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131 results for “Dissipation”
Acute stress and restricted diet reduce bill-mediated heat dissipation in the song sparrow (Melospiza melodia): Implications for optimal thermoregulation
<p>We used thermal imaging to show that two environmental factors—acute stress and diet—influence thermoregulatory performance of a known thermal window, the avian bill. The bill plays important roles in thermoregulation and water balance. Given that heat loss through the bill is adjustable through vasoconstriction and vasodilation, and acute stress can cause vasoconstriction in peripheral body surfaces, we hypothesized that stress may influence the bill's role as a thermal window. We further hypothesized that diet influences heat dissipation from the bill given that body condition influences the surface temperature of another body region (the eye region). We measured the surface temperature of the bills of song sparrows (<em>Melospiza</em> <em>melodia</em>) before, during, and after handling by an observer at 37°C ambient temperature. We fed five birds a restricted diet intended to maintain bodyweights typical of wild birds, and we fed six birds an unrestricted diet for five months prior to experiments. Acute stress caused a decrease in the surface temperature of the bill, resulting in a 32.4% decrease in heat dissipation immediately following acute stress, before recovering over approximately 2.3 minutes. The initial reduction and subsequent recovery provide partial support for the haemoprotective and thermoprotective hypotheses, which predict a reduction or increase in peripheral blood flow, respectively. Birds with unrestricted diets had larger bills and dissipated more heat, indicating that diet and body condition influence bill-mediated heat dissipation and thermoregulation. These results indicate that stress-induced vascular changes and diet can influence mechanisms of heat loss and potentially inhibit optimal thermoregulation.</p>
Dissipative Solitons and Switching Waves in Dispersion-Modulated Kerr Cavities
<p>Execution tested with Matlab 2020a or newer on Windows. Unzip folder to access files.</p> <p><br> Contact miles.anderson@epfl.ch for any serious questions on the contents.<br> All matlab code remains under copyright by the authors: Miles Anderson and Tobias J. Kippenberg, and is provided solely to be used to reproduce the figures of the aforementioned paper and example simulation results pertaining to the paper.</p> <p>Figure data and generation code is found in "Figure Data\Scripts and Data". Run matlab scripts in the given folder to generate the figures. Other relevant figures containing data is found in "\Other".</p> <p>Seven example matlab simulation scripts are found in "Simulation Example Code".</p> <ul> <li>Running 'lle_cavity_v4_CW_FI_Low2' models CW Faraday Instability appearance from Figure 3, in dimensionless units.</li> <li>Running 'lle_cavity_v4_Soliton_FI_1' models a dissipative soliton with Kelly sidebands or higher-order dispersive waves in dispersion modulated cavity, from Figure 4, in dimensionless units.</li> <li>Running 'lle_cavity_v4_SW_FI_Low2' models a switching wave with FI-motivated satellites in dispersion modulated cavity, from Figure 7, in dimensionless units.</li> <li>Running 'lle_SiNcavity_v4_SW_FaradaySatellite_F9C15R6_1_1b' (or just '1') uses experimental data to reproduce the experiment for the pulse-driven switching wave according to the LLE, the results of which are shown in Figure 7(f) of the main paper, and Figure S5 of the supplementary information.</li> <li>Running 'lle_SiNcavity_v4_SW_FaradaySatellite_F2C15R5_2_3' (and also '3_1') uses experimental data to reproduce the experiment for the pulse-driven switching wave according to the LLE, the results of which are shown in Figure 8 and 9 of the main paper, and Figure S6 of the supplementary information.</li> <li>Running 'lle_SiNcavity_v4_SolitonHDW_F1C16R6TM_5_s2' uses experimental data to reproduce the experiment as seen in Figure 6 for the pulse-driven soliton according to the LLE, results of which are shown in Figure S9 of the supplementary information.</li> </ul> <p>The script parameters may be modified to find results under different driving conditions and over different time periods and sampling rates as required.</p> <p>M. Anderson apologises in advance for the complexity, readability, and optimisation of the script.</p> <p>This work was supported by Contract No. D18AC00032 (DRINQS) from the Defense Advanced Research Projects Agency (DARPA). This material is based upon work supported by the Air Force Office of Scientific Research under Grant No. FA9550-19-1-0250. This work was further supported by the European Union’s Horizon 2020 Program for Research and Innovation under Grant No. 812818 (Marie Skłodowska-Curie ETN MICROCOMB) and by the Swiss National Science Foundation under Grant Agreement No. 192293.</p>
Scripts and datas for "Global Estimation of the Eddy Kinetic Energy Dissipation from a Diagnostic Energy Balance"
<p>Input and output datasets used for a global reconstruction of the eddy kinetic energy (EKE) dissipation rate in relation to a submitted work :</p> <p><strong>R. Torres, R. Waldman, J. Mak and R. Séférian </strong>: <em>Global Estimation of the Eddy Kinetic Energy Dissipation from a Diagnostic Energy Balance</em>.</p> <p>Inputs datas include a merge of 2 datasets from the World Ocean Atlas 2018 (WOA18, Garcia et al., 2019) and cover the 1995-2017 (95B7) period. Folder structure for the surface altimetry L4 datasets from the EU-Copernicus Marine Services (2021) is kept empty in order to limit the archive size. Datas can be download <a href="https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_L4_MY_008_047/services">here</a>.</p> <p>Optional datasets include CMEMS MDT product (<em>CMEMS/SEALEVEL_GLO_PHY_MDT_008_063/P20Y</em>) downloaded <a href="https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_MDT_008_063/">here</a> and ocean masks (<em>misc/basins/doi_10.5281</em>) from Martinez-Moreno et al. (2021).</p> <p>In addition, simulation outputs from the NEMO-OMIP2 model runned with the GEOMETRIC parameterization are processed (mainly time-averaged) and stored in <em>CNRM/runs/omip2_LR.Geom_Emin0-alpha01_1cyc-trd/post</em>. These files are used in the uncertainties and errors quantification.</p> <p>Outputs and published results are stored in each individual product post-processing folder while final EKE dissipation computation are located in the <em>EKE_dissipation_rate</em> folder since it results from a combination of multiple products.</p> <p>IPython notebooks for computing and plotting global maps are also provided :</p> <ul> <li><em>1-post_process_climato.ipynb</em> : compute from the climatology (e.g. WOA18 datas) the EKE dissipation timescales (units in days) and the surface modes with rough topography (LaCasce and Groeskamp, 2020).</li> <li><em>2-post_process_altimetry.ipynb</em> : compute from altimetry (CMEMS) datasets the EKE at surface and eventually coarsen the grid from 0.25 to 1 degree in order to match the climatology grid.</li> <li><em>3-compute_global_eke_dissipation.ipynb</em> : combine both outputs from the two above scripts to compute the global EKE dissipation. The script also plots new maps.</li> <li><em>0-plot_global_maps.ipynb</em> : plot the global maps for climatology and altimetry products.</li> <li><em>0-plot_lbekedis_ogcm.ipynb</em> : plot and analyse EKE timescale errors from the NEMO-OMIP2 simulation outputs.</li> </ul> <p>Note however that these scripts use the author python library XOCE availbale on GitHub: https://github.com/torresr-cnrm/xoce. All the scripts have been runned using the version 0.2 of XOCE. Feel free to contact (romain.torres@meteo.fr) for any help in installing and using this library.</p>
Constraining an eddy energy dissipation rate due to relative wind stress for use in energy budget-based eddy parameterisations
<p>Code and data to reproduce results in the EGU Ocean Science journal paper, entitled 'Constraining an eddy energy dissipation rate due to relative wind stress for use in energy budget-based eddy parameterisations'.</p> <p>The data and corresponding scripts in this repository are:</p> <ul> <li>MITgcm simulation data for an anticyclone and cyclone under absolute and relative wind stress. <ul> <li>ACE_eta_{absolute or relative}_10km_A25_v2_ext.nc</li> <li>ACE_tau_{absolute or relative}_10km_A25_v2_ext.nc</li> <li>ACE_temp_{absolute or relative}_10km_A25_v2_ext.nc</li> <li>CE_eta_{absolute or relative}_10km_A25_v2.nc</li> <li>CE_tau_{absolute or relative}_10km_A25_v2.nc</li> <li>CE_temp_{absolute or relative}_10km_A25_v2.nc</li> </ul> </li> <li>Mean energetics computed using eddy_energy_mean.m. User may need to comment out lines of code relating to wvel. This also requires geostrophic_uv.m, rho_ref.mat, and ocean_vertical_grid.nc. <ul> <li>{ACE or CE}_energy_{absolute or relative}_total_10km_A25_mean.nc</li> </ul> </li> <li>Predicted eddy energy computed using predict_*.m scripts. n.b. viscous term left in absolute scripts, though we only need the first index of total eddy energy in abs cases. The abs cases are really just making the abs.mat files, see time_series_plots.py.</li> <li>Time-series figures (3 and 5) produced using time_series_plots.py.</li> <li>Initial figures (1 and 2) produced using initial_plots.py.</li> <li>Relative vorticity in Fig. 4 computed and plotted using eddy_evolution_plot.py.</li> <li>Dissipation rates computed in calc_dissipation_rate.m. Requires dynmodes.m and GSW toolbox to run. Also needs data Chelton2011_Le.csv and Chelton2011_Rd.csv. <ul> <li>diss_rate*.nc</li> </ul> </li> <li>Dissipation rate and climatology figures (6, 7, 8, and 9) made in diss_rate_plot.py</li> </ul> <p>Information and data needed to run the MITgcm can be found <a href="https://github.com/thomaswilder/jpo_eddy-scripts">here</a>.</p>
Data from: Can IR images of the water surface be used to quantify the energy spectrum and the turbulent kinetic energy dissipation rate?
Open the record for dataset details and reuse information.
Acute stress and restricted diet reduce bill-mediated heat dissipation in the song sparrow (Melospiza melodia): Implications for optimal thermoregulation
Open the record for dataset details and reuse information.
Temperature differences in hardwood trees using thermal dissipation probes in Hubbard Brook Experimental Forest, NH and Bartlett Experimental Forest, NH
The MELNHE study looks at patterns of resource limitation through nutrient manipulations in three study sites in New Hampshire: Bartlett Experimental Forest, Hubbard Brook Experimental Forest, and Jeffers Brook, located in the White Mountain National Forest. The investigation is monitoring stem diameter, leaf area, sap flow, foliar chemistry, leaf litter production and chemistry, foliar nutrient resorption, root biomass and production, mycorrhizal associations, soil respiration, heterotrophic respiration, N and P availability, N mineralization, soil phosphatase activity, soil carbon and nitrogen, nutrient uptake capacity of roots, and mineral weathering. Applications of N and P began in June 2011 and continue at the rate of 30 kg N/ha/yr (as NH4NO3) and 10 kg P/ha/yr (as NaH2PO4). This dataset was produced using thermal dissipation probes in hardwood trees. We recorded temperature differences between the reference and heated over multiple days in five hardwood species across 5 years. Sites are located in Bartlett Experimental Forest and Hubbard Brook Experimental Forest in NH. The number of trees in each plot and species vary among years. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Data and code for figures in "A dissipative quantum reservoir for microwave light using a mechanical oscillator"
<p>Data and code used to produce the figures in "A dissipative quantum reservoir for microwave light using a mechanical oscillator".</p> <p>The code is tested with Python 2.7.10, Matplotlib 2.0.0b4, Scipy 0.18.0.</p>
Numerical dataset for quantum trajectory simulations of a dissipative qubit under continuous measurement and feedback
<p>The data consist of numerical results obtained from quantum trajectory simulations of a dissipative qubit under continuous measurement and feedback.</p> <p>These data are used in the preprint titled <em>"Heat current and fluctuations between a dissipative qubit and a monitor under continuous measurement and feedback."</em></p> <p>We performed numerical simulations of the stochastic master equation using the supercomputer at ISSP.</p> <p>The contents are as follows:</p> <ul> <li>Numerical results for the correlation functions (<code>F*.dat</code>).</li> <li>Numerical results for the Fano factor and the power spectrum (<code>fano_factor*.dat</code>).</li> <li>Python code to calculate the Fano factor and the power spectrum from the correlation functions (<code>fano_factor_v6.py</code>).</li> <li>Figures illustrating the Fano factor and the power spectrum (<code>fig*.eps</code>).</li> </ul>
Data for "Wave dispersion and dissipation in landfast ice: comparison of observations against models"
<p>Data to replicate Figures 2, 3 and 7 in the manuscript: Wave dispersion and dissipation in landfast ice: comparison of observations against models. Article submitted for review to The Cryosphere (https://doi.org/10.5194/tc-2021-210)</p>
Cross-shore distribution of the wave-induced circulation over a dissipative beach under storm wave conditions: the dataset
<p>###</p> <p>Author: Marc Pezerat (marc.pezerat@univ-lr.fr or pezeratm@gmail.com)</p> <p>Date: 19/01/2022</p> <p>Purpose: This repository provides the field observations presented in the paper referred below</p> <p>Reference: Pezerat, M., Bertin, X., Martins, K. and Lavaud, L. (2022) Cross-shore distribution of the wave-induced circulation over a dissipative beach under storm wave conditions. Submitted to Journal of Geophysical Research-Ocean</p> <p>###</p> <p>* The directory Obs includes :</p> <p>(1) Wave bulk parameters, computed as described in the paper for the 7 sensors used in this study (.dat files) : the offshore AWAC and ADCP 600 kHz, the intertidal ADCP2MHz, PT2, PT3, ADV and PT5. For the three ADCP and the ADV, the average velocity measurements within the fixed wave cell of both horizontal components of the current in the ENU frame are provided ("uwcell" and "vwcell"). The field "wdepth" corresponds to the water depth above the seabed (i.e. corrected from sensor's elevation). The fields "fmin" and "fc" are the boundaries for the wave energy frequency spectra integration performed to compute the wave bulk parameters.</p> <p>(2) The vertical velocity profiles of the three components of the current in the ENU frame (u,v,w and hv, which corresponds to the norm of the horizonal current) for the three ADCP, provided in netCDF files in which the coordinate "z" corresponds to the height above the seabed.</p> <p>* The file sensors_loc.dat gathers the coordinates and the elevation above the seabed of each sensor.</p> <p>* The file "SaintTrojan_bathy_topo_ST2021.gr3" corresponds to the grid with the bathymetry used for this study in a format compliant with SCHISM-WWM.</p> <p>* The file "ww3.bnds_SaintTrojan_0.2d_ZWND14m_20210110_20210301_spec.nc" contains wave energy spectra issued from a North Atlantic application of Wavewatch III model that are used to force WWM at the offshore boundary.</p>
Wake vortices and dissipation in a tidally modulated flow past a three-dimensional topography
<p>LES simulation data of tidally modulated flow past an abyssal hill. Data used in the figures are available</p>
Dataset for XBeach model calibration and simulation of sample storms in an intermediate-to-dissipative, microtidal coast (Sabaudia, Italy)
<p>The archive contains XBeach input data and datasets used for the calibration of the hydrodynamic model XBeach and subsequent simulation of six sample storms at different tidal levels at the intermediate-to-dissipative, microtidal coast of Sabaudia (Tyrrhenian Sea, Italy).</p> <p>VERSION v2 (January 24, 2022): uploaded a new version of the dataset to support the revised version of the manuscript.</p>
Wave dissipation and mean circulation on a shore platform under storm wave conditions: the dataset
<p>###</p> <p>Author: Laura Lavaud (laura.lavaud@univ-lr.fr or llavaud@orange.fr)</p> <p>Date: 11/02/2022</p> <p>Purpose: This repository provides the field observations presented in the paper referred below</p> <p>Reference: Lavaud, L., Bertin, X., Martins, K., Pezerat, M., Coulombier, T., Dausse, D. (2022). Wave dissipation and mean circulation on a shore platform under storm wave conditions. Submitted to Journal of Geophysical Research-Earth Surface</p> <p>###</p> <p>* The directory storm_conditions is relative to the field campaign conducted in storm conditions, it includes:</p> <p>(1) Wave bulk parameters, computed as described in the paper for the 8 sensors used in this study: (SENSOR_Date_WDepth_Hm0_Tm02_Tpc_Fmin_Fmax.dat files) : the offshore ADCP 600 kHz and PT2, the intertidal PT4, 5, 6, 8, 9 and 10. The field "WDepth" in the title of each file corresponds to the mean water depth above the seabed (i.e. corrected from sensor's elevation above the bed), Hm0 is the significant wave height, Tm02 the mean wave period and Tpc the continuous peak period. The fields "Fmin" and "Fmax" are the boundaries for the integration of the wave energy frequency spectra performed to compute the wave bulk parameters.</p> <p>(2) The file ADV7_Date_WDepth_horizontal_current_ENU_20minburst.dat contains the WDepth and the horizontal components of the velocity at the ADV in the ENU frame, averaged over bursts of 20 minutes. </p> <p>(3) The file sensors_coordinates_storm_cond.dat gathers the coordinates and the NGF (IGN69) elevation of the seabed at the location of each sensor.</p> <p>* The directory fair_weather_conditions is relative to the field campaign conducted in fair weather conditions, it includes:</p> <p>(1) Wave bulk parameters, computed for the 6 sensors used in this study (SENSOR_Date_WDepth_Hm0_Tm02_Tp_Fmin0pt04_Fmax0pt25.dat files) : the intertidal ADCP 2MHz, PT0, PT1, ADV, PT2 and PT3.</p> <p>(2) The file sensors_coordinates_fairweather_cond.dat gathers the coordinates of each sensor.</p> <p>* The directory model_input_files includes the files used to run the simulations presented in this study:</p> <p>(1) The SCHISM and WWM input files (param.nml and wwminput.nml) and the vertical grid (vgrid.in)</p> <p>(2) The file "ww3.bnd_spec_20200120_20200229.nc" which corresponds to directional wave energy spectra used to force WWM at the open boundary of the computational grid. These spectra were computed from a North Atlantic application of Wavewatch III model forced by CFSR wind fields. </p>
Dissipation-enhanced collapse singularity of a nonlocal fluid of light in a hot atomic vapor
<p>This repository contains the data presented in the manuscript titled " Dissipation-enhanced collapse singularity of a nonlocal fluid of light in a hot atomic vapor " by P.Azam et al., Phys. Rev. A <strong>104</strong>, 013515 – Published 15 July 2021</p> <p>The .zip file contains a folder for each figure, a folder ("mesures") with the full dataset and analyzed measured and a code .mat to plot fig 1,2,3,6.</p> <p>Codes to plot fig 4 and 5 are in respective folders.</p>
Data and code for the article "Hierarchical tensile structures with ultralow mechanical dissipation"
<p>Data and code for the article "Hierarchical tensile structures with ultralow mechanical dissipation", consisting of all the ringdown measurements, spectra and codes for data analysis and generation of the fabrication GDS masks.</p>
Data+Analysis+Plotting scripts for "Constraint on the dissipative tidal deformability of neutron stars"
<p>The .zip file contains three directories. </p> <p>1. GW170817-Strain: the raw data (glitch free). Downloaded from https://gwosc.org/events/GW170817/.<br>2. Bilby-Output: the output from running our Bilby sampling scripts. These can be found at https://github.com/JLRipley314/NRTidal-D/tree/main<br>3. Plotting-Scripts: the plotting scripts we used in our paper https://arxiv.org/abs/2312.11659.</p> <p>NOTE: If you want to make sure the plotting scripts work properly, you should download bilby and related dependencies as described in https://github.com/JLRipley314/NRTidal-D/tree/main (or at https://doi.org/10.5281/zenodo.11589416)</p>
Unitary unraveling for the dissipative continuous spontaneous localization model: Application to optomechanical experiments
<p>bounds.nb - Main program </p>
Tidal dissipation and evolution of white dwarfs around massive black holes: an eccentric path to tidal disruption
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017MNRAS.468.2296V">Tidal dissipation and evolution of white dwarfs around massive black holes: an eccentric path to tidal disruption</a></p>
Dynamical tides in highly eccentric binaries: chaos, dissipation, and quasi-steady state
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.476..482V/abstract">Dynamical tides in highly eccentric binaries: chaos, dissipation, and quasi-steady state</a></p>
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