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1,509 results for “Calibrations”
Crowdsourced dataset of firefly trajectories obtained by automated stereo calibration of 360-degree cameras
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Atmospheric data used for calibrating the tropopause in global chemistry-climate or chemistry-transport models
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Data from: Dispersal in a house sparrow metapopulation: an integrative case study of genetic assignment calibrated with ecological data and pedigree information
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Ancillary Files for Paper: Implementation of the XY interaction family with calibration of a single pulse
<p>These are the supplementary materials for the paper `Implementation of the XY interaction family with calibration of a single pulse`.</p> <p>The analysis and plots from the paper can be recreated from the Jupyter notebook `XY Paper Plotting<br> and Analysis.ipynb`. The notebook depends on the helper functions in the python files<br> `chevron_analysis.py`, `fidelity_analysis.py`, `models.py`, and `utils.py`. The data is stored in<br> JSON and txt files that are in a compressed tarball that can be extracted with the following commands:</p> <p>```bash<br> > tar xjf data.tar.bz2<br> ```</p>
KALI: calibration and validation results
<p>The presented .zip archive consists of calibration and validation results we obtained while investigating the effect of calibration data length on the performance of different hydrological models.</p> <p>For more information, please visit our GitHub repository at <a href="https://github.com/hydrogo/KALI">https://github.com/hydrogo/KALI</a>.</p>
Calibrated data of stable water isotope measurements in water vapour at 8 m a.s.l. on the port side of the ship, made in the austral summer of 2016/2017 around the Southern Ocean during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>This data set includes the calibrated data of stable water vapour isotope (δ18O, δ2H, deuterium excess) and water vapour mixing ratio measurements at approximately 8 m a.s.l. on the port of the ship, taken around the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from November 2016 to April 2017 using a Picarro laser spectrometers L2120. The data provide continuous timelines of atmospheric water vapour properties in the marine boundary layer for studies of the atmospheric water cycle.</p> <p>The raw data from which this calibrated dataset originates has been published separately (Kozachek, 2020; DOI 10.5281/zenodo.3667535).</p> <p>Two other calibrated stable water isotope measurement datasets were also collected during ACE. They differ by the location of measurement on the ship: 8 m a.s.l on the starboard side (DOI: 10.5281/zenodo.3739335) and 13.5 m a.s.l (DOI: 10.5281/zenodo.3250790).</p> <p><strong>Dataset contents</strong></p> <p>Measurements on portside:</p> <ul> <li>ACE_watervapour_isotopes_SWI8-ps_1h.csv, data file, comma-separated values</li> <li>ACE_watervapour_isotopes_SWI8-ps_5min.csv, data file, comma-separated values</li> <li>cal_runs_SWI8-ps.csv, metadata, comma-separated values</li> <li>cal_flag_times_SWI8-ps.csv, metadata, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p>NaN values denote missing values which occur because of e.g., maintenance, instrument calibration, large cavity variations.</p> <p><strong>Dataset license</strong></p> <p>This calibrated stable water isotope measurements in water vapour is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Dataset for publication "Setup and Characterisation of Reference Current-to-Voltage Transformers for Wideband Current Transformers Calibration up to 2 kA"
<p>This is dataset related to paper published in AMPS 2019:</p> <p>Y. Chen, E. Mohns, H. Badura, P. Räther and M. Luiso: Setup and Characterisation of Reference Current-to-Voltage Transformers for Wideband Current Transformers Calibration up to 2 kA, <a href="https://doi.org/10.7795/EMPIR.17NRM01.CA.20190411">https://doi.org/10.7795/EMPIR.17NRM01.CA.20190411</a></p> <p>Excel file contains the data for Figures 7, 8, 9 and 10.</p>
Reliably predicting pollinator abundance: challenges of calibrating process-based ecological models
<p>1. Pollination is a key ecosystem service for global agriculture but evidence of pollinator population declines is growing. Reliable spatial modelling of pollinator abundance is essential if we are to identify areas at risk of pollination service deficit and effectively target resources to support pollinator populations. Many models exist which predict pollinator abundance but few have been calibrated against observational data from multiple habitats to ensure their predictions are accurate.</p> <p>2. We selected the most advanced process-based pollinator abundance model available and calibrated it for bumblebees and solitary bees using survey data collected at 239 sites across Great Britain. We compared three versions of the model: one parameterised using estimates based on expert opinion, one where the parameters are calibrated using a purely data-driven approach and one where we allow the expert opinion estimates to inform the calibration process.</p> <p>3. All three model versions showed significant agreement with the survey data, demonstrating this model's potential to reliably map pollinator abundance. However, there were significant differences between the nesting/floral attractiveness scores obtained by the two calibration methods and from the original expert opinion scores.</p> <p>4. Our results highlight a key universal challenge of calibrating spatially-explicit, process-based ecological models. Notably, the desire to reliably represent complex ecological processes in finely mapped landscapes necessarily generates a large number of parameters, which are challenging to calibrate with ecological and geographical data that is often noisy, biased, asynchronous and sometimes inaccurate. Purely data-driven calibration can therefore result in unrealistic parameter values, despite appearing to improve model-data agreement over initial expert opinion estimates. We therefore advocate a combined approach where data-driven calibration and expert opinion are integrated into an iterative Delphi-like process, which simultaneously combines model calibration and credibility assessment. This may provide the best opportunity to obtain realistic parameter estimates and reliable model predictions for ecological systems with expert knowledge gaps and patchy ecological data.</p>
All simulation results, figures and code regarding the manuscript: Calibrating models of cancer invasion: parameter estimation using Approximate Bayesian Computation and gradient matching
<p>We present two different methods to estimate parameters within a partial differential equation (PDE) model of cancer invasion. The model describes the spatio-temporal evolution of three variables -- tumour cell density, extracellular matrix density and matrix degrading enzyme concentration -- in a one-dimensional tissue domain. The first method is a likelihood-free approach associated with Approximate Bayesian Computation (ABC); the second is a two-stage gradient matching method based on smoothing the data with a Generalized Additive Model (GAM) and matching gradients from the GAM to those from the model. Both methods performed well on simulated data. To increase realism, additionally we tested the gradient matching scheme with simulated measurement error and found that the ability to estimate some model parameters deteriorated rapidly as measurement error increased.</p>
A quantitative method to calibrate the SWAN wave model - pre-processed model outputs
<p>The pre-processed MAT files for the paper 'A quantitative method to calibrate the SWAN wave model'</p>
Dataset for testing the calibration of the variant prediction methods
<p>Dataset used for testing the calibration of 6 methods for predicting the impact of single nucleotide variants in the publication: </p> <p><em>Benevenuta S, Capriotti E, Fariselli P</em>. (2021). Calibrating variant-scoring methods for clinical decision making. <strong>Bioinformatics</strong>. DOI: <a href="http://doi.org/10.1093/bioinformatics/btaa943">10.1093/bioinformatics/btaa943</a>.</p> <p>The file contains the following columns:</p> <ol> <li>CHROM: Chromosome number </li> <li>POS: Chromosome coordinate</li> <li>REF: Reference Allele </li> <li>ALT: Alternative Allele </li> <li>Coding: Coding Variants (Yes/No) </li> <li>Effect: Variant impact (Pathogenic/Benign) </li> <li>DANN: DANN output </li> <li>PhDSNP: PhD-SNPg output </li> <li>FATHMM: FATHMM output </li> <li>CADD: CADD output </li> <li>DeepSea: DeepSea output</li> <li>Eigen: Eigen output</li> </ol> <p> </p> <p> </p> <p> </p> <p> </p>
Insights from empirical analyses and simulations on using multiple fossil calibrations with relaxed clocks to estimate divergence times
<p>Relaxed clock methods account for among-branch-rate-variation when estimating divergence times by inferring different rates for individual branches. In order to infer different rates for individual branches, important assumptions are required. This is because molecular sequence data does not provide direct information about rates, but instead provides direct information about the total number of substitutions along any branch, which is a product of the rate and time for that branch. Often, the assumptions required for estimating rates for individual branches depend heavily on the implementation of multiple fossil calibrations in a single phylogeny. Here, we show that the basis of these assumptions is often critically undermined. First, we highlight that the temporal distribution of the fossil record often violates key assumptions of methods that use multiple fossil calibrations with relaxed clocks. With respect to "node calibration" methods, this conclusion is based on our inference that different fossil calibrations are unlikely to reflect the relative ages of different clades. With respect to the fossilised-birth-death-process, this conclusion is based on our inference that the fossil recovery rate is often highly heterogeneous. We then demonstrate that methods of divergence time estimation that use multiple fossil calibrations are highly sensitive to assumptions about the fossil record and among-branch-rate-variation. Given the problems associated with these assumptions, our results highlight that using multiple fossil calibrations with relaxed clocks often does little to improve the accuracy of divergence time estimates.</p> <p> </p>
NDVI datasets related with the article "A comparative study of cross-product NDVI dynamics in the Kilimanjaro region - a matter of sensor, degradation calibration, and significance"
<p>AHVRR GIMMS and MODIS NDVI input datasets and main results on seasonal and long-term NDVI dynamics related with the manuscript "A comparative study of cross-product NDVI dynamics in the Kilimanjaro region - a matter of sensor, degradation calibration, and significance" recently published in Remote Sensing 8(2), 159, doi: 10.3390/rs8020159.</p>
floodX Preprocessed Calibration Data
<p><strong>Warning</strong></p> <p><strong>Since the first publication of this data, the flow velocity data (data sources "c3_v_radar_hach" and "c3_v_radar_nivus") have been found to contain systematic errors of up to 50%. The absolute velocity measurement values must be disregarded.<br> ----------------------------------------------------------------------------------------------------------------------</strong></p> <p>This package contains a preprocessed subset of the flooding experiments for which the data quality is appropriate for <strong>urban flood model calibration and validation</strong> research. The data are organized by experiment in folders named after the experiment numbers. The package includes text-based data only – videos and images of flooding can be found in the “floodX Flooding Videos” and “floodX Flooding Images” packages, respectively.</p> <p> </p> <p>This package belongs to a collection of packages containing data collected from the floodX urban flash flood experiments.</p> <p> - floodX Raw Data, Metadata, and Preprocessing Code (doi: 10.5281/zenodo.830505)<br> - floodX Preprocessed Monitoring Data (doi: 10.5281/zenodo.830511)<br> - floodX Preprocessed Calibration Data (doi: 10.5281/zenodo.830513)<br> - floodX Flooding Videos (doi: 10.5281/zenodo.830451)<br> - floodX Flooding Images (doi: 10.5281/zenodo.830501)<br> - floodX Data Logger Images (doi: 10.5281/zenodo.830507)<br> - floodX Data Logger Videos (doi: 10.5281/zenodo.830504)<br> - floodX Documentation (doi: 10.5281/zenodo.830506)</p>
WWV calibration data from Piradar
<p>Piradar in Hamilton Branch State Park, South Carolina with non-resonant 200 ft. tip-to-tip dipole.</p> <p>Using WWV recordings as a performance reference.</p>
Dataset: Thermal noise calibration of functionalized cantilevers for force microscopy: effects of the colloidal probe position.
<p>Dataset for article "Thermal noise calibration of functionalized cantilevers for force microscopy: effects of the colloidal probe position"</p><p>The raw data is in the 6 zip files (AIO*.zip), which contains thermal noise spectra measured on the raw cantilevers close to the free end (folders AIO#, where #=1, 2 or 3 for samples A, B or C), or on the loaded cantilever at various positions along its length (folders AIO#-ScanHF, where #=1, 2 or 3 for samples A, B or C). The file format is Matlab data file (.mat), it include the vectors f (for frequency axis, in Hz) and p (power spectrum density, in m^2/Hz). Other variables are erreur (some internal check that the calibration of the interferometer is pertinent) and PointW (mean intensity collected by the interferometer, and mean contrast on the 2 quadrature signals). For the loaded cantilever, we also record the laser spot position (XFaisceau and YFaisceau, in µm, origin close to the free end on the cantilever), some timing information to track for drifts, and ellipse (a calibration step of the quadrature phase interferometer).</p><p>The SEM images of the samples are included in the zip file SEMimages.zip</p><p>All analysis scripts (Matlab .m files) are included:</p><ul><li>AnalyseAll.m reads the raw data files and extract all the pertinent information, saving it to file AnalyseAll.mat</li><li>Analysis_cp analyses the pre-processed data with the single contact point model</li><li>Analysis_endload analyses the pre-processed data with the rigid end load model</li><li>figspectrum.m creates Fig. 4 of the article</li><li>plot_cp_endload.m creates Fig. 5 and 6 of the article</li></ul><p>All other scripts (.m) are dependencies that are necessary for the 3 former scripts to run. All scripts are commented and should be self explanatory. Of interest are the scripts mode_shape_cp.m and mode_shape_endload.m, which compute the resonant mode shape of a loaded cantilever for the two models, when given the parameters on the load size and position.</p>
Geometric calibration of a double-line X-ray cone-beam tomography system
<p>This dataset correspond to the raw data and measurements presented in the article "Geometric calibration of a double-line X-ray cone-beam tomography system". In this study, an existing single-line calibration method is extended to the case of a double-line X-ray tomograph, based only on the geometrical relation between the different components, and using a simplified calibration phantom. The methodology is tested on the new double tomograph system at INSA Lyon. Walnuts are used as testing phantoms due to their natural irregularity and outstanding internal texture under X-rays.</p><p>Two scanning scenarios are selected to represent the wide range of possible geometries that the system can resolve. The first test, referred to as NXGP04, corresponds to an assembly of walnuts inside a container, scanned at a voxel size of 111 μm, and a geometric magnification (i.e., the ratio between SDD and SOD) of 2.7. The second test, referred to as NXGP05, constitutes a scan of a single walnut using a voxel size of 28 μm and a geometric magnification of 10.7. For a given test, all the geometric parameters (i.e., SOD and SDD), as well as the scanning parameters (e.g., voltage and exposure time) are set equally for both lines. </p><p>Calibration phantoms are used to measure the geometry of the system for each test. They consist of a set of 7 metallic spheres attached to a foam board arranged along a line. For the test NXGP04, the spheres have 2.5 mm in diameter and are placed using a spacing of 20 mm, while for the test NXGP05, the spheres have 0.8 mm in diameter and spacing of 8.75 mm. In both cases, the size of the spheres in the detectors is such that more than 700 pixels are used to determine their centre, which increases the sensitivity of the calculation. </p>
Static and Dynamic Model Calibration for Upper Thermosphere Determination (2023SW003810)
<p>The dataset contains the background and static calibration models, associated with the figure data and routines. </p>
A new perspective on the taxonomy and systematics of Arvicolinae (Gray, 1821) and a new time-calibrated phylogeny for the clade
<p><strong>Background.</strong> Arvicoline rodents are one of the most speciose and rapidly evolving mammalian lineages. Fossil arvicolines are also among the most common vertebrate fossils found in sites of Pliocene and Pleistocene age in Eurasia and North America. However, there is no taxonomically robust, well-supported, time-calibrated phylogeny for the group. </p> <p><strong>Methods.</strong> Here we present well-supported hypotheses of arvicoline rodent systematics using maximum likelihood and Bayesian inference of DNA sequences of two mitochondrial genes and three nuclear genes representing 146 (82% coverage) species and 100% of currently recognized arvicoline genera. We elucidate well-supported major clades, reviewed the relationships and taxonomy of many species and genera, and critically compared our resulting molecular phylogenetic hypotheses to previously published hypotheses. We also used five fossil calibrations to generate a time-calibrated phylogeny of Arvicolinae that permitted some reconciliation between paleontological and neontological data. </p> <p><strong>Results.</strong> Our results are largely congruent with previous molecular phylogenies, but we increased the support in many regions of the arvicoline tree that were previously poorly-sampled. Our sampling resulted in a better understanding of relationships within Clethrionomyini, the early-diverging position and close relationship of true lemmings (<em>Lemmus</em> and <em>Myopus</em>) and bog lemmings (<em>Synaptomys</em>), and provided support for recent taxonomic changes within Microtini. Our results indicate an origin of ~6.4 Ma for crown arvicoline rodents. These results have major implications (e.g., diversification rates, paleobiogeography) for our confidence in the fossil record of arvicolines and their utility as biochronological tools in Eurasia and North America during the Quaternary.</p>
High resolution wind speed measurements with multicopters of the SWUF-3D UAS fleet - calibration and verification in a wind tunnel with active grid
<p>This dataset contains aggregated measurements from multicopter UAS. The data were measured during the period from October 5, 2022 to October 12, 2022 in the ForWind wind tunnel at the University of Oldenburg with UAS of the SWUF-3D fleet against Constant Temperature Anemometer (CTA). </p><p>Recorded data are provided for measurement flights in different generated wind profiles, i.e. staircase profiles, gusts, velocity steps and statistical turbulence. The measurement data consist of the accelerations measured by the UAS in its longitudinal and lateral axes, as well as the wind speeds measured by the CTA. The latter data were sampled down to the sampling rate of the UAS wind measurement. For the measurements in statistical turbulence, additional files are provided which contain the wind speeds measured by the CTA in its original sampling rate. Each file contains the data for a single measurement flight, as well as information in the header about the ambient conditions in the wind tunnel. The file names contain the following metadata:</p><p>for "gust" files:</p><ul><li>V0 : inertial velocity [m/s]</li><li>V_g : gust velocity amplitude [m/s]</li></ul><p>for "staircase" files:</p><ul><li>uas : the ID of the UAS used [-]</li><li>heading : yaw angle of UAS in relation to longitudinal axes of wind tunnel</li></ul><p>for "turbulence" files:</p><ul><li>V0 : fan wind speed [m/s]</li><li>I : turbulence intensity [%]</li><li>f_cta : sampling frequency of reference sensor [Hz] (for files with original sampling rate)</li></ul><p>for "velocity step" files:</p><ul><li>V0 : lower wind speed</li><li>V_du : wind speed aimed for of upward and downward velocity step</li></ul><p>All filenames end with the test date in YYYY-MM-DD format.</p>
ScienceDex guides
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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.