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6,498 results for “Physicality”
1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2016
<p>The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2016 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.</p> <p> </p> <p>References:</p> <p> </p> <p>Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726</p> <p> </p> <p>Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791</p> <p> </p> <p>Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687</p> <p> </p> <p>Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097</p> <p> </p> <p>Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.</p> <p> </p> <p>Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO<sub>2</sub>. <em>Journal of Advances in Modeling Earth Systems</em>, <em>12</em>, e2019MS002043. https://doi.org/10.1029/2019MS002043</p>
1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2015
<p>The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2015 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.</p> <p> </p> <p>References:</p> <p> </p> <p>Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726</p> <p> </p> <p>Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791</p> <p> </p> <p>Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687</p> <p> </p> <p>Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097</p> <p> </p> <p>Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.</p> <p> </p> <p>Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO<sub>2</sub>. <em>Journal of Advances in Modeling Earth Systems</em>, <em>12</em>, e2019MS002043. https://doi.org/10.1029/2019MS002043</p>
1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2018
<p>The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2018 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.</p> <p> </p> <p>References:</p> <p> </p> <p>Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726</p> <p> </p> <p>Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791</p> <p> </p> <p>Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687</p> <p> </p> <p>Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097</p> <p> </p> <p>Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.</p> <p> </p> <p>Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO<sub>2</sub>. <em>Journal of Advances in Modeling Earth Systems</em>, <em>12</em>, e2019MS002043. https://doi.org/10.1029/2019MS002043</p>
Data from: a physics-based digital twin for model predictive control of autonomous unmanned aerial vehicle landing
<p>This paper proposes a two-level, data-driven, digital twin concept for the autonomous landing of aircraft, under some assumptions. It features a digital twin instance for model predictive control; and an innovative, real-time, digital twin prototype for fluid-structure interaction and flight dynamics to inform it. The latter digital twin is based on the linearization about a pre-designed glideslope trajectory of a high-fidelity, viscous, nonlinear computational model for flight dynamics; and its projection onto a low-dimensional approximation subspace to achieve real-time performance, while maintaining accuracy. Its main purpose is to predict in real-time, during flight, the state of an aircraft and the aerodynamic forces and moments acting on it. Unlike static lookup tables or regression-based surrogate models based on steady-state wind tunnel data, the aforementioned real-time digital twin prototype allows the digital twin instance for model predictive control to be informed by a truly dynamic flight model, rather than a less accurate set of steady-state aerodynamic force and moment data points. The paper describes in detail the construction of the proposed two-level digital twin concept and its verification by numerical simulation. It also reports on its preliminary flight validation in autonomous mode for an off-the-shelf unmanned aerial vehicle instrumented at Stanford University.</p>
Motor performance in violin bowing: Effects of attentional focus on acoustical, physiological and physical parameters of a sound-producing action
<p>Violin bowing is a specialised sound-producing action, which may be affected by psychological performance techniques. In sport, attentional focus impacts motor performance, but limited evidence for this exists in music. We investigated the effects of attentional focus on acoustical, physiological, and physical parameters of violin bowing in experienced and novice violinists. Attentional focus significantly affected spectral centroid, bow contact point consistency, shoulder muscle activity, and novices’ violin sway. Performance was most improved when focusing on tactile sensations through the bow (somatic focus), compared to sound (external focus) or arm movement (internal focus). Implications for motor performance theory and pedagogy are discussed.</p>
Spectroscopic and Electric Properties of the TaO$^+$ Molecule Ion for the Search of New Physics: A Platform for Identification and State Control: Dataset
<p>This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper titled "Spectroscopic and Electric Properties of the TaO<sup>+</sup> Molecule Ion for the Search of New Physics: A Platform for Identification and State Control", by Ayaki Sunaga and Timo Fleig.</p>
Physical Informed Deep Learning Reconstructs Missing Climate Information in the Antarctic
<p>Here is the code and data corresponding to the Physical Informed Deep Learning Reconstructs Missing Climate Information in the Antarctic article.</p> <p><strong>Reanalysis data</strong><br> In the reanalysis data folder, skin temperature data and wind speed data are in two different folders. The reanalysis data is the monthly average of the ERA-Interim from European Centre for Medium-Range Weather Forecasts (ECMWF) for 40 years from 1979 to 2018, with 1.5° latitude × 1.5° longitude resolution. The first 30 years are used as training data, and the next 10 years are used as test data. And the variables such as skin temperature (K, Kelvins) and surface wind speed (m/s, meter per second) are selected for experiments in Antarctic region (longitude (0°-360°), latitude (60°S-90°S)). </p> <p><strong>Station data</strong><br> The station data folder contains real observations from 180 weather stations in the Antarctic region. These include variables such as temperature, wind speed, and wind direction.</p> <p><strong>PI-RFR</strong><br> The PI-RFR folder contains the code for this method, including training, testing, mask generation and network structure.</p> <p>Requirements:<br> - Python >= 3.6<br> - PyTorch >= 1.6<br> - Numpy == 1.20.3<br> - NetCDF4 == 1.5.7<br> - h5py == 3.3.0</p> <p><strong>Train & Test</strong><br> To training or testing, use</p> <pre><code class="language-python">python run.py python run.py --test</code></pre> <p><br> </p>
Dataset for "Quantifying the physical impact of bottom trawling based on high-resolution bathymetric data"
<p>Bathymetric point cloud data and ship log data used for the article "Quantifying the physical impact of bottom trawling based on high-resolution bathymetric data" by Mischa Schönke, David Clemens and Peter Feldens (<a href="https://doi.org/10.3390/rs14122782">https://doi.org/10.3390/rs14122782</a>)</p>
Taking up and terminating leisure-time physical activity over the life course: The role of life events in the familial and occupational life domains
<p>Dataset used for the analyses in the following publication:</p> <p>Lenze, L., Klostermann, C., Lamprecht, M. & Nagel, S. (2021). Taking up and terminating leisure-time physical activity over the life course: The role of life events in the familial and occupational life domains. <em>International Journal of Environmental Research and Public Health</em>, <em>18</em>, 9809. https://doi.org/10.3390/ijerph18189809</p>
Data for "Physically Based Deep Learning Framework to Model Intense Precipitation Events at Engineering Scales"
<p>The dataset consists of high resolution (250 m) and low resolution (0.025 degree) climate model outputs in netCDF format. Each file contains data for one variable and one month.</p> <p>Low resolution files follow the naming scheme: montrealC_0025deg_200x200_ERA5_1m_YYYYMM_VAR.nc</p> <p>High resolution files follow the naming scheme: montrealC_250m_324x324_ERA5_TEB_100_noconv_YYYYMM_VAR.nc</p> <p>YYYYMM stands for the year (first 4 digits) and month (last 2 digits).</p> <p>_VAR indicates the variable contained in the file:</p> <ul> <li>_UU700 stands for the east-west component of wind at a pressure level of 700 hPa (hourly frequency)</li> <li>_VV700 stands for the north-south component of wind at a pressure level of 700 hPa (hourly frequency)</li> <li>When _VAR is omitted, the variable is precipitation at 1-minute temporal resolution</li> </ul>
Dolutegravir in Real Life: self-reported mental and physical health outcomes after transitioning from efavirenz- to dolutegravir-based antiretroviral therapy in a prospective cohort study in Lesotho
<p>Pseudonymized dataset for the accepted manuscript "<em>Dolutegravir in Real Life: self-reported mental and physical health outcomes after transitioning from efavirenz- to dolutegravir-based antiretroviral therapy in a prospective cohort study in Lesotho</em>"</p>
Porous Media Modeling and Physical Property Analysis
<p>This is a supplementary dataset for the submitted manuscript. The dataset includes CT samples, porous media models, permeability and elasticity result data, and Matlab code to implement the modeling.</p>
Evolution of physical linkage between loci: simulations output
<p>Coupling of multiple barriers to gene-flow, such as divergent local adaptation and reproductive isolation, facilitates speciation. However, alleles at loci that contribute to barrier effects can be dissociated by recombination. Models of linkage between diverging alleles often consider elements that reduce recombination, such as chromosomal inversions and alleles that modify recombination rate between existing loci. In contrast, here we consider the evolution of linkage due to close proximity of loci on the same chromosome. Examples of such physical linkage exist in several species, but in other cases strong associations are maintained without physical linkage. We use an individual-based model to study the conditions under which physical linkage between loci controlling ecological traits and mating preferences might be expected to evolve. We modelled a single locus controlling an ecological trait that acts also as a mating cue<span>.</span> Mating preferences are controlled by multiple loci, formed by mutations that are randomly placed in the "genome", within varying distances from the ecological trait locus, allowing us to examine which genomic architectures spread across the population. </p>
Research data for "Indirect learning and physically guided validation of interatomic potential models"
<p>This dataset contains structural data, potential parameter files, and data shown in the plots for the publication "Indirect learning and physically guided validation of interatomic potential models". Details of the contents can be found in README.txt.</p>
Datasets for The Dynamics of Megafire Smoke Plumes in Climate Models: Why a Converged Solution Matters for Physical Interpretations
<p>The data in this repository contains the information needed to reproduce the core results of the paper, "The Dynamics of Megafire Smoke Plumes in Climate Models: Why a Converged Solution Matters for Physical Interpretations" submitted to the Journal of Advances in Modeling Earth Systems (JAMES) on 10/3/2022.</p> <p> </p> <p>The "intsmoke*.txt" files are text files with the globally integrated smoke mass above 150 hPa for all simulations in the paper. A header is provided in each file.</p> <p>The "spectra*.mat" files are matlab files that contain fields used to plot the kinetic energy spectra for all simulations. The variable "kes" is the kinetic energy as a function of wavelength, "wvl" are the associated wavelengths of "kes". The variables "hcut" and "lcut" represent the indices of the data "kes" and "wvl" that are used to make the kinetic energy spectra plots in the paper.</p> <p>The "budget*.nc" files contain the budget terms for the relative, vertical vorticity evolution equation at the appropriate date/time. The fields in the netcdf file are self-describing. These budget terms are for the "optimal simulation" described in the paper.</p> <p>The "vort*.nc" file contains the vorticity fields just before the plume forcing starts based on the date/time on the file.</p>
1/8˚ resolution MOM6-COBALT physical and biogeochemical diagnostics interpolated to 1˚, monthly means between 1965-2017
<p>Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research. This dataset contains dissolved oxygen, nitrate, temperature and salinity data interpolated to monthly means with 1˚ latitude/longitude horizontal resolution, between 1965-2017.</p> <p>References:</p> <p> </p> <p>Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726</p> <p> </p> <p>Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791</p> <p> </p> <p>Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687</p> <p> </p> <p>Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097</p> <p> </p> <p>Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.</p> <p> </p> <p>Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO<sub>2</sub>. <em>Journal of Advances in Modeling Earth Systems</em>, <em>12</em>, e2019MS002043. https://doi.org/10.1029/2019MS002043</p> <p> </p>
Figure 3 in Macroinvertebrates responses based on chemical and physical variables in urban streams
Figure 3. Canonical correspondence analysis (CCA) between the benthic macroinvertebrates groups and the water variables from the sampled streams.
Figure 1 in Macroinvertebrates responses based on chemical and physical variables in urban streams
Figure 1. Map showing the sampled streams. Letters represent the following streams: E = Espraiado, B = Belvedere, C = Canchim, P = Ponte de Tábua, S = São Rafael and D = Douradinho.
Figure 1 in Physical clutter affects the use of artificial ponds by the Lesser Bulldog Bat Noctilio albiventris (Chiroptera: Noctilionidae)
Figure 1. Artificial pond at Universidad de los Llanos where the experiments using Noctilio albiventris were done. In the image is shown the situation using the highest density of obstacles.
Figure 2 in Physical clutter affects the use of artificial ponds by the Lesser Bulldog Bat Noctilio albiventris (Chiroptera: Noctilionidae)
Figure 2. Number of passes (A) and feeding buzzes (B) made by Noctilio albiventris in five-minutes recordings while foraging over an artificial pond with different levels of clutter: without obstacles (control), with one line of obstacles, and with two lines of obstacles. There were only significant differences between the control and the treatment with the highest clutter density. The line inside the boxes is the median, whereas the top and bottom are the 75 and 25 percentiles, respectively; the whiskers indicate the 90 and 10 percentiles, and the points are outliers.
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.