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86 results for “Laboratory measurement”
Measurements of leaf litter Carbon and Nitrogen from the Coweeta LTER Terrestrial Gradient sites, Coweeta Hydrological Laboratory, Otto, NC
This project was started by Haines and Crossley in 1992 to compare leaf litter weights among the five gradient plots (though data from the first collections were not included in this dataset because the original dataset did not represent a complete quarter of collection). Litter is collected from ten 91.4 x 91.4 cm leaf collectors within each of the gradient plots. Litter is collected on a quarterly basis (monthly in the autumn). The litter is then separated by category, dried, weighed, and processed in a Wiley mill for later carbon and nitrogen analyses. Since the project first started, the collection process has expanded to include non-leaf litter (e.g., lichens, bark, and seeds), fine twigs (0-2.5 cm diameter), and medium twigs (2.5-10 cm diameter).
Soil respiration and flux measurements from Watersheds 17 and 18,Coweeta Hydrologic Laboratory, Otto, NC.
In order to better understand soil respiration and Carbon Dioxide (CO2) fluxes, 90 closed container chambers were installed in 18 plots located at upper, mid, and lower-slope lcoations within Coweetas watersheds 17 and 18. For eighteen months, soil moisture, soil temperature, and CO2 measurements were taken through the collars of pipes located within each plots. These measurements were used to determine total flux and other statisitcal information in order to better understand these forest processes.
Water Level, Water Temperature, and Flow Measurements from the Ball Creek weir house #9, Coweeta Hydrologic Laboratory, Otto, NC.
This data set contains water level, water temperature, and calculated discharge values from the Ball Creek weir house #9, Coweeta Hydrologic Laboratory, Otto, NC. Using a pressure transducer, measurements are taken every 60 seconds with the average, minimum, and maximum values for water pressure and water temperature saved to the output data table hourly. Water level and discharge are calculated using the hourly average water pressure, and saved to the online data files.
Data Set - Laboratory measurement of the wave–induced plastic particles motion: The influence of wave period, plastic size and plastic density
<p><strong>Data set - Laboratory measurement of the wave–induced plastic particles motion: The influence of wave period, plastic size and plastic density</strong></p> <p>This data set describes the wave flume experimental data on the wave-induced plastic particles motion induced by different wave conditions and different plastic particles density and size. A manuscript is currently under review describing the analysis of the data.</p> <p>The data set is divided in two parts:</p> <p>- <strong>Wave flume hydrodynamics</strong>. With measured water surface elevation at different locations within the wave flume. These data are stored in txt files with headings describing the type of measurement, i.e. wave paddle motion, water surface elevation at different sensors, synchronization signal for the video-cameras.</p> <p>- <strong>Lagrangian trajectories. </strong>hdf5 files with information of the particles position, velocity and time (with respect to the synchronization signal in the respective hydrodynamic file) for each experiment. Two tar.gx files have been uploaded with trajectories information:</p> <p> - TOPIOS_Trajectories_FloatingParticles.tar.xz, with information of floating plastic particles and,</p> <p> - TOPIOS_Trajectories_NonfloatingParticles.tar.xz, with information of non-floating plastc particles.</p> <p>An excel file with information of filenames, cross-shore locations of sensors, plastic particles and wave conditions is also uploaded (TOPIOS_Control_exp.xlsx).</p> <p>Any question regarding the data can be addressed at jose.alsina@upc.edu</p>
A Novel Laboratory Technique for Measuring Grain Size Specific Transport Characteristics of Bed Load Pulses
<p>We present a novel, time-efficient and non-destructive laboratory technique to investigate grain size specific transport characteristics of bed load pulses. The method consists of a through-water, high-resolution image acquisition followed by the application of a supervised color classification algorithm (Gaussian Maximum Likelihood Classification). Quality assessment based on a confusion matrix approach and basic random sampling showed a high classification performance. By statistically analyzing the temporal and spatial color distribution of the experimental reach, characteristic parameters to describe the propagation behavior were determined. The analyzed bed load pulse consisted of five different grain size classes of dyed quartz sand and gravel, each having a unique color. The initial experimental bed was uni-colored and contained the same size fractions as the augmented pulse.</p>
Datasets for "Precision and accuracy of single-molecule FRET measurements – a multi-laboratory benchmark study"
<p>Supplementary material (raw data) for Fig. 2 in "<strong>Precision and accuracy of single-molecule FRET measurements – a multi-laboratory benchmark study</strong>" to be published with Nature Methods</p> <p>The confocal data is given in ht3 and hdf5 format.</p> <p>For the TIRF data the original TIFF-stacks are uploaded including the calibration files.</p>
Laboratory data of measurements conducted on an n-decane saturated limestone sample using the forced-oscillation method
<p>This supporting information provides the numerical results of the laboratory experiments conducted on an n-decane saturated limestone sample with varying dead fluid volume. The supporting information includes: (1) the extensional attenuation, Poisson ratio, elastic moduli and strains in the rock measured at 0.1 Hz with the dead volume varying from 2 ml to 260 ml and also with the open fluid line, and (2) the frequency dependences of the attenuation, elastic moduli, Poisson ratio and strains obtained in the frequency range from 0.1 Hz to 120 Hz.</p>
Transformer Inrush Measurements in a Distribution Grid Laboratory
<p>This data set contains measurement data of distribution transformer inrush transients obtained in the Distribution Grid Laboratory at the IAEW at RWTH Aachen University. Within the framework of the investigations, a medium voltage feeder with one or multiple medium/low voltage transformers is energised. The setup is either supplied by the public medium voltage grid or by a grid-forming converter. In the latter case, grid voltage distortions can be observed during the inrush transient due to output current limitation of the converter.</p> <p>The inrush measurements were carried out within the framework of the project DiSCo (Distribution System Inrush From Grid-Forming Converters). The authors gratefully acknowledge funding by E.ON SE as well as the technical support in development, execution and analysis of the experimental investigations by Westnetz GmbH. In addition, we would like to thank the colleagues of the Institute for Power Generation and Storage Systems (PGS) for their support and the informative discussions.</p>
Dataset in support of "Laboratory wave and stress measurements quantify the aerodynamic sheltering in extreme winds" by Tan et al. (2023, JGR: Oceans)
<p><strong>Data introduction:</strong></p> <p> There are three datasets used in this research: dataset 1 from Wind-Only (WO) experiment, dataset 2 from JONSWAP experiment with 10-cm significant wave height (J10), and dataset 3 from monochromatic wave experiment with 7.5-cm amplitude (M7.5).</p> <p> Each dataset contains quality-controlled data of the respective experiment mentioned above. The data files are in the mat (MATLAB) format. There are 9 mat files in each dataset, and each file represents data collected under a specific wind forcing condition, with the fan frequency in the 10-50 Hz range with 5 Hz interval.</p> <p> Each file contains four variables: <em>seg</em> (water elevation time series collected by the wave-wire with the units of <em>m</em>, demeaned and detrended), <em>U</em> (along-tank, downwind component of wind sampled by the IRGASON anemometer with the units of <em>m/s</em>), <em>V</em> (cross-tank component of wind sampled by the IRGASON anemometer with the units of <em>m/s</em>), and <em>W</em> (vertical component of wind collected by the IRGASON anemometer with the units of m/s). All four variables were collected at a sampling frequency of 20 Hz.</p>
Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution - Part B - Particle Number Concentrations - Dataset
<p>This repository contains the data used for the analysis of the paper "Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution - Part B - Particle Number Concentrations (PNC)" which is under submission.</p> <p> </p> <p>The experimental conditions and the instruments used are detailed in Bulot, F.M.J.; Russell, H.S.; Rezaei, M.; Johnson, M.S.; Ossont, S.J.J.; Morris, A.K.R.; Basford, P.J.; Easton, N.H.C.; Foster, G.L.; Loxham, M.; Cox, S.J. Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution. <em>Sensors</em> <strong>2020</strong>, <em>20</em>, 2219. https://doi.org/10.3390/s20082219</p> <p>The files are available in .csv and in .rds (for R) formats. For details about the measurement equipment used<br> during this study, please refer to the methods section of the paper.</p> <p> </p> <p>sensors_raw.csv contains the following headers:</p> <ul> <li>Bin0 to Bin15: Alphasense OPC-R1 particle number concentrations for different size bins</li> <li>Bin[1-3-5-7]MToF: mean time of flight of particles within the corresponding size bins of the Alphasense OPC-R1</li> <li>Checksum: checksum of the Alphasense OPC-R1</li> <li>SFR: sample flow rate of the Alphasense OPC-R1</li> <li>Humidity: relative humidity measured by the Alphasense OPC-R1</li> <li>Temperature: temperature measured by the Alphasense OPC-R1</li> <li>SamplingPeriod: sampling period of the Alphasense OPC-R1</li> <li>gr03um, gr05um, gr10um, gr25um, gr50um, gr100um: PNC measured by the Plantower PMS5003</li> <li>n05, n1, n25, n4, n10: PNC measured by the Sensirion SPS30</li> <li>humidity: relative humidity measured by a Sensirion SHT-3x</li> <li>temperature: temperature measured by a Sensirion SHT-3x</li> <li>sensor: id of the sensors</li> <li>site: name of the air quality monitor hosting the sensors</li> <li>exp: name of the experiment conducted</li> <li>source: source used to generate PM (incense or candle)</li> <li>variation: whether the sensors were exposed to stable or peak concentrations of PM pollution</li> <li>date: date in format yyyy-mm-dd HH:MM:SS</li> </ul> <p>For more explanations about the fields of individual sensors, please refer to their manual (Alphasense OPC-R1: https://kolegite.com/EE_library/datasheets_and_manuals/sensors/OPC/072-0500_OPC-R1_manual_issue_1_250219.pdf ; Plantower PMS5003: https://www.aqmd.gov/docs/default-source/aq-spec/resources-page/plantower-pms5003-manual_v2-3.pdf ; Sensirion SPS30: https://sensirion.com/products/catalog/SPS30/)</p> <p> </p> <p>ops.csv and ops.rds contains the readings from the OPS with the following cut sizes for the bins:</p> <ul> <li>Bin 1 Cut Point (um),0.300</li> <li>Bin 2 Cut Point (um),0.374</li> <li>Bin 3 Cut Point (um),0.465</li> <li>Bin 4 Cut Point (um),0.579</li> <li>Bin 5 Cut Point (um),0.721</li> <li>Bin 6 Cut Point (um),0.897</li> <li>Bin 7 Cut Point (um),1.117</li> <li>Bin 8 Cut Point (um),1.391</li> <li>Bin 9 Cut Point (um),1.732</li> <li>Bin 10 Cut Point (um),2.156</li> <li>Bin 11 Cut Point (um),2.685</li> <li>Bin 12 Cut Point (um),3.343</li> <li>Bin 13 Cut Point (um),4.162</li> <li>Bin 14 Cut Point (um),5.182</li> <li>Bin 15 Cut Point (um),6.451</li> <li>Bin 16 Cut Point (um),8.031</li> <li>Bin 17 Cut Point (um),10.000</li> </ul> <p>nanotracer.csv and nanotracer.rds contain the measurements from the Nanotracer:</p> <ul> <li>N.1.: particles/cm3</li> <li>dp_avg.1.: mean diameter of the particles (nm)</li> <li>P.1.:</li> <li>S_al.1.: Lung Deposited Surface Area in um2/cm3</li> </ul> <p> </p> <p>experimental_conditions.csv and experimental_conditions.rds contain the end dates and start dates of each of the experiment conducted.</p> <p> </p> <p> </p> <p>"pm100_cf1","pm10_cf1","pm25_cf1"</p> <p> </p> <p> </p>
Laboratory measurements of nitrous oxide production rates in agricultural soils from Lancaster, PA, estuarine sediments from the Scheldt Estuary Belgium/Netherlands, and estuarine soils from the Delaware River NJ under gradients of physicochemical perturbation
A set of experiments was performed to test 1) how various physicochemical perturbations (salinity, zinc, temperature, soil moisture, and pH) influenced denitrification and nitrous oxide production on short timescales (<1 day) in agricultural soils from Lancaster, PA, USA, 2) how variation in a single parameter (salinity) influenced rates of denitrification and nitrous oxide production in sediments that experience a range in that parameter (tidal freshwater, oligohaline, and mesohaline estuarine sediments from the Scheldt River estuary Belgium/Netherlands) on short timescales (< 1 day), and 3) how denitrification and nitrous oxide production along with key functional gene expression in tidal freshwater estuarine soils from the Delaware River, NJ, USA responded to a long-term (6 month) change in a single parameter (salinity) in a press experiment with subsequent short-term (< 1 day) pulses. In the final long-term experiment, nitrite reductase (nirS) and nitrous oxide reductase (nosZ) gene expression were also measured at three timepoints (days 7, 35, and 110).
Microclimate Measurements from the Terrestrial Gradient Plots, Coweeta Hydrologic Laboratory, North Carolina
The terrestrial gradient study at Coweeta compares vegetation, soils, and understory microclimate of five sites: 118 low elevation (782 m) pine-oak, 218 low elevation (795 m) cove hardwood, 318 low elevation (865 m) mixed oak, 427 high elevation (1001 m) mixed oak, 527 high elevation (1347 m) northern hardwood. Understory microclimate stations were installed in representative locations at the downslope margin of each 20 x 40 m gradient plot (within the 80 x 80 m plot).
Continuously measured soil moisture, soil temperature, and air temperature from stations in Watershed 2, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from stations in Watershed 5, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from stations in Watershed 7, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from a side-slope station located in Watershed 27, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from a ridge station in Watershed 18, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from stations in Watershed 32, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from stations in Watershed 36, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Data S1. Laboratory behavioral data from: Measuring the fitness advantage conferred by autotomy in the wild
<p>Data S1. Laboratory behavioral data. The composition is summarized in figure S1.</p> <p>Autotomy, the self-amputation of body parts, serves as an anti-predator defense in many taxonomic groups of animals. However, its adaptive value has seldom been quantified. Here, we propose a novel modeling approach for measuring the fitness advantage conferred by the capability for autotomy in the wild. Using a predator-prey system where a land snail autotomizes and regenerates its foot specifically in response to snake bites, we conducted a laboratory behavioral experiment and a 3-year multi-event capture–mark–recapture (CMR) study. Combining these empirical data, we developed a hierarchical model and estimated the basic life history parameters of the snail. Using samples from the posterior distribution, we constructed the snail's life table as well as that of a snail variant incapable of foot autotomy. As a result of our analyses, we estimated the monthly encounter rate with snake predators at 3.3% (95% CI: 1.6–4.9%), the contribution of snake predation to total mortality until maturity at 43.3% (15.0–95.3%), and the fitness advantage conferred by foot autotomy at 6.5% (2.7–11.5%). This study demonstrated the utility of the multi-method hierarchical modeling approach for the quantitative understanding of the ecological and evolutionary processes of anti-predator defenses in the wild.</p>
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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.
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.