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13,800 results for “test”
Creating multi-themed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method
This dataset was created for the following publication: Cheruvelil, K.S., S. Yuan, K.E. Webster, P.-N. Tan, J.-F. Lapierre, S.M. Collins, C.E. Fergus, C.E. Scott, E.N. Henry, P.A. Soranno, C.T. Filstrup, T. Wagner. Under review. Creating multi-themed ecological regions for macrosystems ecology: Testing a flexible, repeatable, and accessible clustering method. Submitted to Ecology and Evolution July 2016. This dataset includes lake total phosphorus (TP) and Secchi data from summer, epilimnetic water samples, as well as 52 geographic variables at the HU-12 scale; it is a subset of the larger LAGOS-NE database (Lake multi-scaled geospatial and temporal database, described in Soranno et al. 2015). LAGOS-NE compiles multiple, individual lake water chemistry datasets into an integrated database. We accessed LAGOSLIMNO version 1.054.1 for lake water chemistry data and LAGOSGEO version 1.03 for geographic data. In the LAGOSLIMNO database, lake water chemistry data were collected from individual state agency sampling and volunteer programs designed to monitor lake water quality. Water chemistry analyses follow standard lab methods. In the LAGOSGEO database geographic data were collected from national scale geographic information systems (GIS) data layers. The dataset is a subset of the following integrated databases: LAGOSLIMNO v.1.054.1 and LAGOSGEO v.1.03. For full documentation of these databases, please see the publication below: Soranno, P.A., E.G. Bissell, K.S. Cheruvelil, S.T. Christel, S.M. Collins, C.E. Fergus, C.T. Filstrup, J.F. Lapierre, N.R. Lottig, S.K. Oliver, C.E. Scott, N.J. Smith, S. Stopyak, S. Yuan, M.T. Bremigan, J.A. Downing, C. Gries, E.N. Henry, N.K. Skaff, E.H. Stanley, C.A. Stow, P.-N. Tan, T. Wagner, K.E. Webster. 2015. Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science and data reuse. GigaScience 4:28 doi:10.1186/s13742-015-0067-4 .
PsPM-REW2: SCR, ECG, respiration, and eyetracking measurements in a Pavlovian appetitive conditioning task with juice delivery with acquisition and recall test after one week
<p>This dataset contains skin conductance responses (SCR), electrocardyogram (ECG), respiration, pupil size (PSR), and gaze coordinates measurements for 34 healthy unmedicated participants (20 females and 14 males aged 24.9 +/- 4.1) participating in a Pavlovian differential cued rewarding conditioning experiment with 2 sessions. <br>CSs were isoluminant colored triangles presented on the screen center with grey background.<br>US was a sip of the favourite juice selected individually. SOA between the CS onset and US was 5.5 s. Participants underwent the conditioning task with CSs (CS+ 50% reinforced) and US delivery in session 1 with 2 blocks, and were tested in a retention/extinction task one week later in session 2 with 2 blocks. No US was delivered during session 2. The ITI was jittered on each trial uniformly at random between 9 to 16 s. The blocks in each session were recorded on the same day with self-paced breaks.</p>
PsPM-REW1: SCR, ECG, respiration, and eyetracking measurements in a Pavlovian appetitive conditioning task with juice delivery with acquisition and recall test after one week
<p>This dataset contains skin conductance responses (SCR), electrocardyogram (ECG), respiration, pupil size (PSR), and gaze coordinates measurements for 37 healthy unmedicated participants (26 females and 11 males aged 24.2 +/- 4.2) participating in a Pavlovian differential cued rewarding conditioning experiment with 2 sessions. <br>CSs were isoluminant colored triangles presented on the screen center with grey background.<br>US was a sip of the favourite juice selected individually. SOA between the CS onset and US was 5.5 s. Participants underwent the conditioning task with CSs (CS+ 50% reinforced) and US delivery in session 1 with 2 blocks, and were tested in a retention/extinction task one week later in session 2 with 2 blocks. No US was delivered during session 2. The ITI was jittered on each trial uniformly at random between 9 to 16 s. The blocks in each session were recorded on the same day with self-paced breaks.</p>
Precipitation-productivity relationships in desert grassland: a test of the double asymmetry hypothesis.
The purpose of this data package is to provide the derived data and R code for analyses presented in the manuscript by Collins et al. Knowing the relationship between precipitation (PPT) and aboveground net primary productivity (ANPP) is essential for understanding and modeling the global carbon cycle. Across grassland to forest gradients, the PPT-ANPP relationship is well-defined and non-linear. Temporal patterns within a site over time, however, are more variable than spatial patterns and nearly always linear. Linear relationships, however, are inconsistent with positive asymmetry occurring when the increase in ANPP in a wet year is greater than the decline in a dry year. The double asymmetry model predicts that concave down non-linearities will occur when extreme high and low PPT years are included in a time series. We used long-term ANPP data from ambient plots, plus rainfall addition and reduction experiments to test the predictions of the double asymmetry model. By combining experimental drought, plus water and nitrogen addition experiments we found some support for the double asymmetry model. However, the response was concave up not down under high precipitation coupled with nitrogen addition. By experimentally extending the range of monsoon precipitation we generated a significant although weak, non-linear PPT-ANPP relationship, but only when nutrient limitation was alleviated. Our results demonstrate that multiple interacting factors govern the PPT-ANPP relationship within a site over time.
Incentive mechanisms and the provision of public goods: Field experiment data for testing alternative economic frameworks to supply ecosystem restoration on Virginia's Eastern Shore: 2008 data.
This dataset consists of participant responses in one of two economic experiments conducted on Virginia's Eastern Shore during 2008 and 2009 by Elizabeth C. Smith used to gauge resident preferences and willingness-to-pay for ecosystem restoration activities. This dataset was designed to be used to examine a practical method to implement an individualized pricing approach to public good provision, grounded in Lindahl's marginal benefit theory. The study's focus was on ecosystem valuation and market approaches that have potential to provide public goods, examining the potential to generate revenues for public goods from consumers. While willingness-to-pay measurement techniques have been used to assess preferences for many environmental goods, this research goes a step further to explore real money auctions that generate revenues sufficient to pay for restoration activities. The data from the field experiments conducted in coastal Virginia were used, along with laboratory experiment data, to evaluate the performance of auction mechanisms in generating revenues relative to potential (Hicksian) willingness to pay for marginal increments in public goods. The field execution of this experiment involved residents of Virginia's Eastern Shore and local public goods. This application involved half-acre increments of ecosystem restoration for sea grass habitat in coastal lagoons, plantings for migratory bird habitat, and, in some auctions, clam-based increments of water quality services, defined as delaying the harvest of clams for six months beyond normal harvest by an existing aquaculture firm. To perform these tasks, participants were provided a budget, between $90 and $150. The auctioneer described for participants the ecosystem services that may result from additional ecosystem restoration associated with each activity. The actual levels of ecosystem restoration provided were based on aggregate offers reaching a pre-determined (but unknown to the participants) provision p
Incentive mechanisms and the provision of public goods: Field experiment data for testing alternative economic frameworks to supply ecosystem restoration on Virginia's Eastern Shore: 2009 data.
This dataset consists of participant responses in one of two economic experiments conducted on Virginia's Eastern Shore during 2008 and 2009 by Elizabeth C. Smith used to gauge resident preferences and willingness-to-pay for ecosystem restoration activities. This dataset was designed to be used to examine a practical method to implement an individualized pricing approach to public good provision, grounded in Lindahl's marginal benefit theory. The study's focus was on ecosystem valuation and market approaches that have potential to provide public goods, examining the potential to generate revenues for public goods from consumers. While willingness-to-pay measurement techniques have been used to assess preferences for many environmental goods, this research goes a step further to explore real money auctions that generate revenues sufficient to pay for restoration activities. The data from the field experiments conducted in coastal Virginia were used, along with laboratory experiment data, to evaluate the performance of auction mechanisms in generating revenues relative to potential (Hicksian) willingness to pay for marginal increments in public goods. The field execution of this experiment involved residents of Virginia's Eastern Shore and local public goods. This application involved half-acre increments of ecosystem restoration for sea grass habitat in coastal lagoons, plantings for migratory bird habitat, and, in some auctions, clam-based increments of water quality services, defined as delaying the harvest of clams for six months beyond normal harvest by an existing aquaculture firm. To perform these tasks, participants were provided a budget, between $90 and $150. The auctioneer described for participants the ecosystem services that may result from additional ecosystem restoration associated with each activity. The actual levels of ecosystem restoration provided were based on aggregate offers reaching a pre-determined (but unknown to the participants) provision p
Testing of a benthic incubation chamber design in a Virginia coastal bay, 2023, 2024, and 2025
Benthic incubation chambers enclose a known volume of water overlying a known area to measure water chemistry changes and are typically used to quantify the metabolic activity of benthic organisms or communities. Here, we report data from a series of tests validating a new benthic incubation chamber design. This data includes dissolved oxygen (DO) concentrations and temperatures recorded during three test deployments in South Bay, Virginia during August 2023 (T1_chamber_do_test_data), as well as data from light transmission tests. Light transmission tests included per wavelength transmission of PAR and ultraviolet radiation through the chamber wall (T2_wall_transmission_test) and lid (T3_lid_transmission_test), an in-situ PAR transmission comparison for two different sensor arrangements (side-mounted versus top-mounted) during July 2025 (T4_sensor_shading_test), and an in-situ comparison of natural ambient PAR versus PAR translated through a deployed chamber during March 2024 (T5_in_situ_light_test).
HOSENG trial – HOme-based oral SElf-testiNG for absent and refusing individuals during a door-to-door HIV testing campaign: a cluster randomised clinical trial in rural Lesotho
<p>These are pseudo-anonymised data from the HOSENG randomized trial: " HOSENG trial – HOme-based oral SElf-testiNG for absent and refusing individuals during a door-to-door HIV testing campaign: a cluster randomised clinical trial in rural Lesotho". The data dictionary explains the data available in the dataset. Between July 2018 and December 2018, 10516 eligible individuals from 106 consenting villages were enrolled from two districts of Lesotho, and followed up for a maximum of 120 days. Main manuscript reference, DOI: <a href="https://doi.org/10.1016/s2352-3018(20)30233-2">10.1016/S2352-3018(20)30233-2. </a>The protocol was published, DOI:10.1186/s13063-019-3469-2.</p>
Dataset and program scripts for the reproducibility of the hierarchical data structure file. Related to the manuscript entitled: Hierarchical Representation of Measurement Data, Metrological Uncertainty and Metadata for Calibrated Battery Tests
<p>We present an interoperable hierarchical data representation for battery tests, leading to improved scalability of data transmission and enhanced data accessibility and comprehensibility for both human interpretation and machine processing. The hierarchical data format includes the raw trace electrical measurement data, the metrological calibration and uncertainty data, the metadata such as experimental settings, instruments and software versions, as well as post-processed data such as electrochemical model fit parameters. This data representation allows repetition of the battery test under the exact same conditions such that identical results are achieved within defined error bounds. This is in line with the general F.A.I.R. data approach and provides repeatability and traceability in the battery value chain. As an application of the hierarchical data representation, we show the classification of cells as pass/fail being performed with quantitative confidence levels. We demonstrate the complete workflow of establishing the hierarchical data structure for electrochemical impedance spectroscopy (EIS), starting from metrological traceability of the calibration and uncertainty analysis towards the storage of the structured data as a single integrated file that preserves the hierarchical data format.</p>
Datasets to "Compressible test-field method and its application to shear dynamos"
<pre>This directory contains an index.html file with links to the run directories and idl plotting routines with secondary data for the other figures for the paper "Compressible test-field method and its application to shear dynamos" by M. J. Kapyla, M. Rheinhardt, & A. Brandenburg (Astrophys. J., in press, arXiv:2106.01107). If anything turns out to be incomplete, please email maarit.kapyla@aalto.fi or brandenb@nordita.org. </pre>
Data for At-home testing to characterize SARS-CoV-2 seroprevalence among children and adolescents
<div> <div>This repository contains the data used to reproduce *At-home testing to characterize SARS-CoV-2 seroprevalence among children and adolescents* by Ahmed et al.</div> </div>
Appendix - Potential COVID-19 test fraud detection: Findings from a pilot study comparing conventional and statistical approaches
<p>The methods and results of the publication "COVID-19 test fraud detection: Findings from a pilot study comparing conventional and statistical approaches" are described in more detail in this appendix. The R-syntax for the calculation is provided, as well as a pseudo data set with which the syntax can also be tested.</p>
CATCH-EyoU: Exploiting European data and testing the integrated theory of youth active EU citizenship: EACEA subset analysis
<p>This dataset was created within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme, Grant Agreement No 649538. Work Package 4 of this project (Exploiting European data and testing the integrated theory of youth active EU citizenship) is focused on the re-analysis of existing European data. This dataset contains a subset of data originally collected within the project “<em>EACEA 2010/03: Youth Participation in Democratic Life</em>”, coordinated by the London School of Economic and Political Science. Specifically, an online questionnaire survey in seven European countries was conducted among young people age 15-30 in 2011. This dataset contains a subset of 22 variables that were employed for the reanalysis within the CATCH-EyoU project.</p>
GPR data used to test the efficient deconvolution method of Schmelzbach and Huber (2015)
<p>GPR data recorded with Pulse Ekko Pro from Sensors & Software on the river bed of the Tagliamento River (NE Italy).</p> <p>This data was used to test the efficient deconvolution scheme of Schmelzbar and Huber (2015):</p> <p>C. Schmelzbach, E. Huber (2015) Efficient Deconvolution of Ground-Penetrating Radar Data. IEEE Transactions on Geoscience and Remote Sensing, 53(9): 5209 - 5217<br> doi: <a href="http://dx.doi.org/10.1109/TGRS.2015.2419235">10.1109/TGRS.2015.2419235</a></p>
Datasets for testing the robustness of LiDAR vegetation metrics to varying point densities
<p><span>The calculation of vegetation metrics from LiDAR point clouds might be affected by the available point density of a dataset. Testing how the same LiDAR vegetation metrics differ with different point densities can therefore inform about their robustness for upscaling metrics to other areas or other LiDAR point clouds. The datasets made available here were generated to test the robustness of LiDAR vegetation metrics to varying point densities and spatial resolutions (i.e., plots of 1 × 1 m, 2 × 2 m, 5 × 5 m and 10 × 10 m size). A total of 25 LiDAR vegetation metrics representing different aspects of vegetation height, vegetation cover and structural complexity were tested (see metric definition in Kissling et al. 2023, </span><span><a href="https://doi.org/10.1016/j.dib.2022.108798"><span>https://doi.org/10.1016/j.dib.2022.108798</span></a></span><span>). The metric calculation was similar to the metric calculation in the Laserchicken software (Meijer et al. 2020, </span><span><a href="https://doi.org/10.1016/j.softx.2020.100626"><span>https://doi.org/10.1016/j.softx.2020.100626</span></a></span><span>) and the Laserfarm workflow (Kissling et al. 2022, https://doi.org/10.1016/j.ecoinf.2022.101836). The Dutch AHN4 dataset from the years 2020–2022 with a point density of 20–30 points/m<sup>2</sup> was used. Initially, 100 plots (i.e., squared polygons around centre points) were randomly placed across the Netherlands in Dutch Natura 2000 sites that predominantly contain woodland habitats (using shapefiles from the European Environmental Agency). For each centre point, square polygons of the desired resolutions (i.e., 1 × 1 m, 2 × 2 m, 5 × 5 m or 10 × 10 m plot size) were generated. The square polygons were subsequently used to clip the LiDAR point clouds from the Dutch AHN4 point cloud dataset. Since not all locations of the 100 randomly placed plots contained points, the actual sample sizes were slightly smaller than 100, i.e., 94 plots for the 1 × 1 m, 2 × 2 m and 5 × 5 m resolution and 95 plots for the 10 × 10 m resolution. Metrics were calculated with the original point density of the Dutch AHN4 dataset (20–30 points/m2) and with six systematically down-sampled point clouds for the same plots (i.e., keeping 5%, 10%, 20%, 40%, 60% and 80% of the points in the original point clouds). For each clipped point cloud of a plot at a given resolution, the points were first sorted according to their GPS acquisition time (from earliest to latest). Points were then systematically discarded and only 5%, 10%, 20%, 40%, 60% and 80% of the points in the original point clouds were kept. The kept points were used for calculating the 25 LiDAR vegetation metrics. </span></p>
Interlaboratory study: Testing reproducibility of solid biofuels component identification using reflected light microscopy
<p><strong>Submitted data was used to write an article: </strong>Drobniak, A., Mastalerz, M., Jelonek, Z., Jelonek, I., Adsul, T., Andolšek, N., Ardakani, O.H., Congo, T., Demberelsuren, B., Donohoe, B.S., Douds, A., Flores, D., Ganzorig, R., Ghosh, S., Gize, A., Goncalves, P.A., Hackely, P., Hatcherian, J., Hower, J.C., Kalaitzidis, S., Kędzior, S., Knowles, W., Kuś, J., Lis, K., Lis, G., Liu, B., Luo, Q., Du, M., Mishra, D., Misz-Kennan, M., Mugerwa, T., O'Keefe, J., Park, J., Pearson, R., Petersen, H., Reyes, J., Ribeiro, J., Niedzwiedzkas, J.L., de la Rosa Rodriguez, G., Sosnowski, P., Valentine, B., Varma, A., Wojtaszek-Kalaitzidi, M., Xu, Z., Zdravkov, A., Ziemianin, K., Interlaboratory study: Testing reproducibility of biomass fuels component identification using reflected light microscopy. International Journal of Coal Geology 277, 104331. <a href="https://doi.org/10.1016/j.coal.2023.104331">https://doi.org/10.1016/j.coal.2023.104331</a>.</p> <p> </p> <p><strong>Funding acknowledgments: </strong>The project is co-financed by the Polish National Agency for Academic Exchange within the Polish Returns Programme (BPN/PPO/2021/1/00005/DEC/1), the National Science Center, Poland (2022/01/1/ST10/00024), and the research activities co-financed by the funds granted under the Research Excellence Initiative of the University of Silesia in Katowice, Poland. </p> <p> </p> <p><strong>Article Abstract: </strong>Considering global market trends and concerns about climate change and sustainability, increased biomass use for energy is expected to continue. As more diverse materials are being utilized to manufacture solid biomass fuels, it is critical to implement quality assessment methods to analyze these fuels thoroughly. One such method is reflected light microscopy (RLM), which has the potential to complement and enhance current standard testing, leading to improving fuel quality assessment and, ultimately, preventing avoidable air pollution. An interlaboratory study (ILS) was conducted to test the reproducibility of biomass fuels component identification using a reflected light microscopy technique. The exercise was conducted on thirty photomicrographs showing biomass and various undesired components (like plastics or mineral matter), which were purposely added (by the ILS organizers) to contaminate wood pellets and charcoal-based grilling fuels. Forty-six participants had various levels of difficulty identifying the marked components, and as a result, the percentage of correct answers ranged from 52.2 to 94.4%. Among the most difficult components to distinguish were petroleum products and inorganic matter. Various reasons led to the misidentification, including insufficient morphological descriptions of the components provided to participants, ambiguities of the nomenclature, limitations of the analytical and exercise method, and insufficient experience of the participants. Overall, the results indicate that RLM has the potential to enhance the quality assessment of biomass fuels. However, they also demonstrate that the petrographic classification used in this exercise requires further refinement before it can be standardized. While a new simplified classification of solid biomass fuels components was created as an outcome of this study, future research is necessary to refine the nomenclature, develop a microscopic morphological description of the components, and verify the accuracy of component identification with a follow-up ILS.</p>
Dataset for "Methodology for fast testing of carbon-based nanostructured 3D electrodes in vanadium redox flow battery"
<p>Here, we describe a technique for integrating carbon-based rod-like nanomaterials into a vanadium redox flow battery and a methodology for fast nanomaterial performance testing. The technique is based on creating a fixed nanomaterial bed sandwiched between two graphite felt electrodes, forming a 3D flow-through electrode in the battery. Performing various positive and negative control experiments, we show the beneficial effect of a nanostructured bed on the primary battery characteristics obtained from short-term electrochemical experiments. We then characterize carbon nanotubes exhibiting promising electrochemical behavior in vanadium electrolytes, as observed in our previous study. The load curves obtained from charge-discharge steps at various current densities and electrolyte flow rates revealed considerable differences in the performance of the tested materials, with few-walled carbon nanotubes reaching unsurpassable characteristics. Although developed for vanadium redox flow batteries, the method enables testing tube-like and rod-like (nano-)materials as electrodes for other flow battery systems. </p>
A blind test on wind turbine wake modelling based on wind tunnel experiments: Phase I – The benchmark case
<p>This data set ("Data files.zip") contains the wind tunnel measurement data from Phase I of the Blind test on wind turbine wake modelling based on wind tunnel experiments organised during the TWEET-IE project (www.tweet-ie.eu).</p> <p>This updated version <strong>replaces</strong> the older versions 1.0.0 (https://doi.org/10.5281/zenodo.10566401), 1.1.0 (https://doi.org/10.5281/zenodo.11370112), 2.0 (https://doi.org/10.5281/zenodo.12188194) and 2.1 (https://doi.org/ 10.5281/zenodo.13918935). In comparison to the previous version 2.1 the data documentation has been updated to follow the template of the TWEET-IE project documents, indicating the Grant Agreement Number with the European Union and the Call Topic of the project.</p> <p>All tests were conducted in the closed-loop, low-speed boundary layer wind tunnel of the Chair of Aerodynamics and Fluid Mechanics at Technische Universität München (TUM). The experiments concerned two wind turbines, aligned with the flow, one downstream of the other, at a distance of 5 diameters. For Phase I, no control was applied to the wind turbine models, which were operating at constant RPM. The turbine models, designed and manufactured by TUM, were instrumented with multiple sensors and actuators and had a diameter of 1.1M. Measurements include velocity, power and loads on the turbines. A detailed description of the experimental set up can be found in the accompanying document ("Data documentation.pdf"). </p> <p>File "Submission procedure.zip" includes the format description and the templates of the output data that should be submitted by the participants in the blind test comparison.</p>
Dataset for the comparison of two Computational Thinking (CT) test for upper primary school (grades 3-4) : the Beginners' CT test (BCTt) and the competent CT test (cCTt)
<p>This dataset contains quantitative student data acquired during the administration of two validated Computational Thinking (CT) assessments for upper primary school (grades 3 and 4): the Beginners' CT test (BCTt) [1] and the comptent CT test (cCTt) [2]</p> <p>To compare the psychometric properties of both instruments a comparative analysis was conducted with data acquired in schools in Portugal from the same school districts. More specifically, we analyse the results of: </p> <p>- the BCTt test administered in March 2020 to 374 students in grades 3-4,</p> <p>- the cCTt test administered in April 2021 to 201 different students in grades 3-4.</p> <p>These students had no prior experience in Computational Thinking, as this was not part of the national curriculum at the times of administration. </p> <p> </p> <p>The detailed psychometric comparison is published in Frontiers in Psychology - Educational Psychology [3] and provides indications regarding the use of both instruments for grades 3-4. </p> <p> </p> <p>A README is included and provides additional information regarding :</p> <p>- the requirements for re-use. </p> <p>- the specific content of the 2 csv files</p> <p> </p> <p>The BCTt is available upon request to maria.zapata@urjc.es and the cCTt items are available in [2] with an editable version being available upon request to laila.elhamamsy@epfl.ch. </p> <p>In case of other inquiries, please contact: laila.elhamamsy@epfl.ch, maria.zapata@urjc.es or pedro.marcelino@treetree2.org</p> <p> </p> <p><strong>References</strong></p> <p>[1] M. Zapata-Cáceres, E. Martín-Barroso and M. Román-González, "Computational Thinking Test for Beginners: Design and Content Validation," <em>2020 IEEE Global Engineering Education Conference (EDUCON)</em>, 2020, pp. 1905-1914, doi: 10.1109/EDUCON45650.2020.9125368.</p> <p>[2] El-Hamamsy, L., Zapata-Cáceres, M., Barroso, E. M., Mondada, F., Zufferey, J. D., & Bruno, B. (2022). The Competent Computational Thinking Test: Development and Validation of an Unplugged Computational Thinking Test for Upper Primary School. <em>Journal of Educational Computing Research</em>, <em>60</em>(7), 1818–1866. <a href="https://doi.org/10.1177/07356331221081753">https://doi.org/10.1177/07356331221081753</a></p> <p>[3] <a href="http://www.frontiersin.org/Community/WhosWhoActivity.aspx?sname=LailaEl-Hamamsy&UID=781667">Laila El-Hamamsy</a>* , <a href="http://www.frontiersin.org/Community/WhosWhoActivity.aspx?sname=Mar%C3%ADaZapata-C%C3%A1ceres&UID=2073859">María Zapata-Cáceres</a>, Pedro Marcelino, Jessica Dehler Zufferey, <a href="http://www.frontiersin.org/Community/WhosWhoActivity.aspx?sname=BarbaraBruno&UID=893934">Barbara Bruno</a>, <a href="http://www.frontiersin.org/Community/WhosWhoActivity.aspx?sname=EstefaniaMart%C3%ADn&UID=2086979">Estefanía Martín-Barroso</a> and <a href="http://www.frontiersin.org/Community/WhosWhoActivity.aspx?sname=MarcosRom%C3%A1n-Gonz%C3%A1lez&UID=760761">Marcos Román-González</a> (2022). <a href="http://www.frontiersin.org/Journal/Abstract.aspx?d=0&name=Educational_Psychology&ART_DOI=10.3389/fpsyg.2022.1082659">Comparing the psychometric properties of two primary school Computational Thinking (CT) assessments for grades 3 and 4: the Beginners' CT test (BCTt) and the competent CT test (cCTt)</a>. <em>Front. Psychol.</em> doi:10.3389/fpsyg.2022.1082659</p>
Flume Erosion Testing Data of Root-Permeated and Organic Matter Amended Soil Samples Using Three Streambank Boundary Conditions.
The data published here is expected to accompany one publicly available dissertation (Chapter 6 of dissertation) and one separate journal publication. Once published and available online, the metadata will be updated with the relevant article information. The journal article/dissertation will have additional information regarding the published datasets and the methods used to collect the data. All data collected from these studies, and the accompanying Acoustic Doppler Profiler MATLAB files, are presented here. Journal Article title: Artificial Roots and Soil Microorganisms Increase Soil Resistance to Fluvial Erosion
ScienceDex guides
Understand access before you commit
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.