mangroves were identified for 1996, with this decreasing by -5,245 km<sup>2</sup> (-13,587 - 3686) resulting in a total extent of 147,359 km<sup>2</sup> (127,925 - 168,895) in 2020, and representing an estimated loss of 3.4 % over the 24-year time period. The Global Mangrove Watch Version 3.0 represents the most comprehensive record of global mangrove change achieved to date and is expected to support a wide range of activities, including the ongoing monitoring of the global coastal environment, defining and assessments of progress towards conservation targets, protected area planning and risk assessments of mangrove ecosystems worldwide. The paper which goes along with this dataset is available at the following reference: Bunting, P.; Rosenqvist, A.; Hilarides, L.; Lucas, R.M.; Thomas, T.; Tadono, T.; Worthington, T.A.; Spalding, M.; Murray, N.J.; Rebelo, L-M. Global Mangrove Extent Change 1996 – 2020: Global Mangrove Watch Version 3.0. Remote Sensing. 2022
DOI: 10.5281/zenodo.7693825
title: High-resolution spatial multi-omics datasets

description: Supplementary raw data. The raw microscopy data are not uploaded owing to their large size (6.8 Tb), but are available upon reasonable request (Long Cai: lcai@caltech.edu, Yodai Takei: ytakei@caltech.edu). These supplementary data contain additional files for RNA seqFISH+, DNA seqFISH+, and sequential immunofluorescence from cell culture and adult mouse cerebellum experiments. DNA seqFISH+ datasets (provided as a tar.gz folder for each replicate): Super-resolved DNA spot locations by DNA seqFISH+ along with sequential immunofluorescence intensity at the rounded voxel location. RNA seqFISH datasets (provided as a zip folder): Super-resolved mRNA or intron spot locations. Sequential immunofluorescence table (provided as a csv file): Mean voxel intensity of each immunofluorescence marker per nucleus for the adult mouse cerebellum datasets. Note that voxel sizes are 103 nm for x and y, and 250 nm for z in our experimental setting. Please find the uploaded readme.txt file for more details.
DOI: 10.5281/zenodo.7933597
title: Data and Code for 'Supercurrent through a single transverse mode in nanowire Josephson junctions'

description: This repository contains data, code, and other materials for the ''Supercurrent through a single transverse mode in nanowire Josephson junctions'' <strong>Guideline:</strong> Extract data and simulation results and python scripts in the same address. <strong>Files:</strong> Raw_data_and_simulation_results.zip: Full original raw data, measurement, and simulation results (plotted extended data beyond paper figures) zipped for different cooldowns. Figure.zip: Paper figures, raw figure data, and data-processing code for paper figures. Python script for generating the main text figure.zip: Paper figures, raw figure data, and data-processing code for paper main text figures. Python script for generating the supplementary figure.zip: Paper figures, raw figure data, and data-processing code for paper supplementary figures. Tin_QPC_paper_simulation_code:Code used to reproduce simulation results in the paper. Tin_QPC_log: Full measurement log and ppt summary Data formats MTX: A simple 2D/3D matrix format developed for Spyview. DAT: Plain-text tabular data. DAT and MTX files can be plotted with Spyview, qtplot (a portable version for Windows can be downloaded here), and Jupyter notebooks in ZIP files or here. SET: Instrument settings. PY: Measurement scripts. IPYNB: Jupyter notebooks with code and figures. They can be previewed on this page.
DOI: 10.5904/gtng-glacreg-2023-07
title: GTN-G Glacier Regions (GlacReg)

description: Glacier regions are useful for regional assessments of glacier change and other parameters (WGMS 1989, Dyurgerov 2002, Radić and Hock 2010, Pfeffer et al. 2014). This dataset defines 20 first-order glacier regions and more than 90 second-order regions encompassing all of earth’s glaciers. The GTN-G Glacier Regions dataset is a joint set of regions recommended by the Global Terrestrial Network for Glaciers (GTN-G) Advisory Board, the Global Land Ice Measurements from Space initiative (GLIMS), the Randolph Glacier Inventory (RGI) Working Group of the International Association of Cryospheric Sciences (IACS), and the World Glacier Monitoring Service (WGMS). These glacier regions are implemented in the Randolph Glacier Inventory (RGI; RGI Consortium 2023) and used for regional aggregation of glacier data, such as from the Glacier Thickness Database (GlaThiDa; GlaThiDa Consortium 2020) and from the WGMS Fluctuations of Glaciers database (FoG; WGMS 2021, 2022).
DOI: 10.60520/ieda/113704
title: Electron Microprobe Analyzer (EMPA) dataset for serpentine minerals in serpentinites

description: EMPA analyses of minerals from a suite of serpentinites from Guatemala Suture Zone.
description: Harlow, G.E., Flores, K.E., Martin, C., Sorenson, S.S. (accepted) Serpentinites of the Guatemala Suture Zone: Varieties, origin, and compositional modifications. American Journal of Science
DOI: 10.6073/pasta/8dbd29c8c22f3295bbc5d3819fb51d00
title: Six decades (1959-2022) of water quality in the upper San Francisco Estuary: an integrated database of 16 discrete monitoring surveys in the Sacramento San Joaquin Delta, Suisun Bay, Suisun Marsh, and San Francisco Bay

description: The upper San Francisco Estuary (SFE) is simultaneously a central
 hub of water delivery in California and home to commercially
 important and endangered fishes, such as Chinook Salmon, Green
 Sturgeon, and Delta and Longfin Smelt. Extensive ecological
 monitoring has been conducted for over 50 years, mainly under the
 auspices of the Interagency Ecological Program for the San Francisco
 Estuary (https://iep.ca.gov/). We integrated water quality data from
 16 boat-based long-term monitoring surveys in the upper SFE. This
 integrated dataset includes measurements of temperature (surface and
 bottom), conductivity (surface), salinity (surface), Secchi depth,
 qualitative concentration of the toxic alga
 Microcystis (surface), Chlorophyll-a
 concentration (surface), nutrients (surface), and other parameters
 from 1959 - 2022. The component surveys range in sampling frequency
 from thrice weekly to monthly and range in duration from 5 – 60
 years. Most component surveys sample at fixed stations, but the
 Enhanced Delta Smelt Monitoring survey uses random sites and some
 stations (with “EZ” in the station name) of the Environmental
 Monitoring Program follow the salinity field. It is highly
 recommended to inspect the documentation of the component surveys
 for more information on their methods.
DOI: 10.6084/m9.figshare.28070153
title: Supplementary Material for: New insights from long-term clinical use of ctDNA-based minimal residual disease monitoring in translocation-associated sarcomas

description: Introduction: Assessment of circulating tumor DNA (ctDNA) as means to monitor disease activity in translocation-associated tumors has become very popular in clinical practice. However, there are still few studies on its clinical application to date. Our study evaluates the clinical applicability of ctDNA as a biomarker for monitoring minimal residual disease (MRD) in patients with translocation-associated sarcomas.
Methods: In this retrospective study, we correlated 285 ctDNA samples from 34 patients diagnosed with translocation-associated sarcoma with the clinical course and images. Blood samples were collected at multiple time points during follow-up (median: 97 weeks, range: 7–398). 
Results: We discovered a significant association between ctDNA levels and the clinical course of the disease, particularly noting differences between patients in remission or with progressive disease (p = 0.001). Furthermore, although we noted that ctDNA levels remained undetectable in a few cases of unilocular recurrence (n = 3), they were consistently higher in patients with multilocular recurrence (n = 14; p = 0.008). 
Conclusion: Monitoring ctDNA levels provides highly specific, additional information enabling early recurrence detection in patients with translocation-associated sarcomas during the follow-up and can be integrated into clinical practice. However, MRD monitoring by ctDNA quantification alone does not allow the reliably detection of 100% of unilocular recurrences and should be complemented by the use of conventional imaging techniques.
DOI: 10.6084/m9.figshare.28184069.v1
title: transitions data (1).xlsx

description: This study assessed the usefulness of incorporating entrepreneurship course into final year students courses. The aim of many Ghanaian Universities is to equip about to graduate students some level of entrepreneurial awareness to elicit some entrepreneurship after graduation. However, the findings revealed that though most of the participants were happy with the course they received at their respective institutions, but they were not ready to take on entrepreneurship activities but rather prefer obtaining a job within the formal sector making the intentions of the universities not realized. The study therefore concluded that universities should take a second look at the entrepreneurship course and re-strategize if the usefulness of the course is to be realized.
DOI: 10.6084/m9.figshare.28533335.v1
title: Datasheet.xlsx

description: <b>Spectrum of Lower Respiratory Tract Infections and antimicrobial resistance pattern in head and neck cancer patients undergoing chemoradiation</b>
DOI: 10.6084/m9.figshare.28566698.v1
title: Data from: Patterns of water-extractable soil organic matter in the US Great Plains: Insights from the Haas Soil Archive

description: Carbon (C) and nitrogen (N) extracted from soil with water are associated with available plant nutrients and microbial activity but information about how they have changed over time in the U.S Great Plains is sparse. We used cool (20 oC) and hot (80 oC) water extracts from historic (1947) and current (2018) soil samples collected at Moccasin, MT, Akron, CO, and Big Spring, TX to evaluate changes to extractable C and N and optical properties after 71 years of dryland cropping. Together, water extracts and optical methods can produce insights into long-term changes in labile soil organic matter while conserving physical samples of archived soil.