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202 results for “rigidity”
Rigid and hinged very large floating structure (VLFS) dataset - Kelvin Hydrodynamics Laboratory
<p>This dataset corresponds to the measurements performed at the Kelvin Hydrodynamics Laboratory at the University of Strathclyde, in August 2022, to assess the motion performance and internal loading of a rigid and hinged very large floating structure (VLFS) under regular waves. The VLFS was constructed with three pontoons and two hinges. The hinges were replaced with aluminium steel bars to built the rigid VLFS. The dimensions of each pontoon of the VLFS were 580 mm x 580 mm x 52 mm. Each pontoon was built with 2 mm layer of carbon fibre and a 50 mm layer of PVC foam.</p><p>The VLFS was tested in regular waves at two incidences: 0 degrees and 30 degrees. For 0 degree incidence, the wave frequencies tested ranged from 0.4 to1.6 Hz in intervals of 0.1 Hz. Four wave heights were tested, h=5, 10, 20 and 40 mm. For 30 degree incidence, the same range of frequencies were tested, but only one wave height, h=5 mm. Preliminary results for some of the data at 0 degrees incidence can be found in the conference paper: https://doi.org/10.36688/ewtec-2023-389. Further analysis of this dataset and additional results are in preparation for a journal manuscript.</p><p>The following files are included as part of the dataset:</p><ol><li>Motion files (Matlab files).</li><li>Strain gauge and wave height files (Matlab files).</li><li>Data description file - Description of files.</li><li>Test matrix - Test cases summarised with nomenclature used in files.</li><li>Matlab script to sort out position of motion spheres as depicted in Figure 1.</li><li>Video of the hinged VLFS subject to a train of regular waves at f=0.8 Hz, i.e. when the wavelength is of similar length to the length of the platform, i.e. f=0.8 Hz.</li></ol><ul><li>The motion files contain the time series information recorded for each of the motion detection spheres. Because the motion raw data is not labelled sequentially, it is necessary to run the Matlab file included in the data repository to sort out the information of the spheres.</li><li>The strain gauge files contain the raw strain gauge data (8 channels) and the wave gauge data with the file number describing the corresponding test in the test matrix.</li></ul><p>The VLFS was equipped with 36 motion detection spheres and 8 strain gauges. The diagram and notation of each sphere is depicted in Figure 1. Figure 1 is available in the Data description document.</p><p> </p>
Certain rigid maximally mutable Laurent polynomials in three variables
<p>This dataset contains certain rigid maximally mutable Laurent polynomials (rigid MMLPs) in three variables. Rigid MMLPs are defined in reference [1].</p> <p>The Newton polytopes of these Laurent polynomials are three-dimensional canonical Fano polytopes. That is, they are three-dimensional convex polytopes with vertices that are primitive integer vectors and that contain exactly one lattice point, the origin, in their strict interior. See references [2] and [3].</p> <p>Although the rigid MMLPs specified in this dataset have 3-dimensional canonical Fano Newton polytope, this is by no means an exhaustive list of such Laurent polynomials. The dataset contains examples of rigid MMLPs that correspond under mirror symmetry to three-dimensional Q-Fano varieties of particulaly high estimated codimension: see reference [4].</p> <p>The file "rigid_MMLPs.txt" contains key:value records with keys and values as described below, separated by blank lines. Each key:value record determines a rigid MMLP, and there are 130 records in the file. An example record is:</p> <p>canonical3_id: 231730<br> coefficients: [1,1,1,1,1,1,1,1,1,1]<br> exponents: [[-1,-1,-1],[0,1,0],[0,1,1],[1,0,0],[1,0,1],[1,2,2],[2,1,2],[2,1,3],[3,3,5],[4,2,5]]<br> period: [1,0,0,12,24,0,540,2940,2520,33600,327600,693000,2795100,35315280,129909780,354666312,3816572760,20559258720,59957561664,435508321248,2969362219824]<br> ulid: 01G5CBH3F86NRYF0TJ8MYWM41H</p> <p>The keys and values are as follows, where f denotes the Laurent polynomial defined by the key:value record.</p> <p>canonical3_id: an integer, the ID of the Newton polytope of f in reference [3]<br> coefficients: a string of the form "[c1,c2,...,cN]" where c1, c2, ... are integers. These are the coefficients of f.<br> exponents: a string of the form "[[x1,y1,z1],[x2,y2,z2],...,[xN,yN,zN]]" where x1, y1, z1, ..., xN, yN, zN are integers. These are the exponents of f.<br> period: a string of the form "[d0,d1,...,d20]" where d0, d1, ..., d20 are non-negative integers that give the first 21 terms of the period sequence for f.<br> ulid: a string that uniquely identified this entry in the dataset</p> <p>The sequences defined by the keys "coefficients" and "exponents" are parallel to each other. The period sequence for f is defined, for example, in equations 1.2 and 1.3 of reference [1].</p> <p>References</p> <p>[1] Tom Coates, Alexander M. Kasprzyk, Giuseppe Pitton, and Ketil Tveiten. Maximally mutable Laurent polynomials. Proceedings of the Royal Society A 477, no. 2254:20210584, 2021.</p> <p>[2] Alexander M. Kasprzyk. Canonical toric Fano threefolds. Canadian Journal of Mathematics, 62(6):1293–1309, 2010.</p> <p>[3] Alexander M. Kasprzyk. The classification of toric canonical Fano 3-folds. Zenodo, https://doi.org/10.5281/zenodo.5866330, 2010.</p> <p>[4] Liana Heuberger. Q-Fano threefolds and Laurent inversion. Preprint, arXiv:2202.04184, 2022.</p>
Supporting Information for "An empirical modification of the force field approach to describe the modulation of galactic cosmic rays close to Earth in a broad range of rigidities"
<p>This supporting information provides the Data Set S1 used to produce Fig. 6 in <strong>"An empirical modification of the force field approach to describe the modulation of galactic cosmic rays close to Earth in a broad range of rigidities"</strong> (Gieseler et al., 2017). It can be used to calculate the rigidity-dependent solar modulation potential <span class="math-tex">\(\phi(P)\)</span> for monthly intervals from 1973-2017 following Eq. 10 in Gieseler et al. (2017).</p> <p>If you use this data, please refer to and cite <strong>BOTH</strong> following publications:</p> <ul> <li>Gieseler, J., B. Heber, and K. Herbst, <em>An empirical modification of the force field approach to describe the modulation of galactic cosmic rays close to Earth in a broad range of rigidities</em>, J. Geophys. Res., 2017 (doi:10.1002/2017JA024763).</li> <li>Usoskin, I. G., G. A. Bazilevskaya, and G. A. Kovaltsov, <em>Solar modulation parameter for cosmic rays since 1936 reconstructed from ground-based neutron monitors and ionization chambers</em>, J. Geophys. Res., 2011 (doi:10.1029/2010JA016105).</li> </ul> <p>This data set contains the solar modulation potential values in MV for monthly intervals from 1973-2017 derived from the proton proxies IMP-8 He and ACE/CRIS C (Phi_pp), and from Usoskin et al. (2011) as provided by http://cosmicrays.oulu.fi/phi/phi.html (Phi_Uso11). The uncertainties of Phi_pp are given in column 4, those of Phi_Uso11 are 26 MV for the observed period. The LIS used to calculate the modulation potentials is that from Burger et al. (2000) as given by Usoskin et al. (2005).</p> <p>Column 1: Fractional year (start of interval)<br> Column 2: Month<br> Column 3: Phi_pp /MV<br> Column 4: Uncertainty of Phi_pp /MV<br> Column 5: Phi_Uso11 /MV</p> <p>Data also available at http://www.ieap.uni-kiel.de/et/ag-heber/cosmicrays</p>
Data files for the manuscript "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes"
<p>This depository contains the data of all DEM simulations used in the manuscript titled "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes" submitted to Soft Matter in July 2024.</p> <p>The data in the excel file are the measurements obtained after the coarse graining procedure.</p>
Data for "Detachment of a rigid flat punch from a viscoelastic material"
<p>This dataset contains all the data generated for the publication</p> <p>[1] Papangelo, A., & Ciavarella, M. (2023). Detachment of a rigid flat punch from a viscoelastic material, Tribology Letters, DOI: 10.1007/s11249-023-01720-9<br> </p> <p>The provided data are those which appear in the figures of Ref. [1]. Data are stored using informative named structures in a ".mat" file. The data are easily accessible through the Commercial Software MATLAB (© 1994-2023 The MathWorks, Inc.) or by using the free software GNU Octave. An exemplary code for loading and plotting the data contained in "dataFlatPunch.mat" is the following:</p> <p>%%%%%%%%%%%%%</p> <p>load('dataFlatPunch.mat') % load workspace containing data</p> <p>figure, hold on % open a new figure</p> <p>curve_number = 1; % select the curve to plot</p> <p>plot(Fig1.x{curve_number},Fig1.y{curve_number}) % Plot the curve number "curve_number" of figure "Fig1"</p> <p>%%%%%%%%%%%%%</p> <p>The code can be easily adapted for plotting the curves of all the figures contained in Ref. [1]. </p>
Perception of shape and space across rigid transformations
<p>Dataset relative to the following publication:</p> <p>Schmidt, F., Spröte, P., & Fleming, R. W. (2016). Perception of shape and space across rigid transformations. <em>Vision Research, 126</em>, 318-329. <a href="http://dx.doi.org/10.1016/j.visres.2015.04.011"> http://dx.doi.org/10.1016/j.visres.2015.04.011 </a></p> <p>Each folder contains the data relative to one experiment and a text file with comments.</p>
Bio-inspired apparatus to produce luminescent cavitation in a rigid walled chamber
<p>A mechanical device inspired by the sudden rotational motion of the pistol shrimp claw was developed. The apparatus consists of a limb with a V-shaped end, which fits into a socket forming a cylindrical compression chamber. Air bubbles of different sizes and in different positions inside the chamber were seeded to study their shape evolution in liquids when subjected to pressure pulses induced by the limb closure. Non-spherical shape dynamics, micro jets and photon emission were observed during bubble collapse. The proposed mechanism represents a low-cost technology useful in the study of cavitation near rigid boundaries of diverse geometries.</p> <p>Experimental data on limb motion and bubble dynamics were obtained by processing videos taken with a high-speed camera. Light signals were acquired with a photomultiplier and force signals were acquired using PVDF piezoelectric sensors. </p> <p>Numerical data describing limb motion were obtained by numerically solving a torque balance model, while radial dynamics curves were obtained by solving the Rayleigh-Plesset equation.</p> <p>Data files are presented in two types of extension .opj (and .opju) that can be opened and analyzed in OriginPro software and also .xlsx that can be opened and analyzed with Microsoft Excel. The name of each file corresponds to the Figure number used in the article. <br> <br> Two notebooks created in Mathematica are made available. One of them was used to simulate the dynamics of clamp closure and the other to estimate the pressure pulse generated during limb closure. The versions of these files are not the most up-to-date, <br> but they contain all the information necessary to reproduce the results presented in the article.</p>
Experimental Data for Wave Decay by Submerged Rigid Vegetation under Orthogonal Wave-Current Conditions
<p>This dataset includes wave amplitude decay data, force prediction and measurement data (organized in spreadsheets), and phase-averaged force measurement data stored in a MATLAB <code>.mat</code> file. The accompanying paper, titled <em>"Wave Decay by Submerged Rigid Vegetation under Orthogonal Wave-Current Conditions,"</em> will be published in <em>Geophysical Research Letters.</em> A detailed description of the variables is provided at the end of each spreadsheet. The detailed measurement methods are described in the paper. The data in the <code>.mat</code> file is arranged according to the experimental case order specified in the spreadsheet named <em>"force measurement."</em></p>
Dataset: Connectivity and rigidity percolation of cytoskeletal networks.
<p>Dataset containing information for "Connectivity and rigidity percolation of cytoskeletal networks."</p> <p>File: Fig1A_MEDYAN_Unbranched_timeseries_motor_333_linker_1500_tmax_122.csv<br> Description:<br> Average MEDYAN simulations in a 1um3 box with 333 motors and 1500 linkers, no branchers.<br> Columns:<br> Last_Timestep: Last time step of the simulations<br> N_Motors: Total number of motors in the simulation<br> N_Linkers: Total number of linkers in the simulation<br> Simulation: Number of simulations<br> M_p: Number of plus ends<br> M_m: Number of minus ends<br> M_c: Number of free binding sites<br> M_M: Number of free motors<br> M_L: Number of free linkers<br> M_pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> M_cMc: Number of bound motors<br> M_cLc: Number of bound linkers<br> M_G: Number of free G-actin<br> M_b: number of free branchers</p> <p>File: Fig1A_ODE_Unbranched_timeseries_motor_333_linker_1500_tmax_10000.csv<br> Description:<br> Chemical kinetics calculations for transient concentrations of motor, linker and brancher for equivalent MEDYAN simulations of a 1um3 box with 333 motors and 1500 linkers, no branchers.<br> Columns:<br> pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> L: Number of free linkers<br> cMc: Number of bound motors<br> cLc: Number of bound linkers<br> c: Number of free binding sites<br> m: Number of minus ends<br> p: Number of plus ends<br> G: Number of free G-actin<br> M: Number of free motors</p> <p>File: Fig1A_Unbranched_MEDYAN.csv<br> Description:<br> Species concentrations in MEDYAN simulations in a 1um3 box with 333 motors and 1500 linkers, no branchers.<br> The simulations can be found in the Simulations_Unbranched folder<br> Columns:<br> Last_Timestep: Measured timestep<br> N_Motors: Total number of motors in the simulation<br> N_Linkers: Total number of linkers in the simulation<br> chem_path: Path of the simulation<br> AD: Number of unbound G-actins<br> MD: Number of unbound motors<br> LD: Number of unbound linkers<br> FA: Number of bound F-actin monomers<br> PA: Number of plus ends<br> MA: Number of minus ends<br> LA: Number of bound linkers<br> MOA: Number of bound motors<br> Simulation: Simulation ID</p> <p>File: Fig1B_Branched_MEDYAN.csv<br> Description:<br> Species concentrations in MEDYAN simulations in a 1um3 box with 333 motors and 1500 linkers, 300 branchers.<br> The simulations can be found in the Simulations_Branched folder<br> Columns:<br> Last_Timestep: Measured timestep<br> N_Motors: Number of motors<br> N_Linkers: Number of linkers<br> chem_path: Path of the simulation<br> AD: Number of unbound G-actins<br> BD: Number of unbound branchers<br> MD: Number of unbound motors<br> LD: Number of unbound linkers<br> FA: Number of bound F-actin monomers<br> PA: Number of plus ends<br> MA: Number of minus ends<br> LA: Number of bound linkers<br> MOA: Number of bound motors<br> BA: Number of bound branchers<br> Simulation: Simulation ID</p> <p>File: Fig1B_MEDYAN_Branched_timeseries_motor_333_linker_1500_tmax_122.csv<br> Description:<br> Average MEDYAN simulations in a 1um3 box with 333 motors and 1500 linkers, 300 branchers.<br> Columns:<br> Last_Timestep: Last time step of the simulations<br> N_Motors: Total number of motors in the simulation<br> N_Linkers: Total number of linkers in the simulation<br> Simulation: Number of simulations<br> M_p: Number of plus ends<br> M_m: Number of minus ends<br> M_c: Number of free binding sites<br> M_M: Number of free motors<br> M_L: Number of free linkers<br> M_pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> M_cMc: Number of bound motors<br> M_cLc: Number of bound linkers<br> M_G: Number of free G-actin<br> M_B: total number of branchers<br> M_cBm: number of bound branchers<br> M_b: number of free branchers</p> <p>File: Fig1B_ODE_Branched_timeseries_motor_333_linker_1500_tmax_10000_v2.csv<br> Description:<br> Chemical kinetics calculations for transient concentrations of motor, linker and brancher for equivalent MEDYAN simulations of a 1um3 box with 333 motors and 1500 linkers, and 300 branchers.<br> Columns:<br> pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> L: Number of free linkers<br> p: Number of plus ends<br> cMc: Number of bound motors<br> cBm: Number of bound branchers<br> cLc: Number of bound linkers<br> c: Number of free binding sites<br> m: Number of minus ends<br> M: Number of free motors<br> G: Number of free G-actin<br> B: Number of free branchers</p> <p>File: Fig1C_Ps_timeseries_unbranched.csv<br> Description:<br> Flory-Stockmayer results for unbranched chemical kinetics calculations<br> Columns:<br> pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> L: Number of free linkers<br> cMc: Number of bound motors<br> cLc: Number of bound linkers<br> c: Number of free binding sites<br> m: Number of free minus ends<br> p: Number free of plus ends<br> G: Number of free G-actin<br> M: Number of free motors<br> P0: Probability that an F-actin monomer is connected to another one on its plus end<br> P1: Probability that an F-actin monomer is connected to another one on its minus end<br> P2: Probability that an F-actin monomer is connected to another one on its binding site<br> Ps: Probability that an F-actin monomer is not connected to an infinite cluster<br> Nb: Average number of bonds per F-actin monomer<br> Nn: Mean cluster size<br> Nw: Mean weighted cluster size<br> Ratio: Nw/Nn Ratio</p> <p>File: Fig1D_Ps_timeseries_branched.csv<br> Description:<br> Flory-Stockmayer results for branched chemical kinetics calculations<br> Columns:<br> pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> L: Number of free linkers<br> cMc: Number of bound motors<br> cBm: Number of bound branchers<br> cLc: Number of bound linkers<br> c: Number of free binding sites<br> m: Number of free minus ends<br> p: Number free of plus ends<br> G: Number of free G-actin<br> M: Number of free motors<br> B: Number of free branchers<br> P0: Probability that an F-actin monomer is connected to another one on its plus end<br> P1: Probability that an F-actin monomer is connected to another one on its minus end<br> P2: Probability that an F-actin monomer is connected to another one on its binding site<br> Ps: Probability that an F-actin monomer is not connected to an infinite cluster<br> Nb: Average number of bonds per F-actin monomer<br> Nn: Mean cluster size<br> Nw: Mean weighted cluster size<br> Ratio: Nw/Nn Ratio<br> Qm: Probability that an F-actin monomer is not connected to an infinite cluster through the minus end<br> Qp: Probability that an F-actin monomer is not connected to an infinite cluster through the plus end<br> Qc: Probability that an F-actin monomer is not connected to an infinite cluster through the binding site</p> <p>File: Fig2_Two-step.csv<br> Description:<br> Representative steady state concentrations for a non-cooperative two-step model of linker binding.<br> Columns:<br> Fc: Concentration of free binding sites<br> FcL: Concentration of linkers bound to a single binding site<br> FcLFc: Concentration of linkers bound to a pair of binding sites<br> L: Concentration of unbound linkers<br> Fc0: Total concentration of binding sites<br> L0: Total concentration of linkers</p> <p>File: Fig3_two_step_heatmap.csv<br> Proportion of the concentration of crosslinks to the concentration of total binding sites as a function of the linker binding equilibrium constant<br> Description:<br> 2D matrix, where the columns indicate the linker binding constant multiplied by the total concentration of binding sites, the rows indicate the total concentration of linkers per binding site , and the value corresponds to the total number of linkers bound to two binding sites divided by the total concentration of binding sites.</p> <p>File: Fig5A_Ps_unbranched.csv<br> Description:<br> 2D matrix, where the columns indicate the proportion of motors to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model without brancher.</p> <p><br> File: Fig5B Ps_branched.csv<br> Description:<br> 2D matrix, where the columns indicate the proportion of motors to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model with brancher.<br> </p> <p>File: Fig6_Ps_Branched_var.csv<br> Description:<br> 2D matrix, where the columns indicate the proportion of branchers to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model without brancher or motors.</p> <p><br> File: Fig7B_Ps_unbranched_linkeronly.csv</p> <p>Description:<br> 2D matrix, where the columns indicate the proportion of motors to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model without brancher. The clusters are defined here as F-actin monomers connected by linkers, and without including motor connections.</p> <p>File: Fig7D_Ps_branched_linkeronly.csv</p> <p>Description:<br> 2D matrix, where the columns indicate the proportion of motors to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model with brancher. The clusters are defined here as F-actin monomers connected by linkers or branchers, and without including motor connections.</p> <p>File: Fig9_data.csv<br> Description:<br> Minimum motor concentration to reach rigidity percolation as a function of the linker concentration for systems with and without brancher, considering both linker and motor connections or just motor connections and for different values of linker rigidity. The motor and linker concentrations are measured as the proportion of linkers or motors to actin.<br> Columns:<br> L: linker concentration <br> "M (unbranched, linkers and motors, bcLc=0)"<br> "M (unbranched, linkers and motors, bcLc=1)"<br> "M (unbranched, linkers and motors, bcLc=2)"<br> "M (unbranched, linkers and motors, bcLc=3)"<br> "M (unbranched, linkers and motors, bcLc=4)"<br> "M (unbranched, linkers and motors, bcLc=5)"<br> "M (unbranched, linkers and motors, bcLc=6)"<br> "M (branched, linkers and motors, bcLc=0)"<br> "M (branched, linkers and motors, bcLc=1)"<br> "M (branched, linkers and motors, bcLc=2)"<br> "M (branched, linkers and motors, bcLc=3)"<br> "M (branched, linkers and motors, bcLc=4)"<br> "M (branched, linkers and motors, bcLc=5)"<br> "M (branched, linkers and motors, bcLc=6)"<br> "M (unbranched, linkers only, bcLc=0)"<br> "M (unbranched, linkers only, bcLc=1)"<br> "M (unbranched, linkers only, bcLc=2)"<br> "M (unbranched, linkers only, bcLc=3)"<br> "M (unbranched, linkers only, bcLc=4)"<br> "M (unbranched, linkers only, bcLc=5)"<br> "M (unbranched, linkers only, bcLc=6)"<br> "M (branched, linkers only, bcLc=0)"<br> "M (branched, linkers only, bcLc=1)"<br> "M (branched, linkers only, bcLc=2)"<br> "M (branched, linkers only, bcLc=3)"<br> "M (branched, linkers only, bcLc=4)"<br> "M (branched, linkers only, bcLc=5)"<br> "M (branched, linkers only, bcLc=6)"</p> <p>File: FigS1_data.csv<br> Description:<br> Connectivity percolation as a function of the probabilities that an F-actin monomer site is bound to another F-actin.<br> Columns:<br> ppm: probability that an F-actin monomer plus end is connected to another F-actin monomer minus end<br> pcc: probability that an F-actin monomer binding site is connected to another F-actin monomer binding site<br> Pcm: probability that an F-actin monomer binding site is connected to another F-actin monomer minus end<br> Qp: Probability that an F-actin monomer is not connected to an infinite cluster through the plus end<br> Qm: Probability that an F-actin monomer is not connected to an infinite cluster through the minus end<br> Qc: Probability that an F-actin monomer is not connected to an infinite cluster through the binding site<br> Ps: Probability that an F-actin monomer is not connected to an infinite cluster<br> Percolated: Whether the system is percolated or not.</p> <p>File: simulations.tar.gz<br> Description: Contains the MEDYAN simulations used for figure 1. Each folder contains an individual simulation, with the following files:<br> systeminput.txt: Contains the input for the system conditions and settings<br> chemistryinput.txt: Contains the input for the chemical species<br> chemistry.traj: Output trajectory containing number of species in the simulations<br> snapshot.traj: Output trajectory containing the coordinates of the species.<br> For more information please reference the MEDYAN user guide and reference:<br> K Popov, JE Komianos and GA Papoian (2016) MEDYAN: Mechanochemical Simulations of Contraction and Polarity Alignment in Actomyosin Networks. PLoS Comput Biol 12(4): e1004877. doi:10.1371/journal.pcbi.1004877</p>
Fig.ç3.D isasterina akajimaensis sp. nov., holotype (NSMT E-6758). A, Anal pore and a patch; B, madreporite; C, proximal part of arm, abactinal view; D, oral plate pair and interradial uncalci ed area, some oral spines have been lost (see also Fig. 6 for oral plate pair and interradial uncalci ed area at another interradius); E, proximal part of ambulacral furrow (oral plates seen at the lower-le corner are drawn in Fig. 6); F, inferomarginal spinelets, abactinal view. Abbreviations: als, actinolateral spine; apo, anal pore; fs, furrow spine; imp, inferomarginal plate; ims, inferomarginal spine; ir, interradial; iua, interradial uncalci ed area; md, madreporite; op, oral plate; os, oral spine; r, radial; rp, rigid patch; sas, subambulacral spine. in A New Asterinid Sea Star, Disasterina akajimaensis (Echinodermata: Asteroidea) from the Ryukyu Islands, Japan, with Notes on the Genus Disasterina
Fig.ç3.D isasterina akajimaensis sp. nov., holotype (NSMT E-6758). A, Anal pore and a patch; B, madreporite; C, proximal part of arm, abactinal view; D, oral plate pair and interradial uncalci ed area, some oral spines have been lost (see also Fig. 6 for oral plate pair and interradial uncalci ed area at another interradius); E, proximal part of ambulacral furrow (oral plates seen at the lower-le corner are drawn in Fig. 6); F, inferomarginal spinelets, abactinal view. Abbreviations: als, actinolateral spine; apo, anal pore; fs, furrow spine; imp, inferomarginal plate; ims, inferomarginal spine; ir, interradial; iua, interradial uncalci ed area; md, madreporite; op, oral plate; os, oral spine; r, radial; rp, rigid patch; sas, subambulacral spine.
How flexible, slit and rigid barriers mitigate two-phase geophysical mass flows: a numerical appraisal
<p>The supplementary videos SV1 and SV2 (presented in Figures 4 and 5) show geophysical flows impacting flexible, slit, and rigid barriers via pile-up mode and runup mode, respectively.</p> <p>The measurement data used for comparison in Figure 7 from 14 centrifuge tests with bouldery and the boulder-debris mixture flows (Song et al., 2018b, 2019), and dry granular flow against open-type dams (Choi et al., 2020) were published open access in their articles.</p> <p>The unique dataset, comprising normalized data obtained from analytical models (Li et al., 2021; Song et al., 2021a), empirical relations (Cui et al., 2015), experiments (Armanini et al., 2020; Choi et al., 2020; Cui et al., 2015; Hu et al., 2020; Song et al., 2021a, 2021b; Tiberghien et al., 2007; Vicari et al., 2021), field events (Hübl et al., 2009), and practical design values (Armanini, 1997; Hungr et al., 1984; Kwan & Cheung, 2012; Wendeler, 2016), is plotted in Figure 10 for comparison.</p> <p>All these articles can be found in the PDF file entitled “References in Figures 7 and 10”.</p>
Data set: Quantifying the Accuracy of Collaborative IoT and Robot Sensing in Indoor Settings of Rigid Objects
<p>This is the data set accompanying the paper "Quantifying the Accuracy of Collaborative IoT and Robot Sensing in Indoor Settings of Rigid Objects" by Sune L. Sørensen and Mikkel Baun Kjærgaard. Please refer to the paper for a description of the hardware used to record the data and how it is recorded.</p> <p>It consists of the following files:</p> <p><em>IoT camera images</em>: RBG images, named img_aa_bbb_0.jpg, where aa is the setup ID, bb is the camera ID (101, 102, 103 or 104).</p> <p><em>Robot RGB images</em>: RBG images, named aa0.png where aa is the setup ID.</p> <p><em>Robot point clouds</em>: pcd-files, named aa0.pcd where aa is the setup ID.</p> <p>The transformation from the IoT coordinate system to the robot coordinate system is:</p> <p>robotTiot = np.array([[0.914428, 0.134934, -0.378832, 3.76475],</p> <p>[0.393661, -0.49845, 0.772371, 0.791051],</p> <p>[-0.0846896, -0.855336, -0.509056, 2.37154],</p> <p>[0.0, 0.0, 0.0, 1.0]])</p> <p>Example, tranforming a pose in IoT coordinates to robot coordinates: p_rob = robotTiot * p_iot</p>
Haptic Saliency Model for Rigid Textured Surfaces
<p>When touching an object, we focus more on some of its parts rather than touching the whole object’s surface, i.e. some parts are more salient than others. Here we investigated how different physical properties of rigid, plastic, relieved textures determine haptic exploratory behavior. We produced haptic stimuli whose textures were locally defined by random distributions of four independent features: amplitude, spatial frequency, orientation and isotropy. Participants explored two stimuli one after the other and in order to promote exploration we asked them to judge their similarity. We used a linear regression model to relate the features and their gradients to the exploratory behavior (spatial distribution of touch duration). The model predicts human behavior significantly better than chance, suggesting that exploratory movements are to some extent driven by the low level features we investigated. Remarkably, the contribution of each predictor changed as a function of the spatial scale in which it was defined, showing that haptic exploration preferences are spatially tuned, i.e. specific features are most salient at different spatial scales.</p> <p>Metzger, A., Toscani, M., Valsecchi, M. & Drewing, K. (2018) Haptic saliency model for rigid textured surfaces. In Prattichizzo, D., Shinoda, H., Tan, H. Z., Ruffaldi, E. & Frisoli, A. (Eds.), Haptics: Science, Technology, and Applications, 11th International Conference, EuroHaptics 2018, Pisa, Italy, June 13-16, 2018, Proceedings, Part I (pp. 389–400). Springer International Publishing, Cham.</p> <p> </p> <p>Data of the experiment is stored in a zip file, containing all data relative to the publication. The 'movement' folder containes participnts' movement data. The 'stimuli' folder containes the 2D and 3D models of the stimuli. </p> <p>Explanaition and coding of the data is provided in the file VARIABLE_CODES.txt.</p>
Text-fig. 7. rigid erect bryozoans. A – colony perhaps belonging to Metrarabdotos and/or Smittina, deposited in NM Prague under number T 3321. B – erect rigid cyclostomatous bryozoans belonging perhaps to the genus Hornera, deposited in NM Prague under number T 3322. C – colony perhaps belonging to Myriapora, deposited in NM Prague under number T 3323. All photographs were taken under the optic microscope, all scale bars 1 mm. in The Priabonian Bryozoan-Decapod Association From The Borové Formation (The Ďurkovec Quarry, Ne Slovakia) And Its Palaeoecological Implications
Text-fig. 7. rigid erect bryozoans. A – colony perhaps belonging to Metrarabdotos and/or Smittina, deposited in NM Prague under number T 3321. B – erect rigid cyclostomatous bryozoans belonging perhaps to the genus Hornera, deposited in NM Prague under number T 3322. C – colony perhaps belonging to Myriapora, deposited in NM Prague under number T 3323. All photographs were taken under the optic microscope, all scale bars 1 mm.
Dataset of globally rigid graphs
<p>This data set collectes all globally rigid graphs for dimension d<=25 with at most d+k vertices, where k might be different.<br> The graphs are collected in a zip file with respect to the dimension. Graphs are stored in graph6 data format.</p>
Data sets for heat generation and associated contact temperature during an oblique impact of a deformable particle and a rigid substrate
<p>This dataset contains essential data from the Finite Element Method model predicting heat generation due to friction and plastic deformation during the oblique impact of a deformable particle and a rigid substrate. Part of this data was processed and published in a journal article (<a href="https://doi.org/10.1016/j.powtec.2023.118481">https://doi.org/10.1016/j.powtec.2023.118481</a>). The following is the description of the data files and the associated Figure in the original paper.</p> <p>‘Heat_Elast_Vt.xlsx’ and ‘Temp_Elast_Vt.xlsx’ data for the evolution of heat and nodal contact temperature, respectively, for varying tangential velocity. Data was used in Figs. 7a and 7b in the associated paper</p> <p>‘Heat_Vt.xlsx’ and Heat_Vn.xlsx’ data for the evolution of heat for various tangential velocities and normal velocities, respectively. Data was used in Figs. 8a and 8b in the associated paper.</p> <p>‘Heat_YM.xlsx’ and ‘Temp_YM.xlsx’ data for the evolution of heat and nodal contact temperatures, respectively, for varying Young’s moduli. Data was used in Figs. 9 and 10 in the associated paper.</p> <p>‘Heat_YS.xlsx’ and ‘Temp_YS.xlsx’ data for the evolution of heat and nodal contact temperatures for varying yield strengths. Data was used in Figs. 11 and 12 in the associated paper.</p> <p>‘Heat_Den.xlsx’ and ‘Temp_Den.xlsx’ data for heat and nodal contact temperature evolution, respectively, for varying yield strengths. Data was used in Figs. 13 and 14 in the associated paper.</p> <p> ‘Temp_TC.xlsx’ data for the evolution of nodal contact temperatures for varying thermal conductivities. Data was used in Fig. 15 in the associated paper.</p> <p>‘Temp_HC.xlsx’ data for the evolution of nodal contact temperatures for varying specific heat capacities. Data was used in Fig. 16 in the associated paper.</p>
Data sets for temperature rise due to frictional heat generation during a sliding contact between an elastic particle and a rigid substrate
<p>This dataset contains essential data from the Finite Element Method model predicting heat generation due to friction during the sliding contact between an elastic particle and a rigid substrate. Part of this data was processed and presented in an article under review for journal publication. The following is the description of the data files and the associated Figure in the original paper.</p> <p>'Temp_CoeffFric_01_055.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various friction coefficient values (0.1-0.55).</p> <p>'Temp_Load_001_01.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various normal load values (0.01-0.1 N).</p> <p>'Temp_Vel_02_1.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various sliding velocity values (0.2-1 m/s).</p> <p>'Temp_TC_5_100.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various thermal conductivity values. (i.e. 5-100 W/m K).</p> <p>'Temp_HC_100_1600.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various thermal conductivity values. (i.e. 100-1600 J/kg K).</p> <p> </p>
Marble graphs with various rigidity properties
<p>This dataset contains examples of graphs comparing rigidity concepts for generic bar-joint frameworks and for marble graphs. A marble graph is the contact graph of a collection of unit spheres in dimension three with non-overlapping interiors.</p> <p>For each graph there is a Graph6 file format and a list of edges in Mathematica notation. We also provide the coordinates that give the unit-distances (also in Mathematica format). The names of the files indicate the rigidity properties of the given graph.</p>
Experimental data: Single- and double-wythe brick masonry walls subjected to four-point bending tests under different support conditions: Simply supported, rigid, non-rigid
<p>This dataset contains the results of laboratory quasi-static monotonic four-point bending tests conducted at RISE Research Institutes of Sweden on eleven natural-scale unreinforced brick masonry walls. The walls were spanning vertically between two reinforced concrete slabs and were tested under three different support conditions defined according to the American manual UFC 3-340-02: simply supported, rigid, non-rigid. The influence of these support conditions on the out-of-plane behavior of the walls was studied on elements with varying thickness – single and double wythe – and subjected to different levels of axial compression (or overload). The walls were tested inside of a bi-axial test setup that allowed not only the lateral, out-of-plane force but also the axial, arching action to be measured throughout the tests. Optical full-field displacement measurements were also acquired by two systems of cameras making use of the 2D and 3D Digital Image Correlation (DIC) technique.</p> <p>The data generated from these tests are made here available to support further investigations on masonry structures subjected to extreme lateral, out-of-plane actions. The dataset includes 3 compressed folders, ordered from 01 to 03, along with an auxiliary document describing the content and organization of the dataset. </p> <p>The data presented here are described in the following research article:</p> <blockquote> <p><a href="https://www.sciencedirect.com/science/article/pii/S0950061823022602?via%3Dihub">Godio M, Flansbjer M, Williams Portal N (2023). Single- and double-wythe brick masonry walls subjected to four-point bending tests under different support conditions: simply supported, rigid, non-rigid, Construction and Building Materials</a></p> </blockquote> <p>To cite this dataset, please refer to the article.</p> <p>The Authors</p>
Rigidity of epithelial tissues as a double optimization problem
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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