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1,007 results for “Smoothing”
Data files for the tabulated MESA equation of state in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<div> <div> <div> <p>** These tables are automatically downloaded from this repository when running phantom **<br><br>This tabulated equation of state in PHANTOM is adapted from the logPgas − Temperature equation of state tables provided with the open source package Modules for Experiments in Stellar Astrophysics MESA (Paxton et al. 2011). Details of the data, originally compiled from blends of equations of state from Saumon, Chabrier, & van Horn (1995) (SCVH), Timmes & Swesty (2000), Rogers & Nayfonov (2002, also the 2005 update), Potekhin & Chabrier (2010) and for an ideal gas, are outlined by Paxton et al. (2011).</p> <p>Code to read these tables is available as part of phantom (<a href="https://github.com/danieljprice/phantom/blob/master/src/main/eos_mesa_microphysics.f90">src/main/eos_mesa.f90</a>). The original version of these tables and the module to read them was contributed by Tom Constantino from the MUSIC code (<a href="https://ui.adsabs.harvard.edu/abs/2017A&A...600A...7Ga">Goffrey et al. 2017</a>), and the phantom implementation described in <a href="http://adsabs.harvard.edu/abs/2018PASA...35...31P">Price et al. (2018)</a>.The current tables were created by Tom Reichardt for the paper Reichardt et al. (2020):<br><br><a href="https://ui.adsabs.harvard.edu/abs/2020MNRAS.494.5333R/abstract">https://ui.adsabs.harvard.edu/abs/2020MNRAS.494.5333R/abstract</a></p> </div> </div> </div> <p>Figure 1 in Reichardt et al. (2020) shows the pressure, temperature, Gamma and P/Pideal shown as a function of internal energy and density from these tables</p>
Turbulence statistics in smooth wall oscillatory boundary layer flow
<p>Experimental and numerical datasets belonging to Van der A, D.A., Scandura, P., O’Donoghue, T. (2018). Turbulence statistics in smooth wall oscillatory boundary layer flow, Journal of Fluid Mechanics, 849, 192-230. </p> <p> </p>
Data from Churan et al. 2018 Comparison of the precision of smooth pursuit in humans and head unrestrained monkeys
<p>Experiments were performed in two rhesus monkeys, B and E. Each monkey made a combination of slow and fast eye-movements following a visual target. The target was stationary at first and then either abruptly started moving (at a speed of 10°/s) in a certain direction (Ramp paradigm) or made a Step before starting the motion (Step-Ramp paradigm). By using a specific Step size and Step direction the initial saccade was eliminated in the Step-Ramp paradigm. The direction of the stimulus motion was predominantly horizontal with a smaller vertical component that was systematically varied between 0° and +-20°. We investigated how precisely the monkeys can follow this vertical component of the stimulus motion.</p> <p><strong>The files:</strong></p> <p>There are separate files for each monkey (B and E) and paradigm (Ramp and Step_Ramp). The files are MATLAB data files.</p> <p>Ramp:</p> <p>Each file consists of three variables – ‘alldatx’, ‘alldaty’, and ‘init’.</p> <p>‘alldatx’ and ‘alldaty’ are cell arrays in which each cell represents one vertical component of the stimulus: 1=20° up, 2=10° up, 3=5° up, 4=2° up, 5=0° , 6=2° down, 7=5° down, 8=10° down, 9=20° down. Each cell contains a matrix of n x 2001 elements. Each row represents the eye velocities during one individual trial between 1000 ms before and 1000 ms after the start of stimulus motion with a sampling rate of 1000 Hz.</p> <p>‘init’ is a cell array in which each cell represents one vertical component of the stimulus (s. above). Each cell contains a structure array which shows the approximate properties of the initial saccade in each trial:</p> <p>‘init.t’: Start end end time of the saccade (in ms) after the start of stimulus motion.</p> <p>‘init.amp’: Amplitude of the initial saccade in deg</p> <p>‘init.startpos’, ‘init.endpos’: start- and end-position (x, y) of the saccade</p> <p>Step_Ramp:</p> <p>Each file consists of two variables – ‘alldatx’, ‘alldaty’. Description is the same as for Ramp.</p>
Figures 1-6 in Gonadal development and fecundity of the smooth weakfish Cynoscion leiarchus (Teleostei: Perciformes: Sciaenidae) in a tropical Brazilian bay
Figures 1-6. Photomicrographs of ovarian (1-4) and testicular (5-6) histology illustrating oocytes and spermatocytes at different development stages of C. leiarchus: (1-2) regenerating ovarian phase; (3) spawning capable ovarian phase; (4) actively spawning subphase; (5- 6) spawning capable testis phase. (PG) Primary growth, (MB) muscle bundle, (CA) cortical alveolar, (OW) ovarian wall, (Vtg1) primary vitellogenic, (Vtg2) secondary vitellogenic, (Vtg3) tertiary vitellogenic, (A) atresia POF: postovulatory follicle complex, (GVM) germinal vesicula migration, (GVBD) germinal vesicular breackdown, (Sg1) primary spermatogonia, (Sz) spermatozoa, (Cy) spermatocyst.
8 9 10 11 Figures 8-11 in Gonadal development and fecundity of the smooth weakfish Cynoscion leiarchus (Teleostei: Perciformes: Sciaenidae) in a tropical Brazilian bay
8 9 10 11 Figures 8-11. Relationship between batch fecundity and gonad weight (8), total weight (9), total length (10), and age (11) of Cynoscion leiarchus in Sepetiba Bay.
Figure 1 in Taxonomic status of a newly described island population of the smooth newt Lissotriton vulgaris (Linnaeus, 1758) from Bozcaada (Çanakkale, Turkey)
Figure 1. Geographic positions of the smooth newt populations used. Locality information is given in Table 1. Colors correspond to the various major clades (named after Babik et al., 2005; Pabijan et al., 2015). The three studied populations are given with a different symbol (star).
Figure 2 in Taxonomic status of a newly described island population of the smooth newt Lissotriton vulgaris (Linnaeus, 1758) from Bozcaada (Çanakkale, Turkey)
Figure 2. Phylogenetic relationships among studied smooth newt populations based on Bayesian Inference of mtDNA sequences (16S rRNA and ND4). Node posterior probabilities> 0.90 are given with asterisks. Population numbers correspond to Figure 1 and Table 1. The studied populations are given by their full names.
Fig. 11 in Description of head scalation variation, hemipenis, reproduction, and behavior of the Indian Smooth Snake, Coronella brachyura (Günther 1866)
Fig. 11. Wallaceophis gujaratensis with two distinct lateral stripes, from Saldi village, Amerli district, Gujarat. Photo credit Bhavesh Trivedi.
Fig. 5. Individual B in Description of head scalation variation, hemipenis, reproduction, and behavior of the Indian Smooth Snake, Coronella brachyura (Günther 1866)
Fig. 5. Individual B, both sides eight supralabials, fourth and fifth in contact with eye, and second and third supralabials in contact with loreal scale. (A) Left side. (B) Right side. (C) Live individual with same scalation. Photo credit Dikansh S. Parmar.
Fig. 4. Individual C in Description of head scalation variation, hemipenis, reproduction, and behavior of the Indian Smooth Snake, Coronella brachyura (Günther 1866)
Fig. 4. Individual C, both sides nine supralabials, fifth and sixth supralabials in contact with eye, and second, third, and fourth supralabials in contact with loreal scale. (A) Left side. (B) Right side. Photo credit Dikansh S. Parmar.
Fig. 3. Individual A in Description of head scalation variation, hemipenis, reproduction, and behavior of the Indian Smooth Snake, Coronella brachyura (Günther 1866)
Fig. 3. Individual A, both sides nine supralabials, fifth and sixth supralabials in contact with eye, and second, third, and fourth supralabials in contact with loreal scale. (A) Left side. (B) Right side. Photo credit Dikansh S. Parmar.
Fig. 1 in Description of head scalation variation, hemipenis, reproduction, and behavior of the Indian Smooth Snake, Coronella brachyura (Günther 1866)
Fig. 1. Two colors of Coronella brachyura. (A) Black color. (B) Brown color. Photo credit Dikansh S. Parmar.
Fig. 2 in Description of head scalation variation, hemipenis, reproduction, and behavior of the Indian Smooth Snake, Coronella brachyura (Günther 1866)
Fig. 2. (A) Male individual found in road kill. (B) Close up of its hemipenis. Photo credit Dikansh S. Parmar.
Fig. 9 in Description of head scalation variation, hemipenis, reproduction, and behavior of the Indian Smooth Snake, Coronella brachyura (Günther 1866)
Fig. 9. Distribution shown in map in all four states of India along with Tropic of Cancer, Narmada and Tapi rivers. Distribution and localities shown separately in Gujarat state, Surat and Tapi districts. Map prepared by Nitin Patel and Smita Ramkumar.
Fig. 4 in Short Communication On the distribution, taxonomy, and natural history of the Indian Smooth Snake, Coronella brachyura (Günther, 1866)
Fig. 4. Map showing distribution range of Coronella brachyura (For all the localities: 1–13, reference Table 2).
Fig. 2 in Short Communication On the distribution, taxonomy, and natural history of the Indian Smooth Snake, Coronella brachyura (Günther, 1866)
Fig. 2. Lateral aspect of Coronella brachyura (NCS 2); a, left side showing 8 supralabials and 5th supralabial partly divided; b, right side showing 9 supralabials, 4–6th touching eye.
Fig. 6 in Flexibility is everything: prey capture throughout the seasonal habitat switches in the smooth newt Lissotriton vulgaris
Fig. 6 First (a) and second (b) phase of the tongue prehension mode shown in Fig. 4a. The time axes are normalized to percentages of corresponding phase duration. Both phases can, therefore, be directly compared to the kinematic profiles shown in Fig. 4. Note the striking similarities of movement patterns of the second phase (b) and the aquatic feeding patterns shown in Fig. 4a, b, c
Fig. 5 in Flexibility is everything: prey capture throughout the seasonal habitat switches in the smooth newt Lissotriton vulgaris
Fig. 5 Significant correlation plots of kinematic variables. The feeding modes are color*coded: blue (a, b) suction feeding in the aquatic stage, liVWt brown (c, d), jaw prehension in the aquatic stage, and Vreen (e–l)
The Meadow Viper's perspective on the diet and predator-prey interactions of the reptile specialist Smooth Snake
<p>Despite its wide distribution, ecological data on the Smooth Snake (Coronella austriaca) remains limited. Previous dietary analyses report that it mainly consumes lizards, but it also eats mammals and snakes. Little information is available on the habitat choice of the species, but vegetation structure and microtopography are considered the main factors determining occupancy of these snakes. As there is limited data on the diet of this species from Central Europe and it was considered a potential predator of the endangered Vipera ursinii rakosiensis (Hungarian Meadow Viper), we conducted a study concerning the diet of C. austriaca in one of the largest habitats of V. ursinii in Hungary. As there is no data on the occupancy of C. austriaca, we tested if the availability of certain prey species affects its occupancy C. austriaca individuals were captured to collect faecal samples, in which the remains were identified. In the obtained samples (n=53) we found remains of lizards (65%), mammals (20%), insects (12.5%) and Smooth Snake (2.5%). The consumed lizard species were Lacerta viridis, Podarcis tauricus and Lacerta agilis. We found no remains of V. ursinii in the faecal samples. We used dynamic two-species occupancy modeling to test if the occupancy of C. austriaca is linked to the presence of its prey species in the area. We found an interaction between C. austriaca and its lizard prey, as occupancy of C. austriaca had a higher probability when these species were present. We found no interaction between C. austriaca and V. ursinii. Our results support that C. austriaca mainly preys on lizards and its site occupancy depends on prey availability. Importantly, we found no evidence that C. austriaca consumes V. ursinii, which is further supported by the lack of interaction between the occupancy of C. austriaca and that of V. ursinii.</p>
Accompanying dataset for the paper "An explicit dynamics framework suited to highly non-smooth interface behaviors"
<h2>Contributions</h2> <ul> <li>Author #1 carried out most of the study, performed numerical simulations, and drafted the manuscript</li> <li>Author #2 helped with implementation and numerical issues</li> <li>All authors developed the methodology, conceived the study, and participated in its design, coordination, and critical review of the manuscript. All authors read and approved the final manuscript.</li> </ul> <h2>Funding sources</h2> <ul> <li>We gratefully acknowledge the French National Association for Research and Technology (ANRT, CIFRE grant number 2021/0957).</li> <li>This work was supported by the "Manufacture Française de Pneumatiques Michelin"</li> </ul> <h2>Data structure and information</h2> <ul> <li><code>data</code> -- folder for raw data<ul> <li><code>Peeling3Dv7.dgibi</code> -- <a href="https://www-cast3m.cea.fr">CAST3M</a> input file to produce the mesh (Gibiane language)</li> <li><code>Peeling3Dv7.inp</code> -- input FE data file (ASCII AVS UCD format)</li> <li><code>Peeling3Dv7.m</code> -- main matlab/Octave source file uses the open-source library matlabEF for reading input data and producing the FE required operators, which is available at <a href="https://github.com/dureisse/matlabEF.git">https://github.com/dureisse/matlabEF.git</a> and <a href="https://hal.science/hal-04647638">https://hal.science/hal-04647638</a>.</li> </ul> </li> <li><code>workflows</code><ul> <li><code>install.sh</code> -- script to reinstall the dependencies</li> <li><code>reproduce.sh</code> -- script for re-running the study</li> </ul> </li> </ul> <h2>Paper Description</h2> <p>Dynamic systems, and in particular mechanical structures, may be subjected to non-smooth loadings such as impacts or shocks. Moreover, their behavior itself may exhibit more or less non-smooth evolutions, as when fracture occurs. Therefore, robust simulation models are of interest to capture such behaviors. A particular focus is made herein on time-stepping explicit dynamics schemes to allow efficient simulations, and non-smoothness is embedded within the discrete resolution model, so that robust simulations can be obtained, with a minimum number of numerical parameters. The original contributions of this article lie in the way the non-smooth behavior is formulated to be embedded in an explicit dynamics framework. This study focuses on the solver for dynamics with non-smooth interface behavior, rather than on the behavior models themselves. The applications concern non-smooth interface behaviors at macroscopic scale, between displacement jump on the 2D interface surface with no thickness, and interfacial force distributions acting on the bodies apart the interface. The proposed test cases which can serve as benchmarks for simulation codes, concern in a first step contact and perfectly plastic interface behavior (for illustrative purpose, on a 0D example). The last numerical test deals with contact, friction, fracture and adhesion for an extrinsic perfectly brittle interface behavior, to exemplify the feasibility on a full 3D finite element model.</p>
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OpenNeuro
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