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opencc-by-4.0May 2017View details →

Fig. 8 in Redescription of Atopocottus tribranchius (Cottidae) from Japan with comments on the generic diagnosis and distribution

Fig. 8. Distributional map of Atopocottus tribranchius. 1: Akita Prefecture; 2: Yamagata Prefecture; 3: Niigata Prefecture; 4: Kyoto Prefecture; 5: Yamaguchi Prefecture; 6: northern East China Sea; 7: Kochi Prefecture; and 8: Ibaraki Prefecture. Stars indicate localities of present specimens. Akita, Yamagata, and Ibaraki based on literature records.

Fig. 20 in Elevation of Pilisaprinus to full generic status with notes on the evolution of termitoxeny in the Saprininae (Coleoptera: Histeridae)

Fig. 20. Excerpt from the unpublished phylogenetic analysis of the Saprininae (Lackner, unpubl. data) showing the position of Pilisaprinus verschureni, Saprinus (Phaonius) pharao Marseul, 1855 and Saprinus (s.str.) semistriatus (Scriba, 1790). Synapomorphies relevant for the phylogenetic placement of Pilisaprinus are numbered: 1 – apical third of 8th sternite of male terminalia with dense setae; 2 – majority of antennal club glabrous apart from large oval or slit-like sensory areas situated on ventral side of club which are densely covered with sensilla (see also Fig. 3); 3 – sensory areas of the antennal club complemented with an apical sensory cap (see also Fig. 3); 4 – pronotal hypomeron setose; 5 – prosternal foveae absent; 6 – metepisternum setose; 7 – antennal annuli present; 8 – sensory structures of the antennal club in a form of slit-like pits not surrounded by sensilla; 9 – inner subhumeral stria absent.

Figs 10–12 in Elevation of Pilisaprinus to full generic status with notes on the evolution of termitoxeny in the Saprininae (Coleoptera: Histeridae)

Figs 10–12. Mouthparts and sensory structures of the antenna of Pilisaprinus verschureni (Thérond, 1959). 10 – mandibles, dorsal view; 11 – labrum, left half showing dorsal view; right half showing ventral view; 12 – antennal club showing sensory structures of the antenna.

Figs 1–9 in Elevation of Pilisaprinus to full generic status with notes on the evolution of termitoxeny in the Saprininae (Coleoptera: Histeridae)

Figs 1–9. External morphology of Pilisaprinus verschureni (Thérond, 1959). 1 – habitus, dorsal view; 2 – same, ventral view; 3 – antennal club, latero-ventral view; 4 – head, dorsal view; 5 – mentum, ventral view; 6 – prosternum; 7 – propygidium and pygidium; 8 – lateral disc of metaventrite + metepisternum; 9 – protibia, dorsal view.

Figs 56–65. Type specimens. 56–57 in Revision of the genus Hesperopenna (Coleoptera: Chrysomelidae: Galerucinae). I. Generic redescription, definition of species groups and taxonomy of H. medvedevi species group

Figs 56–65. Type specimens. 56–57 – Hesperopenna flava Medvedev & Dang, 1981 (male, holotype, 7.6 mm); 58–59 – Calomicrus persimilis Kimoto, 1989 (male, paratype, 7.1 mm); 60–61 – Martinella merkli Medvedev, 2000 (male, paratype, 8.5 mm); 62–63 – Liroetiella englerae Medvedev, 1995 (female, paratype, 5.8 mm); 64–65 – Liroetiella warisan Mohamedsaid, 1998 (female, paratype, 4.1 mm). 56, 58, 60, 62, 64 – habitus; 57, 59, 61, 63, 65 – labels.

Figs 15–18 in Revision of the genus Hesperopenna (Coleoptera: Chrysomelidae: Galerucinae). I. Generic redescription, definition of species groups and taxonomy of H. medvedevi species group

Figs 15–18. Aedeagus (a – dorsal view; b – lateral view; c – ventral view). 15 – H. bonifaci sp. nov.; 16 – H. helferi sp. nov.; 17 – H. sipekorum sp. nov.; 18 – H. zofka sp. nov. Scale bar 1 mm.

Figs 41–47. Spermatheca. 41 in Revision of the genus Hesperopenna (Coleoptera: Chrysomelidae: Galerucinae). I. Generic redescription, definition of species groups and taxonomy of H. medvedevi species group

Figs 41–47. Spermatheca. 41 – Hesperopenna medvedevi nom. nov.; 42 – H. persimilis (Kimoto, 1989); 43 – H. tibialis (Kimoto, 1989); 44 – H. arnoldi sp. nov.; 45 – H. helferi sp. nov.; 46 – H. sipekorum sp. nov.; 47 – H. zofka sp. nov. Scale bar 0.25 mm.

Figs 34–40. Female pygidium. 34 in Revision of the genus Hesperopenna (Coleoptera: Chrysomelidae: Galerucinae). I. Generic redescription, definition of species groups and taxonomy of H. medvedevi species group

Figs 34–40. Female pygidium. 34 – Hesperopenna medvedevi nom. nov.; 35 – H. persimilis (Kimoto, 1989); 36 – H. tibialis (Kimoto, 1989); 37 – H. arnoldi sp. nov.; 38 – H. helferi sp. nov.; 39 – H. sipekorum sp. nov.; 40 – H. zofka sp. nov. Scale bar 1 mm.

Fig. 70 in Revision of the genus Hesperopenna (Coleoptera: Chrysomelidae: Galerucinae). I. Generic redescription, definition of species groups and taxonomy of H. medvedevi species group

Fig. 70. Aedeagus of Hesperopenna granulicollis (Kimoto, 1989) (paratype) (a – dorsal view; b – lateral view; ventral view). Scale bar 1 mm.

Figs 1–10 in Revision of the genus Hesperopenna (Coleoptera: Chrysomelidae: Galerucinae). I. Generic redescription, definition of species groups and taxonomy of H. medvedevi species group

Figs 1–10. Morphological details of Hesperopenna sipekorum sp. nov. 1 – head; 2 – pronotum in lateral view; 3 – prothorax; 4 – meso- and metathorax; 5 – left elytron in lateral view; 6 – right antenna; 7 – left hind leg; 8 – claw; 9 – vaginal palpi; 10 – tignum and sternite VIII. Scale bars: 1 mm for Figs 1–5 and 9–10, 2 mm for Figs 6–7, 0.25 mm for Fig. 8.

Figs 66–69 in Revision of the genus Hesperopenna (Coleoptera: Chrysomelidae: Galerucinae). I. Generic redescription, definition of species groups and taxonomy of H. medvedevi species group

Figs 66–69. Aedeagus (a – dorsal view; b – lateral view; ventral view). 66 – Hesperopenna vietnamica (Medvedev, 2000) (paratype); 67 – H. antennalis (Kimoto, 1989); 68 – H. minor (Kimoto, 1989) (paratype); 69 – H. bicolor (Kimoto, 1989) (paratype). Scale bar 1 mm.

opencc-by-4.0Jan 2022View details →

Supplementary material: Picosecond pulse-shaping for strong three-dimensional field-free alignment of generic asymmetric-top molecules

Supplementary material to the manuscript "Picosecond pulse-shaping for strong three-dimensional field-free alignment of generic asymmetric-top molecules" by Terry Mullins, Evangelos T. Karamatskos, Joss Wiese, Jolijn Onvlee, Arnaud Rouzée, Andrey Yachmenev, Sebastian Trippel, and Jochen Küpper, Nat Commun 13, 1431 (2022). <a href="https://doi.org/10.1038/s41467-022-28951-z">https://doi.org/10.1038/s41467-022-28951-z</a>, arXiv: <a href="https://arxiv.org/abs/2009.08157">2009.08157 </a> <ul> <li> simulations_part.z* is split zip archive containing simulations data for indole molecule, such as files with rotational probability density distributions computed at different times \(t=0..1500\) ps during the laser pulse and field-free evolution, and example python scripts for data retrieval.</li> <li>rawdata_part.z* is split zip archive containing raw experimental data.</li> <li>analysis_scripts.zip is zip archive containing experimental analysis codes.</li> </ul> The simulations_part.zip contains the following files and folders: <ul> <li>prob_density_euler_angles contains files rotdens_av_<time>.gz with simulated state-averaged rotational probability density distributions in terms of Euler angles for different times <time>, ranging from the beginning of the alignment laser pulse at \(t=0\) up to \(t=1500\) ps with a time step of 1 ps. Calculations of probability density distributions were done using <a href="https://github.com/CFEL-CMI/richmol">Richmol</a> program. The gzipped ASCII data files rotdens_av_<time>.gz contain in columns the values of the Euler angles \(\phi,\theta,\chi\) followed by the normalized probability density value.</li> <li>prob_density_atoms_xyz contains files monte_carlo_av_<time>.h5 with state-averaged rotational probability density distributions of all atoms in the indole molecule in terms of their Cartesian coordinates, for different times <time>, ranging from the beginning of the alignment pulse at \(t=0\) up to \(t=1500\) ps with a time step of 1 ps. Structure of monte_carlo_av_<time>.h5 HDF5 files: Key        Description -----        ---------------- 'C10'     - Cartesian coordinates of carbon atom no. 10 'C11'     - Cartesian coordinates of carbon atom no. 11 'C12'     - ... 'C14'     - ... 'C3'      - ... 'C6'      - ... 'C7'      - ... 'C9'      - ... 'N4'      - ... 'H1-C3'   - Cartesian coordinates of a vector pointing from carbon atom no. 3 to hydrogen atom no. 1 'H13-C11' - ... 'H15-C12' - ... 'H16-C14' - ... 'H2-N4'   - ... 'H5-C7'   - ... 'H8-C9'   - ... 'ref_vectors' - reference molecular-frame Cartesian coordinates of all atoms 'x'       - coordinates of the x-axis of Principal Axes of Inertia Frame 'y'       - coordinates of the y-axis of Principal Axes of Inertia Frame 'z'       - coordinates of the z-axis of Principal Axes of Inertia Frame 'pol_x'   - coordinates of the x-axis of Principal Axes of Polarizability Frame 'pol_y'   - coordinates of the y-axis of Principal Axes of Polarizability Frame 'pol_z'   - coordinates of the z-axis of Principal Axes of Polarizability Frame</li> <li>indole_deflected_states.txt ASCII file contains initial populations of rotational states of indole in the deflected beam. The following data is arranged in columns: m, J, id, energy, normalized population. The J and m are rotational quantum numbers of the total angular momentum and its Z-projection, the id number refers to the state's index in file indole_energies_j0_j20.txt listing rotational states of indole.</li> <li>indole_data.py Python module provides basic functions to extract information from HDF5 data files monte_carlo_av_<time>.h5. It can also be used to compute alignment and orientation.</li> <li>example_cos.py and example_dens.py Python scripts that demonstrate how to use indole_data.py module for computing and plotting alignment traces and a 2D projection of the probability density distribution, respectively.</li> <li>monte_carlo.py Python script that was used to compute through Monte-Carlo sampling probability density distributions for Cartesian positions of atoms in indole (monte_carlo_av_<time>.h5 files) using probability density distribution functions in Euler angles (outputs of Richmol program rotdens_av_<time>.gz).</li> </ul> The analysis_scripts.zip contains the following files and folders: <ul> <li>H_Plus folder contains codes relevant for the analysis of H+ ion data. <ul> <li>analyse_full_alignment_scans.m: subtracts background and combines delay scan data sets together, takes account of errors.</li> <li>calculate_resamped_df.m: called by analyse_full_alignment_scans.m to calculate the frequency sampling.</li> <li>unique_mean.m: called by analyse_full_alignment_scans.m when combining data sets. Combines non-unique data points into a single data point.</li> </ul> </li> <li>C_Plus2 folder contains codes for the analysis of C2+ ion data. The file descriptions are identical to those in the H_Plus directory.</li> <li>intensity/calculate_intensity.m: calculates peak intensity of the laser pulse from measured parameters as well as statistical error.</li> <li>intensity/compare_exp_sim.m: fits experimental and theoretical tomography and delay-dependent 2D projection values.</li> <li>intensity/nir2hdf5_kHz.py: converts raw data files (from rawdata_part.z* archive) into hdf5 files.</li> </ul>

opencc-by-4.0Jun 2022View details →

Generic solving of a multi-compartment physiologically-based kinetic model

This repository makes available supplementary material related to a scientific paper in progress.

opencc-by-4.0Sep 2022View details →

Applying a generic and fast coarse-grained molecular dynamics model to extensively study the mechanical behavior of polymer nanocomposites: supplementary information and dataset

Abstract: (from [1]) <blockquote> The addition of nano-sized filler particles enhances the mechanical performance of polymers. The resulting properties of the polymer nanocomposite depend on a complex interplay of influence factors such as material pairing, filler size, and content as well as filler-matrix adhesion. As a complement to experimental studies, numerical methods, such as molecular dynamics (MD), facilitate an isolated examination of the individual factors in order to understand their interaction better. However, particle-based simulations are, in general, computationally very expensive, rendering a thorough investigation of nanocomposites’ mechanical behavior both expensive and time-consuming. Therefore, this paper presents a fast coarse-grained MD model for a generic nanoparticle-reinforced thermoplastic. First, we examine the matrix and filler phase individually, which exhibit isotropic elasto-viscoplastic and anisotropic elastic behavior, respectively. Based on this, we demonstrate that the effect of filler size, filler content, and filler-matrix adhesion on the stiffness and strength of the nanocomposite corresponds very well with experimental findings in the literature. Consequently, the presented computationally efficient MD model enables the analysis of a generic polymer nanocomposite. In addition to the obtained insights into the mechanical behavior, the material characterization provides the basis for a future continuum mechanical description, which bridges the gap to the engineering scale.  </blockquote>   Contact: Maximilian Ries Institute of Applied Mechanics Friedrich-Alexander-Universität Erlangen-Nürnberg Egerlandstr. 5 91058 Erlangen Software: All MD simulations were performed with LAMMPS [2], version: 29 Oct 2020 / 20201029 Compiled with Compiler: GNU C++ 4.8.5 20150623 (Red Hat 4.8.5-39) with OpenMP not enabled C++ standard: C++11 Active compile time flags: -DLAMMPS_GZIP -DLAMMPS_SMALLBIG Installed packages: CLASS2, KSPACE, MANYBODY, MC, MOLECULE, MPIIO, OPT, VORONOI, USER-INTEL, USER-MISC, USER-MOLFILE, USER-NETCD Polymer and polymer composite samples generated with self-avoiding random-walk algorithm [3] Post-processing Matlab R2019b Evaluation of polymer entanglements with Z1-Algorithm [4]   License: Creative Commons Attribution 4.0 International   Context: Data set supplementing  journal paper: [1] M. Ries, J. Seibert, P. Steinmann, S. Pfaller. “Applying a generic and fast coarse-grained molecular dynamics model to extensively study the mechanical behavior of polymer nanocomposites”, Express Polymer Letters, 2022, 16. This dataset contains the results presented in [1] and the necessary data to obtain those as well as supplementary information. Content: supplementary material: supplementary_information.pdf data:     folder names vary depending on the context, explained in the following:   01_matrix <ul> <li> 01_equilibration sample equilibration to different temperatures nomenclature: equil_<chains>-<chain_atoms>-box_<initial_box_length>-min_<SARW_distance>-angle_<SARW_angle>-T_<final_temperature>[-<batch_ID>] <ul> <li> chains: 200 </li> <li> chain_atoms: 200 </li> <li> initial_box_length: 100 </li> <li> SARW_distance: 0.9 </li> <li> SARW_angle: 50 </li> <li> final_temperature: 0.1-1.0 </li> <li> batch_ID: 2-5  </li> </ul> </li> <li> 02_temperature_dependence uniaxial tension simulations to identify temperature dependence nomenclature: 01_UT_<chains>-<chain_atoms>-box_<initial_box_length>-min_<SARW_distance>-angle_<SARW_angle>-T_<final_temperature> <ul> <li> chains: 200 </li> <li> chain_atoms: 200 </li> <li> initial_box_length: 100 </li> <li> SARW_distance: 0.9 </li> <li> SARW_angle: 50 </li> <li> final_temperature: 0.1-1.0 </li> </ul> </li> <li> 03_directional_dependence uniaxial tension simulations to prove isotropy in Y and Z direction; X direction in 04_rate_dependence nomenclature: 03_UT_<chains>-<chain_atoms>-box_<initial_box_length>-min_<SARW_distance>-angle_<SARW_angle>-T_<final_temperature>-rate_<strain_rate>-<batchID> <ul> <li> chains: 200 </li> <li> chain_atoms: 200 </li> <li> initial_box_length: 100 </li> <li> SARW_distance: 0.9 </li> <li> SARW_angle: 50 </li> <li> final_temperature: 0.3 </li> <li> strain_rate: 5E-5 </li> <li> batchID: 1-5 </li> </ul> </li> <li> 04_rate_dependence uniaxial tension simulations to identify strain rate dependence nomenclature: 03_UT_<chains>-<chain_atoms>-box_<initial_box_length>-min_<SARW_distance>-angle_<SARW_angle>-T_<final_temperature>-rate_<strain_rate>[-<batchID>] <ul> <li> chains: 200 </li> <li> chain_atoms: 200 </li> <li> initial_box_length: 100 </li> <li> SARW_distance: 0.9 </li> <li> SARW_angle: 50 </li> <li> final_temperature: 0.3 </li> <li> strain_rate: 5E-4, 5E-5, 5E-6 </li> <li> batchID: 1-5 </li> </ul> </li> <li> 05_cyclic_loading sinusoidal uniaxial deformation nomenclature: 05_UT_<chains>-<chain_atoms>-box_<initial_box_length>-min_<SARW_distance>-angle_<SARW_angle>-T_<final_temperature>-rate_<strain_rate>-sin_<strain_amplitude> <ul> <li> chains: 200 </li> <li> chain_atoms: 200 </li> <li> initial_box_length: 100 </li> <li> SARW_distance: 0.9 </li> <li> SARW_angle: 50 </li> <li> final_temperature: 0.3 </li> <li> strain_rate: 5E-4 </li> <li> strain_amplitude: 0.01, 0.05, 0.15, 0.2 </li> </ul> </li> <li> 06_relaxation relaxation subsequent to time-proportional deformation nomenclature: 07_UT_<chains>-<chain_atoms>-box_<initial_box_length>-min_<SARW_distance>-angle_<SARW_angle>-T_<final_temperature>-rate_<strain_rate>-sin_<strain_amplitude>_relax <ul> <li> chains: 200 </li> <li> chain_atoms: 200 </li> <li> initial_box_length: 100 </li> <li> SARW_distance: 0.9 </li> <li> SARW_angle: 50 </li> <li> final_temperature: 0.3 </li> <li> strain_rate: 5E-4 </li> <li> strain_amplitude: 0.01, 0.05, 0.15, 0.2 </li> </ul> </li> <li> 07_simple_shear time-proportional simple shear deformation with different strain rates nomenclature: SS_P2VPSi-rate_<strain_rate>-<batchID> <ul> <li> strain_rate: 5E-4, 5E-5, 5E-6 </li> <li> batchID: 1-5 </li> </ul> </li> <li> 08_large_deformation uniaxial deformation up to 100% strain nomenclature: 02_UT_<chains>-<chain_atoms>-box_<initial_box_length>-min_<SARW_distance>-angle_<SARW_angle>-T_<final_temperatur>-strain_<max_strain> <ul> <li> chains: 200 </li> <li> chain_atoms: 200 </li> <li> initial_box_length: 100 </li> <li> SARW_distance: 0.9 </li> <li> SARW_angle: 50 </li> <li> final_temperature: 0.3 </li> <li> max_strain: 1 </li> </ul> </li> </ul> 02_filler <ul> <li> 01_Silica_equilibration sample equilibration </li> <li> 02_time_proportional time-proportional uniaxial and simple shear tests nomenclature: Silica_BV-<loadcase>_<direction>-strain_<max_strain>-rate_<strain_rate> <ul> <li> loadcase: uniaxial tension (UT), simple shear (SS) </li> <li> max_strain: 0.1 </li> <li> direction: X, Y, Z (UT); XY, XZ, YZ (SS) </li> <li> strain_rate: 5E-4, 5E-5, 5E-6 </li> </ul> </li> <li> 03_time_periodic time-periodic uniaxial and simple shear tests nomenclature: Silica_BV-<loadcase>_<direction>_sin-ampl_<strain_amplitude>-rate_<max_strain_rate> <ul> <li> loadcase: uniaxial tension (UT), simple shear (SS) </li> <li> direction: X, Y, Z (UT); XY, XZ, YZ (SS) </li> <li> strain_amplitude: 0.025 </li> </ul> </li> </ul> 03_composite <ul> <li> 01_equilibration sample equilibration nomenclature: equil_P2VPSi-rNP_<filler_radius>-nNP_<filler_number>-<batchID> <ul> <li> filler_radius: 2.5-10.0 </li> <li> filler_number: 1-160 (depending on filler_radius) </li> <li> batchID: 1-5 </li> </ul> </li> <li> 02_uniaxial-tension uniaxial tension simulations nomenclature: UT_P2VPSi-rNP_<filler_radius>-nNP_<filler_number>-<batchID> <ul> <li> filler_radius: 2.5-10.0 </li> <li> filler_number: 1-160 (depending on filler_radius) </li> <li> batchID: 1-5 </li> </ul> </li> <li> 03_filler-maxtrix-adhesion equilibration and uniaxial deformation of samples with mid and weak filler-matrix adhesion (for strong adhesion see 01_equilibration and 02_uniaxial-tension nomenclature: see above </li> <li> 04_IP_equilibration equilibration of samples to evaluate the microstructure for neat polymer and composites with filler radius 2.5-7.5 nomenclature: P2VPSi-<chains>x<chain_atoms>_rNP_<filler_radius>-nNP_<filler_number>_pos_<filler_pos>-<batchID> <ul> <li> chains: 200 </li> <li> chain_atoms: 200 </li> <li> filler_radius: 0 (neat), 2.5, 5.0, 7.5 </li> <li> filler_number: 0 (neat), 1 </li> <li> batchID: 1-20 </li> </ul> </li> </ul>       Each simulation directory contains: <ul> <li> lammps input file (*.in) of the specific simulation </li> <li> data file (*.data) containing the initial sample configuration </li> <li> input.prm: input parameters of the specific simulation (read by the input file) </li> <li> meta.info: meta data of the specific simulation run </li> <li> LAMMPS_out: simulation results (lammps thermo_out) in tabulated form, an overview of columns is given below <ul> <li> thermo_out.Dat: raw output  </li> <li> thermo_out_SG.Dat: smoothed output (Savitzky-Golay filter) </li> <li> thermo_out_STD.Dat: standard deviation of raw output </li> </ul> </li> </ul>   Output quantities (columns of *.Dat files): Please note that the normalized Lennard-Jones unit set is used, so all quantities are normalized to fundamental mass, length, energy, time and the Boltzmann constant. Thus all entries are unitless [1]. <ul> <li> Step: time step  </li> <li> Time: time  </li> <li> TotEng: total energy  </li> <li> PotEng: potential energy </li> <li> KinEng: kinetic energy  </li> <li> E_pair: pair energy  </li> <li> E_bond: bond energy  </li> <li> E_angle: angle energy  </li> <li> E_dihed: dihedral energy  </li> <li> Temp: temperature </li> <li> Press: hydrostatic pressure </li> <li> Pxx: xx component of pressure tensor  </li> <li> Pyy: yy component of pressure tensor  </li> <li> Pzz: zz component of pressure tensor  </li> <li> Pxy: xy component of pressure tensor </li> <li> Pxz: xz component of pressure tensor </li> <li> Pyz: yz component of pressure tensor </li> <li> Volume: volume of simulation box  </li> <li> Lx: box length in x direction   </li> <li> Ly: box length in y direction   </li> <li> Lz: box length in z direction   </li> <li> Density: density   </li> <li> c_RG: radius of gyration scalar  </li> <li> c_RG[1]: squared radius of gyration tensor (xx component)   </li> <li> c_RG[2]: squared radius of gyration tensor (yy component)   </li> <li> c_RG[3]: squared radius of gyration tensor (zz component)   </li> <li> c_RG[4]: squared radius of gyration tensor (xy component)   </li> <li> c_RG[5]: squared radius of gyration tensor (xz component)   </li> <li> c_RG[6]: squared radius of gyration tensor (yz component)   </li> <li> c_bondave[1]: bond energy averaged over all atoms   </li> <li> c_bondave[2]: bond distance averaged over all atoms   </li> <li> c_bondave[3]: squared bond distance averaged over all atoms   </li> <li> c_angleave[1]: angle energy averaged over all atoms   </li> <li> c_angleave[2]: angle averaged over all atoms degree </li> <li> c_angleave[3]: cosine of angle  </li> <li> c_angleave[4]: squared cosine of angle  </li> <li> c_MSD[1]: mean squared displacement x-direction   </li> <li> c_MSD[2]: mean squared displacement y-direction   </li> <li> c_MSD[3]: mean squared displacement z-direction   </li> <li> c_MSD[4]: total mean squared displacement   </li> <li> c_COM[1]: x coordinate of center of mass   </li> <li> c_COM[2]: y coordinate of center of mass   </li> <li> c_COM[3]: z coordinate of center of mass   </li> <li> v_strain_xx: xx component of engineering strain tensor    </li> <li> v_strain_yy: yy component of engineering strain tensor     </li> <li> v_strain_zz: zz component of engineering strain tensor     </li> <li> v_vMisesequivstress: von Mises equivalent stress  </li> <li> v_Cauchy_xx: xx component of stress tensor   </li> <li> v_Cauchy_yy: yy component of stress tensor </li> <li> v_Cauchy_zz: zz component of stress tensor </li> <li> v_Cauchy_xy: xy component of stress tensor  </li> <li> v_Cauchy_xz: xz component of stress tensor  </li> <li> v_Cauchy_yz: yz component of stress tensor  </li> <li> v_strain_xy: xy component of engineering strain tensor    </li> <li> v_strain_xz: xz component of engineering strain tensor    </li> <li> v_strain_yz: yz component of engineering strain tensor    </li> </ul>   References: [1] M. Ries, J. Seibert, P. Steinmann, S. Pfaller. “Applying a generic and fast coarse-grained molecular dynamics model to extensively study the mechanical behavior of polymer nanocomposites”, Express Polymer Letters, 2022, 16. [2] S. Plimpton, “Fast parallel algorithms for short-range molecular dynamics,” Journal of computational physics, 1995, 117, 1-19. [3] A. P. Thompson et al., “LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales,” Computer Physics Communications, vol. 271, p. 108171, 2022. [4] M. Ries, V. Dötschel, J. Seibert, S. Pfaller. “A self-avoiding random walk algorithm (SARW) for generic thermoplastic polymers and nanocomposites”, Zenodo, 2022. <a href="https://doi.org/10.5281/zenodo.6245699">https://doi.org/10.5281/zenodo.6245699</a>

Figures 6‒9 in Modification in the generic diagnosis of Bursaustium (Acari: Erythraeidae) with description of a new species from southeast of Iran

Figures 6‒9. Bursaustium zabolensis Noei sp. nov. (larva) – 6. Ti I-Ta I; 7. Tr I-Ge I; 8. Ti II -Ta II; 9. Tr II-Ge II.

Figures 13‒17. 13–16 in Modification in the generic diagnosis of Bursaustium (Acari: Erythraeidae) with description of a new species from southeast of Iran

Figures 13‒17. 13–16. Bursaustium zabolensis Noei sp. nov. (larva) – Dorsal scutum position on dorsal surface of propodosoma; 17. Dorsal scutum of the holotype of B. gaspari, sent by Prof. R. Haitlinger.

Figures 3‒5 in Modification in the generic diagnosis of Bursaustium (Acari: Erythraeidae) with description of a new species from southeast of Iran

Figures 3‒5. Bursaustium zabolensis Noei sp. nov. (larva) – 3. Ventral view of idiosoma; 4. Ventral view of palpal tibia and tarsus; 5. Dorsal (right) and ventral (left) view of gnathosoma.

Figures 1–2 in Modification in the generic diagnosis of Bursaustium (Acari: Erythraeidae) with description of a new species from southeast of Iran

Figures 1–2. Bursaustium zabolensis Noei sp. nov. (larva) – 1. Dorsal view of idiosoma; 2. Dorsal scutum.

Figures 10‒12 in Modification in the generic diagnosis of Bursaustium (Acari: Erythraeidae) with description of a new species from southeast of Iran

Figures 10‒12. Bursaustium zabolensis Noei sp. nov. (larva) – 10. Ti III-Ta III; 11. Tr III-Ge III; 12. Habitus.