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619 results for “configuration”
NaCl force field study: All the radial distribution functions and final configurations (PDB)
<p>The package contains all the radial distribution functions and final configurations (PDB) from our NaCl force field study</p> <ul> <li><a href="http://dx.doi.org/10.1002/jcc.10417">Systematic comparison of force fields for microscopic simulations of NaCl in aqueous solutions: Diffusion, free energy of hydration and structural properties</a>, M. Patra and M. Karttunen, physics/0211059. J. Comp. Chem. 25, 678-689 (2004) .</li> </ul> <p> </p> <p> </p>
Configuration de la rue Dinso - Proposition d'une méthodologie de reconstruction d'évènement à partir d'images
<p>Le fichier doit être téléchargé et visionné à l'aide d'un lecteur multimédia.</p> <p>Figure 3a. Présentation de la configuration de la rue Dinso avec les véhicules, les protagonistes et les points de vue des caméras : en rouge les caméras de vidéosurveillance, en cyan la dernière image du caméraman et en jaune l'image de la personne muni d'un drapeau.</p> <p>Cette animation est générée à partir d'un modèle 3D de la scène. Il s’agit d’un agrégat d’actions qui se sont déroulées à des moments différents. Ils sont ajoutés à une même représentation, qui donne une vue d’ensemble des situations reconstruites</p>
2D Ising model Monte Carlo configurations for the paper Entropy from Machine Learning
<p>Monte Carlo configurations for the 2D Ising model on a periodic 20x20 lattice used in the paper <em>Entropy from Machine Learning.</em></p> <p>Contains:</p> <ul> <li>20000 configurations for each temperature in the range T=1.0 to T=4.0 in 0.1 intervals</li> <li>40000 configurations at T=Tc</li> <li>README.md file with information about reading into Python</li> </ul> <p>See repository <a href="https://github.com/rmldj/ml-entropy">github.com/rmldj/ml-entropy.</a></p>
Understanding How Feature Dependent Variables Affect Configurable System Comprehensibility
<p><strong>Background:</strong> #ifdefs allow developers to define source code related to features that should or should not be compiled. A feature dependency occurs in a configurable system when source code snippets of different features share code elements, such as variables. Variables that produce feature dependency are called dependent variables. The dependency between two features may include just one dependent variable or more than one. It is reasonable to suspect that a high number of dependent variables and their use make the analysis of variability scenarios more complex. In fact, previous studies show that #ifdefs may affect comprehensibility, especially when their use implies feature dependency. <strong>Aims:</strong> In this sense, our goal is to understand how feature dependent variables affect the comprehensibility of configurable system source code. We conducted two complementary empirical studies. In Study 1, we evaluate if the comprehensibility of configurable system source code varies according to the number of dependent variables. Testing this hypothesis is important so that we can recommend practitioners and researchers the extent to which writing #ifdef code with dependencies is harmful. In study 2, we carried out an experiment in which developers analyzed programs with different degrees of variability. Our results show that the degree of variability did not affect the comprehensibility of programs with feature dependent variables. <strong>Method:</strong> We executed a controlled experiment with 12 participants who analyzed programs trying to specify their output. We quantified comprehensibility using metrics based on time and attempts to answer tasks correctly, participants’ visual effort, and participants' heart rate. <strong>Results:</strong> Our results indicate that the higher the number of dependent variables the more difficult it was to understand programs with feature dependency. <strong>Conclusions:</strong> In practice, our results indicate that comprehensibility is more negatively affected in programs with higher number of dependent variables and when these variables are defined at a point far from the points where they are used.</p>
H2020 ENODISE: VKI Experimental dataset of configuration C for numerical optimization
<p>The database includes acoustic and load measurements performed in the ALCOVES anechoic facility of the von Karman Institute on co-rotating coaxial propellers. This configuration corresponds to Config. C of the ENODISE project. This database has been used for numerical optimization. </p>
H2020 ENODISE: GPUP Configuration A Numerical Databases with Mitigation
<p>This dataset contains the numerical prediction for A2 configuration as defined in the H2020 ENODISE project (<a href="https://www.vki.ac.be/index.php/about-enodise">https://www.vki.ac.be/index.php/about-enodise</a>)</p> <p>The dataset contains numerical simulation results for Band-Limited Overall Sound Pressure Level (BL-OASPL) for a rotor operating at inflow velocities of 15 m/s, 27 m/s, 45 m/s, 60 m/s, and 75 m/s with the rotation rate of 6500 RPM. Three setups are investigated with the rotor located at 1000mm, 800mm, and 480mm. The BL OASPL is obtained at 90-degree observer angle in an overhead array. These simulations are based on the experimental setup by the University of Bristol on the investigation of turbulence-ingestion-rotor noise. </p>
H2020 ENODISE: GPUP Configuration B Numerical Databases with Mitigation
<p>This dataset contains the numerical prediction for A2 configuration as defined in the H2020 ENODISE project (<a href="https://www.vki.ac.be/index.php/about-enodise">https://www.vki.ac.be/index.php/about-enodise</a>)</p> <p>The dataset corresponds to the Band-Limited Overall Sound Pressure Level (BL OASPL) measurements obtained for Configuration B, focusing on the acoustic performance of propellers under different configurations. Two main setups were tested:</p> <ol> <li><strong>Propeller without Serrations</strong>: This configuration represents the baseline case where the propeller operates without any modifications to its trailing edge.</li> <li><strong>Propeller with Serrations</strong>: This configuration represents the case where the propeller operates with serrations at the trailing edge of the propeller.</li> </ol> <h1><strong>Setup </strong></h1> <ol> <li> <p><strong>Rotors</strong>: The setup involves three rotors:</p> <ul> <li><strong>Rotor_C (Central Rotor)</strong></li> <li><strong>Rotor_L (Left Rotor)</strong></li> <li><strong>Rotor_R (Right Rotor)</strong></li> </ul> <p>The Left and Right Rotors (Rotor_L and Rotor_R) are fixed at a position of <strong>x = -0.22m</strong>.</p> </li> <li> <p><strong>Axial Locations and Phase Angles</strong>: The central rotor (Rotor_C) was moved in the axial direction, and three distinct setups were investigated:</p> <ul> <li><strong>Baseline Case (Δx = 0Db)</strong>: Rotor_C located at <strong>x = -0.22m</strong>.</li> <li><strong>Forward Case (Δx = -0.2Db)</strong>: Rotor_C moved forward to <strong>x = -0.26m</strong>.</li> <li><strong>Backward Case (Δx = +0.2Db)</strong>: Rotor_C moved backward to <strong>x = -0.18m</strong>.</li> </ul> <p>For each axial location, four phase angles were tested: <strong>0°, 45°, 90°, 135°</strong>.</p> </li> </ol> <h1>Dataset :</h1> <ol> <li> <p><strong>Total Simulations</strong>:</p> <ul> <li>Each propeller configuration (serrated and non-serrated) was tested under the three axial locations and four phase angles, resulting in a total of <strong>12 simulations</strong> for each setup.</li> <li>This results in <strong>24 simulations</strong> (12 simulations with serrations + 12 simulations without serrations) across all configurations.</li> </ul> </li> <li> <p><strong>Measured Parameters</strong>:</p> <ul> <li><strong>Area-averaged Bandlimited Prms</strong>: The overall sound pressure level averaged over the area, given in both linear scale and converted to decibels (dB).</li> <li><strong>Maximum Bandlimited Prms</strong>: The maximum sound pressure level observed within the band, also provided in both linear scale and dB.</li> </ul> </li> <li><strong>Script</strong> <ul> <li>Python script is provided which converts original dataset to log scale </li> </ul> </li> </ol>
APECOSM configuration files used in the Earth's Future "Past and Future of Marine Ecosystems" special issue
<p>This dataset contains the configuration files to run the <em>piControl-spinup</em> and <em>piControl</em> experiment in the ToE paper.</p> <p>In the <em>piControl</em> experiment, light is provided by the <em>rsdo </em>variable, which is is converted into PAR by using a constant conversion factor (0.43). However, this variable is not available for the <em>piControl-spinup</em> experiment, in which PAR has been reconstructed from chlorophyll and solar radiation using the <a href="https://github.com/apecosm/par-calculation" target="_blank" rel="noopener">par-calculation</a> tool (version <code>58ab94c</code>)</p> <p>All the other simulations use the same parameters as in the <em>piControl</em> , except for the forcing and restart paths.</p> <p>The APECOSM version used is <code>c0a910b8</code>.</p> <p> </p>
Displacement time series from Foamquake and Gelquake in single- and double asperity configurations: Supplementary material to "Scaled seismotectonic models of megathrust seismic cycles through the lens of dynamical system theory"
<p><span>This dataset includes displacement data from 4 experiments performed with Foamquake and Gelquake (Mastella et al. 2022, Corbi et al., 2013), two scaled seismotectonic models reproducing the megathrust seismic cycle running at the Laboratory of Experimental Tectonics LET (Univ. Roma Tre). These models enable the generation of hundreds of quasi-periodic cycles of stress accumulation and sudden release through the spontaneous nucleation of frictional instabilities within one or many analog seismic asperities. Models are monitored by the means of a high-resolution top-view monitoring camera acquiring images at 7.5 and 50 frames per second for Gelquake and Foamquake, respectively. This dataset has been created with particle image velocimetry (PIV, using MatPIV (Sveen 2004)) through the cross-correlation between consecutive images. The PIV provides us with velocity field time series. These are integrated to obtain displacement time series. From the whole model surface, in each experiment we selected data from a cross-section striking parallel to the trench and located at the downdip center of the asperities. Cross sections are discretized in 28 and 29 target points in Gelquake and Foamquake, respectively. </span></p> <p><span>Displacement time series have been normalized to zero mean and unit variance to ensure the same level of magnitude for comparison between different experiments. Linear and second order polynomial trends have been removed to make the stick-slip confined in a given range and avoid non-stationary behavior. Time series data are not passed through filters (e.g., smoothing or moving average).</span></p> <p><span>Filename informs about the nature of the analog upper plate (i.e., foam and gel) and geometrical configuration of asperities (i.e., mono and twin). Together with individual files for each experiment, this dataset includes a Matlab script (i.e., all_timeseries.m) that allows visualization of displacement time series from individual target points. </span></p> <p><span>This dataset is supplementary to the paper in SEISMICA "Scaled seismotectonic models of megathrust seismic cycles through the lens of dynamical system theory” by Corbi et al. (2024), where detailed descriptions of models and experimental results can be found.</span></p>
H2020 ENODISE: DLR Configuration B, Analytical
<p>A varitiation of phase shift and tip gap between adjacent propellers of configuration B1 has been carried out and acoustically investigated. For further description please read <em>D5-7_B1.pdf.</em></p>
Current and Voltage for a Series-Parallel Configurations of Piezoelectric Transducers Dataset
<p>The piezoelectric elements used are arranged in two test configurations for the experiments: a series electrical connection of two units and a parallel electrical connection of two units, while remaining mechanically isolated. It is important to emphasize that although the elements are electrically connected, they are not mechanically coupled. Data collection focuses on two input variables—oscillation frequency and load resistance—with the output being the voltage across the piezoelectric elements and the current through the load. The experiments involve frequency sweeps from 0 to 200 Hz in 1 Hz increments and load resistance sweeps, fixed at 5 k<span><span>Ω</span></span> and ranging from 10 k<span><span>Ω</span></span> to 300 k<span><span>Ω</span></span>.</p> <div> <div> <div> <div> <p><span>The currents and voltages obtained from the measurement of the piezoelectric elements are included, as well as the frequency and resistance values. Finally, a test.m file is included in which the data from one of the sets can be viewed.</span></p> </div> </div> </div> </div>
Production of Marine Shrimp Integrated with Tilapia at High Densities and in a Biofloc System: Choosing the Best Spatial Configuration
<p>Dataset with experimental results.</p>
The configurations, inputs and outputs of the EFDC model for all simulated episodes
<p>TAIHU EFDC.zip includes two file folders named 2015 and 2018. The 2015 file folder is the configurations, inputs and outputs of the EFDC model for the numerical experiment named EFDC of 2015. The 2018 file folder is the configurations, inputs and outputs of the EFDC model for the numerical experiment named EFDC of 2018.</p>
restart (/ pickup) for MITgcm configuration hs94.cs-32x32x5
<p>Pickup was generated by running the verification experiment forward for 43200 time steps.</p> <p>This can be used to restart the model from a typical solution (rather than starting from rest).</p> <p>Files included : </p> <p>- STDOUT.0000<br> - pickup.0000043200.data<br> - pickup.0000043200.meta</p> <p> </p>
Molecular models of the FtsQ-FtsL-FtsB-FtsW-FtsI complex (FtsQLBWI) in mono- and diprotomeric configurations
<p>The data consists of five Protein Data Bank (PDB) structure files of the complex formed by FtsQ, FtsL, FtsB, FtsW, and FtsI of the divisome of Escherichia coli (FtsQLBWI). The five PDB files consist of an original AlphaFold2 model, partially validated through mutagenesis in vivo, and a series of derivatives remodeled seeking insight into the potential structural transitions that lead to activation of the FtsWI complex, which produced peptidoglycan during cell division. In the original model (file <strong>FtsQLBWI_protomer_original.pdb</strong>), FtsLB serves as a support for FtsI, placing its periplasmic domain in an extended and possibly active conformation. We remodeled the periplasmic domain of FtsI to assess it the model is compatible with a compact and possibly inactive conformation (file <strong>FtsQLBWI_protomer_compact.pdb</strong>). Additionally, the complex was remodeled to assume an Fts[QLBWI]<sub>2</sub> diprotomeric configuration, using FtsLB as a central hub (file <strong>FtsQLBWI_diprotomer_clashing.pdb</strong>). This was performed by applying the C2 symmetry operation (180° rotation) to the Fts[QLBWI]<sub>1</sub> complex that reconstructs the Fts[LB]<sub>2</sub> complex in the Y-model configuration from the Fts[LB]<sub>1</sub> AlphaFold2 prediction. In this model, a severe steric overlap occurs between FtsQ and FtsI, which occupy the same region of space adjacent to FtsLB. To address whether this clash could be solved by providing flexibility to a hinge in the CCD region of FtsLB, we used a procedure, based on docking of FtsQ with HADDOCK followed by loop reconstruction with Rosetta (file <strong>FtsQLBWI_diprotomer_extended.pdb</strong>). Finally, we reconfigured the initial diprotomeric model in a compact state (file <strong>FtsQLBWI_diprotomer_compact.pdb</strong>).</p>
Malwa survey : GIS data Badoh-Pathari, part 4, site configurations
<p>Malwa survey : GIS data Badoh-Pathari, part 4, site configurations (2008)</p>
Fracture propagation captured by high-speed camera 2: Video (configuration 4)
<p>The video presents the target plate captured by high-speed camera 2 during testing, and shows the damage for configuration 4. A line can be observed between the first and the third impact and a lighter one between the second and third impact. A deeper analysis of the three enlarged holes highlights the location of crack tips and the crack between the first and the third hole. The line between impact 1 and 3 corresponds, to a full crack formation on the plate. On the contrary, there is only an initiation of crack formation between impacts 2 and 3.</p>
Penetration and perforation process of 12.7mm FSP on plate captured by high-speed camera 2: Video (Test 2 of configuration 2).
<p>The penetration and the perforation process of configuration 2 is recorded using HSC 2. It is shown that at the moment of impact, the FSP causes a localized bulge at the rear side of the plate. A localized shearing of material, induced by the FSP front surface, is created in the contact zone. Immediately after, the FSP penetrates and a circular plug is punched through the plate, leaving a clean cut hole. Subsequently, the punched plug can be seen attached to the front surface of the projectile. After that, the punched plug is separated from the FSP.</p>
"Pitch-angle of FSP before and after ballistic impact on plate captured by high-speed camera 1: Video (configuration 2)".
<p>The figure reveals that the pitch-angle of a 12.7mm FSP both before and after the ballistic impact on an Aluminum plate is low.</p>
Alb500_configuration_files
<p>Configuration files for running the Alb500 simulation with CROCO ocean model.</p>
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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.