cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/af60720c1e404a9e9d2c145d2b2ead4e
title: ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2010, 2017, 2018, 2019 and 2020, v4

description: This dataset comprises estimates of forest above-ground biomass for the years 2010, 2017, 2018, 2019 and 2020. They are derived from a combination of Earth observation data, depending on the year, from the Copernicus Sentinel-1 mission, Envisat’s ASAR instrument and JAXA’s Advanced Land Observing Satellite (ALOS-1 and ALOS-2), along with additional information from Earth observation sources. The data has been produced as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme by the Biomass CCI team. This release of the data is version 4. Compared to version 3, version 4 consists of an update of the three maps of AGB for the years 2010, 2017 and 2018 and new AGB maps for 2019 and 2020. New AGB change maps have been created for consecutive years (2018-2017, 2019-2018 and 2020-2019) and for a decadal interval (2020-2010). The pool of remote sensing data now includes multi-temporal observations at L-band for all biomes and for all years. The AGB maps rely on revised allometries which are now based on a longer record of spaceborne LiDAR data from the GEDI and ICESat-2 missions. Temporal information is now implemented in the retrieval algorithm to preserve biomass dynamics as expressed in the remote sensing data. Biases between 2010 and more recent years have been reduced. The data products consist of two (2) global layers that include estimates of: 1) above ground biomass (AGB, unit: tons/ha i.e., Mg/ha) (raster dataset). This is defined as the mass, expressed as oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees excluding stump and roots 2) per-pixel estimates of above-ground biomass uncertainty expressed as the standard deviation in Mg/ha (raster dataset) In addition, files describing the AGB change between two consecutive years (i.e., 2018-2017, 2019-2018 and 2020-2010) and over a decade (2020-2010) are provided (labelled as 2018_2017, 2019_2018, 2020_2019 and 2020_2010). Each AGB change product consists of two sets of maps: the standard deviation of the AGB change and a quality flag of the AGB change. Note that the change itself can be simply computed as the difference between two AGB maps, so is not provided directly. Data are provided in both netcdf and geotiff format.
DOI: 10.6084/m9.figshare.23992803.v1
title: <b>Shaping Medical Assessment with Expert Consensus: A Theory-Based Summative Evaluation Blueprint for Community Medicine</b>

description: This dataset contains comprehensive data collected as part of a blueprint project aimed at developing a theory-based summative evaluation blueprint for medical education. The project involved collaboration with experts from multiple institutes to create an effective assessment tool.<b>Data Components:</b><b>Response Time of Participating Experts</b><b>Chapterwise Inter Rater Agreement</b><b>Intraclass Coefficient:</b> Measures of reliability among experts' evaluations for specific topics.<b>Impact and Frequency Scores by Participating Experts:</b> Scores assigned by experts indicating the impact and frequency of each topic within the chapters.<b>Average Impact and Frequency Score of Each Topic:</b> Mean impact and frequency scores for each topic, providing insights into general perception.<b>Impact*</b><b>Frequency (I</b><i><b>*</b></i><b>F) of Each Topic of All Chapters:</b> Calculated combined scores based on the multiplication of impact and frequency scores for each topic.<b>Sum of I*F of All Topics of a Chapter:</b> Total combined scores for each chapter, considering all topics.
DOI: 10.7488/ds/1947
title: GB Postcode Area, Sector, District

description: This dataset represents the Postal Boundaries for 2012. Included in the zip file are postcode Areas (AB, EH,..), districts (AB1, AB2,..) and sectors (AB1 1, AB1 2, ..). This data was sourced from Geolytix (https://blog.geolytix.net/2012-11-20-postal-sector-boundaries-by-geolytix/). The source data is released under a OGL licence which allows users to use the data without charge but requires them to attribute the following: Postal Boundaries © GeoLytix copyright and database right 2012 Contains Ordnance Survey data © Crown copyright and database right 2012 Contains Royal Mail data © Royal Mail copyright and database right 2012 Contains National Statistics data © Crown copyright and database right 2012. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2014-03-14 and migrated to Edinburgh DataShare on 2017-02-22.
description: ESRI Shapefile
DOI: 10.11575/4p8e-1k65
title: Transition Region Explorer - RGB Dataset

description: Documentation for Transition Region Explorer (TREx) RGB data is available via https://data.phys.ucalgary.ca alongside the data itself. Any questions about the instrumentation or data should be directed to the creators.
DOI: 10.12751/g-node.ysgsy1
title: Multi-channel spatio-temporal MRI atlas of the normal fetal brain development from the developing Human Connectome Project

description: This repository contains multi-channel spatio-temporal MRI atlas of the normal fetal brain development during 21-36 weeks GA cretated as a part of the Developing Human Connectome Project (dHCP).
description: IsSupplementTo: Andreas Schuh, Antonios Makropoulos, Emma C. Robinson, Lucilio Cordero-Grande, Emer Hughes, Jana Hutter, Anthony N. Price, Maria Murgasova, Rui Pedro A. G. Teixeira, Nora Tusor, Johannes Steinweg, Suresh Victor, Mary A. Rutherford, Joseph V. Hajnal, A. David Edwards, and Daniel Rueckert, Unbiased construction of a temporally consistent morphological atlas of neonatal brain development, bioRxiv, 2018. (https://doi.org/10.1101/251512)
DOI: 10.1285/i20705948v12n4p748
title: An investigation of mobility of Italian Ph. Doctors

description: Migration is a permanent phenomenon rooted in history and recently involves high-skilled workers (HSWs). Among them, a crucial role is played by PhDs. HSWs face the risk to not find a job matching their skills and they can opt to accept to be overeducated for the job or move to another country or region. Mobility of HSW can be interpreted as a positive issue that can help to match jobs and skills. However, the emergence of a clear path between areas of countries or regions (e.g. from south to north Italy) highlights the risks of a drain of human capital from areas with low development to more developed ones. In this paper, we focus on a category of HSWs who have been almost neglected by the literature, the PhDs. The aim of the paper is to shed light on the mobility pattern of Italian PhDs, paying attention to PhDs from Southern Italy. This aim will be pursued by using microdata from the 2014 ISTAT Survey on the professional conditions of Italian PhDs at 4 and 6 years after the end of their studies.This work highlights that Southern PhDs have higher probability to move to other area of the countries, while Northern PhDs seem to prefer to move abroad thus confirming previous studies which identified a similar pattern for graduates. While the Northern part of the country compensate the drain of human capital with the mobility from the other part of Italy, the Southern face a relevant drain of 'talents'.
DOI: 10.13026/c2pd5b
title: Fetal PCGs

description: The project collects a series of 26 fetal phonocardiographic (PCG) signals from different pregnant women during the last months of their singleton physiological pregnancies (gestational week between 31 and 40). All women were healthy and aged between 25 and 35 years old. The files were recorded in a private clinical practice in 2010 by means of a portable phonocardiographic device (Fetaphon Monitoring System by Pentavox) during sessions lasting 20 minutes on average. The data was digitized with a sampling frequency of 333 Hz at 8-bits ADC; for each file, gestational week (GW) and patient id (P) are reported in the file name.
DOI: 10.13026/tjtq-5911
title: EPHNOGRAM: A Simultaneous Electrocardiogram and Phonocardiogram Database

description: The electro-phono-cardiogram (EPHNOGRAM) project focused on the development of
low-cost and low-power devices for recording simultaneous electrocardiogram
(ECG) and phonocardiogram (ECG) data, with auxiliary channels for capturing
environmental audio noise, which could be used for PCG quality enhancement
through signal processing. The current database, recorded by version 2.1 of
the developed hardware, has been acquired from 24 healthy adults aged between
23 and 29 (average: 25.4 ± 1.9 years) in 30min stress-test sessions during
resting, walking, running and biking conditions, using indoor fitness center
equipment. The dataset also contains several 30s sample records acquired
during rest conditions. This data is useful for simultaneous multi-modal
analysis of ECG and PCG. It provides interesting insights into the inter-
relationship between the mechanical and electrical mechanisms of the heart,
under rest and physical activity.
DOI: 10.15138/tjpq-0d69
title: NOAA Greenhouse Gas Marine Boundary Layer Reference - CH4.
DOI: 10.15141/s5q94m
title: Penn World Table 10.0
DOI: 10.15156/bio/2483912
title: UNITE general FASTA release for Fungi 2

description: This release consists of a single FASTA file: the RepS/RefS of all SHs, adopting the dynamically use of clustering thresholds whenever available. Includes global and 97% singletons.
DOI: 10.17632/8bctsm8jz7.1
title: Brain MRI Dataset of Multiple Sclerosis with Consensus Manual Lesion Segmentation and Patient Meta Information

description: Magnetic resonance imaging (MRI) provides a significant key to diagnose and monitor the progression of Multiple Sclerosis (MS) disease. Manual MS-Lesion segmentation, Expanded Disability Status Scale (EDSS) and patient’s meta information can provide a gold standard for research in terms of automated MS-lesion quantification, automated EDSS prediction and identification of the correlation between MS-lesion and patient disability. In this dataset, we provide a novel multi-sequence MRI dataset of 60 MS patients with consensus manual lesion segmentation, EDSS, general patient information and clinical information. On this dataset, three radiologists and neurologist experts segmented and validated the manual MS-lesion segmentation for three MRI sequences T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR). The dataset can be used to study the relationship between MS-lesion, EDSS and patient clinical information. Furthermore, it also can be used to development of automated MS-lesion segmentation, patient disability prediction using MRI and correlation analysis between patient disability and MRI brain abnormalities include MS lesion location, size, number and type.
DOI: 10.17863/cam.109745
title: 3D Flow MRI data of steady flow through a 3D-printed aorta at Re = 554 and 1526 with SNR ~ 5

description: The research data supports Kontogiannis, A., Elgersma, S. V., Sederman, A. J. & Juniper, M. P. `Bayesian inverse Navier–Stokes problems: joint flow field reconstruction and parameter learning`, https://doi.org/10.48550/arXiv.2406.18464, 2024. The flow MRI experiment is described in section 5.1 of that paper and in citated papers. The data is contained in two folders: 'highRe' corresponds to data at Reynolds number = 1526; 'lowRe' corresponds to data at Reynolds number = 554. Each folder contains three npy files (standard binary file format for a NumPy array): flow_data.npy contains the velocity components [u,v,w] on a [115,54,77] uniform mesh; mang.npy contains the mean magnitude image (nuclear spin density) on this mesh; mask_data.npy contains a mask that identifies the fluid regions on this mesh. The code RUNME.py is a Python file that converts these npy files to centimetres-grammes-seconds (cgs) dimensions and plots slice number 'y_slice_idx' of the data to screen.
DOI: 10.17909/t9h59d
title: GALEX/MCAT

description: The GALEX Merged Catalog of Sources (MCAT)
DOI: 10.18462/iir.icr.2023.0195
title: Breaking the limits of electric-powered whole-body cryotherapy.
DOI: 10.26188/22344973.v1
title: Ferric carboxymaltose versus standard-of-care oral iron to treat second-trimester anaemia in Malawian pregnant women: Analysis dataset

description: The dataset contains de-identified data of 862 pregnant women and their neonates from Southern Malawi, who were randomised in the REVAMP (RandomisEd trial of intraVenous iron for Anaemia in Malawian Pregnant women) trial. This trial aimed to explore the effect of a single dose of a modern IV iron formulation (ferric carboxymaltose) compared to standard-of-care (oral iron) for anaemia treatment in Malawian pregnant women and their neonates up to 1-month post-partum. <br> This project contains six separate datasets and corresponding data dictionaries which underlie the variables used in the analysis of the main manuscript. These consist of: - Baseline characteristics - Maternal efficacy - Neonate efficacy - Maternal safety - Neonate safety - Maternal infusion related events <br> To maintain the privacy and confidentiality of the research participants, access is provided to de-identified data only. Certain variables have not been included due to their risk of re-identification, as outlined in the data dictionaries. These variables are available by the corresponding author (Sant-Rayn Pasricha: pasricha.s@wehi.edu.au) upon reasonable request. For reference, participant record identifiers for both the mothers and neonates were derived independently to reduce the risk of re-identification and therefore cannot be used to link the maternal and neonate data together.
DOI: 10.34740/kaggle/ds/3152196
title: Air Pollution Image Dataset from India and Nepal
DOI: 10.35111/647p-yt29
title: Chinese Web 5-gram  Version 1

description: <h3>Introduction</h3> <p>Chinese Web 5-gram Version 1, Linguistic Data Consortium (LDC) catalog number LDC2010T06 and isbn 1-58563-539-1, was created by researchers at Google Inc. It consists of Chinese word n-grams and their observed frequency counts generated from over 800 million tokens of text. The length of the n-grams ranges from unigrams (single words) to 5-grams. This data should be useful for statistical language modeling (e.g., segmentation, machine translation) as well as for other uses. </p><p>Included with this publication is a simple segmenter written in Perl using the same algorithm used to generate the data.</p> <h3>Data Collection</h3> <p>N-gram counts were generated from approximately 883 billion word tokens of text from publicly accessible web pages. This data set contains only n-grams that appeared at least 40 times in the processed sentences. Less frequent n-grams were discarded. While the aim was to identify and collect only Chinese language pages, some text from other languages is incidentally included in the final data.</p> <p>Data collection took place in March 2008; no text that was created on or after April 1, 2008 was used to develop this corpus.</p> <h3>Preprocessing</h3> <p>The input character encoding of documents was automatically detected, and all text was converted to UTF-8. The data was tokenized by an automatic tool, and all continuous Chinese character sequences were processed by the segmenter.</p> <p>The following types of tokens are considered valid:</p> <ul> <li>A Chinese word containing only Chinese characters.</li> <li>Numbers, e.g., 198, 2,200, 2.3, etc.</li> <li>Single Latin tokens, such as Google, &ab, etc.</li> </ul><h3>Extent of Data</h3> <ul> <li>File sizes: approx. 30 GB compressed (gzip'ed) text files</li> <li>Number of tokens: 882,996,532,572</li> <li>Number of sentences: 102,048,435,515</li> <li>Number of unigrams: 1,616,150</li> <li>Number of bigrams: 281,107,315</li> <li>Number of trigrams: 1,024,642,142</li> <li>Number of fourgrams: 1,348,990,533</li> <li>Number of fivegrams: 1,256,043,325</li> </ul><h3>Sample</h3> <a href="./desc/addenda/LDC2010T06.jpg" rel="nofollow">Sample screen shot</a>  </br>
Portions © 2008 Google Inc., © 2010 Trustees of the University of Pennsylvania
DOI: 10.3886/e208605v1
title: Data and Code for: The Global Financial Resource Curse

description: Since the late 1990s, the United States has received large capital flows from developing countries - a phenomenon known as the global saving glut - and experienced a productivity growth slowdown. Motivated by these facts, we provide a model connecting international financial integration and global productivity growth. The key feature is that the tradable sector is the engine of growth of the economy. Capital flows from developing countries to the United States boost demand for U.S. non-tradable goods, inducing a reallocation of U.S. economic activity from the tradable sector to the non-tradable one. In turn, lower profits in the tradable sector lead firms to cut back investment in innovation. Since innovation in the United States determines the evolution of the world technological frontier, the result is a drop in global productivity growth. This effect, which we dub the global financial resource curse, can help explain why the global saving glut has been accompanied by subdued investment and growth, in spite of low global interest rates.
DOI: 10.5067/aqua/modis/l3b/chl/2022
title: Aqua MODIS Level 3 Binned Chlorophyll Data, Version R2022.0
DOI: 10.5281/zenodo.10152141
title: ROcD-nGoM: A River-Ocean Coupled Database for the Northern Gulf of Mexico

description: This is a River-Ocean Coupled Database for the Northern Gulf of Mexico. This database contains river chemistry and discharge (Q) data for 54 rivers, streams, and bayous entering the nGoM. It has both the raw observations (ConcAve) as well as a daily concentration (ConcDay) and flux estimations from the USGS WRTDS model. The database also contains 17 chemical and physical ocean parameters from the Gulf of Mexico Coastal Ocean Observing System (GCOOS) and the MODIS and seaWiFS satellite sensors.
The data is provided in two formats: (1) raw with outlier flags and (2) cleaned and time averaged. The raw format provides the daily concentrations of the USGS and GCOOS data and monthly data for the satellite product. There are two outlier flags for parameters which indicate if the value is in the 0.5 percentile of high or low concentrations of all the data. They are called "outlier_99.5" for the 0.5% of data on the high end of the distribution and "outlier_0.05" for the 0.5% of the data on the low end of the distribution. The USGS river data has outlier flags for "ConcAve", "ConcDay", and "Q". The ConcDay range designation is defined by the distribution of the actual raw measurements (ConcAve). The ocean data has outlier flags for each parameter except wind/current direction. The time averaged format includes monthly, seasonal, and yearly values of all the parameters. These values are calculated following the removal of the outliers in the raw data.
The R script used to create the river portion of the database is also included as ROcDnGoM_river_script.
DOI: 10.5281/zenodo.13117599
title: Makarova et al. (2024)_Medford_Millville_datasets

description: These datasets contain the data for the manuscript "Warming and Carbon Injection at the Paleocene-Eocene Boundary: Bayesian Modeling Supports Synchroneity" by M. Makarova, W.J. Schmelz, K.G. Miller, T.D. Herbert, L.G. Podrecca, J.V. Browning, R.A. Mortlock, L.V. Godfrey, and J.D. Wright.

The dataset file includes records of: % coarse fraction (Medford cores MAP 3A and 3B), d13C of TOC (MAP 3A, MAP 3B, Millville), d13C and d18O of planktonic (Subbotina spp.) and benthic (Cibicidoides spp., Anomalinoides spp.) foraminifera (MAP 3B), and TEX86 (MAP 3A, MAP 3B, Millville). All data were generated by M. Makarova at Rutgers University and Brown University.

Site Locations: MAP 3A and 3B core are from Medford, NJ, USA (39.86°N, 74.82°W). The ODP Leg 174AX Millville core is from Millville, NJ, USA (39.40°N, 75.09°W).
DOI: 10.5281/zenodo.13880506
title: Data analysis & code: Quantifying the impact of climate change and forest management on Swedish forest ecosystems using the dynamic vegetation model LPJ-GUESS

description: This file contains code to optimize the allometric parameters, to plot the figures, and details of the underlying data analysis in "Quantifying the impact of climate change and forest management on Swedish forest ecosystems using the dynamic vegetation model LPJ-GUESS" (Bergkvist et al.).
DOI: 10.5281/zenodo.13890803
title: HFCs Feedstock Data and Code

description: This is the data and code used for my Bayesian work on CFC emissions from HFC production. Revisions were submitted to Nature Communications on October 8, 2024. To complete the analysis, place all code in a directory and run the CFCs_113_114_115_HCFC_133_BPE.m file.
DOI: 10.5281/zenodo.13957625
title: Neuromorphic-enabled video-activated cell sorting
DOI: 10.5281/zenodo.13997332
title: Crater couting files at the CE6 landing site
DOI: 10.5281/zenodo.14041344
title: Experimental dataset: "Minimal vertex model explains how the amnioserosa avoids fluidization during Drosophila dorsal closure"

description: This repository contains experimental data supporting our paper "Minimal vertex model explains how the amnioserosa avoids fluidization during Drosophila dorsal closure".

Original Publication:Tah, I., Haertter, D., et al. (2024). Minimal vertex model explains how the amnioserosa avoids fluidization during Drosophila dorsal closure. PNAS (in press).Preprint available at: https://doi.org/10.1101/2023.12.20.572544

Dataset Structure

amnioserosa_time_lapses/

This directory contains confocal microscopy time-lapse recordings of eCadherin-labeled Drosophila melanogaster embryos during dorsal closure:



Imaging parameters:



Frame interval: 15 seconds

Pixel size: 0.158 µm



Data files:



*_data.p: Morphometric features of individual amnioserosa cells during closure

*_junctions.p: Morphometric features of individual cell-cell adherens junctions

read_filter_data.py: Python script demonstrating data reading and filtering procedures




junction_laser_cuts/

This directory contains high-speed recordings of UV-laser junction ablation experiments:



Imaging parameters:



Frame rate: 5 Hz

Pixel size: 0.364 µm



Content: Time series of eCadherin-labeled embryos before, during, and after precise UV-laser severing of individual junctions


data_figures/

This directory contains processed data and analysis results presented in Figures 1-3 of the main manuscript. The data are organized by figure number and include all measurements and simulation results used to generate the plots shown in these figures.

 

For detailed experimental methods and protocols, please refer to the published paper.
DOI: 10.5281/zenodo.14107749
title: Longitudinal Network Changes and Phenoconversion Risk in Isolated REM Sleep Behavior Disorder
DOI: 10.5281/zenodo.4896571
title: Long-term spatially explicit information on land use 1830-1960-2015: Case study of the municipalities Waidhofen/Ybbs and Paldau, Austria

description: The dataset contains historical land use/land cover (LULC) pattern for the Austrian municipalities Waidhofen/Ybbs (Lower Austria) and Paldau (Styria). Three time cuts comprising nearly 200 years were digitized using various spatial data sources: 1820: Maps of Franciscan Cadastre 1960: Aerial photographs 2015: Aerial orthophotos combined with IACS (Integrated Administration and Control System) The dataset consistently discerns four LULC categories (forest land, cropland, grassland, and “settlement and other”) and provides additional information on biomass extraction. The following files are available: <em>README.txt</em>: Metadata and descriptions of spatial data and attributes <em>Waidhofen.zip</em>: Spatial data of Waidhofen/Ybbs, Lower Austria <em>Paldau.zip</em>: Spatial data of Paldau, Styria
description: The data was created within the Integrating Land Use Legacies in Landslide Risk Assessment to Support Spatial Panning (ILLAS) project funded by the Austrian Climate Research Program (ACRP), grant number ACRP9-ILLAS-KR16AC0K13226. The contribution of S. Gingrich was also financially supported by the European Research Council (ERC-2017-StG 757995 HEFT).