cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/d42f8294c71b7b3b00f06e4ca4bfebd0
title: Monthly small nekton samplings collected in the Plum Island Estuary, years 2012-2014
DOI: 10.6073/pasta/d44812e09f1126713849b37ef4c985fe
title: Monthly small nekton samplings collected in the Plum Island Estuary in 1993
DOI: 10.6073/pasta/d6a824bda2099c28af26c8886ce21db6
title: Monthly small nekton samplings collected in the Plum Island Estuary in 2002
DOI: 10.6084/m9.figshare.28191398
title: Enhanced diagnosis of multi-drug-resistant microbes using group association modeling and machine learning

description: This repository contains the supplemental data files from the analysis of Group Association Modeling (GAM) applied to M. tuberculosis (Mtb) and S. aureus. The data provides insights into significant variants, genes, and SNPs, along with results from Linear Mixed Model (LMM) analyses.
 
 
 
Contents: 
 Significant variants identified for all GAM Mtb groups (SF2). 
 
Results of LMM analysis for Mtb (SF3).

Significant SNPs identified for all GAM S. aureus groups (SF4).

Significant genes identified for all GAM S. aureus groups (SF5).

GAM significant variants for S. aureus (SF6).

Results of LMM analysis for S. aureus SNPs (SF7).

Results of LMM analysis for S. aureus genes (SF8).

Group-specific significance thresholds used in the GAM analysis (SF9). 

Large files (Data.zip) for code on Zenodo (https://doi.org/10.5281/zenodo.14975407)
DOI: 10.7281/t1ms3qn7
title: Serial block face scanning electron microscopy image stack of larval zebrafish olfactory bulb
DOI: 10.13127/stromboli/gnss_1997-2022
title: Stromboli GNSS data from 1997 to 2022

description: The dataset contains the GNSS data recorded by the ground deformations monitoring network of Stromboli volcano from 1997 to 2022. The network configuration is shown in Figure. In 1997, the first three stations,  Punta Labronzo (SPLB), Punta Lena (SPLN) and Timpone del Fuoco (STDF), were installed. The Trimble 4000 receivers collected data only for a few hours/day, due to limitations in power supply. Since 2003, when the receivers were replaced with Leica 500 model, the stations have collected data 24 hours/day. In 2003, a new station was set up in San Vincenzo COA (Centro Operativo Avanzato, SVIN). Since 2003, the data have been transmitted in real time at high frequency (1Hz), to the INGV, Osservatorio Etneo, in Catania, through WiFi connections. In this dataset, the data are resampled at 30 seconds.
description: GNSS observation data files are stored by GNSS station/day in the Hatanaka-compressed Receiver Independent Exchange (RINEX, Version 3.01 and 3.05). The Hatanaka-compressed format (Hatanaka, 2008) is used to reduce the file size of the RINEX data files. 
The station coordinates are reported in Table 1 and the station.info file contains receiver, antenna and occupation-time information for each site.

The naming convention for the archived files is as follows:
STRYYYY: contains the RINEX files for the year YYYY and all the stations of Stromboli (STR)
SITESTRYYYY: contains the RINEX files for the year YYYY and the SITE station  (SPLB, SPLN, STDF or SVIN) 
When the maximum file size is exceeded, the folder is divided into _a and _b

References
Hatanaka, Y. (2008), A Compression Format and Tools for GNSS Observation Data, Bulletin of the Geographical Survey Institute, 55, 21-30
DOI: 10.14278/rodare.3640
title: Data publication: Short wavelength limit of the dynamic Matsubara local field correction

description: This repository contains all PIMC data presented in the publication "Short wavelength limit of the dynamic Matsubara local field correction", with the same units and conventions as in the figures.
DOI: 10.15121/1777912
title: Utah FORGE: Well 16A(78)-32 Logs

description: This dataset contains all well logs from Utah FORGE well 16A(78)-32. This includes the mud log, Sanvean Technologies logs, and Schlumberger logs. Please see the file descriptions below for information about each log.
DOI: 10.15468/dl.5wk4ue
title: Occurrence Download

description: A dataset containing 48208 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-104.76009 -61.06322,-21.89051 -61.06322,-21.89051 23.89008,-104.76009 23.89008,-104.76009 -61.06322))",
 "HasGeospatialIssue is false",
 "TaxonKey is Curimatidae"
 ]
}

 The dataset includes 48208 records from 162 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0272413-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/t77vw2s3tn.1
title: Research data for the manuscript (2024JD042568) submitted to JGR: Atmospheres in 2024

description: This dataset is used in the manuscript submitted to JGR: Atmospheres in 2024 by Men Xia. Field observation data of reactive chlorine species alongside related measurements is recorded here.
DOI: 10.18712/nsd-nsd0195-1-v1
title: Family and Occupation Survey, 1988, female sample

description: Family- and Occupation Survey 1988, female sample, shows the change in fertility, marriage and cohabitation. It is a follow-up study of the Fertility Survey 1977, but has a somewhat wider framework. Together, the two surveys give extensive knowledge of fertility and marriage patterns. This makes it possible to describe and analyze important aspects of the family formation process from the first steps and up to the family situation at the beginning of the 40-year age. The survey in 1988 placed great emphasis on obtaining retrospective educational and occupational histories. This is the female sample, the file for the male sample is documented in a separate file.
DOI: 10.24432/c5jw2k
title: Amazon Access Samples
DOI: 10.25850/nioz/7b.b.0f
title: Gridded high-resolution current meter and hydrographic data from the Irminger Current mooring array from 2014 - 2022

description: Gridded field of daily mooring data from 2014 - 20022 from the Irminger Current mooring array. Details on data processing and deployments can be found in https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020JC016193 and https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021JC018188. The NIOZ mooring data is combined with teh M! data on the eastern flank of the Reykjanes Ridge which is included in this gridded data set.
DOI: 10.34740/kaggle/dsv/4451415
title: Smart Bee Colony Monitor: Clips of Beehive Sounds
DOI: 10.48529/gvwc-vx89
title: Refugee and Host Communities Household Survey 2018
title: UGA_2018_RHCS_v01_M
DOI: 10.5066/p9iapcz5
title: Simulated inundation extent and depth at Whittier, Alaska resulting from the hypothetical rapid motion of landslides into Barry Arm Fjord, Prince William Sound, Alaska

description: This data release contains postprocessed model output from simulations of hypothetical rapid motion of landslides, subsequent wave generation, and wave propagation. A modeled tsunami wave was generated by rapid motion of unstable material into Barry Arm Fjord. This wave propagated through Prince William Sound and then into Passage Canal east of Whittier. Here we consider only the largest wave-generating scenario presented by Barnhart and others (2021a, 2021b) and use a simulation setup similar to that work. The results presented here are not identical to those presented in Barnhart and others (2021a, 2021b) because the results in this data release were obtained using an expanded dataset of topography and bathymetry. This data release presents the extent of simulated inundation and does not include simulation results related to other related phenomena (e.g., current strength).
DOI: 10.5281/zenodo.10445643
title: Interplanetary magnetic field By controlled Alfven wings at Earth during encounter of a coronal mass ejection

description: This data set contains input and output of the global MHD simulation in the article "Interplanetary magnetic field By controlled Alfven wings at Earth during encounter of a coronal mass ejection". 

1. Simulation input files:   a) IMF.dat: solar wind conditions for the simulation   b) PARAM.in.ss and PARAM.in.ta: input files for the steady state (.ss) and time accurate (.ta) stages

2. Simulation output:   a) sim.csv: simulation output along the virtual satellite trajectory, which is used for figure2.   b) 3d__var_4_t00220000_n02275984_vtk.zip: 3D output that is used for figure3-7. After decompression, it is a vtu file and can be opened with Paraview.
DOI: 10.5281/zenodo.10679720
title: A Novel 2D Transport Model for Bed Load Pulses Caused by Local Sediment Surplus

description: Bed load pulses are highly complex phenomena which can be observed under a wide range of flow conditions, stream types and sediment supply. Although a large variety of field and laboratory research was conducted in the last decades, many uncertainties remain in characterizing and modeling sediment pulse propagation. The present paper complements existing research by providing a detailed analysis of the two dimensional transport and dispersal behavior of bed load pulses originating from locally installed sediment deposits. Moreover, a novel two dimensional model, based on a two-parameter gamma distribution (GGM), to predict the pulse propagation is introduced. Therefore, laboratory experiments were conducted using a contactless, image-based measurement technique to determine the distribution patterns of the pulse. The results reveal a decreasing trend in the bidirectional sediment advection and dispersion over time, following the shape of a power law decay function. Further, predominance of the advective component was found for both directions. The proposed model is capable in predicting the magnitude, shape and extent of the propagating sediment pulses on a high level of accuracy.
DOI: 10.5281/zenodo.12212768
title: Sources and meteorology influencing highly-time resolved PM2.5 trace elements at 3 urban sites in extremely polluted Indo Gangetic Plain in India, Measurement_Report_Data_21-06-2024
DOI: 10.5281/zenodo.13794736
title: The Role of Grain Size on Shear Localization Illuminated by Acoustic Emissions

description: Shear localization within the fault core, as evidenced by grain comminution in fault gouge, plays a crucial role in the initiation of frictional instabilities. To upscale the physics of shear localization and understand the influence of grain size, it is essential to identify the governing physical parameters and micro-mechanisms. In this study, we conducted double-direct shear experiments on quartz fault gouges with varying initial grain sizes (coarse, fine, and bi-disperse mixtures) under constant normal stress and shearing velocity, while continuously monitoring Acoustic Emissions (AE). Microstructural analyses were performed on the deformed samples to complement the mechanical and AE data. Our results reveal that, while the initial grain size and distribution do not substantially alter the steady-state friction coefficient, they significantly influence the early stages of frictional evolution leading to steady state, which is reflected in a different rate and amplitude of AEs. Specifically, coarse grains and bi-disperse mixtures exhibit strain-hardening behavior before reaching steady-state friction, whereas fine grains show strain-weakening behavior. Microstructural observations further indicate that bi-disperse mixtures retard the localization of deformation with increasing fault displacement. The AE data shows a strong dependence on both the average grain size and the evolving state of the gouge layer. Notably, there is a direct correlation between the average AE amplitude and the average grain size within the gouge. These findings suggest that variations in AE attributes are indicative of distinct micro-mechanisms active during different stages of shear localization, which are not fully captured by mechanical data and microstructural analysis alone.

The data uploaded are structured as follows:



ReadMe.pdf explains the different parts of the data repository

'Mechanical_and_acoustic_data' gathers all the mechanical and acoustic catalogs used in the paper

Python files are used to plot the figures of the paper and supplementary information
DOI: 10.5281/zenodo.14512248
title: A 30-meter resolution global land productivity dynamics dataset from 2013 to 2022

description: This dataset is the first global scale 30 m land productivity dynamics (LPD) dataset from 2013 to 2022, which provides essential data support for SDG 15.3.1 monitoring and reporting globally. 

Method

The dataset leveraging the Google Earth Engine (GEE) platform and utilizing Landsat-8 and MODIS imagery, employed the Gap-filling and Savitzky–Golay filtering (GF-SG) algorithm, advanced spatiotemporal filtering method, FAO-WOCAT methodology to generate.

Data download instructions

The global 30 m LPD result described in this paper are available in Zendo (https://doi.org/10.5281/zenodo.1389040160) format under the Creative Commons license CC-BY. The result is divided into 56 ZIP files based on longitude (0°, ±45°, ±90°, ±135°, ±180°) and latitude (0°, ±28°, 52°N, 68°N, 78°N, 84°N). Each ZIP file contains the LPD result in TIFF format and is named as “Global_LPD_30m_13_22_geometry[a]_[b]_[c]”, where [a] represents the sequential number from 1 to 56, [b] denotes the longitude of the upper-left corner of the LPD tile, and [c] denotes the latitude of the upper-left corner of the LPD tile. After downloading a specific ZIP file, the user can mosaic the TIFF files within it and then start using them.

Data description

Pixel value 1 represents declining land productivity, 2 represents early signs of decline of land productivity, 3 represents stable but stressed land productivity, 4 represents stable and not stressed land productivity, and 5 represents increasing land productivity.
DOI: 10.5281/zenodo.14646115
title: Distribution and cycling of siderophores in the North and Tropical East Pacific Oceans
DOI: 10.5281/zenodo.14886229
title: Numerical Source Data for Graphs and Charts-Nicotinic Acetylcholine Receptors Regulate Growth Hormone in Pituitary Somatotrophs of Tigers
DOI: 10.5281/zenodo.14917866
title: Data for the manuscript 'Smart mixture design can steer the fate of root derived carbon into mineral-associated and particulate organic matter in intensively managed grasslands'

description: To determine the fate of root-derived carbon (C) input from grassland mixtures into distinct soil organic carbon pools — particulate organic matter (POC) and mineral-associated organic carbon (MAOC) — a field trial was established, comparing pure stands of perennial ryegrass under high and low nitrogen (N) fertilizer application rates with grassland mixtures containing legumes and forbs at increasing levels of species richness. The mixtures received the low N application rate.

Through multiple-pulse ¹³C-CO₂ labeling during the first growing season (2022), we captured the net formation of MAOC and POC. At the end of the growing season, soil cores with a diameter of 30 cm were excavated to a depth of 25 cm (topsoil) and transferred to the lab. We removed roots from the soil and performed particle-size fractionation to trace fresh organic carbon (net rhizodeposited C) into particulate organic matter (POM) and mineral-associated organic matter (MAOM). Using a cut-off of 50 μm, particles larger than 50 μm were classified as POM, while those smaller than 50 μm were classified as MAOM.

We related these soil C fractions to five morphological root traits, as well as to the lignocellulose index and the C:N ratio in root biomass.
DOI: 10.5281/zenodo.14976898
title: Spectra From Precise Bolometric Luminosities and Effective Temperatures of 23 late-T and Y dwarfs Obtained with JWST

description: This archive contains the data behind Figures 5-7 of the published version of the manuscript listed above (Beiler et al. 2024b, https://doi.org/10.3847/1538-4357/ad6301). These data include the merged JWST NIRSpec and MIRI LRS.  The full reduction, marging, and calibration process can be found in Section 4. For any questions, contact Samuel Beiler <Samuel.Beiler@rockets.utoledo.edu>.
DOI: 10.5281/zenodo.14994355
title: Large-scale biosynthetic analysis of human microbiomes reveals diverse protective ribosomal peptides

description: Supplementary Data for the manuscript: "Large-scale biosynthetic analysis of human microbiome reveals diverse protective ribosomal peptides".
DOI: 10.5281/zenodo.2536040
title: Soil organic carbon stock in kg/m2 for 5 standard depth intervals (0–10, 10–30, 30–60, 60–100 and 100–200 cm) at 250 m resolution

description: Soil organic carbon stock in kg/m<sup>2</sup> for 5 standard depth intervals (0–10, 10–30, 30–60, 60–100 and 100–200 cm) at 250 m resolution. To convert to t/ha multiply by 10. Derived using soil organic carbon content (https://doi.org/10.5281/zenodo.1475457), bulk density (https://doi.org/10.5281/zenodo.1475970) and coarse fragments (https://doi.org/10.5281/zenodo.2525681), predicted from point data at 6 standard depths. Depth to bed rock has been ignored, hence total stocks might be about 10–15% lower then reported. Processing steps are described in detail <strong>here</strong>. Antarctica is not included. To access and visualize maps use: <strong>https://openlandmap.org</strong> If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: sol = theme: soil, organic.carbon.stock = variable: soil organic carbon stock in kg/m2, msa.kgm2 = determination method: derived from organic carbon content, bulk density and coarse fragments, m = mean value, 250m = spatial resolution / block support: 250 m, b0..10cm = vertical reference: 0-10 cm layer below surface, 1950..2017 = time reference: period 1950-2017, v0.2 = version number: 0.2,
description: {"references": ["Sanderman, J., Hengl, T., Fiske, G., (2017). The soil carbon debt of 12,000 years of human land use. PNAS, https://dx.doi.org/10.1073/pnas.1706103114", "Hengl, T., de Jesus, J.M., Heuvelink, G.B., Gonzalez, M.R., Kilibarda, M., Blagoti\u0107, A., Shangguan, W., Wright, M.N., Geng, X., Bauer-Marschallinger, B. and Guevara, M.A., (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS one, 12(2), p.e0169748. https://doi.org/10.1371/journal.pone.0169748", "Hengl, T., MacMillan, R.A., (2019). Predictive Soil Mapping with R. OpenGeoHub foundation, Wageningen, the Netherlands, 370 pages, www.soilmapper.org, ISBN: 978-0-359-30635-0."]}
DOI: 10.5281/zenodo.3362844
title: CHAOS - Combined (CT-MR) Healthy Abdominal Organ Segmentation Challenge Data

description: This is the train and testing dataset of Combined (CT-MR) Healthy Abdominal Organ Segmentation (CHAOS) Challenge. This data consists of images of Abdominal CT and MRI from different patients. There are 20 training and 20 testing cases in the CT dataset. MRI dataset contains 20 training and 20 testing cases with T1-Dual and T2 SPIR sequences. Train data contains both DICOM images and their ground truth masks. The testing set only contains DICOM images. In CT cases only livers were annotated. In MRI cases, livers, left/right kidneys, and spleens were annotated. For further information about the data and challenge, please visit https://chaos.grand-challenge.org/ and read the CHAOS_Submission_Manual.pdf <em><strong>Important note: </strong>Ground truths/references of the test data are reserved for challenge validation and <strong>will never be shared publicly. </strong>Such requests will be ignored<strong>.</strong></em> Scientists may use this data not only join to the CHAOS challenge but also for other works as long as they give appropriate credit, provide a link to the license, and indicate if changes were made. Bibtex: <pre><code>@dataset{CHAOSdata2019, author = {Ali Emre Kavur and M. Alper Selver and Oğuz Dicle and Mustafa Barış and N. Sinem Gezer}, title = {{CHAOS - Combined (CT-MR) Healthy Abdominal Organ Segmentation Challenge Data}}, month = Apr, year = 2019, publisher = {Zenodo}, version = {v1.03}, doi = {10.5281/zenodo.3362844}, url = {https://doi.org/10.5281/zenodo.3362844} }</code></pre> IEEE Style: <pre><code>Ali Emre Kavur, M. Alper Selver, Oğuz Dicle, Mustafa Barış, and N. Sinem Gezer, "CHAOS - Combined (CT-MR) Healthy Abdominal Organ Segmentation Challenge Data". Zenodo, 11-Apr-2019.</code></pre> APA Style: <pre><code>Ali Emre Kavur, M. Alper Selver, Oğuz Dicle, Mustafa Barış, & N. Sinem Gezer. (2019). CHAOS - Combined (CT-MR) Healthy Abdominal Organ Segmentation Challenge Data (Version v1.03) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3362844</code></pre>
DOI: 10.5281/zenodo.3474071
title: tvb-data - Extended Dataset

description: Various demonstration datasets for use with The Virtual Brain project are provided here.


Here you will find:



	
compatible file/folder structures that can be uploaded through the web interface of TVB.  For this usage scenario, you should just download, and unzip the current package. Independently, download TVB_Distribution from  https://www.thevirtualbrain.org/ and from its web GUI upload files from this unzipped folder, at need. 
	
the default datasets used when working in console or library mode. For this usage scenario, you should download, unzip, and install in your python distribution this tvb-data as a regular python package.



More information on TVB documentation site: http://docs.thevirtualbrain.org/ or on the main webpage of the project https://www.thevirtualbrain.org/
DOI: 10.5281/zenodo.7664166
title: Quasi-periodic spin down variations in 17 puslars

description: Spindown time-series as computed in Keith & Nitu 2023. For each pulsar, columns are MJD, frequency-derivative value, and frequency derivative error.
DOI: 10.5281/zenodo.8239305
title: GLC_FCS30D: the first global 30-m land-cover dynamic monitoring product with fine classification system from 1985 to 2022

description: GLC_FCS30D is the first global fine land cover dynamic product at a 30-meter resolution that adopts continuous change detection. It utilizes a refined classification system containing 35 land-cover categories and covers the time span from 1985 to 2022. Before the year 2000, the update cycle was every 5 years, while after 2000, it is updated annually. In specific, it developed by combining the continuous change detection method, local adaptive updating models and the spatiotemporal optimization algorithm from dense time-series Landsat imagery, and was validated to achieve an overall accuracy of 80.88% (±0.27%) for the basic classification system 10 major land-cover types) and 73.24% (±0.30%) for the LCCS level-1 validation system (17 LCCS land-cover types). The GLC_FCS30D has been compressed into 36 zip files, and<strong> <em>the details about the GLC_FCS30D can be found in the User's guides.</em></strong>