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235 results for “data filtering”
DisVis-based filtering of contacts from co-evolution data (or other sources)
<p>Dataset described in the manuscript: <em>Improving the Quality of Co-evolution Intermolecular Contact Prediction with DisVis</em>Siri Camee van Keulen, Alexandre M.J.J. Bonvin</p> <p>Details about the data set can be found at: https://github.com/haddocking/contact-filtering</p> <p>This archive contains in addition all the models generated with HADDOCK.</p>
Data for "PTP Over Wide Area Networks With Offset Measurement Outlier Filtering"
<p>Dataset used in the manuscript "PTP Over Wide Area Networks With Offset Measurement Outlier Filtering". This dataset contains synchronization accuracy measurements over long distance links using both NTP and PTP, as well as synthetically generated PTP replays used for offline testing.</p> <p>A detailed description of the contents is found in the <code>README.md</code> file at the root of the dataset.</p>
Data: Weak Cation Selectivity in HCN Channels Results from K+-mediated release of Na+ from selectivity filter binding sites
<p>Complementary data for the paper: Weak Cation Selectivity in HCN Channels Results from K+-mediated release of Na+ from selectivity filter binding sites.</p>
Equatorial wave filtering during May-September 2020 in the ECMWF OSE experiments with and without Aeolus data
<p>These are files with the global analyses produced by the observing system experiment with and without Aeolus data, and decomposed using the MODES software. Every file contain the zonal and meridional wind components and the pseudo-geopotential. Note that the paper makes use of the zonal winds only. Files including "hel1" in their titles belong to the OSE without Aeolus winds whereas the files with "hel4" in their names are from OSE including Aeolus winds. </p> <p>File names starting with KW belong to the Kelvin waves, file names starting with All contain the total fields, IGMRG denoted the non-Rossby modes whereas Rot belongs to file names containing only the signal associated with the Rossby modes. The Kelvin wave analyses are updated for the period from 1 May to 30 September, whereas other files are available for the periods discussed in the paper.</p> <p>The two movies are named MODES_KW_May2Sep2020.gif and MODES_BalancedUwind_May2Sep2020.gif for the Kelvin and balanced (Rossby modes) zonal winds averaged within 15 degrees N and 15 degrees S, respectively. Individual figures which constitute the movies are available at https://modes.cen.uni-hamburg.de.</p> <p> </p> <p> </p>
Data for "Ecosystem size filters life-history strategies to shape community assembly in lakes"
<p>Dataset 1. List of 71 fish species collected from north temperate lakes in Wisconsin USA. Data include critical life-history data used for strategy classifications according to Winemiller and Rose (1992), principal component scores, and strategy classification according to the cluster analysis.</p> <p>Dataset 2. Species occurrence data in all study lakes along with results from the 'soft classification" according to Euclidean distance.</p> <p>Dataset 3. Limnological and fish community characteristics of study lakes including species richness, lake area, estimated lake volume, and convex hull statistics for the overall fish community and each life-history strategy type.</p>
The Spitzer Data Fusion Astronomical Photometric Filter Database
<p>The Spitzer Data Fusion Astronomical Photometric Filter Database - <a href="https://doi.org/10.5281/zenodo.7850783">https://doi.org/10.5281/zenodo.7850783</a></p> <p>A collection of photometric filters from a variety of astronomical observatories by</p> <p>Lucia Marchetti (University of Cape Town) & Mattia Vaccari (University of Cape Town)</p> <p>The complete collection of filters is also available at: <a href="https://www.mattiavaccari.net/df/filters">https://www.mattiavaccari.net/df/filters</a></p> <p>Based on the Spitzer Data Fusion Project - <a href="https://doi.org/10.5281/zenodo.7850783">https://doi.org/10.5281/zenodo.7850783</a> - <a href="https://mattiavaccari.net/df">https://mattiavaccari.net/df</a></p> <p>Lucia Marchetti and Mattia Vaccari acknowledge financial support from the Inter-University Institute for Data Intensive Astronomy (IDIA), a partnership of the University of Cape Town, the University of Pretoria, the University of the Western Cape and the South African Radio Astronomy Observatory, and from the South African Department of Science and Innovation's National Research Foundation under the ISARP RADIOSKY2020 Joint Research Scheme (DSI-NRF Grant Number 113121) and the CSUR HIPPO Project (DSI-NRF Grant Number 121291).</p>
Perturbed Parameters for ICEPACK-DART Study Titled "Exploring Bounded Non-parametric Ensemble Filter Impacts on Sea Ice Data Assimilation"
<p>The file contains the values of the two perturbed CICE parameters that were used in the study titled "Exploring Bounded Non-parametric Ensemble Filter Impacts on Sea Ice Data Assimilation." The tw perturbed parameters are the standard deviation of the dry snow grain radius (Rsnow), and the thermal conductivity of snow (Ksnow). There are 80 values since the ensemble used in the study had 80 members.</p>
Phenotypic differences between interfertile Chlamydomonas species- focus-filtered timelapse data and measurements
<p>This repository contains focus-filtered timelapse microscopy data of two interfertile <i>Chlamydomonas</i> algal species. The protocol to generate this data is described in the associated publication, <a href="https://doi.org/10.57844/arcadia-35f0-3e16">"Phenotypic differences between interfertile <i>Chlamydomonas</i> species"</a>, and summarized here. Cells were collected from agar plates and suspended in water, then left to sit overnight to encourage gamete formation. During this time, non-motile cells settled, allowing for the enrichment of motile cells in the supernatant. These enriched cells were then loaded onto agar microchambers (100 micron diameter and 40 micron depth) for imaging. We collected videos on a Nikon Ti2-E microscope equipped with a Photometrics Kinetix digital scMos camera. We performed differential interference contrast (DIC) imaging using a Plan Apo 10× 0.45 Air objective. We collected videos with a 5.1 ms exposure with acquisition every 50 ms for three minutes. We placed a red light filter [IR longpass, 610 nm (ThorLabs)] in the light path to maintain swimming behavior of cells. The procedure was standardized and repeated four times to ensure consistency. Focus-filtered timelapse data of <i>C. reinhardtii </i>or C<i>. smithii </i>cells in agar microchamber wells are shared here. The code for focus-filtering and collection of measurements can be found in the <a href="https://github.com/Arcadia-Science/chlamy-comparison">associated Github repository</a>.</p><h4>Reference</h4><p><a href="https://doi.org/10.57844/arcadia-35f0-3e16">Essock-Burns T, Garcia III G, MacQuarrie CD, Mets DG, York R. (2023). Phenotypic differences between interfertile <i>Chlamydomonas </i>species</a></p><h4>Notes</h4><p>In addition to the raw data, the dataset includes sample images that are intermediates in the image processing pipeline, as well as 2D morphology measurements of the cells in a csv file.</p><p>"Cr" indicates <i>Chlamydomonas reinhardtii</i></p><p>"Cs" indicates <i>Chlamydomonas smithii</i></p><p>Frame rate: 20 frames per second (fps)</p><p>Pixel size: 0.6398 microns/pixel</p>
INP Teflon filter measurements and OPC data from the WesCon campaign
<p>Ice Nucleating Particle (INP) measurements taken during the Met Office's Wessex Convection Experiment (WesCon) in Jun-Aug 2023. The samples were collected on Sartorius 47 mm 1.2 um PTFE filters onboard the FAAM aircraft and at the Netheravon field site (51.24 deg N, 1.78 deg W). Aircraft filters are in the "FAAM Subtracted Samples" folder and start with a "C". Ground measurements are in the "Digitel Subtracted Samples" folder and start with "S". Information about each measurement can be found in the respective info csv file. Handling blanks were taken throughout the campaign and the data has been background subtracted.</p> <p> </p> <p>The filters were analysed through the drop-on method, which is used in Price et al., 2014 and Raif et al., 2024 (Preprint).</p>
NEON Biorepository Benthic Microbe Collection (Sterivex Filters) (repackaging of occurrences published by the NEON Biorepository Data Portal)
This collection contains benthic biofilm samples collected on 67 mm long, 1.7 cm diameter, 0.22 um Sterivex capsule filters (NEON sample class: amb_fieldParent_in.archiveID). Benthic biofilm samples are collected 3 times per year at the same time and location as periphyton (microalgae) samples and microbe samples sent for sequencing analysis, three times per year in wadeable streams during aquatic biology bout windows, roughly in spring, summer, and fall. Benthic biofilms are not collected in lakes and rivers. Samples are collected from rock and wood scrubs using field-sterile methods, and filtered through a 0.22 um Sterivex SVGP capsule filters. In wadeable streams, periphyton samples are collected in the two most dominant benthic habitat types (e.g. riffles, runs, pools, step pools). Sterivex filters are capped and flash-frozen in the field and then shipped to the Biorepository to be archived at -80 degrees Celsius. See related links below for protocols and NEON related data products.
NEON Biorepository Particulate Mass Filter Collection (repackaging of occurrences published by the NEON Biorepository Data Portal)
This collection contains quartz microfiber particulate mass filters (NEON sample class: dpm_fieldData_in.sampleID and dpm_filterBlank_in.sampleID). Particulate mass sampling is executed at six of NEON's terrestrial sites, located in Domains 10, 13, and 15. The subset of sites included for sampling are those in the Basin and Range, Eastern and Western slopes of the Rocky Mountains, and the Eastern plains of Colorado. This selection of sites enables focus on transportation of particulate matter from the Great Basin and the Colorado Plateau by prevailing westerly winds over the Colorado Rocky Mountains, to receptor sites in the Rockies and Great Plains. Samples are collected by an automated assembly that pulls air through a quartz microfiber filter with a porosity of 10 micrometers, to collect PM10. Filters are weighed at high precision pre- and post-deployment at the Colorado Department of Public Health and Environment Air Resources Laboratory to determine dust deposition mass. Filters are then shipped to the Biorepository to be archived at 4 degrees Celsius in air-tight plastic sleeves. Subsamples of the filters are available to the science community upon request to enable the assessment of chemical and nutrient inputs in the region. Additionally, 5 filter blanks from each box of filters are archived and available upon request. See related links below for protocols and NEON related data products.
NEON Biorepository Surface Water Microbe Collection (Sterivex Filters) (repackaging of occurrences published by the NEON Biorepository Data Portal)
This collection contains surface water microbe samples collected on 67 mm long, 1.7 cm diameter, 0.22 um Sterivex capsule filters (NEON sample class: amc_fieldCellCounts_in.archiveID). Surface water microbe samples are collected at the same time and location as surface water cell count samples and surface water chemistry samples once per month in wadeable streams (12 times per year) and every-other month in lakes and rivers (6 times per year). Details on sampling locations and timing are provided in the NEON document titled Surface Water Chemistry Sampling in Aquatic Habitats (https://data.neonscience.org/documents). In wadeable streams, surface water microbe samples are collected near the downstream S2 sensor location. In lakes, microbial samples are collected near the the 'buoy', 'littoral 1', and 'littoral 2' sensors, and sampling depth(s) is dependent on lake stratification. In rivers, microbial samples are collected near the buoy sensor. Water samples are filtered on 0.22 um Sterivex capsule filters, capped and flash-frozen in the field. Sterivex filters are archived at the NEON Biorepository at -80 degrees Celsius. See related links below for protocol.
A Kalman Filter Approach to the Fusion of Acceleration, GNSS position and Rotation Sensor Data from Robot Motions
<p><strong>GNSS data:</strong></p> <ul> <li>Instrument: Javad antenna and Septentrio receiver</li> <li>sampling rate: 100 Hz</li> <li>Bandwidth of loop filter: auto adjust</li> <li>Relative positioning </li> <li>Baseline: ultra short with distance of 5 m</li> <li>files in Rinex format: Rover (moving antenna) and Base (stationary antenna), .20G (GLONASS Navigation data), .20N (GPS Navigation data), .20L (Galileo Navigation data), .20O (Observations)</li> </ul> <p><strong>Accelerometer data:</strong></p> <ul> <li>Instrument: EpiSensor and Centaur Digitizer</li> <li>Sampling rate: 250 Hz</li> <li>Unit: counts</li> <li>unfiltered</li> <li>file: XKUK_centaur-6_1233_20200908_114500.seed</li> </ul> <p><strong>Angular rate data:</strong></p> <ul> <li>Instrument: IMU KvH 1750 (includes accelerometer and rotational sensor)</li> <li>Sampling rate: 250 Hz</li> <li>Unit gyro: rad/s</li> <li>Unit accelerometer: g (gravitational acceleration)</li> <li>file: LOGGING_1750_IMU_1308K004_11_57_25_250.csv</li> </ul> <p><strong>Robot Feedback:</strong></p> <ul> <li>Instrument: KUKA model AGILUS KR 6 R900 sixx</li> <li>Sampling rate: 250 Hz</li> <li>Unit translation: m</li> <li>Unit rotation: degree</li> <li>files: kuka_motion_*.txt, 1-4 are consecutive in time.</li> </ul> <p><strong>Experiments:</strong></p> <ul> <li>T: translations, R: rotations, XL, L, S denote the relative amplitudes</li> <li>10 experiments: TLRXL, TLRXL, TLRL, TLRL, TLRS, unfinished TLRS, TLRS, TLRS, TSRS, TSRS (Robot feedback (1,2), angular rate, GNSS data)</li> <li>9 experiments: TLRXL, TLRXL, TLRL, TLRL, TLRS, unfinished TLRS, TLRS, TSRS, TSRS (Robot feedback (3,4), accelerometer data</li> </ul>
Automatic plankton image classification - can capsules and filters help coping with data set shift?
<p>This data set is related to the article 'Automatic plankton image classification - can capsules and filters help coping with data set shift?' published in 'Limnology and Oceanography: Methods' by Plonus <em>et al.</em> (2021).</p> <p>The images belong to the trainings set used to train the models in the aforementioned paper (training_) and three different additional data sets which were used to evaluate the performance of the trained models in application mode (fs446_; fs466_; fs534_). The Python-Script 'separate_files.py' can be used to move all the images in different folders for each data set and class respectively.</p>
Output of Optimized gross primary productivity over the croplands within the BEPS particle filtering data assimilation system (BEPS_PF v1.0)
<p>Output of Optimized gross primary productivity over the croplands within the BEPS particle filtering data assimilation system (BEPS_PF v1.0)</p>
Inner filter effect correction for fluorescence measurements in microplates (ZINFE and NINFE) - experimental data
<p>Experimental data for the paper entitled <em>Inner Filter Effect Correction for Fluorescence Measurements in Microplates Using Variable Vertical Axis Focus</em> (https://doi.org/10.1021/acs.analchem.2c01031).</p> <p>Separate datasets are provided for data with background correction, without background correction, and absorbance-corrected data.</p> <p>All results were obtained using the online calculator service written in Javascript: https://ninfe.science (version 15.9.2021.).</p> <p>For additional details please visit: https://glymech.pharma.hr//GlyMech.html.</p> <p> </p>
NetCDF data used in analysis presented in "Assessment of the z~ time-filtered Arbitrary Lagrangian-Eulerian coordinate in a global eddy-permitting ocean model"
<p>NetCDF data used in analysis presented in "Assessment of the z~ time-filtered Arbitrary Lagrangian-Eulerian coordinate in a global eddy-permitting ocean model", submitted to Journal of Advances in Modelling the Earth System.</p> <p>The data are produced from an ensemble of six experiments based on the GO8p0 configuration of NEMO v4.0.1 on a global 1/4° grid, as described in the paper. The ensemble is intended to test the z~ vertical coordinate, and includes a control with the default "z-star" fixed coordinate, and five experiments with the z-tilde vertical coordinate, using a selection of values for the two z-tilde timescale parameters. The data includes time series of global mean ocean and ice fields; large-scale transports; and fields from diapycnal mixing analysis.</p> <p>The first part of each filename refers to the experiment from the ensemble ("zstar", "ztilde_5_30", "ztilde_10_30", "ztilde_20_30", ztilde_20_60" and "ztilde_40_60"); the following five-character string identifies the respective suite on the Met Office Rose system and the MASS archive system; and the rest of the name specifies the type of data contained in the file.</p>
Data and code for Freshwater corridors in the conterminous US: a coarse-filter approach based on lake-stream networks
<p>This repository contains various datasets used to map and analyze freshwater connectivity (i.e., corridors) in the conterminous US based on networks of lakes, streams and rivers. We considered lake-stream networks as analogous to habitat corridors. Hub lakes are individual lakes that are disproportionately important for maintaining intact networks. We also analyzed the protection status of freshwater connectivity using the US Protected Areas Database v. 2.0. R analysis scripts can also be found in this repository. Much of the data we used came from published or soon-to-be published sources, which are referenced below.</p>
Hierarchical trait filtering at different spatial scales determines beetle assemblages in deadwood: Additional data
<p>Contains data used in the following publication:</p> <p>Felix Neff, Jonas Hagge, Rafael Achury, Didem Ambarlı, Christian Ammer, Peter Schall, Sebastian Seibold, Michael Staab, Wolfgang W. Weisser, Martin M. Gossner (2022). <em>Hierarchical trait filtering at different spatial scales determines beetle assemblages in deadwood. </em>Functional Ecology. <a href="https://doi.org/10.1111/1365-2435.14186">https://doi.org/10.1111/1365-2435.14186</a></p> <p>These are complementary data, which are needed to reproduce the analyses. Most data are archived in the Biodiversity Exploratories Information System (<a href="https://doi.org/10.17616/R32P9Q">https://doi.org/10.17616/R32P9Q</a>).</p> <p>The following data are included:</p> <ul> <li><strong>BELongDead_Subplots_Normal.csv</strong>: List of <em>normal</em> subplots within the BELongDead projects (only these were included in the analyses)</li> <li><strong>Body_length.csv</strong>: Body length data for study species assembled from Freude et al. (1965-1998)</li> <li><strong>Lightness_completion.csv</strong>: Colour lightness recorded from measured individuals and photos from coleonet.de (Lompe, 2002)</li> <li><strong>Name_standardisation.csv</strong>: Dataset used to standardise taxonomic names from different sources</li> <li><strong>Saproxylic_species_sub.csv</strong>: List of saproxylic species (according to Schmidl & Bussler (2004)), which were recorded in the project</li> <li><strong>Similar_Species.csv</strong>: List of similar species for species with missing traits. Based on these, missing traits were estimated</li> </ul> <p><strong>References</strong></p> <p>Freude, H., Harde, K. W., & Lohse, G. A. (1965–1998). <em>Die Käfer Mitteleuropas Band 1-15</em>. Goecke und Evers.</p> <p>Lompe, A. (2002). <em>Käfer Europas</em>. <a href="http://coleonet.de/">http://coleonet.de/</a></p> <p>Schmidl, J., & Bussler, H. (2004). Ökologische Gilden xylobionter Käfer Deutschlands. <em>Naturschutz und Landschaftsplanung</em>, <em>36</em>(7), 202–218.</p>
Ground tilt data at Campi Flegrei filtered in the fortnightly (Mf=13.66d) and [12h-90d] bands.
<p>Ground tilt (NS and EW components) at Campi Flegrei from April 1st 2015 to April 30th 2022 recorded at three borehole instruments (CMP, ECO and HDM) of the INGV network. </p> <p>1) Time series filtered in the fortnightly (Mf =13.66 days) tidal band [13 - 14.083 days]. Sampling rate=1min. </p> <p>2) Time series filtered in the [12 hours - 90 days] band. Sampling rate=1hour. </p>
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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.