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37 results for “POPE”
Doppler spectra collected by a transect of three MRR-PRO during the POPE 2020 campaign at Princess Elisabeth Antarctica
<p>This repository contain the datasets of Doppler spectra collected by three K-band Doppler profiling radars (MRR-PRO) deployed in a transect across the Sør Rondane Mountains, in the vicinity of the Belgian research base Princess Elisabeth Antarctica (PEA).</p> <p>The measurement campaign has been conducted by the Environmental Remote Sensing Laboratory (LTE) of the École Polytechnique Fédérale de Lausanne (EPFL), with the logistical support of the International Polar Foundation (IPF).</p> <p>The datasets are described in the article “Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica”, by Alfonso Ferrone and Alexis Berne. The article was submitted to Earth System Science Data in August 2022, and is available at the following URL: <a href="https://doi.org/10.5194/essd-2022-295">https://doi.org/10.5194/essd-2022-295</a> .</p> <p>This repository complements "Radar and ground-level measurements collected during the POPE 2020 campaign at Princess Elisabeth Antarctica", uploaded on Zenodo at: <a href="https://doi.org/10.5281/zenodo.7428690">https://doi.org/10.5281/zenodo.7428690</a> . The radar variables in the MRR-PRO data files contained in the latter have been computed from the raw spectra stored in the current repository.</p> <p> </p> <p><strong>Content of the archives</strong></p> <p>- <em>MRR_PRO_23_raw_spectra.zip,</em><br> This archive contains the Doppler spectra collected by the MRR-PRO 23, deployed at the lowest altitude in the transect, at1543 m above mean sea level (a.m.s.l.), at the following coordinates: latitude 72° 6’ 50.4” S, longitude 23° 30’ 50.4” E.</p> <p>- <em>MRR_PRO_06_raw_spectra.zip,</em><br> This archive contains the Doppler spectra collected by the MRR-PRO 06, deployed at approximately 2000 m a.m.s.l. of altitude, at the following coordinates: latitude 72° 7’ 4.8” S, longitude 23° 20’ 49.2” E.</p> <p>- <em>MRR_PRO_22_raw_spectra.zip,</em><br> This archive contains the Doppler spectra collected by the MRR-PRO 22, deployed at the highest location in the transect (2360 m a.m.s.l.), at the following coordinates: latitude 72° 13’ 37.2” S, longitude 23° 11’ 27.6” E.</p> <p> </p> <p><strong>Content of the NetCDF4 files</strong></p> <p>A “short name” is associated to each variables in the NetCDF4 files stored in the three archives.</p> <p>The relevant variables in each data file are:<br> – the raw spectral power, identified in the files by the short name “spectrum_raw”;<br> – the transfer function, used to convert the raw spectral power to spectral reflectivity, as described in Ferrone et al. (2022), and identified in the files by the short name “transfer_function”.</p> <p> </p> <p><strong>References</strong></p> <p>Ferrone, A., Billault-Roux, A.-C., and Berne, A.: ERUO: a spectral processing routine for the Micro Rain Radar PRO (MRR-PRO), Atmospheric Measurement Techniques, 15, 3569–3592, https://doi.org/10.5194/amt-15-3569-2022, 2022</p> <p>Ferrone, A., and Berne, A., Radar and ground-level measurements collected during the POPE 2020 campaign at Princess Elisabeth Antarctica (1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7428690, 2023</p>
Radar and ground-level measurements collected during the POPE 2020 campaign at Princess Elisabeth Antarctica
<p>This repository contain the datasets of radar and ground-level measurements collected in the vicinity of the Belgian research base Princess Elisabeth Antarctica (PEA).</p> <p>The measurement campaign has been conducted by the Environmental Remote Sensing Laboratory (LTE) of the Scole Polytechnique Fédérale de Lausanne (EPFL), with the logistical support of the International Polar Foundation (IPF).</p> <p>The datasets and their processing are described in the article “Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica”, by Alfonso Ferrone and Alexis Berne. The article was submitted to Earth System Science Data in August 2022, and is available at the following URL: <a href="https://doi.org/10.5194/essd-2022-295">https://doi.org/10.5194/essd-2022-295</a> .</p> <p><br> <br> <strong>Content </strong><strong>of the archives</strong><br> The datasets have been divided into compressed archives. Each of them contains a series of data files, all saved in NetCDF4 format.</p> <p>The content of each archives is listed below.</p> <p>- <em>WProf.zip</em><br> This archive contains the radar variables collected by the W-band Doppler profiling cloud radar (WProf) deployed at PEA.<br> The liquid water path and integrated water vapor (retrieved thanks to the 89 GHz radiometer included in the instrument) has also been included in the files.</p> <p>- <em>MXPol_PPI.zip</em><br> This archive contains the polarimetric radar variables collected by the X-band Doppler dual-polarization scanning weather radar (MXPol) during the nearly-vertical PPI scans.</p> <p>- <em>MXPol_sector_scans_2019.zip</em><br> This archive contains the polarimetric radar variables collected by MXPol during the sector scans (PPI scans limited to a sector of the full azimuth circle) scans performed in December 2019. Sector scans collected in the following months have been stored separately, due to a limitation on the maximum number of files in input to the creation of the zip archive.</p> <p>- <em>MXPol_sector_scans_2020.zip</em><br> This archive contains the polarimetric radar variables collected by MXPol during the sector scans scans performed in January and February 2020.</p> <p>- <em>MXPol_hydrometeor_types.zip</em><br> This archive contains the polarimetric radar variables collected by MXPol during the RHI scans. The files also contain information on the proportion of hydrometeor classes and the dominant hydrometeor type computed from the measurements of MXPol.</p> <p>- <em>MRR_PRO_06.zip, MRR_PRO_22.zip, and MRR_PRO_23.zip</em><br> The three archives contain the radar variables collected by the K-band Doppler profiling radars (MRR-PRO) deployed in a transect across the mountain range south of PEA.</p> <p>- <em>aws_radiometers.zip</em><br> This archive contains the measurements collected by the Automated Weather Station (AWS) installed alongside each of the three MRR-PRO. The data from the two radiometers deployed at the MRR-PRO 06 site have also been included in the archive.</p> <p> </p> <p><strong>Content of the NetCDF4 files</strong></p> <p>A “short name” is associated to each variables in the NetCDF4 files. This section provides a list of all the relevant variables collected by each instruments, alongside their short name.</p> <p> </p> <p>The following polarimetric variables are available for all the scans performed by MXPol, stored in the archives <em>MXPol_PPI.zip</em>, <em>MXPol_hydrometeor_types.zip</em>, <em>MXPol_sector_scans_2019.zip</em>, and <em>MXPol_sector_scans_2020.zip</em>:</p> <p>– the horizontal reflectivity factors (Z<sub>H</sub>), identified in the files by the short name “Zh”;</p> <p>– the vertical reflectivity factors (Z<sub>V</sub>), identified by the short name “Zv”;</p> <p>– the differential reflectivity (Z<sub>DR</sub>), identified by the short name “Zdr”;</p> <p>– the signal-to-noise ratio on the horizontal polarization channel (SNR<sub>H</sub>), identified by the short name “SNRh”;</p> <p>– the signal-to-noise ratio on the vertical polarization channel (SNR<sub>V</sub>), identified by the short name “SNRv”;</p> <p>– the mean Doppler radial velocity (V), identified by the short name “RVel”;</p> <p>– the spectral width (SW), identified by the short name “Sw”;</p> <p>– the total differential phase shift (Ψ<sub>DP</sub>), identified by the short name “Psidp”;</p> <p>– the differential phase shift (Φ<sub>DP</sub>), identified by the short name “Phidp”;</p> <p>– the specific differential phase on propagation (K<sub>DP</sub>), identified by the short name “Kdp”;</p> <p>– the co-polar correlation coefficient (ρ<sub>hv</sub>), identified by the short name “Rhohv”.</p> <p> </p> <p>The hydrometeor classification (Besic et al., 2016) and the retrieval of the proportion of each hydrometeor category in the radar volume (Besic et al., 2018) has been applied to all RHI scans of MXPol (archive <em>MXPol_hydrometeor_types.zip</em>), producing the following variables:</p> <p>– the dominant hydrometeor type, identified by the short name “hydro”,</p> <p>– the entropy computed by the classification algorithm, which provides an estimate of the confidence on the label assigned to the volume, identified by the short name “hydroclass_entropy”;</p> <p>– the proportion of each hydrometeor type in the volume, stored in the variables “proportion_AG” (aggregates), “proportion_CR” (ice crystals), “proportion_LR” (light rain), “proportion_RP” (rimed particles), “proportion_RN” (rain), “proportion_VI” (vertically-aligned ice), “proportion_WS” (wet snow), “proportion_MH” (melting hail);</p> <p>– the entropy computed by the demixing algorithm, identified by the short name “entropy”.</p> <p> </p> <p>The following radar variables are available for all the profiles collected by WProf, stored in the archive <em>WProf.zip</em>:</p> <p>– the equivalent reflectivity factor (Z<sub>e</sub>), identified in the files by the short name “Ze”</p> <p>– the signal-to-noise ratio (SNR), identified in the files by the short name “SnR”;</p> <p>– the mean Doppler radial velocity, identified in the files by the short name “Mean-velocity”;</p> <p>– the spectral width, identified in the files by the short name “Spectral-width”;</p> <p>– the skewness, identified in the files by the short name “Spectral-skewness”;</p> <p>– the kurtosis, identified in the files by the short name “Spectral-kurtosis”;</p> <p>– the noise level at each range gate gate, identified in the files by the short name “Noise_level”;</p> <p>– the noise floor at each range gate gate, identified in the files by the short name “Noise_floor”.</p> <p> </p> <p>The following retrievals (Billault-Roux et al., 2021) have been included in the WProf data files, stored in the archive <em>WProf.zip</em>:</p> <p>– the Integrated Water Vapor (IWV), identified in the files by the short name “Integrated-water-vapor”;</p> <p>– the Liquid Water Path (LWP), identified in the files by the short name “Liquid-water-path”.</p> <p> </p> <p>The following atmospheric variables, recorded by the automated weather station integrated in the radar, have been included in the WProf data files, stored in the archive <em>WProf.zip</em>:</p> <p>– the atmospheric pressure, identified in the files by the short name “Barometric-pressure”;</p> <p>– the air temperature, identified in the files by the short name “Environment-temp”;</p> <p>– the relative humidity with respect to liquid water, identified in the files by the short name “Rel-humidity”;</p> <p>– the horizontal wind direction, identified in the files by the short name “Wind-direction”;</p> <p>– the horizontal wind speed, identified in the files by the short name “Wind-speed”.</p> <p> </p> <p>The following variables are available for all the profiles collected by the three MRR-PRO, stored in the archives <em>MRR_PRO_06.zip, MRR_PRO_22.zip,</em><em> and</em><em> MRR_PRO_23.zip</em>:</p> <p>– the attenuated equivalent reflectivity factor (Z<sub>ea</sub>), identified in the files by the short name “Zea”;</p> <p>– the mean Doppler radial velocity, identified in the files by the short name “VEL”;</p> <p>– the spectral width, identified in the files by the short name “SW”;</p> <p>– the signal-to-noise ratio, identified in the files by the short name “SNR”;</p> <p>– the noise level computed by ERUO (Ferrone et al., 2022) at each range gate gate, identified in the files by the short name “noise_level”;</p> <p>– the noise floor computed by ERUO at each range gate gate, identified in the files by the short name “noise_floor”.</p> <p> </p> <p>The following variables are available for all the measurements collected by the three weather stations, stored in the archive <em>aws_radiometers.zip</em>:</p> <p>– the atmospheric pressure, identified in the files by the short name “pressure”;</p> <p>– the air temperature, identified in the files by the short name “temperature”;</p> <p>– the relative humidity with respect to liquid water, identified in the files by the short name “relative_humidity”;</p> <p>– the horizontal wind direction, identified in the files by the short name “wind_speed”;</p> <p>– the horizontal wind speed, identified in the files by the short name “wind_direction”.</p> <p> </p> <p>The following variables are available for all the measurements collected by the pyrgeometer and pyranometer, stored in the archive <em>aws_radiometers.zip</em>::</p> <p>– the total downwelling irradiance in the shortwave, identified in the files by the short name “shortwave_irradiance”;</p> <p>– the total downwelling irradiance in the longwave, identified in the files by the short name “longwave_irradiance”.</p> <p> </p> <p> </p> <p><strong>References</strong></p> <p>Besic, N., Figueras i Venturra, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmospheric Measurement Techniques, 9, 4425–4445, https://doi.org/10.5194/amt-9-4425-2016, 2016.</p> <p>Besic, N., Gehring, J., Praz, C., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Unraveling hydrometeor mixtures in polarimetric radar measurements, Atmospheric Measurement Techniques, 11, 4847–4866, https://doi.org/10.5194/amt-11-4847-2018, 2018<strong> </strong></p> <p>Billault-Roux, A.-C. and Berne, A.: Integrated water vapor and liquid water path retrieval using a single-channel radiometer, Atmospheric Measurement Techniques, 14, 2749–2769, https://doi.org/10.5194/amt-14-2749-2021, 2021</p> <p>Ferrone, A., Billault-Roux, A.-C., and Berne, A.: ERUO: a spectral processing routine for the Micro Rain Radar PRO (MRR-PRO), Atmospheric Measurement Techniques, 15, 3569–3592, https://doi.org/10.5194/amt-15-3569-2022, 2022</p>
Pure POPE membrane simulations with the CHARMM-Drude force field (OpenMM 7.5.0)
<p>MD simulation data of a pure POPE membrane with the CHARMM-Drude force field generated with the OpenMM 7.5.0 simulation engine.</p> <p>All the input parameters are available in the *inp file. The initial structures have been obtained from CHARMM-GUI.</p> <p>Total simulation duration is 300 ns (100 ns x 3, continuing from the last frame, combined with the mdconvert). First 50 ns is discarded as equilibration. This data set contains 300 ns data with 3000 frames (saving frequency is 100 ps).</p> <p>In total, 72 POPC lipids in each leaflet (144 in total), 5040 SWM4-NPD water molecules.</p> <p><strong>It has been discovered that (https://github.com/NMRLipids/Databank/issues/2#issuecomment-1357871243) the previously uploaded trajectory did not have the correct timestamp: the timestep between two consecutive simulation frames was not correctly embedded into the trajectory information. Therefore, with the latest version we are uploading the "unwrapped_all_fixed_dt.xtc" which has the correct timestamp. The frame saving frequency in this trajectory is 100 ps. </strong></p> <p><strong>This new update should not invalidate any previous calculations that did not explicitly read the timestamp information from the trajectory.</strong></p> <p><strong>This simulation consists of 3 sub-trajectories, each of which starts from the last frame of the previous one. These trajectories (originally in dcd format) were concatenated and saved in xtc format with MDAnalysis.</strong></p> <p> </p> <p> </p>
Output of several experiments with Fenics_ice over Smith, Pope, and Kohler Glaciers
<p>Output of several experiments with <a href="https://github.com/EdiGlacUQ/fenics_ice">Fenics_ice</a> over Smith, Pope, and Kohler Glaciers. The code to produce this output can be found in the following repository; <a href="https://github.com/bearecinos/smith_glacier">Smith_glacier</a></p> <p>More information on how to read and plot this data can be found in the smith glacier repository <a href="https://github.com/bearecinos/smith_glacier/wiki">wiki</a>: </p> <p>Citation for the smith glacier repository used to produce this data:</p> <pre>https://zenodo.org/badge/latestdoi/101511241</pre> <p>Citation for the Fenics_ice version used to produce this data:</p> <pre>https://zenodo.org/badge/latestdoi/417440075</pre> <p> </p>
Simulation of a POPE bilayer, lipid model based on OPLS-aa by Rog et al.
<p>A 500 ns-long simulation of a bilayer consisting of 144 POPE lipids and 40 water molecules per lipid. All GROMACS-compatible input and output files are required. Topologies are provided by their original authors.</p> <p>If you use the topologies, please cite the papers indicated in the POPE.itp file.</p>
MacRog pure POPE MD simulation (300 K - 500ns - 1 bar)
<p>MacRog POPE pure bilayer simulation. Starting structure from CHARMM-GUI: the initial PDB file was modified to match MacRog nomenclature and atom order. Temperature was set to 300 K and pressure to 1 bar with 128 POPE lipids fully hydrated: 40 water molecules per lipid. The trajectory contains the whole simulation from 0 to 500 ns skipped every 100 ps and centered on the P atoms. No ions were added as there is no charge in the system. This bilayer was used to calculate the order parameter and the area per lipid for the NMRLipids project (on the time window 200-500 ns).</p> <p>The pope.itp file was obtained from the paper doi : 10.1016/j.dib.2016.03.067. Several corrections have been made to the original file (for more information, go check <a href="https://www.dsimb.inserm.fr/~fuchs/project_Samuli/POPC_POPE/report_results_comparison.pdf">https://www.dsimb.inserm.fr/~fuchs/project_Samuli/POPC_POPE/report_results_comparison.pdf</a>). We provide here the corrected itp file.</p>
Popes pilskalns
Popes pilskalna 3D modelis. Koordinātas: 57.40652,21.8471 https://www.latvijas-pilskalni.lv/popes-pilskalns/ Source: Objaverse 1.0 / Sketchfab
Pure POPE membrane simulations with the CHARMM-Drude force field at 310K (OpenMM)
<p>MD simulation data of a pure POPE membrane with the CHARMM-Drude force field generated with the OpenMM simulation engine at 310K.</p> <p>Parameters from CHARMM-GUI.</p>
MD Simulation data for a pure POPE bilayer with AMOEBA force field + OpenMM
<p>MD simulation data for the POPE bilayer with the AMOEBA-based force field developed by Li (<a href="https://doi.org/10.1080/00268976.2018.1436201">https://doi.org/10.1080/00268976.2018.1436201</a>).</p> <p>The simulation contains 72 POPE lipids and 2880 water molecules. The trajectory is 305,94 ns long (30594 frames with 10 ps saving frequency).</p> <p><strong>It has been discovered that (https://github.com/NMRLipids/Databank/issues/2#issuecomment-1357871243) the openmm_combined.dcd trajectory did not have the correct timestamp: the timestep between two consecutive simulation frames was not correctly embedded into the trajectory information. Therefore, with the latest version we are uploading the "wrapped_full.xtc" which has the correct timestamp. The frame saving frequency in this trajectory is 10 ps. The correction to the timestamp was done via MDAnalysis.</strong></p> <p><strong>This new update should not invalidate any previous calculations that did not explicitly read the timestamp information from the trajectory.</strong></p> <p> </p>
OpenMM simulations of POPE using the CHARMM Drude2023 force field
<p><br> The dataset contains a PSF, a formatted coordinate file (CRD), and DCD files with the final 200 ns from<br> each of 3 replicate simulations from the paper</p> <p><br> <strong>Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion:<br> Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids</strong><br> Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,*<br> Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda*<br> https://doi.org/10.1021/acs.jctc.3c00203</p> <p><br> DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file; each file has frames spaced at 10 ps over a 50 ns interval.</p>
All-atomic simulation of POPE bilayer with RFZ
<p>We have performed simulations of POPE to check if the <strong>reaction-field-zero</strong> mode of calculating electrostatics is a good substitute for PME if we want to avoid PME for some reasons (e.g. for stress calculations). We started this simulation from the configuration deposited by Matti Javanainen (10.5281/zenodo.2641987). We performed the simulation of about 500 ns with the reaction-field-zero protocol supplemented as well. DMPC simulated with the same RFZ protocol is deposited in a separate dataset (10.5281/zenodo.8431709).</p>
Simulation of POPC:POPE 1:1 membrane with the Slipids force field
<p>A POPC:POPE 1:1 bilayer with 100 lipids per leaflet is simulated for 300 ns using the Slipids model and Gromacs simulation engine version 2019.4. The trajectory (.xtc) is saved every 100ps. The simulation parameters (.mdp), the energy file (.edr), the continue point to extend the simulation (.cpt), the run input parameters (.tpr), and the final structure (.gro) are also given. The lipid topologies (.itp) are provided, and the Slipids force field is available at http://www.fos.su.se/~sasha/SLipids/</p>
FIGURE 1 in Anthias albofasciatus Fowler and Bean, 1930, a junior synonym of Tosana niwae Smith and Pope, 1906 (Teleostei: Serranidae: Anthiadinae)
FIGURE 1. Holotypes of A) Anthias albofasciatus, USNM 89988, 74.9 mm SL; B) Tosana niwae, USNM 55618, 83.3 mm SL. (Photographs by S. Raredon)
FIGURE 3 in Anthias albofasciatus Fowler and Bean, 1930, a junior synonym of Tosana niwae Smith and Pope, 1906 (Teleostei: Serranidae: Anthiadinae)
FIGURE 3. Tongues of holotypes of A) Anthias albofasciatus, USNM 89988, 74.9 mm SL; B) Tosana niwae, USNM 55618, 83.3 mm SL. (Photos by S. Raredon)
OpenFF POPE Simulation (64:64 at 310K)
<p>128 lipid bilayer (64:64) hydrated with 5120 TIP3P waters. Equilibrated for 100 ns and simulated for 200 ns at 310K. Full input and output from: https://github.com/PEFrankel/OpenFF_Bilayer.</p><p>Parameters generated by OpenFF Toolkit (Mobley et al., 2018) + Interchange (https://zenodo.org/records/8229243). Forcefield line: 'openff-2.1.0.offxml' from OpenFF Sage (Boothroyd et al., 2023 / https://zenodo.org/records/7889050)</p>
Bronze Pope
sculpture at the entrance of the Carlo Bilotti museum. Source: Objaverse 1.0 / Sketchfab
OpenFF POPE (64:64)
<p>128 lipid bilayer (64:64) hydrated with 5120 TIP3P waters. Equilibrated for 100 ns and simulated for 200 ns at 300K</p> <p>Partial charges assigned with OpenFF AM1BCC</p> <p>Parameters generated by OpenFF Toolkit (Mobley et al., 2018) + Interchange. Forcefield line: 'openff-2.1.0.offxml' from OpenFF Sage</p> <p> </p> <p>/media/julianne/DATA/Lipids/OpenFFLipid/POPC/</p>
GROMOS-CKP POPE Simulations (versions 1 and 2) 313 K
<p>Two GROMOS-CKP POPE bilayer simulations performed using GROMACS 5.0.6 for 500 ns with different starting velocities. Simulations were performed with a 1.4 nm cut-off with PME for the Coulombic and a 1.4 nm cut-off for the van der Waals interactions with a dispersion correction. These simulations were performed at 313 K with a 128 lipid bilayer. The full trajectories are provided bar the initial 100 ns. The starting structure was taken from an equilibrated POPE membrane simulated with an older version of the force field which used the PC charges in the head group (see the SI of https://pubs.acs.org/doi/abs/10.1021/jp207013v). The newer PE parameters were constructed using the standard GROMOS lysine parameters.</p>
Berger POPE Simulations (versions 1 and 2) 303 K - larger repulsive H
<p>Two Berger-based POPE bilayer simulations performed using GROMACS 4.0.7 for 200 ns with different starting velocities. Simulations were performed with a 1.0 nm cut-off with PME for the Coulombic and a 1.0 nm cut-off for the van der Waals interactions with a dispersion correction. These simulations were performed at 303 K with a 128 lipid bilayer. The full trajectories are provided bar the initial 100 ns. The starting structure was taken from an equilibrated POPE membrane simulated with the GROMOS-CKP force field. The PE parameters were constructed following the approach for DOPE used by de Vries et al (https://pubs.acs.org/doi/abs/10.1021/jp0366926), but with a slightly larger repulsive potential included for the explicit hydrogen atoms (designed to increase the area per lipid).</p>
Berger POPE Simulations (versions 1 and 2) 303 K - de Vries repulsive H
<p>Two Berger-based POPE bilayer simulations performed using GROMACS 4.0.7 for 200 ns with different starting velocities. Simulations were performed with a 1.0 nm cut-off with PME for the Coulombic and a 1.0 nm cut-off for the van der Waals interactions with a dispersion correction. These simulations were performed at 303 K with a 128 lipid bilayer. The full trajectories are provided bar the initial 100 ns. The starting structure was taken from an equilibrated POPE membrane simulated with the GROMOS-CKP force field. The PE parameters were constructed following the approach for DOPE used by de Vries et al (https://pubs.acs.org/doi/abs/10.1021/jp0366926), and so include a small repulsive potential on the explicit hydrogen atoms.</p>
ScienceDex guides
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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