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430 results for “Hydration”
Supplementary Material to "Exothermic reactions and 39Ar–40Ar thermochronology: Hydration leads to younger apparent ages"
<p>Here we briefly describe the supplementary materials for the publication "Exothermic reactions and 39Ar–40Ar thermochronology: Hydration leads to younger apparent ages" in Geology, 52(6), 458-462 by Schorn, S., Moulas, E., & Stüwe, K. (2024).</p>
Supplementary data for "Molecular-scale thermally activated fractures in methane hydrates: A molecular dynamics study"
<p>In this dataset you can find</p> <p>- a data sample that can be used to confirm the plots in the paper. This can be found in the folder "data_sample". Each folder inside "data_sample" is one simulation. It contains the thermodynamic output from the simulation (log.lammps), and the input script (mw_hydrate_pennycrack.in) and input data (s1_unit_cell_mw.data and water_methane_hydrate.sw) that enables rerunning the simulation using LAMMPS.</p> <p>- A custom LAMMPS region, region_ellipsoid. This has to be compiled into LAMMPS in order to create the systems that we simulate.</p> <p>- A python script, plot_data.py, that shows how to extract the relevant data from the lammps log files, which enables the partial reproduction of figure 3 in the paper. See instructions below for requirements to use this script.</p> <p> </p> <p>"region_ellipsoid" and "data_sample" are in zip containers. In order to use them, please unzip them and leave the resulting folders in the same directory as this README file.</p> <p> </p> <p>Installation instructions to make "plot_data.py" work (assuming you already have numpy and matplotlib):</p> <p>> pip3 install git+https://github.com/henriasv/regex-file-collector.git</p> <p>> pip3 install git+https://github.com/henriasv/lammps-logfile.git</p> <p> </p> <p>If this does not work, please contact Henrik Andersen Sveinsson, henriasv@fys.uio.no</p>
Research data for Structure and function of skin barrier lipids: Effects of hydration and natural moisturizers in vitro
<p>Research data for 10.1016/j.bpj.2024.10.006 Research data for Structure and function of skin barrier lipids: Effects of hydration and natural moisturizers in vitro. Biophysical Journal 2024.</p>
Barefoot Rover Hydration Data
<p>This archive contains test data of the Barefoot Rover wheel on hydrated materials.</p> <p>The Barefoot Rover wheel was used to demonstrate an instrumented wheel concept which utilizes a 2D pressure grid, an electrochemical impedance spectroscopy (EIS) sensor and machine learning (ML) to extract meaningful metrics from the interaction between the wheel and surface terrain. These include continuous slip/skid estimation, balance, and sharpness for engineering applications. Estimates of surface hydration, texture, terrain patterns, and regolith physical properties such as cohesion and angle of internal friction are additionally calculated for science applications. Traditional systems rely on post-processing of visual images and vehicle telemetry to estimate these metrics. Through in-situ sensing, these metrics can be calculated in near real time and made available to onboard science and engineering autonomy applications. This work aims to provide a deployable system for future planetary exploration missions to increase science and engineering capabilities through increased knowledge of the terrain.</p> <p>More detailed information about data structures, material properties and test configurations can be found here: https://github.com/JPLMLIA/Barefoot_Rover/tree/master/data</p>
Raw data for"Early hydration of Belite-Ye'elimite-Ferrite cements: role of admixtures"
<p>Raw data for "Early hydration of Belite-Ye’elimite-Ferrite cements: role of admixtures". <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.conbuildmat.2023.130765" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.conbuildmat.2023.130765</span></a></p> <p>Diffraction data is attached here.</p> <pre> </pre>
Data for Hydration in Deep Eutectic Solvents Induces Non-monotonic Changes in the Conformation and Stability of Proteins
<p>This dataset contains the full set of data related to the publication "Hydration in Deep Eutectic Solvents Induces Non-monotonic Changes in the Conformation and Stability of Proteins", published in the Journal of the American Chemical Society 2022, 144 (51), 23657-23667; doi: 10.1021/jacs.2c11190. Full details on data treatment and logging are included in the file "DataLogging.pdf". All data use ASCII encoding in delimited .txt files.</p>
Datasets associated with Uruti Basin gas hydrate heat flow feature investigated as part of Roger Revelle voyage RR1508
<p>Processed seismic reflection data and associated files from Roger Revelle voyage RR1508: 16 May - 18 June 2015. The research voyage aimed to characterise the thermal regime of the gas hydrate systems on the southern Hikurangi margin east of New Zealand. Data were processed using the Globe Claritas processing software.</p> <p>All SEG-Y files have the following binary header word definitions, required for loading data:</p> <p>Start time: 2-byte integer: Bytes 105-106</p> <p>Trace Sample Count: 2-byte integer: Bytes 115-116</p> <p>Sample Interval (microseconds): 2-byte integer: Byte 117-118</p> <p>CDP Number: 4-byte integer: Bytes 5-8</p> <p>CDP X location: 4-byte integer: Bytes 197-200 (Note: Coordinates are in metres of UTM Zone 60S, WGS84 Datum)</p> <p>CDP Y location: 4-byte integer: Bytes 201-204 (Note: Coordinates are in metres of UTM Zone 60S, WGS84 Datum)</p>
Scrutinizing the protein hydration shell from molecular dynamics simulations against consensus small-angle scattering data (Simulation input files)
<p>Simulation input files for gromacs to reproduce the data from the manuscript "Scrutinizing the protein hydration shell from molecular dynamics simulations against consensus small-angle scattering data" (submitted to Comm. Chem.)</p>
Hydration and evaporative water loss of lizards change in response to temperature and humidity acclimation
<p>Data and code associated with the 2023 publication in the Journal of Experimental Biology (doi:10.1242/jeb.246459).</p>
Prevention of Urinary Stones With Hydration
ClinicalTrials.gov study NCT03244189. IPD Sharing: YES. Countries: 1. Publications: 3.
Dataset for NMR quadrature echo and T1 saturation recovery pulse sequences underlying the publication 'On the quantification of solid phases in hydrated cement paste by 1H nuclear magnetic resonance relaxometry'
<p>This record comprises the datasets of combined 1H NMR quadrature echo and T1 saturation recovery pulse sequences underlying the publication “On the quantification of solid phases in hydrated cement paste by 1H nuclear magnetic resonance relaxometry” by Robert Schulte Holthausen & Peter J. McDonald, Cement and Concrete Research, https://doi.org/10.1016/j.cemconres.2020.106095.</p> <p><br> In this work different solid phases, important to cement paste hydration, are investigated with low-field bench top 1H nuclear magnetic resonance with a view to developing an alternate characterisation methodology that requires minimal invasive or destructive sample preparation.</p> <p><br> A combination of the well-established quadrature echo pulse sequence with variable pulse gap together with a T1 saturation recovery quadrature echo pulse sequence is used.</p>
Dataset for "Influence of curing temperature on belite cement hydration: a comparative study with Portland cement" paper
<p>Dataset for paper (doi: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.cemconres.2021.106499" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.cemconres.2021.106499</span></a>) with the abstract "Belite cements (BCs) could be a more sustainable binder than Portland cements (PCs) but adequate knowledge of the hydration features has still to be built. In particular, the mild curing hydration temperature effects have been extensively studied for PCs but not for BCs. This research was triggered by a previous work reporting improved mechanical strengths of BCs at higher curing temperatures. Here, we report the hydration characteristics of a BC at 20, 40 and 60ºC and compared to those of a typical PC. We have corroborated previous findings and used a multi-technique approach including Rietveld phase analysis, thermal analysis, calorimetry, silicon MAS-NMR, mercury intrusion porosimetry and chiefly synchrotron X-ray microtomography, to thoroughly understand the different behavior. In a nutshell, the improved mechanical performances at mild curing temperatures for BCs are due to a much larger belite degree of reaction without a significant porosity coarsening."</p>
The Characteristics and Its Implications of Hydraulic Fracturing in Hydrate-Bearing Clayey Silt
<p>Datasets of the figures in the manuscript 'The Characteristics and Its Implications of Hydraulic Fracturing in Hydrate-Bearing Clayey Silt' to Journal of Natural Gas Science and Engineering.</p>
Data associated to the manuscript "Size-dependence of hydrophobic hydration at electrified gold/water interfaces"
<p>Contains input files and data used to generate the figures of the article: </p> <p>Size-dependence of hydrophobic hydration at electrified gold/water interfaces </p> <p>Alessandra Serva, Mathieu Salanne, Martina Havenith and Simone Pezzotti, <em>arXiv</em>, 2011.08825, 2020</p> <p><a href="https://arxiv.org/abs/2011.08825">https://arxiv.org/abs/2011.08825</a></p> <p>The folder <em>typical_input_files</em> contains typical MetalWalls input files used to perform the simulations. </p> <p>The folder <em>DATA_ASCII_FIGURES</em> contains the processed data used to plot all the figures of the paper.</p>
MD simulation trajectory and related files for POPC bilayer in low hydration (Berger model delivered by Tieleman, Gromacs 4.5)
<p>Equilibrated POPC lipid bilayer simulation in low hydration (7 water per lipid molecule) ran with Gromacs 4.5, Berger force field delivered by Peter Tieleman (http://wcm.ucalgary.ca/tieleman/downloads) with fixed double bond dihedrals, 60ns, T=298K, 128 POPC molecules, 896 water molecules. This data is used in the nmrlipids.blospot.fi project. More details from nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi. If data is used, please cite the nmrlipids.blogspot.fi project and the original publications related to the force field.</p>
MD simulation trajectory and related files for POPC bilayer in low hydration (GAFFlipid, Gromacs 4.5)
<p>Equilibrated POPC lipid bilayer simulation ran with Gromacs 4.5, GAFFlipid force field (http://dx.doi.org/10.1039/C2SM26007G) in low hydration, 40ns, T=303K, 126 POPC molecules, 896 water molecules. This data is ran for the nmrlipids.blospot.fi project. More details from nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi. If data is used, please cite nmrlipids.blogspot.fi project and the original publication of the parameters: Dickson et al. Soft Matter, 2012,8, 9617-9627 http://dx.doi.org/10.1039/C2SM26007G.</p>
Hydrated DPPC, MD simulation trajectory and related files for UA charmm36 model by Lee et al 2014
<p>MD simulation files</p> <p>72 hydrated DPPC + 2189 water TIP3P </p> <p>NPgT</p> <p>P=1atm, gamma=0, T=323K (liquid crystalline phase)</p> <p>20 ns equilibration (not here)</p> <p>50 ns trajectory (dcd file)</p> <p>Model : Lee S, Tran A, Allsopp M, Lim JB, Hénin J, Klauda JB. CHARMM36 United Atom Chain Model for Lipids and Surfactants. <em>J Phys Chem B</em>. 2014;118(2):547-556. doi:10.1021/jp410344g.</p> <p>----<br /> * bilayer-72DPPC-c36-AU.psf : NAMD2.10 structure file Obtained with psfgen utility, using</p> <p>1) topology from Lee et al. 2014</p> <p>2) positions from J. Klauda.</p> <p>http://terpconnect.umd.edu/~jbklauda/research/download.html</p> <p>----</p> <p>* dppc_c36_AU.equil.2.dcd : trajectory file of 2635 frames every 20 ps.</p> <p>---<br /> * measure_SCD_heads.tcl : file used to measure order parameters for the head hydrogens using vmd-1.9</p> <p>---</p> <p>*namd_input.tar files usefull to launch the simulations using NAMD(2.10).</p>
Hydrated DPPC, MD simulation trajectory and related files for UA charmm36 model by Lee et al 2014
<p>MD simulation files</p> <p>72 hydrated DPPC + 2189 water TIP3P </p> <p>NPgT</p> <p>P=1atm, gamma=0, T=323K (liquid crystalline phase)</p> <p>20 ns equilibration (not here)</p> <p>50 ns trajectory (dcd file)</p> <p>Model : Lee S, Tran A, Allsopp M, Lim JB, Hénin J, Klauda JB. CHARMM36 United Atom Chain Model for Lipids and Surfactants. <em>J Phys Chem B</em>. 2014;118(2):547-556. doi:10.1021/jp410344g.</p> <p>----<br /> * bilayer-72DPPC-c36-AU.psf : NAMD2.10 structure file Obtained with psfgen utility, using</p> <p>1) topology from Lee et al. 2014</p> <p>2) positions from J. Klauda.</p> <p>http://terpconnect.umd.edu/~jbklauda/research/download.html</p> <p>----</p> <p>* dppc_c36_AU.equil.2.dcd : trajectory file of 2635 frames every 20 ps.</p> <p>---<br /> * measure_SCD_heads.tcl : file used to measure order parameters for the head hydrogens using vmd-1.9</p> <p>---</p> <p>*namd_input.tar files usefull to launch the simulations using NAMD(2.10).<br /> </p>
Underlying data for "Evaluating parameterization protocols for hydration free energy calculations with the AMOEBA polarizable force field"
<p>This dataset includes underlying data for the publication "Evaluating<br /> parameterization protocols for hydration free energy calculations with the<br /> AMOEBA polarizable force field"</p> <p>Contents:<br /> Modified valence parameters for the Poltype software (valence.py). This can be<br /> substituted for the existing valence.py module packaged with Poltype to make the<br /> parameter assignment changes detailed in the article supplementary information. </p> <p>Results files for each parameter set (*.txt). Each consists of a 4 x 47 array of<br /> numbers. Rows correspond to entries for each sequential ligand. The first column<br /> in each row is the experimental hydration free energy. The following three rows<br /> are computational hydration free energy predictions from three independent<br /> repeat simulations.</p> <p>Script for analysis of results files (analyse_hfe.py). Short script to produce<br /> descriptive statistics for packaged datasets. Expects input files in the syntax<br /> of *.txt (i.e. 4 x 47 arrays)</p>
Molecular dynamics simulation trajectory of a fully hydrated DMPC lipid bilayer
<p><strong>System: </strong>DMPC (dimyristoylphosphatidylcholine) bilayer in water.</p> <p><strong>Number of lipids: </strong>128.<br> <strong>Number of waters:</strong> 5097.</p> <p><strong>Lipid model:</strong> 'Berger' united-atom [<em>Biophys. J.</em> <strong>72</strong> 2002 (1997)].<br> <strong>Water model:</strong> SPC [In <em>Intermolecular Forces,</em> ed. Pullman. 331 (1981)].</p> <p><strong>Simulation engine:</strong> Gromacs 3.x [www.gromacs.org]</p> <p><strong>Trajectory length:</strong> 110 ns.<br> <strong>Previously equilibrated for:</strong> 20 ns.<br> <strong>Sampling rate:</strong> every 10 ps.</p> <p><strong>Time integration step:</strong> 2 fs.</p> <p><strong>Thermodynamic ensemble:</strong> NpT. <br> <strong>Temperature coupling:</strong> 'Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984)] with lipids and water coupled separately at T = 323 K.<br> <strong>Pressure coupling: '</strong>Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984)] with xy and z coupled separately at p = 1.0 bar.</p> <p><strong>Electrostatics: </strong>PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993); <em>J. Chem. Phys.</em> <strong>103</strong> 8577 (1995)], real-space cutoff at 1.0 nm.<br> <strong>Van der Waals:</strong> Truncated at 1.0 nm.</p> <p><strong>Constraints: </strong>Covalent bond lengths in lipids using LINCS [<em>J. Comput. Chem.</em> <strong>18</strong> 1463 (1997)], in water using SETTLE [J. Comput. Chem. <strong>13</strong> 952 (1992)].</p> <p><strong>Used in publications: </strong>[1] Markus S. Miettinen, Andrey A. Gurtovenko, Ilpo Vattulainen, and Mikko Karttunen: "Ion Dynamics in Cationic Lipid Bilayer Systems in Saline Solutions". <em>J. Phys. Chem. B</em> <strong>113</strong> 9226 (2009). DOI: 10.1021/jp810233q. [2] Markus S. Miettinen: "Computational Modeling of Cationic Lipid Bilayers in Saline Solutions". PhD Thesis. Aalto University School of Science and Technology, Helsinki, Finland. (2010). ISBN 978-952-60-3194-1.</p>
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)
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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.