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661 results for “temperature measurement”
Measuring Temperatures of Tissues During Endoscopy
ClinicalTrials.gov study NCT00868504. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Prevention of Secondary Foot Ulcers in Patients With Diabetes Using Systematic Measuring of Skin Temperature.
ClinicalTrials.gov study NCT01269502. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Microstructure turbulence, conductivity-temperature-depth, and current velocity measurements of a submesoscale eddy in Terra Nova Bay (2018-2019)
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Data from: Evaluation of two methods for minimally invasive peripheral body temperature measurement in birds
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Measures of CTmax and gene expression in <em>Daphnia</em> clones acclimated to three temperatures
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European Sempervivum tectorum soil pH and iButton soil temperature time series measurement raw data.
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Snowpack, precipitation, and temperature measurements at the Central Sierra Snow Laboratory for water years 1971 to 2025
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Full vector low-temperature magnetic measurements of geologic materials
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Daily sea-surface temperature measurements, collected and provided by the Shore Stations Program, La Jolla CA, 1916 - May 2019
Personnel from the Stephen Birch Aquarium-Museum at Scripps take daily temperature and salinity samples from the end of the Scripps Pier at the sea surface and a depth of about 5 meters. The proximity of Scripps Pier to the deep waters at the head of La Jolla submarine canyon results in data quite representative of oceanic conditions. Scripps Pier is a total of 1084 ft. long (330.4 M) and 22.5 ft. wide for most of it's length. However it is 46.0 ft. wide at the end where the lab/pump house structure is situated with the west wall standing 88.0 ft. from the end of the pier (=996 ft. from the shore). The orientation is 277 / 97 degrees magnetic, 14 degrees East variation. The deck of the pier is 33.5 ft. above Mean Low Low Water (MLLW). Data provided by Shore Stations Program with current funding provided by the "California Department of Parks and Recreation, Division of Boating and Waterways, Award# DPR-C1370020". Data are collected by staff aquarists and volunteers with the Birch Aquarium at Scripps. Contact shorestation@ucsd.edu if you have questions
Cruise measurements (temperature, salinity, density, chlorophyll, C14, phosphate, silicate, nitrate, nitrite) collected from CTD casts aboard CalCOFI cruises in the California Current, and averaged annually and by cruise, from 1984 - 2019 (updated periodically).
Water column bottle sample data averaged across up to 46 standard stations (inshore and offshore) per cruise and then averaged over a varying number of cruises in any one year to give an annual average.
2-minute PALMOS automatic weather station meteorological measurements (precipitation, radiation, cloud base, temperature, etc.) from Palmer Station Antarctica, 2001 - March 2017.
Automated weather observation station at Palmer Station Antarctica using Coastal Environment sensors. Started recording in November 2001. Overlapped for two years with manual observations. In December 2003, the PalMOS automated report generator was brought online and the manual observations discontinued. The sole manual observation remaining is the daily snow-level and new snow level measurements.
In situ temperature and brGDGTs measurements in soils from the Tropical Andes of Colombia and a tropical soil brGDGT compilation dataset
<p>This dataset contain:</p> <p>Table S1. Air and soil mean monthly temperatures from the new 16 sites in the Eastern Cordillera of Colombia with data presented in this study.<br> Table S3. Soil Branched glycerol dialkyl glycerol tetraethers (brGDGTs) from the Eastern Cordillera of Colombia and data compilation from the tropics.<br> Table S4. nonlinear brGDGTs predictors for the tropical compilation data.</p> <p> </p>
Temperature and humidity stationary measurements in the Greater Paramaribo Region
<p>The data include air temperature and humidity measured with wireless sensors (Kestrel Drop D2). The www.groenparamaribo.org dashboard shows data temperature data and is updated monthly till Oct 2023. On the upper right of the dashboard, you can view temperatures over time for all sensors at once. You can choose how the 24hrs per day shall be aggregated: to the daily mean, the maximum or minimum temperature recorded by each sensor. Graphs for individual sensors might have missing data (i.e., no data is shown) if the sensor was only placed after a certain time, the battery was out at that time or the sensor was stolen. A separate file for measurement locations is provided. Details on the data collection and learning are presented in the metadata document.</p><p>The data were collected for the Tropenbos Suriname and the University of Twente-Faculty Geo-information Science and Earth Observation (ITC) project ' (UTSN 31-123-M-G ), Keeping track of changes towards healthy-living in a green urban Suriname "(project number NWA.1418.20.010). And must be accredited as follows: </p><p><br><i>Lisa Best, Davita Obergh, Rudi van Kanten, Nina Schwarz, Louise Willemen, Temperature and humidity stationary measurements in the Greater Paramaribo Region, Suriname, product of ''Keeping track of changes towards healthy-living in a green urban Suriname "(project number NWA.1418.20.010) by Tropenbos Suriname and University of Twente-ITC. DOI: 10.5281/zenodo.6778859. Licensed under the </i><a href="https://creativecommons.org/licenses/by-nc-sa/4.0/"><i>Creative Commons License CC BY-NC-SA 4.0</i></a><i>.</i></p>
Distributed ground surface temperature measurements in Terelj, Mongolia
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Mechanical data of rotary shear experiments, temperature measurements, and temperature numerical models for the manuscript: "Mechanical energy dissipation during seismic dynamic weakening in calcite-bearing faults"
<p>All data included in this data repository is ancillary to the manuscript "Energy dissipation during dynamic weakening in calcite-bearing fault rocks", submitted to Journal of Geophysical Research: Solid Earth. </p><p>The data consists in time series of high velocity friction experiments run with SHIVA (INGV, Rome), time series acquired from a two-color pyrometer (UC3M), the synchronization of the two, and numerical models. The data format is .mat, proprietary to Matlab, but they can be easily accessed with Python (see <a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.loadmat.html">link</a>). Each .mat contains vector of the measured variables when opened from Matlab, or dictionaries when opened using the scipy.loadmat() function. </p><p>SHIVA and PYRO red data (calibrated data), fin data (synchronized data), and shivaRED vect data (numerical model data) are included in this data repository in separate folders. Numerical models are grouped in subfolder by type of model (the relation fin data to model is 1:n). We included the scripts to convert SHIVA raw data into SHIVA red data (<a href="https://github.com/aretu/shivaUNIX">link to shivaUNIX</a>), SHIVA and PYRO red data into fin data (/scripts/syncing2021.m), to obtain numerical models from fin data (<a href="https://github.com/aretu/shivaRED">link to shivaRED</a>), and to plot data (/scripts/making plots.ipynb).</p>
Dataset for publication "Uncertainty assessment for very high temperature thermal diffusivity measurements on molybdenum, tungsten and isotropic graphite"
<p>Experimental data presented in the paper:</p> <p>Hay B., Beaumont O., Failleau G., Fleurence N., Grelard M., Razouk R., Davée G., Hameury J., Uncertainty assessment for very high temperature thermal diffusivity measurements on molybdenum, tungsten and isotropic graphite, <em>International Journal of Thermophysics</em> 43:2 (2022). https://doi.org/10.1007/s10765-021-02926-6.</p> <p>Excel file contains the data for Figures 3 to 5.</p>
The fiber optic thermometer was used to measure the plasma discharge region temperature.
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Air temperature and thermal comfort data measured and modelled for 121 workplaces in the Upper Rhine Valley
<p>The uploaded files contain the measured and modelled indoor data at different workplaces in the Upper Rhine Valley between August 1, 2021, and July 31, 2022 presented in the article "Predicting Indoor Air Temperature and Thermal Comfort in Occupational Settings Using Weather Forecasts, Indoor Sensors, and Artificial Neural Networks" by Sulzer et al. (2023), <a href="http://doi.org/10.1016/j.buildenv.2023.110077">doi.org/10.1016/j.buildenv.2023.110077</a>. Information about the characteristics of each workplace can be found in the appendix of the article. For every workplace two files are uploaded, one for the data of the indoor air temperature (Ta) and one for indoor physiological equivalent temperature (PET). The workplace ID and variable are stated in the filename. The columns in the files contain the following data:</p> <ul> <li>"Datetime (UTC)": This column contains the timestamp in UTC of the starting point of the interval used for the one-hour mean values .</li> <li>"MoBiMet data": This column contains the one-hour mean values of Ta or PET of the data derived every five minutes by the low-cost Mobile Biometeorology System (MoBiMet) at the corresponding workplace in °C. The MoBiMet are presented in detail in <a href="http://doi.org/10.3390/s22051828">doi.org/10.3390/s22051828</a>.</li> <li>"Used for": This column contains the information if the data point was used for training of the models (t), evaluation of the models (e), or not used for model training or evaluation due to missing indoor observation data (n).</li> <li>"Product 0 (ICON_outdoor)": This column, in the files for the indoor air temperature, contains the ICON-D2 data of the air temperature 2m a.g.l. in °C of the grid cell in which the associated work station is located.</li> <li>"Product 0 (ICON_outdoor) air temperatur 2m (C) input for PET calculation using RayMan","Product 1 (ICON_outdoor) vapor pressure 2m (hPa) input for PET calculation using RayMan","Product 1 (ICON_outdoor) wind speed 10m (m/s) input for PET calculation using RayMan", and "Product 1 (ICON_outdoor) global radiation surface (W/m²) input for PET calculation using RayMan": This columns contain the data of the outdoor air temperature 2m a.g.l. in °C, the vapor pressure 2m a.g.l., derived from the ICON-D2 weather forecast data of the grid cell in which the associated work station is located, which were used in RayMan Pro to calculate the PET for outdoors.</li> <li>"Product 2 (ANN_Generic)": This column contains the indoor data of PET or air temperature in °C modelled by an artificial neural network using generic data as input. The generic data contain hourly solar altitude and azimuth at each location, the weekday, and a sine and cosine function of the daily and yearly cycle.</li> <li>"Product 3 (ANN_AWS) without past data": This column contains the indoor data of PET or air temperature in °C modelled by an artificial neural network using generic data and the meteorological data of air temperature, vapor pressure, mean sea level pressure, global radiation, longwave downwelling radiation, and wind speed of an automated weather station in Freiburg (Station FRCHEM; 48°00’04’’ N; 7°50’55’’ E).</li> <li>"Product 3 (ANN_AWS) with past data": This column contains similar data than the column before but the artificial neural network models used "past data" of the automated weather station as additional input variables to model indoor air temperature and PET in °C. Additional to the hourly average of the meteorological data for each actual time (t), hourly averages for t-1 h, t-3 h, t-6 h, t-12 h, and t-24 h of air temperature, global radiation, and Longwave downwelling radiation are used as so called "past data".</li> <li>"Product 4 (ANN_ICON) without past data": This column contains the indoor data of PET or air temperature in °C modelled by an artificial neural network using generic data and the meteorological data of air temperature, vapor pressure, mean sea level pressure, global radiation, longwave downwelling radiation, and wind speed derived from the ICON-D2 weather forecast data of the grid cell in which the associated work station is located.</li> <li>"Product 4 (ANN_ICON) with past data": This column contains similar data than the column before but the artificial neural network models used "past data" of the ICON-D2 weather forecast data as additional input variables to model indoor air temperature and PET in °C. Additional to the hourly average of the meteorological data for each actual time (t), hourly averages for t-1 h, t-3 h, t-6 h, t-12 h, and t-24 h of air temperature, global radiation, and Longwave downwelling radiation are used as so called "past data".</li> <li>"Product 5 (ANN_Mixed) without past data": This column contains the indoor data of PET or air temperature in °C modelled by the same artificial neural network models as in Product 3 but applied for the same input data of Product 4.</li> <li>"Product 5 (ANN_Mixed) with past data": This column contains similar data than the column before but also takes into account the "past data".</li> </ul> <p>The data of Product 3 (ANN_AWS) and Product 5 (ANN_Mixed) are only available for locations in Freiburg, because the data of an automated weather station in Freiburg was used.<br> Data which is not available is stated as NA.</p>
Measurements of rate coefficients of CN+, HCN+ and HNC+ collisions with H2 at cryogenic temperatures
<p>Raw experimental data and post-processing scripts for DOI: 10.1063/5.0153699</p>
ibutton temperature measurements - Vallon de Nant
<pre>A field campaign was set up from July 2021 to September 2023 in order to have in-situ temperature measurements, which represent an additional data source for estimating the performance of the temperature products and better describe the local site effects in the valley. A series of 28 mini-temperature sensors (ibutton loggers) distributed in the basin is installed, in particular at the bottom of the valley. 28 loggers (12 masts + 18 single loggers) were installed in August 2021. The data were recorded in August 2022 and the loggers were finally uninstalled in September 2023. The sensors are installed on a mast, under a plastic shelter at 2 m from the ground. The measurement time step is 2 hours. </pre>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
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.
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.
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.
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.