Find research datasets worth reusing

opencc-by-nc-4.0Oct 2024View details →

Data from: Process-based modelling of nonharmonic internal tides using adjoint, statistical, and stochastic approaches. Part II: adjoint frequency response analysis, stochastic models, and synthesis

Meta data updated after publication.

opencc-by-nc-4.0Oct 2024View details →

Data from: Process-based modelling of nonharmonic internal tides using adjoint, statistical, and stochastic approaches. Part I: statistical model and analysis of observational data

Meta data updated after publication.

opencc-by-4.0Sep 2022View details →

Data Used in "Close view of of the lightning attachment process unveils the streamer zone fine structure"

This page contains high-speed video files as .gif and .cine files, for the complete video of Figure 2 (Movie S1 and S3). It also contains the video (Movie S2) from a second high-speed (Phantom V711) looking in a different direction that saw other UUL leaders not registered by the Phantom V2012 camera. There is also an Excel file containing the data analysis. The data uploaded here is sufficient to reproduce the results of the paper titled "Close view of of the lightning attachment process unveils the streamer zone fine structure", submitted for publication in Geophysical Research Letters. Instructions to watch the videos: Movie S1.cine and Movie S2.cine: Download and use the software Phantom Camera Control (PCC)  available at: <a href="https://www.phantomhighspeed.com/resourcesandsupport/phantomresources/pccsoftware">https://www.phantomhighspeed.com/resourcesandsupport/phantomresources/pccsoftware</a> The Phantom Camera Control (PCC) software is compatible with Windows 7 Pro and Windows 8.1 and Windows 10, for both 32 and 64-bit operating systems.

Processed Data for Figures of "Declining Amazon biomass due to deforestation and subsequent degradation losses exceeding gains"

Processed output data for generating figures of "Declining Amazon biomass due to deforestation and subsequent degradation losses exceeding gains". Most datasets are aggregated to 0.25 degree resolution of L-VOD data. Data are organised in folders but should be added to a single directory for easy use with provided code. <ul> <li>AGC_LVOD: Aboveground carbon [Mg C ha] (2011-2019) and trends [Mg C ha yr] derived from different L-VOD indices calibrated to AGC using the ESA CCI biomass map. Provides data based on smoothed, max and trend indices as well as their mean.</li> <li>modelprocesschanges: Annual and total aboveground carbon changes [Mg C ha] (2011-2018) derived for different processes following methods described in the manuscript.</li> <li>inputData: pre-processed landcover fraction information at 1 km resolution, used as input for Figure 1b.</li> <li>forestcover: Forest cover and intact (old-growth) forest cover fractions derived from mapbiomas. (2011-2018)</li> <li>masks: Raster mask of areas considered in analysis.</li> <li>valuerangeserrors: Upper and lower value boundaries for AGC and processes, derived from standard errors in ESA CCI biomass map.</li> </ul> When using any of the data listed above please cite the original paper (Fawcett et al., 2022) as well as the original data sources mentioned in the manuscript.

Data from: Molecular and cellular processes of deafferentation after plexus injury in human dorsal root ganglia

Dataset of human dorsal root ganglia (DRG) images and deep learning models Sections of six control and six plexus patient DRG were immunostained and imaged using large-field (tile) microscopy. Two staining combinations were investigated:  - neurofilament (NF), fatty acid binding protein 7 (FABP7), and clusterin (APOJ) - neurofilament (NF), ionized calcium-binding adapter molecule 1 (IBA1), and microtubule-associated protein 2 (MAP2)  NF-positive neurons were segmented with a deep learning method (deepflash2). FABP7 and IBA1 were segmented with a thresholding method. Provided are: - all images and corresponding segmentation masks for NF, FABP7, and IBA1  - images and annotated segmentation masks of NF-positive neurons (3 experts annotated the same 10 images, the estimated ground truth masks were used for training of deep learning models) - the deep learning model ensemble (3) for segmentation of NF-positive neurons

Data for MILP algorithm for control strategy optimisation of a hybrid solar thermal plant consisting of two different solar fields working for two processes at different temperatures, a three tanks storage and a boiler for SHIP applications

This repository contains the results of simulations exposed in the article MILP algorithm for control strategy optimisation of a hybrid solar thermal plant consisting of two different solar fields working for two processes at different temperatures, a three tanks storage and a boiler for SHIP applications. Notebooks for easy plotting of the results are contained in this repository. The README.txt contains light explainations regarding how to use those notebooks. This article is yet to be published at the time of writing.

opencc-by-4.0Dec 2021View details →

Figure S4. Mass cytometry data pre-processing

Figure S4: Mass cytometry data pre-processing. Paired myocardial and blood samples were collected from patients undergoing cardiac surgery and who underwent DNA sequencing. Each sample was barcoded and samples were acquired in bulk with one sample was rerun for each CyTOF run in order to correct batch effect. A gating on CD45+ live cells was then performed. A dimension reduction algorithm was then applied and the clustering algorithm ClusterX was applied on the entire data set. Cells clusters identification was then performed according to Heatmap based on cell markers associated with each cluster.

A Scalable Data Management System Data Model facilitating the integration of any inspection system and the automated data digitalization process.

In the context of the EU-funded project PILOTING (No. 871542), a scalable Data Management System (DMS) was deployed and facilitated the easy integration of nine different robotic systems and various payloads and the storing of all the data observations produced during the inspections. In particular, a three-phase methodology was adopted for the creation of the DMS Data Model (DMS-DM) in order to define the architectural design of the DMS.  The first phase was to semantically define the entities of the PILOTING ecosystem, identifying assets and activities that were important to the data providers, and including them in the data model design. The second phase was to identify relationships between the entities, focusing on information that must pre-exist for entities to be semantically accurate, hierarchies between entities, especially physical assets, and the data needed to form the inspection plan. For the third phase, the information collected by the previous two stages of the data model construction was used to create the overall data model, taking into consideration the possible integration with third parties and the needs of the I&M Visualization portal.  The constructed document is attempted to present the designed Entity-Relationship-Diagram (ERD) of the DMS-DM. Additional definitions of the existing entities and the relations between them are also depicted.

Data and processing scripts from "Morphodynamic Preservation of Fluvial Channel Belts"

This compilation contains data reported in the manuscript Cardenas, Lamb, Jobe, Mohrig, and Swartz, Morphodynamic preservation of fluvial channel belts. As of Nov 2022, this manuscript is submitted to SEPM (Society for Sedimentary Geology) journal The Sedimentary Record. Compilation contains: (1) Table showing the edge coordinates of each channel belt in the associated manuscript. (2) Table showing centerline point coordinates. (3) Table showing all width measurements for each channel belt. (4) A compilation table showing representative geometric measurements for each belt. (5) A python script to generate paleoflow directions from centerline coordinates. (6) A script to generate various geometric measurements from belt edge coordinates. (7) A script to plot histograms of geometric measurements.

Informes de casos de estudio finales en hábitats humanos (anexo del libro: La visión sistémica del ambiente construido, 2024). [Data sets for the article: The Habitat Intervention Design Process -Part II]

From the book: Estos informes están escritos en español por los estudiantes que se mencionan en cada informe, quienes son los autores. Cada uno de estos seis documentos contiene casos de estudio y muestra la implementación de la metodología del 'Proceso de Diseño de Intervención del Hábitat' (IDP) en cada uno de los 6 casos mencionados en el libro (Capítulo 2.5 y Capítulo 3.2) (Libro: La visión sistémica del ambiente construido).  Estos hacen parte de la Fase 2 Fundamentos Prácticos del Modelo del proyecto de investigación "Modelo Pedagógico para la Enseñanza del Diseño de Intervención del Hábitat en Programas de Educación Superior".  From the article: These reports are Spanish-written. Each of these six documents contains one of the case studies and shows the implementation of the 'Habitat Intervention Design Process' (IDP) methodology in each of the 6 case studies mentioned in the article "The Habitat Intervention Design Process -Part II: A Transdisciplinary Model in the Pedagogy of the Design of the Built Environment" published in The International Journal of Design Education in its 2023 version. Find it here: <a href="https://doi.org/10.18848/2325-128X/CGP/v17i02/155-195">https://doi.org/10.18848/2325-128X/CGP/v17i02/155-195 </a>

Data for Intra-seasonal variability in sediment provenance and transport processes in the Brahmaputra basin

No description provided.

Processed Data MOST

Processed eddy-covariance data used to reproduce the figures of the paper "Relaxed eddy accumulation outperforms Monin-Obukhov flux models under non-ideal conditions"

Processed BCO data for Vial et al. 2023

The folder contains yearly netCDF files with the hourly-averaged cloud radar data from the Barbados Cloud Observatory (BCO) used in Vial, Albright, Vogel, Musat, Bony (2023), Cloud transition across the daily cycle illuminates model responses of trade cumuli to warming, PNAS. Also provided is the file ‘radar_diurnalCMIP_files_version.txt’, which contains information about the version of the raw data used to create the processed files. The raw data can be accessed through the BCO intake catalog, which can be accesses using <a href="https://www.python.org/">Python</a> and <a href="https://intake.readthedocs.io/">intake</a> e.g. as follows: from intake import open_catalog cat = open_catalog("https://bco.pages.gwdg.de/intake/catalog.yaml") ds = cat.Level_1.Backscatter_MBR2.to_dask() ds.SNR.sel(time="2022-08-01", range=slice(0, 5000)).T.plot(robust=True)

opencc-zeroFeb 2023View details →

dryad36/100

REGAIN trial intervention development process evaluation data

Background: Up to half of people hospitalised with COVID-19 report diverse and persistent symptoms affecting quality of life for months and sometimes years after discharge (long-COVID). We describe the development of an online group exercise and behavioural support intervention for people who continue to experience such physical and/or emotional health problems more than three months after hospital discharge. Methods: Intervention development was informed by the Medical Research Council framework for complex interventions. Our multidisciplinary team of academics, clinicians, and people with long-COVID, had collective expertise in the development and testing of complex interventions. We integrated a bio-psycho-social model of care drawing on rehabilitation literature for long-term health conditions and experiences from our pre-pilot study. Multiple stakeholder meetings were held to refine the intervention which was designed to be deliverable within the UK National Health Service. We adhere to TIDieR guidance for transparent and explicit reporting of telehealth interventions. Results: The final REGAIN online exercise and behavioural support intervention consisted of an initial 1:1 consultation with a trained practitioner, followed by eight online group exercise, and six group support, sessions delivered over eight weeks. Participants could also access an online library of on-demand exercise and support videos. Conclusions: The final REGAIN intervention, combining exercise and behavioural support, is fully manualised with clear pathways to delivery and implementation. It is currently being tested in a randomised controlled trial. The intervention, developed with extensive patient and stakeholder engagement, could be incorporated into existing NHS rehabilitation programmes, should it prove to be clinically and cost-effective for people with long-COVID. Trial registration: International Standard Randomised Controlled Trial Number (ISRCTN) 11466448: Rehabilitation exercise and psychological support after COVID-19 infection: REGAIN.

opencc-by-4.0Feb 2023View details →

Raw data for the Github repository "Collection of scripts to download & process hydropower generation data in Argentina, Bolivia, Brazil, Uruguay"

This is the raw data downloaded from the websites of the following system operators:   - CNDC, Comité Nacional de Despacho de Carga (Bolivia): https://www.cndc.bo/home/index.php   - ONS, Operador Nacional do Sistema Elétrico (Brazil): https://www.ons.org.br/   - UTE, Usinas y Trasmisiones Eléctricas (Uruguay): https://www.ute.com.uy/   - CAMMESA, Compañía Administradora del Mercado Mayorista Eléctrico Sociedad Anónima (Argentina): https://cammesaweb.cammesa.com Hydropower generation data is extracted using the R scripts available here: https://github.com/matteodefelice/hydro-sam

Processed CMIP6 data for "The climate response to the Mt Pinatubo eruption does not constrain climate sensitivity"

Processed CMIP6 output for Pauling et al. "The climate response to the Mt Pinatubo eruption does not constrain climate sensitivity" submitted to Geophysical Research Letters in 2023. Download this code repository: https://doi.org/10.5281/zenodo.7553024 and follow the instructions in the README to download data and reproduce the results of the paper.

opencc-zeroMar 2023View details →

dryad36/100

Data for: A spatially explicit trait-based approach uncovers changes in assembly processes under warming

The re-assembly of plant communities during climate warming depends on several concurrent processes. Here we present a novel framework that integrates spatially explicit sampling, plant trait information and a warming experiment to quantify shifts in these assembly processes. By accounting for spatial distance between individuals, our framework allows separation of potential signals of environmental filtering from those of different types of competition. When applied to an elevational transplant experiment in the French Alps, we found common signals of environmental filtering and competition in all communities. Signals of environmental filtering were generally stronger in alpine than in subalpine control communities, and warming reduced this filter. Competition signals depended on treatments and traits: Symmetrical competition was dominant in control and warmed alpine communities, while hierarchical competition was present in subalpine communities. Our study highlights how distance dependent frameworks can contribute to a better understanding of transient re-assembly dynamics during environmental change.

opencc-by-4.0Mar 2023View details →

DATA: Language experience predicts music processing in a half-million speakers of fifty-four languages

This repository contains the data for the paper 'Language experience predicts music processing in a half-million speakers of fifty-four languages' The code that accompanies this data can be found on GitHub - https://github.com/themusiclab/language-experience-music

opencc-by-4.0Mar 2023View details →

Data for Process Design and Energy Assessment of an Onboard Carbon Capture System with Boilers or Heat Pumps for Additional Steam Generation

1. Supporting file includes main stream information used in Aspen HYSYS model, process simulations of boiler and heat pump for model construction. 2. Supporting file also includes main information used in ProMAX model, process simulations of carbon capture process for model construction.