cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26564140.v6
title: Global surface ocean fCO2 from CSIR-ML6 (v2024)

description: The CSIR-ML6-v2024 is an update to the original CSIR-ML6 method by Gregor et al. (2019), extending the CO2 data product until 2023-12-15. The following changes have been made:SOCAT-v2024 is used;ERA5 reanalysis wind data and mean sea level pressure (MSLP) are used (instead of ERA-interim);The gas-exchange coefficient (kw) used, is appropriately scaled for the ERA5 wind product as recommended by Fay and Gregor et al. (2021);fCO2, the sea surface fugacity of CO2 is reported as per the Global Carbon Budget recommendation instead of pCO2, the sea surface partial pressure of CO2.<br><b>NETCDF FILE:</b>The dataset is stored in a single netCDF file and it mainly contains the following data variables:sfco2 = surface fugacity of CO2 for the ensemble average (in µatm). Therefgco2 = air-sea CO2 fluxes (in mol m-2 yr-1).area = is the total surface ocean area per 1º by 1º grid cell (in m2) - doubles as mask for the data.sol: is the solubility of CO2 in seawater, in units mol m−3 𝜇atm−1, calculated using the Weiss (1974) parameterization with EN4 salinity and OISST temperatures.kw: is the gas transfer velocity, calculated for wind speed (ERA-5) scaled independently to a 14-C bomb flux estimate of 16.5 cm/hr using the quadratic formulation by Wanninkhof (1992).𝑖𝑐𝑒: is the ice fraction, i.e. the open ocean fraction, to account for the seasonal ice cover in high latitudes.afco2: is the atmospheric fCO2 from NOAA's marine boundary layer product.<br><b>CITATION</b>Please cite the dataset as Djeutchouang et al. (2024), see the DOI: 10.6084/m9.figshare.26564140, as well as the original publication by Gregor et al. (2019), see the DOI: 10.5194/gmd-12-5113-2019.<br><b>HOST</b>CSIR, Southern Ocean Carbon – Climate Observatory (SOCCO)
DOI: 10.6084/m9.figshare.5417593.v1
title: Datasets for Loffler & Hoey Journal of Ecology

description: Data describing changes in Sargassum density and height after manipulations mimicking storm damage.<br><br>Also includes data on changes in number of holdfasts on rocks caged and exposed to herbivory over 16 weeks. <br>
DOI: 10.6084/m9.figshare.5669527.v1
title: MAP2 ELISA in K-diff PC12 cells

description: Assay for MAP2 levels after potassium-induced differentiation in PC12 cells silenced for NOS2 expression.
DOI: 10.17632/sdtjyys7gr
title: Growth phenotypes for the European flat oyster (Ostrea edulis)

description: Phenotypic data of four growth-related traits measured on 840 individuals. 6-month old oysters were placed in cages and deployed in the River Hamble (50.861° N, 1.312° W). After ~10 months of growth, the following traits were measured: body weight (BW), shell length (SL, the maximum distance between the anterior and posterior margins), shell height (SH, the maximum distance between the hinge to the furthermost edge), and shell width (SW, the maximum distance at the thickest part of the two shell valves). Shell measurements were taken with traceable digital callipers (0.02 mm precision). Weight was recorded in grams up to one decimal place. 

The data comprises a text file containing five tab-separated columns that indicate: Individual ID (1st column), BW measurement (in g) (2nd column), SH (in mm) (3rd column), SW (in mm) (4th column), and SL (in mm) (5th column).
DOI: 10.6084/m9.figshare.28254731.v1
title: Skin Lesion Analysis for Melanoma Detection

description: There are 10,015 training images and 1512 test images in ISIC 2018, including lesion categories of melanoma, melanocytic nevus, basal cell carcinoma, actinic keratosis, benign keratosis, dermatofibroma, and vascular regions. The ISIC 2019 dataset contains 25,531 training images and 8238 test images divided into nine categories, including melanoma, melanocytic nevus, basal cell carcinoma, actinic keratosis, and benign keratosis, dermatofibroma, vascular regions, and an unknown class. PH2 datasets aimed at melanoma diagnosis and ISIC datasets are biased towards melanocytic lesions. For detailed datasets please visit the site (http://www.fc.up.pt/addi/, accessed on 18 March 2022), and International Skin Imaging Collaboration (ISIC) 2018–2019 archives (http://isic-archive.com,
DOI: 10.15468/dl.mn9far
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Holtbyrnia innesi (Fowler, 1934)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((40.3006 -16.7147,40.6365 -16.1504,35.9648 -16.1504,35.9648 -19.5556,36.0796 -19.4498,36.663 -19.2358,37.5966 -18.1093,38.5624 -17.638,39.3949 -17.5133,39.577 -17.186,40.3006 -16.7147))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013432-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.12162597.v1
title: GTT-1-protein-066.dcd

description: Trajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.29166725.v1
title: Swiatek_et.al_Characteristics-of-Eib-chain-formation.zip

description: This dataset contains high-resolution epifluorescence microscopy images of E. coli cells, acquired on a Nikon Eclipse Ti2-U and Nikon AXR with NSPARC microscope. Images were prepared on agarose pads and imaged at 1000x magnification. Images are provided in raw and processed formats with full metadata and acquisition details.This dataset contains raw microscopic images related to the manuscript entitled <i>"Chain formation mediated by Escherichia coli immunoglobulin-binding proteins EibD and EibG depends on expression levels and localization of proteins."</i> The manuscript is currently under submission and has not yet been made publicly available. These images support the experimental findings presented in the manuscript.
DOI: 10.17632/fyc4tgsp3n
title: Modelling dataset of precipitation stable isotope in China, 1961-2022 (0.5°×0.5°)

description: We developed a highly effective fusion machine learning model (δ18O model with resulted RMSE = 2.66, R2 = 0.74), created a precipitation isotope dataset for 1961-2022.
DOI: 10.6084/m9.figshare.14368046.v1
title: MLST similarity matrix

description: Similarity matrix generated from a multiple-sequence alignment of the concatenated housekeeping-gene sequences of the 354 recognized sequence types of the <i>K. oxytoca </i>MLST scheme (as of 19 March 2021) against the corresponding regions of publicly available <i>K. oxytoca</i> complex and <i>Raoultella</i> spp. genomes (<i>n</i>=150).<br>
DOI: 10.6084/m9.figshare.22278283.v1
title: Nutritional management of type 2 diabetes

description: This data is a summary of dietray management of type 2 diabetes from the pre-diabetes stage to full blown type 2 diabetes with complications. It also presents the glycaemic indices of common foods. Data was collated from previous research in our laboratory and other related research from literature.
DOI: 10.6084/m9.figshare.25041584.v1
title: Main data files for Marshall et al. Almost 30,000 wild species: how much do we really know about legal wildlife trade?

description: Main Data for Marshall et al. Almost 30,000 wild species: how much do we really know about legal wildlife trade?, that aimed to describe the patterns present in 20 years of LEMIS wildlife import records.Summary: An analysis of 22 years of publicly accessible US wildlife trade data, of almost 30,000 species and over 2.85 billion individuals, provides insights into global trade trends and emphasises the importance of accessible trade data in biodiversity conservation efforts.Explanation of files and fields is in MainDataFileDetails.txt. Users of this data should be aware that the data still contains errors even after the correction of names and removal of outliers. Caution should be exercised when using and interpreting this trade dataset. The associated publication and supplementary discussion contains details on the limitations of this data. Further details on the cleaning of the pre-2014 data can be found Eskew, E. A., White, A. M., Ross, N., Smith, K. M., Smith, K. F., Rodríguez, J. P., ... & Daszak, P. (2020). United States wildlife and wildlife product imports from 2000–2014. Scientific Data, 7(1), 22. and Eskew, E. A., White, A. M., Ross, N., Smith, K. M., Smith, K. F., Rodríguez, J. P., ... & Daszak, P. (2019). United States LEMIS wildlife trade data curated by EcoHealth Alliance. <i>Zenodo Dataset</i>, <i>10</i>. https://doi.org/10.5281/ZENODO.3565869
DOI: 10.17632/vdtcp2yt9n
title: Hinglish Language Corpus: A Blend of Synthetically Generated and Manually Written Sentences for NLP Research

description: This dataset is a unique collection of Hinglish (a mix of Hindi and English) sentences, consisting of both synthetically generated text using various Large Language Models (LLMs) such as ChatGPT, Gemini AI, Claude, Groq, and Deep Seek, as well as manually written sentences. The dataset encompasses a diverse range of text sources, including meeting minutes, debates, articles, short essays, emails, letters, tweets, communications, and quotes, all composed in Hinglish.
The primary objective of this dataset is to support and facilitate research in the field of Natural Language Processing (NLP), particularly in the context of code-mixed languages like Hinglish. By providing a substantial corpus of Hinglish text from various domains and sources, this dataset aims to enable researchers to develop and test novel NLP techniques, models, and applications tailored to handle the unique challenges posed by code-mixed languages.
The synthetic portion of the dataset, generated using state-of-the-art LLMs, offers a large volume of diverse Hinglish text that can be used for training and fine-tuning NLP models. The manually written sentences, on the other hand, provide a valuable benchmark for evaluating the performance of these models on human-generated Hinglish text.
DOI: 10.6084/m9.figshare.26028760.v1
title: Transcriptome data of <i>Synechocystis </i>sp. PCC 6803 cultured with ammonium or nitrate as a nitrogen source

description: Supplementary Data S1: Transcriptome data of all genes in comparison between nitrate and ammonium conditions on 1-day and 4-day.Supplementary Data S2: Transcriptome data of the representative genes showing transcriptional differences between nitrate and ammonium conditions on 4-day.Supplementary Data S3: Transcriptome data of the genes for amino acid synthesis, in comparison between nitrate and ammonium conditions on 4-day.
DOI: 10.6084/m9.figshare.1394686.v2
title: EMG data sets for classification

description: These files contain category-labeled training and test data sets for EMG signal classification. The data sets are preprocessed. For more details, see articles below. Hand movement EMG data is published with: Hahne JM, Graimann B, M üller KR. Spatial filtering for robust myoelectric control. IEEE Transactions on Biomedical Engineering 59: 1436-1443, 2012. Finger lift EMG data published with: Kauppi JP, Hahne J, Müller KR, Hyvärinen A. Three-way analysis of spectrospatial electromyography data:<br>classi cation and interpretation, PLOS ONE, accepted, 2015. Please cite these articles if you use the provided EMG data sets in your research.
DOI: 10.6084/m9.figshare.28047047.v1
title: Final Publication AiiDA Archive

description: This dataset contains the molecular DFT calculations used in calculation of raman spectra, HOMO/LUMO energies, and salt pair association constants. All calculations were run with AiiDA version 2.5.1 and ORCA 5.0.4 on University of Colorado, Boulder's Alpine cluster. These calculations can be most easily viewed by loading in the aiida archive file following AiiDA's documentation: https://aiida.readthedocs.io/projects/aiida-core/en/stable/howto/data.htm<br><br>
DOI: 10.6084/m9.figshare.3550359.v1
title: Supplement 1. All data used in analyses of relationships among functional traits and demographic rates for trees and saplings from Barro Colorado Island, Panama.

description: File List Supplement_20100505.txt Description The Supplement_20100505.txt file is a tab-delimited ASCII file. The file contains nomenclature, wood specific gravity, seed mass, maximum height and leaf mass per area for each species. The file also contains average, 90th percentile and 95th percentile diameter growth rates and sample sizes for saplings and large trees of each species. The file also contains overall mortality rates and mortality rates of the slowest growing 50% and 25% of individuals in the previous census interval and sample sizes for saplings and large trees of each species. Missing values for functional traits and values that would be based on inadequate sample sizes for demographic variables are represented as "-99". Column definitions follow: 1 = GENUS$ - genus (truncated at 12 letters) 2 = SPECIES$ - species (truncated at 12 letters) 3 = FAMILY$ - family (truncated at 12 letters) 4 = WSG – Mean wood specific gravity (g cm-3) 5 = SEEDMASS – Mean seed dry mass (g) 6 = HEIGHT – Mean height of six largest individuals (m) 7 = LMA – Mean leaf mass per area determined from leaf discs for the six smallest individuals of each species (g m-2) 8 = RGR95SAP – 95th percentile relative growth rate for saplings (cm cm-1 yr-1) 9 = RGR90SAP – 90th percentile relative growth rate for saplings (cm cm-1 yr-1) 10 = RGRAVGSAP – Mean relative growth rate for saplings (cm cm-1 yr-1) 11 = N_RGRSAP – sample size to determine relative growth rates for saplings 12 = MRT25SAP – Mortality rate for the 25% of saplings with the slowest growth rates in the previous census (% 5 yr-1) 13 = MRT50SAP – Mortality rate for the 50% of saplings with the slowest growth rates in the previous census (% 5 yr-1) 14 = MRTALLSAP – Mortality rate for all saplings (% 5 yr-1) 15 = N_MRTSAP – sample size to determine mortality rates for saplings 16 = RGR95TRE – 95th percentile relative growth rate for large trees (cm cm-1 yr-1) 17 = RGR90TRE – 90th percentile relative growth rate for large trees (cm cm-1 yr-1) 18 = RGRAVGTRE – Mean relative growth rate for large trees (cm cm-1 yr-1) 19 = N_RGRTRE – sample size to determine relative growth rates for large trees 20 = MRT25TRE – Mortality rate for the 25% of large trees with the slowest growth rates in the previous census (% 5 yr-1) 21 = MRT50TRE – Mortality rate for the 50% of large trees with the slowest growth rates in the previous census (% 5 yr-1) 22 = MRTALLTRE – Mortality rate for all large trees (% 5 yr-1) 23 = N_MRTTRE – sample size to determine mortality rates for large trees Check sum values are: For the first row, there are 9 missing values and Checksum = 4459.035 For the final row, there are zero missing values and Checksum = 1501.341 For the fourth column, there are 5 missing values and Checksum = 74.980 For the seventh column, there is one missing value and Checksum = 7425.420
DOI: 10.6084/m9.figshare.5129299.v1
title: Supplementary Material for: Decrease of Hyperintense Vessels on Fluid-Attenuated Inversion Recovery Predicts Good Outcome in t-PA Patients

description: <b><i>Background and Purpose:</i></b> Hyperintense vessels (HV) detected on fluid-attenuated inversion recovery (FLAIR) in patients with acute ischemic stroke (AIS) indicate cerebral hypoperfusion. However, the clinical meaning of changes in HV is yet to be clarified. Here, we investigated serial changes to HV in patients with AIS who received tissue plasminogen activator (t-PA) therapy. <b><i>Methods:</i></b> We studied t-PA patients presenting with HV on FLAIR in the middle cerebral artery territory. Patients underwent brain MRI 1 h before and after t-PA infusion. HV scores (range 1-7) were evaluated according to Alberta Stroke Program Early Computed Tomography Score territories, and then by subtracting HV scores at 1 h after t-PA infusion from those on admission, with a result of &gt;1 defined as decrease in HV score (DHV). Patients were divided into 2 groups based on the presence or absence of DHV. Multivariate logistic regression analysis was conducted to identify variables independently associated with good outcome (modified Rankin Scale score at 90 days after stroke onset of 0-1). <b><i>Results:</i></b> A total of 118 consecutive patients were enrolled (73 men; mean age 76 ± 9.7; median initial National Institutes of Health Stroke Scale (NIHSS) 13; median initial HV score 5), of whom 52 (44%) had DHV. Patients with DHV showed a significantly lower NIHSS time course (p &lt; 0.001) and significantly smaller infarct volume time course (p &lt; 0.001) compared to those without DHV. Multivariate analysis showed that DHV was independently associated with good outcome (OR 3.89; 95% CI 1.55-9.77; p &lt; 0.01). The sensitivity and specificity of DHV for good outcome were 70 and 68%, respectively. <b><i>Conclusion:</i></b> A DHV on FLAIR predicts good outcome in patients receiving t-PA.
DOI: 10.6084/m9.figshare.22654945.v1
title: An open dataset for intelligent recognition and classification of abnormal condition in longwall mining

description: This work developed image dataset of underground longwall mining face (DsLMF+), which consists of 138004 images with annotation 6 categories of mine personnel, hydraulic support guard plate, large coal, towline, miners’ behaviour and mine safety helmet. All the labels of dataset are publicly available in YOLO format and COCO format.The dataset aims to support further research and advancement of the intelligent identification and classification of abnormal conditions for underground mining.
DOI: 10.6084/m9.figshare.22795997.v1
title: <strong>Salgado et al. (2023). </strong>"<strong>Protected land enhances the survival of native aquatic macrophytes and limits invasive species spread in the Panama Canal" </strong>

description: Macrophyte and plant macrofossil data collected in Gatun Lake, Panama Canal.
DOI: 10.6084/m9.figshare.3547371.v1
title: Appendix B. A figure showing GLS-derived penguin locations and sea ice concentration and extent, 2003–2005.

description: A figure showing GLS-derived penguin locations and sea ice concentration and extent, 2003–2005.
DOI: 10.6084/m9.figshare.14379059.v1
title: PERMITMW.csv

description: The data set contains data on the Housing Start and Building Permit of the US National level and the four census regions. They all are in csv format.
DOI: 10.6084/m9.figshare.21550599.v1
title: Evaluating the effect of digital technology on the learning of orthodontic cephalometric measurement

description: This study investigated the effect of applying the digital technology (the Dolphin software®) in cephalometric learning, demonstrating better effect and acceptance of this technology.
DOI: 10.6084/m9.figshare.25449847.v2
title: An empirical test of scale-dependence of β-diversity in a large temperate forest region

description: Data and code from: "An empirical test of scale-dependence of β-diversity in a large temperate forest region".
DOI: 10.6084/m9.figshare.28804583.v1
title: a 4.53 A resolution density map in Fig. 2a and a 3.23 A resolution map in Fig. 2b

description: A 4-nt G-C mismatched substrate yields a RAD51 mini-filament density map at 4.53 Å resolution. The density shows an unbent dsDNA interacting with two adjoining NTDs of the presynaptic filament, presenting the initial recruitment state of homologous dsDNA (Figure 2a). Increasing the mismatch to 8-nt yielded another density map at 3.23Å (Figure 2b), where dsDNA displayed pronounced curvature, interacting with four adjoining NTDs (N+1, N+2, N+3, and N+4). These two structures represent the recruitment of homologous dsDNA via nonspecific interactions of NTDs.
DOI: 10.17632/bvncmx7vvb
title: Freshwater biodiversity risk exposure of Natura 2000 sites to industrial pollution

description: Data of the background study. 

Title&gt; Freshwater biodiversity risk exposure of Natura 2000 sites to industrial pollution

published by the Environmental Impact Assessment Review, 2025
https://www.sciencedirect.com/science/article/pii/S0195925524003846
Cite this article
Szilárd Erhart, Bálint Menyhért, Kornél Erhart, Andrea Hagyó,
Freshwater biodiversity risk exposure of Natura 2000 sites to industrial pollution,
Environmental Impact Assessment Review,
Volume 113,
2025,
107797,
ISSN 0195-9255,
https://doi.org/10.1016/j.eiar.2024.107797.
DOI: 10.17632/rbx3ybd5zx
title: Data for Dual-Probe Transcranial Full-waveform Inversion: a Brain Phantom Feasibility Study

description: This dataset contains ultrasound computed tomography (USCT) data for the article "Dual-Probe Transcranial Full-waveform Inversion: a Brain Phantom Feasibility Study" (Robins et al., 2023). This study investigated the application of full-waveform inversion (FWI) for performing transcranial brain imaging by applying FWI to reconstruct a brain-mimicking phantom. Imaging datasets were acquired using a custom dual-probe acquisition system which consisted of a large water tank (0.7 x 0.6 x 0.6 m^3) and a pair of P4-1 cardiac probes rotated about an imaging target to form a ring array (see Experimental_Imaging_Setup.png). All datasets were acquired using the same imaging sequence which involved a ring array of 16 probe positions (see Dual_Probe_Ring_Array.png). Estimated sets of transducer element positions (elementList.txt) and source signals (signal_filtered.mat, seen plotted in Source_Signal_Filtered.png) have been optimised for running FWI to image the phantom. All transducer positions and source signals were calibrated using a watershot dataset, which was acquired by performing the scan without the phantom being present.

Paper DOI: https://doi.org/10.1016/j.ultrasmedbio.2023.06.001

Imaging sequence:
 o Imaging was performed by a pair of P4-1 cardiac probes (ATL, 96 elements per array) .
 o The ring array consisted of 3072 element positions (1536 over 16 Probe 01 positions, 1536 over 16 Probe 02 positions).
 o 384 source elements.
 o Sampling frequency (Fs) = 22.727 MHz.
 o [Number of time samples (Nt), No. of Traces] = [3328, 442368].
 o Source-receiver pairings for all 442368 traces is given by elementRelas.txt.

These imaging experiments include:
(1) 01_Experimental_USCT_Brain.mat:
 o USCT data from imaging the 2.5D PVA brain phantom.

(2) 02_Synthetic_USCT_Brain.mat:
 o USCT data from synthetic imaging the 2.5D numerical brain phantom.
 o The true numerical brain phantom for this imaging problem is given in TrueVp.mat.

(3) 03_Experimental_USCT_WaterShot.mat:
 o USCT data from imaging just water.
 
Additional files include:
elementList.txt: Calibrated transducer element positions, [Element ID, x,y,z - positions]
elementRelas.txt: The source-receiver transducer element IDs for all traces [Trace ID, Source ID, Receiver ID]
signal_filtered.mat: 384 source wavelets for all source elements (filtered by *)
TrueVp.mat: True velocity model of the numerical brain phantom (dx = 0.186 mm, dimensions = [957, 958])

* To filter USCT data 'dataset' to match the source signals, apply the following matlab solution (or equivalent):
Fs = 22.727e06;
N = 100;
F01 = 0.4e06;
F02 = 2.0e06;
[Hd a] = fir1(N,[F01, F02]/(Fs/2)); 
dataset_filtered = filtfilt(Hd,a,dataset);
DOI: 10.6084/m9.figshare.3847086.v12
title: Phase Transfer Entropy in Matlab

description: Script to compute phase transfer entropy (PTE) in Matlab. <br>This function is free software, distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY.It is designed and distributed for research purposes only. The authors accept no responsibility for its use.
DOI: 10.6084/m9.figshare.13070675.v1
title: Plant and herbivore datasets and R scripts

description: Here, we provide the plant and herbivore datasets and R scripts used in the meta-analysis.<br>
DOI: 10.6084/m9.figshare.13126847.v1
title: Data For "Spatially and Temporally Coherent Reconstruction of Tropospheric NO2 over China combining OMI and GOME-2B measurements"

description: Reconstructed Data For "Spatially and Temporally Coherent Reconstruction of Tropospheric NO2 over China combining OMI and GOME-2B measurements", including OMI QA4ECV, RECON-1, and RECON-2 in "OMI-RECON.nc".
DOI: 10.17632/4xdsnd2tp7
title: Formal Verification Book errata

description: FV book errata