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25 results for “RCM”

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zenodo48/100

RoCliB - Bias corrected CORDEX RCM dataset over Romania

This dataset contains a set of four climate variables from 10 General Circulation Models (GCMs), dynamically downscaled in the EURO-CORDEX initiative by several Regional Climate Models (RCMs) and adjusted (bias-corrected) over Romania for the period 1971–2100. The climate models data were obtained from the <a href="https://cordex.org/data-access/">EURO-CORDEX archive</a>. Two climate change scenarios were selected, namely the moderate (RCP4.5) and business-as-usual scenario (RCP8.5). The multivariate bias correction by the N-dimensional probability density method (MBCn) was used to bias correct the RCMs outputs [1], using as reference the ROCADA gridded dataset [2]. Characteristic: <ul> <li>Climate variables: air temperature (tasAdjust - Celsius degree), maximum air temperature (tasmaxAdjust - Celsius degree), minimum air temperature (tasminAdjust - Celsius degree) and precipitation (prAdjust - mm)</li> <li>Bias-correction method: multivariate bias correction (N-pdft)</li> <li>The reference period used for bias correction: 1971-2005</li> <li>The observational dataset used as a reference for bias correction: ROCADAv1</li> <li>Temporal resolution: daily</li> <li>Temporal extent:  <ul> <li>Historical: 1971-2005;</li> <li>RCP4.5 and RCP8.5: 2006-2100.</li> </ul> </li> <li>Spatial resolution: 0.1 degrees (~10km)</li> <li>Spatial extent: from 20.1 to  29.8°E and 43.5 to 48.4°N</li> <li>File format: netCDF,  CF-1.4-compliant format using netCDF4 compression</li> <li>Coordinate system: WGS 1984 (EPSG:4326)</li> <li>Naming conventions: variablename_ROU-11_cmip5experiment_globalmodel_run_regionalmodel_rcmversionid_timefrequency_starttime-endtime.nc</li> <li>RMCs (Institution or working group, RCM Model, GCM Institute, GCM  Driving):  <ul> <li>Climate Limited-area Modelling Community (CLMcom) CCLM4-8-17 CNRM-CERFACSCNRM-CM5</li> <li>Royal Netherlands Meteorological Institute (KNMI) RACMO22E CNRM-CERFACS CNRM-CM5</li> <li>Swedish Meteorological and Hydrological Institute (SMHI) RCA4CNRM-CERFACS CNRM-CM5</li> <li>Climate Limited-area Modelling Community (CLMcom) CCLM4-8-17 ICHECEC-EARTH</li> <li>Swedish Meteorological and Hydrological Institute (SMHI) RCA4I CHECEC-EARTH</li> <li>Royal Netherlands Meteorological Institute (KNMI) RACMO22E ICHECEC-EARTH</li> <li>Danish Meteorological Institute (DMI) HIRHAM5 ICHECEC-EARTH</li> <li>Climate Limited-area Modelling Community (CLMcom) CCLM4-8-17 MPI-MMPI-ESM-LR</li> <li>Swedish Meteorological and Hydrological Institute (SMHI) RCA4 MPI-MMPI-ESM-LR</li> <li>Climate Service Center Germany (GERICS) REMO2015 NCC NorESM1-M</li> </ul> </li> </ul> The terms of use for RoCliB datasets are the same as those from the original EURO-CORDEX simulations obtained from ESGF servers: <a href="https://is-enes-data.github.io/cordex_terms_of_use.pdf">https://is-enes-data.github.io/cordex_terms_of_use.pdf</a>. To access and visualize relevant facts and statistics about climate change based on the RoCliB datasets use <a href="http://suscap.meteoromania.ro/en/roclib">http://suscap.meteoromania.ro/en/roclib</a>. Acknowledgement This work was supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CCCDI-UEFISCDI, project number COFUND-SUSCROP-SUSCAP-2, within PNCDI III. We also acknowledge the World Climate Research Programme's Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5.

opencc-by-4.0Apr 2021View details →

zenodo44/100

Bias-corrected EURO-CORDEX RCM simulations for the OPTAIN case studies

Bias-corrected EURO-CORDEX RCM simulations are available on a daily timescale for: -period 1981-2099/2100, -6 RCM, -3 scenarios (RCPs 2.6, 4.5 and 8.5), -7 variables (mean, minimum and maximum temperature, precipitation, solar radiation, wind speed at 2 m and relative humidity) and -18 domains and 23 locations within these domains. Bias correction and further downscaling to 0.1° was done using <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=overview">ERA5-Land</a> reanalysis data with non-parametric empirical quantile mapping. Moreover, the interpolation of gridded bias-corrected climate model simulations to the locations was made using universal kriging. Organization of the data The name of the files are domain-type.zip, where type is gridded (NetCDF) or point (csv). Each zip file contains multiple files, organized in subfolders: experiment/modelNumber/variable.nc for gridded and experiment/modelNumber/variable-pilotFieldNumber.txt for point data, where experiment is rcp26, rcp45 or rcp85. domain and pilotFieldNumber <table> <tbody> <tr> <td> domain </td> <td> domain location (min and max. Longitude, min and max latitude) </td> <td> pilotFieldNumber </td> <td> pilot field location (longitude, latitude) </td> <td> case study number </td> <td> country </td> <td> Name (OPTAIN case study) </td> </tr> <tr> <td> 01 </td> <td> 50.95 51.45 14.55 15.05 </td> <td> </td> <td>   </td> <td> 1 </td> <td> DEU </td> <td> Schoeps </td> </tr> <tr> <td> 02 </td> <td> 46.35 47.05 6.55 7.15 </td> <td> 2 </td> <td> 46.816667 6.95 </td> <td> 2 </td> <td> CHE </td> <td> Petite Glane </td> </tr> <tr> <td> 02_1 </td> <td> 46.75 47.25 7.25 7.75 </td> <td> 1 </td> <td> 46.983333 7.466667   </td> </tr> <tr> <td> 02_34 </td> <td> 47.35 47.85 8.35 </td> <td> 3 4 </td> <td> 47.433333 8.516667 47.683333 8.616667 </td> </tr> <tr> <td> 02_5 </td> <td> 46.15 46.65 5.95 6.45 </td> <td> 5 </td> <td> 46.4 6.233333 </td> </tr> <tr> <td> 03a </td> <td> 46.65 47.15 17.45 17.95 </td> <td> 1 2 3 4 </td> <td> 46.92649 17.68246 46.9166 17.68976 46.91283 17.69754 46.91283 17.69723 </td> <td> 3a </td> <td> HUN </td> <td> Csorsza </td> </tr> <tr> <td> 03b </td> <td> 46.45 46.95 16.65 17.15 </td> <td> </td> <td>   </td> <td> 3b </td> <td> HUN </td> <td> Felso Valicka </td> </tr> <tr> <td> 04 </td> <td> 52.35 52.85 18.45 18.95 </td> <td> 1 </td> <td> 52.597469 18.728617 </td> <td> 4 </td> <td> POL </td> <td> Upper Zglowiaczka </td> </tr> <tr> <td> 05 </td> <td> 46.35 46.85 15.35 15.85 </td> <td> </td> <td>   </td> <td> 5 </td> <td> SVN </td> <td> Pesnica </td> </tr> <tr> <td> 06 </td> <td> 46.45 46.95 16.15 16.65 </td> <td> </td> <td>   </td> <td> 6 </td> <td> HUN/SVN </td> <td> Kebele/Kobiljski </td> </tr> <tr> <td> 07 </td> <td> 49.85 50.35 4.75 5.25 </td> <td> </td> <td>   </td> <td> 7 </td> <td> BEL </td> <td> La Wimbe </td> </tr> <tr> <td> 08 </td> <td> 55.15 55.75 23.55 24.05 </td> <td> 1 2 </td> <td> 55.522057 23.799235 55.42233194 23.82580339 </td> <td> 8 </td> <td> LTU </td> <td> Dotnuvele </td> </tr> <tr> <td> 09 </td> <td> 45.45 45.95 9.65 10.15 </td> <td>   </td> <td>   </td> <td> 9 </td> <td> ITA </td> <td> Cherio </td> </tr> <tr> <td> 10 </td> <td> 59.45 59.95 10.75 11.25 </td> <td> 1 2 3 4 5 6 7 8 </td> <td> 59.71949 10.83576 59.6833306 10.8833298 59.6833306 10.8833298 59.665 10.9475 59.665 10.9475 59.841012 10.903597 59.757631 11.072031 59.539623 10.856447 </td> <td> 10 </td> <td> NOR </td> <td> Krogstad </td> </tr> <tr> <td> 11 </td> <td> 46.45 46.95 17.55 18.05 </td> <td> 1 2 </td> <td> 46.658333 17.75583 46.656944 17.75833 </td> <td> 11 </td> <td> HUN </td> <td> Tetves </td> </tr> <tr> <td> 12 </td> <td> 49.35 49.85 14.75 15.25 </td> <td> 1 </td> <td> 49.616837 15.078266 </td> <td> 12 </td> <td> CZE </td> <td> Cechticky </td> </tr> <tr> <td> 13 </td> <td> 55.85 56.35 25.85 26.45 </td> <td>   </td> <td>   </td> <td> 13 </td> <td> LVA </td> <td> Dviete </td> </tr> <tr> <td> 14 </td> <td> 59.75 60.25 17.55 18.05 </td> <td>   </td> <td>   </td> <td> 14 </td> <td> SWE </td> <td> Ingvastaan Lehstaan </td> </tr> </tbody> </table>   modelNumber <table> <tbody> <tr> <td> modelNumber </td> <td> Driving Model (GCM) </td> <td> Ensemble </td> <td> RCM </td> <td> End date </td> </tr> <tr> <td> 1 </td> <td> EC-EARTH </td> <td> r12i1p1 </td> <td> CCLM4-8-17 </td> <td> 31.12.2100 </td> </tr> <tr> <td> 2 </td> <td> EC-EARTH </td> <td> r3i1p1 </td> <td> HIRHAM5 </td> <td> 31.12.2100 </td> </tr> <tr> <td> 3 </td> <td> HadGEM2-ES </td> <td> r1i1p1 </td> <td> HIRHAM5 </td> <td> 30.12.2099 </td> </tr> <tr> <td> 4 </td> <td> HadGEM2-ES </td> <td> r1i1p1 </td> <td> RACMO22E </td> <td> 30.12.2099 </td> </tr> <tr> <td> 5 </td> <td> HadGEM2-ES </td> <td> r1i1p1 </td> <td> RCA4 </td> <td> 30.12.2099 </td> </tr> <tr> <td> 6 </td> <td> MPI-ESM-LR </td> <td> r2i1p1 </td> <td> REMO2009 </td> <td> 31.12.2100 </td> </tr> </tbody> </table>   variable <table> <tbody> <tr> <td> variable </td> <td> description </td> <td> Unit </td> </tr> <tr> <td> Tmean </td> <td> Mean temperature </td> <td> °C </td> </tr> <tr> <td> Tmin </td> <td> Min temperature </td> <td> °C </td> </tr> <tr> <td> Tmax </td> <td> Max temperature </td> <td> °C </td> </tr> <tr> <td> prec </td> <td> Precipitation </td> <td> mm </td> </tr> <tr> <td> solarRad </td> <td> Solar radiation </td> <td> MJ/m2 </td> </tr> <tr> <td> windSpeed </td> <td> Wind speed at 2m </td> <td> m/s </td> </tr> <tr> <td> relHum </td> <td> Relative humidity </td> <td> % </td> </tr> </tbody> </table>   Methodolody Bias correction was done using non-parametric empirical quantile mapping with modified method from R package <a href="https://cran.r-project.org/web/packages/qmap/index.html">qmap</a>. Parameters selected were: corrections for each day of the year using a moving windows for a 31 days; 100 quantiles; wet days corrections for precipitation. The reference period is 1981-2010. The interpolation of gridded bias-corrected climate model simulations to the location was made using universal kriging  with R packages <a href="https://cran.r-project.org/web/packages/automap/index.html">automap</a> and <a href="https://cran.r-project.org/web/packages/gstat/index.html">gstat</a> with (external) variables x, y, x2, y2, x*y, z, where x is latitude, y is longitude, and z is elevation. For Digital Elevation Model <a href="https://webmap.ornl.gov/wcsdown/dataset.jsp?dg_id=10008_1">Shuttle Radar Topography Mission</a> was used. If there was an error using above mentioned variables, the number of variables was reduced to x, y, x*y, z and if there was still an error to x, y, z.   Funding This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862756.

opencc-by-4.0Feb 2022View details →

zenodo44/100

5405 MHz SigMF baseband recording of RCM-2 (Radarsat Constellation) using PlutoPlus SDR and four log periodic array (LPA) antennas

This dataset contains a recording of the <a href="https://www.asc-csa.gc.ca/eng/satellites/radarsat/technical-features/radarsat-comparison.asp">RCM-2</a> (<a href="https://en.wikipedia.org/wiki/RADARSAT_Constellation">Radarsat Constellation</a>) satellite as it passed over Berkeley, California. The recording was made on 2024-08-13 and is about 15 seconds long, containing acquisition of signal pulses and loss of signal at the tail end of the recording. The dataset is stored in SigMF format. The data files are compressed with xz to reduce their size. The IQ sample rate is  20.0 Msps and the center frequency is 5405 MHz. The linear antenna array used to record contained four HT5 antennas, labeled as:  "HT5 antenna UWB log-periodic antenna 1300MHz-10GHz". These four antennas were spaced 21 cm apart.  The input from these four antennas was combined with a SP-TX-4B splitter/combiner using equal lengths of LMR400 coax, then amplified using an LNA labeled as "RF AMP 04A: TQP3M9037 0.1-6GHz". The LNA was powered via a +5 volt bias-tee.  A "Pluto+" or Pluto Plus SDR was used to sample, with SatDump software.

opencc-by-4.0Aug 2024View details →

zenodo44/100

Gridded global organic matter reactivity (RCM parameter a, in years)

Gridded data product for the globally extrapolated RCM parameter a (in yrs) and its respective reactivity k (in 1/yrs from k = nu/a). This represents a combination of the two datasets presented in the main text in Fig. 9. The deep-sea extrapolation uses data from Seiter, Hensen, and Zabel (2005), while the shallow ocean (SFD<1000m) uses data from Jørgensen, Wenzhöfer, Egger, and Glud (2022). The area South-Est of Australia remains empty as in Seiter et al. (2005) and for reasons given in the main text.

opencc-by-4.0May 2023View details →

zenodo40/100

Dataset: RCM Technologies, Inc. (RCMT) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

opencc-zeroJun 2024View details →

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Dataset: R1 RCM Inc. (RCM) Stock Performance

opencc-zeroJun 2024View details →

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UKCP18 RCM precipitation and temperature bias corrected using ISIMIP3BA change-preserving quantile mapping.

We present bias-corrected UK Climate Projections 2018 (UKCP18; Met Office Hadley Centre, 2018) regional datasets for temperature, precipitation, and potential evapotranspiration (1981-2080). All 12 members of the 12 km ensemble were corrected using quantile mapping and a change-preserving variant (Lange, 2019; Lange, 2020). Both methods effectively reduce biases in multiple statistics, while maintaining projected climatic changes. We provide guidance on using the bias-corrected datasets for climate change impact assessment. Please find a detailed description and evaluation in the metadata and accompanying data paper (Reyniers et al., 2025). --- Met Office Hadley Centre (2018): UKCP18 Regional Projections on a 12km grid over the UK for 1980-2080. CEDA, 8 March 2022. <a href="https://catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604">https://catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604</a> Lange, S. (2019). Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1. 0). GMD, 12(7), 3055-3070. Lange, S. (2020). ISIMIP3BASD (2.4.1). Zenodo. https://doi.org/10.5281/zenodo.3898426 Reyniers, N., Zha, Q., Addor, N., Osborn, T. J., Forstenhäusler, N., & He, Y. (2025). Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain. Earth System Science Data, 2025, 17(5), 2113–2133.

opencc-by-4.0Mar 2022View details →

zenodo36/100

Cup-marked stone, Tregiffian burial chamber, RCM

This cup-marked stone was moved from the site at Tregiffian for safe-keeping and display at the [Royal Cornwall Museum](https://www.royalcornwallmuseum.org.uk), Truro. There are potentially as many as 47 cup marks on this stone. Some of the larger 'jellybean' depressions appear to have started out as two separate cup marks which have been joined together. Slight depressions of the original cup marks can still be seen on some of them. Whether these represent re-working of existing cup marks, or were simply a method for creating the jellybean shape, is difficult to tell. A replica of this stone has been installed in the original location at Tregiffian burial chamber in West Penwith. [Explore Tregiffian burial chamber in 3D](https://sketchfab.com/3d-models/tregiffian-burial-chamber-cornwall-uk-1b6d39159c844ea5b24d869508fa3fd9) and discover more of its cup marks. *The project was funded by a British Academy/Leverhulme small research grant.* Source: Objaverse 1.0 / Sketchfab

opencc-byAug 2021View details →

zenodo36/100

Energetic Particle Injection during Short Isolated Bubble as seen in RCM Simulation and Spacecraft Observations in the Flow Braking Region

The names of the RCM simulation output files specify the simulation time in a format of "hhmmss". The stored quantities are, "I","J","COLAT","ALOCT","MLT","BNDLOC","XMIN","YMIN","FTV","BMIN","V", "BIRK_fromV(NH)","P(RCM),nPa", "PV_gamma","Vtotx", "Vtoty","Vx_exb","Vy_exb","vel_x","vel_y","Ey","PEDLAM", "PEDPSI", "HALL", "RCM_T_p","RCM_T_e","RCM_N_e","EFLUX","EAVG","f_i_50-75","f_i_75-125","f_i_125-200","f_i_200-300","f_e_50-75","f_e_75-125","f_e_125-200","f_e_200-300","Vm","dbxdz","dbydz","dbrdz","dbzdx","dbzdy". For the first hour of substorm-growth-phase-like quasi-steady convection, we uploaded the RCM simulation output files at 1-minute intervals. Then, the RCM output files were uploaded at 20-second intervals for the next 7 minutes of bubble injection, and at 1-minute intervals for the rest of the simulation.

opencc-by-4.0Jul 2023View details →

zenodo36/100

UKCP18 RCM precipitation and temperature bias corrected using non-parametric quantile mapping method

The UKCP18 RCM PPE (Met Office Hadley Centre, 2018) projections of precipitation and daily average temperature were bias adjusted using a non-parametric quantile mapping method based on empirical quantiles (Boe et al, 2007, Gudmundsson et al, 2012). The datasets cover the period from December 1980 to November 2080 and are intended for use in climate change impact assessments, where the bias correction helps reduce biases in multiple statistics while maintaining projected climatic changes. ------------------------------------------------- Met Office Hadley Centre (2018): UKCP18 Regional Projections on a 12km grid over the UK for 1980-2080. CEDA, 8 March 2022. <a href="https://catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604">https://catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604</a> Boe, J.; Terray, L.; Habets, F. & Martin, E. Statistical and dynamical downscaling of the Seine basin climate for hydro-meteorological studies. International Journal of Climatology, 2007, 27, 1643-1655, doi: 10.1002/joc.1602. Gudmundsson, L.; Bremnes, J. B.; Haugen, J. E. & Engen-Skaugen, T. Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations - a comparison of methods. Hydrology and Earth System Sciences, 2012, 16, 3383-3390, doi:10.5194/hess-16-3383-2012. Paper Citation: We kindly ask users of this dataset to cite the paper that describes the dataset. The paper is published and can be accessed via the following link: <a href="https://doi.org/10.5194/essd-17-2113-2025" target="_new" rel="noopener">https://doi.org/10.5194/essd-17-2113-2025</a>. Please reference the paper as: Reyniers, N., Zha, Q., Addor, N., Osborn, T. J., Forstenhäusler, N., and He, Y.: Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain, Earth Syst. Sci. Data, 17, 2113–2133, https://doi.org/10.5194/essd-17-2113-2025, 2025.

opencc-by-4.0Aug 2023View details →

zenodo32/100

Selected and Post-Processed Outputs of LFM-TIEGCM-RCM Simulation of 2013 March 17 Event

This dataset is associated with the publication "SAPS in the 2013 March 17 Storm Event: Initial Results from the Coupled Magnetosphere-Ionosphere-Thermosphere Model". In particular, the NCAR Community Model: Coupled Magnetosphere-Ionosphere-Thermosphere (CMIT) with Ring Current extension, which is also known as the LFM-TIEGCM-RCM (LTR) model, has been used to investigate the subauroral polarization streams during the 2013 March 17 storm event. The LTR model was driven by realistic solar wind conditions for 2013 March 17. Model outputs of ionospheric electron precipitation energy flux, ion zonal drifts, field-aligned currents, electrostatic potential, conductances, total electron content, as well as diagnostic variables of key features of SAPS were analyzed and used in producing a paper: 'SAPS in the 2013 March 17 Storm Event: Initial Results from the Coupled Magnetosphere-Ionosphere-Thermosphere Model'.

opencc-by-4.0Dec 2018View details →

zenodo32/100

Future wave climate in the Mediterranean Sea and associated uncertainty from an ensemble of 31 GCM-RCM wave simulations

The data provided is used in a study aimed at assessing future changes in the Mediterranean wave climate. A total of 31 GCM-RCM simulations were used to characterize the wave climate during the historical (1979-2005), mid-century (2034-2060), and end-century (2074-2100) periods. Changes in seasonal significant wave height (Hs) and peak period (Tp) wave parameters are evaluated for both the mean and intense (quantile 0.95) wave climate, along with the shift in wave direction (wave peak dominant direction, θp) for sea states characterized as intense. The robustness of the climate change signal is evaluated following the guidelines outlined in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change. Additionally, using a wave hindcast as a reference, the changes in future extreme events are assessed by fitting a GEV to a unique and coherent set of bias-corrected annual maxima from each model. We provide data used to obtain the results of our study, comprising: 1) wave climate statistics for Hs, Tp, and θp for each model and each period studied; 2) two sets of annual maxima distribution for each model, which were bias-corrected assuming that the set of extreme events follows either a Gumbel distribution or a GEV distribution. For more details on the methods to obtain these files describing wave climate statistical as used in the study, please refer to Toomey et al., 2024: "Future wave climate in the Mediterranean Sea and associated uncertainty from an ensemble of GCM-RCM wave simulations."

opencc-by-4.0Jun 2024View details →

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RCM_data

RCM data file

opencc-by-4.0Nov 2022View details →

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CP_OdU (Climate Projections for Odesa, Ukraine): Climate indices and daily meteorological variables for Odesa (Ukraine) in 2021-2050 by different RCM simulations from Euro-CORDEX

<ol> <li>ODS-UA_RCM_outputs_day_20210101-20501231.zip file contains outputs from Euro-CORDEX RCM’s simulation for a land-located point closest to the Odesa meteorological site (46.44N, 30.77E).</li> <li>The RCM grids define the coordinates for this point (the gridpoint is mostly located in the city center (Kateryninska^Troitska) or near the 7-km market.</li> <li>The nomenclature of files and variables in these files are defined in http://is-enes-data.github.io/cordex_archive_specifications.pdf.</li> <li>Other files contain the so-called climate indices as described in <a href="https://knmi-ecad-assets-prd.s3.amazonaws.com/documents/atbd.pdf">https://knmi-ecad-assets-prd.s3.amazonaws.com/documents/atbd.pdf</a> and table in 0readme.pdf.</li> </ol>

opencc-by-4.0Dec 2022View details →

ClinicalTrials.gov32/100

RCM to Diagnose BCC - Reflectance Confocal Microscopy to Diagnose Basal Cell Carcinoma

ClinicalTrials.gov study NCT03331874. IPD Sharing: NO. Countries: 1. Publications: 12.

closedIPD-NOFeb 2026View details →

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Supplementary material 1 from: Brito RN, Souza RCM, Diotaitui L, Lima VS, Ferreira RA (2021) Coleção de Vetores de Tripanosomatídeos (Fiocruz/COLVET) held at the institution Fiocruz Minas in Brazil: diversity of Triatominae (Hemiptera, Reduviidae) and relevance for research, education, and entomological surveillance. ZooKeys 1074: 17-42. https://doi.org/10.3897/zookeys.1074.69700

Figure S1

opencc-zeroDec 2021View details →

zenodo28/100

Figure 3 from: Brito RN, Souza RCM, Diotaitui L, Lima VS, Ferreira RA (2021) Coleção de Vetores de Tripanosomatídeos (Fiocruz/COLVET) held at the institution Fiocruz Minas in Brazil: diversity of Triatominae (Hemiptera, Reduviidae) and relevance for research, education, and entomological surveillance. ZooKeys 1074: 17-42. https://doi.org/10.3897/zookeys.1074.69700

Figure 3 Total number of services provided by the Coleção de Vetores de Tripanosomatídeos (Fiocruz / COLVET) between 2013-2019. The services included were for scientific research, entomological surveillance and educational activities as described in the Methods section of the main text.

opencc-by-4.0Dec 2021View details →

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Figure 2 from: Brito RN, Souza RCM, Diotaitui L, Lima VS, Ferreira RA (2021) Coleção de Vetores de Tripanosomatídeos (Fiocruz/COLVET) held at the institution Fiocruz Minas in Brazil: diversity of Triatominae (Hemiptera, Reduviidae) and relevance for research, education, and entomological surveillance. ZooKeys 1074: 17-42. https://doi.org/10.3897/zookeys.1074.69700

Figure 2 Summary of the specimens caught in sylvatic and domestic/peri-domestic environments deposited in the Coleção de Vetores de Tripanosomatídeos (Fiocruz/COLVET) according to species and location (North, Central, and South American countries). Countries colored pale pink have at least one specimen deposited in the collection. Countries are abbreviated as follows: (US) United States, (MX) Mexico, (GT) Guatemala, (CR) Costa Rica, (PA) Panama, (VE) Venezuela, (CO) Colombia, (EC) Ecuador, (PE) Peru, (BO) Bolivia, (CL), Chile, (PY) Paraguay, (AR) Argentina, and (UY) Uruguay. Also, nine specimens of P. megistus from Paraguay, three specimens of Rhodnius robustus from Ecuador, two of T. dimidiata from Guatemala, and one specimen, respectively, of Pantrongylus geniculatus and Mepraia spinolai from Costa Rica and Chile are deposited in the scientific repository Ficoruz/COLVET. One specimen morphologically identified as a Psammolestes sp. and caught in Venezuela is also deposited in the collection.

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Figure 1 from: Brito RN, Souza RCM, Diotaitui L, Lima VS, Ferreira RA (2021) Coleção de Vetores de Tripanosomatídeos (Fiocruz/COLVET) held at the institution Fiocruz Minas in Brazil: diversity of Triatominae (Hemiptera, Reduviidae) and relevance for research, education, and entomological surveillance. ZooKeys 1074: 17-42. https://doi.org/10.3897/zookeys.1074.69700

Figure 1 Summary of the whole/semi-whole triatomine specimens according to Brazilian state deposited in the Coleção de Vetores de Tripanosomatídeos (Ficoruz/COLVET). The Brazilian states are abbreviated as follows: (AC) Acre, (AL) Alagoas, (AP) Amapá, (AM) Amazonas, (BA) Bahia, (CE) Ceará, (DF) Distrito Federal, (ES) Espírito Santo, (GO) Goiás, (MA) Maranhão, (MT) Mato Grosso, (MS) Mato Grosso do Sul, (MG) Minas Gerais, (PA) Pará, (PB) Paraíba, (PR) Paraná, (PE) Pernambuco, (PI) Piauí, (RJ) Rio de Janeiro, (RN) Rio Grande do Norte, (RS) Rio Grande do Sul, (RO) Rondônia, (RR) Roraima, (SC) Santa Catarina, (SP) São Paulo, (SE) Sergipe, and (TO) Tocantins.

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Supplementary material 2 from: Brito RN, Souza RCM, Diotaitui L, Lima VS, Ferreira RA (2021) Coleção de Vetores de Tripanosomatídeos (Fiocruz/COLVET) held at the institution Fiocruz Minas in Brazil: diversity of Triatominae (Hemiptera, Reduviidae) and relevance for research, education, and entomological surveillance. ZooKeys 1074: 17-42. https://doi.org/10.3897/zookeys.1074.69700

Table S1

opencc-zeroDec 2021View details →

ScienceDex guides

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record