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FIGURE 7 in Review of Pandara DeLong & Freytag (Insecta: Hemiptera: Cicadellidae: Gyponini), raised to generic status, including three new species and an identification key
FIGURE 7. Geographical distribution of Pandara species in different ecological regions of South America.
FIGURES 46–50 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 46–50. Cremnomymar fernandezi, male (Plazoleta del Yunque, Robinson Crusoe Island, Juan Fernández Islands, Valparaíso, Chile). 46. Antenna (without scape). 47. Head, frontal, scapes, and pedicels. 48. Mesosoma. 49. Fore wing. 50. Genitalia.
FIGURES 38–41. Cremnomymar tucumanum, female. 38 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 38–41. Cremnomymar tucumanum, female. 38. Habitus (Anillaco, La Rioja, Argentina). 39–41 (Santa Vera Cruz, La Rioja). 39. Head, frontal. 40. Antenna. 41. Wings.
FIGURES 42–45 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 42–45. Cremnomymar?fernandezi, female (Plazoleta del Yunque, Robinson Crusoe Island, Juan Fernández Islands, Valparaíso, Chile). 42. Antenna. 43. Mesosoma and matasoma. 44. Propodeum. 45. Wings.
FIGURES 32–35. Cremnomymar sagittifer, male. 32–33 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 32–35. Cremnomymar sagittifer, male. 32–33 (paratype of Parapolynema sagittifer, Bella Vista, Buenos Aires, Argentina). 32. Habitus. 33. Slide. 34. Habitus (Luján, Buenos Aires). 35. Genitalia (La Plata, Buenos Aires).
FIGURES 29–31 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 29–31. Cremnomymar sagittifer, female (Luján, Buenos Aires, Argentina). 29. Fore wing base. 30. Metasoma, lateral. 31. Wings.
FIGURES 1–6 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 1–6. Cremnomymar fidalgoi sp. n., female (holotype). 1. Slide. 2. Antenna. 3. Mesosoma, dorsal. 4. Metasoma, lateral. 5. Fore wing base. 6. Fore wing.
FIGURES 7–10 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 7–10. Cremnomymar fidalgoi sp. n. (paratypes). 7. Female head, frontal (Fuerte Bulnes, Magallanes and Chilean Antarctica, Chile). 8. Female habitus (Nahuelbuta National Park, Araucanía, Chile). 9. Female hind wing (Río Puntra, Isla Grande de Chiloé, Los Lagos, Chile). 10. Male antenna (Terao, Isla Grande de Chiloé).
FIGURES 21–24. 21–22 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 21–24. 21–22. Cremnomymar nahuelbutae sp. n., female (holotype). 21. Fore wing. 22. Hind wing. 23–24. Cremnomymar sagittifer, female (paratype of Parapolynema sagittifer, José C. Paz, Buenos Aires, Argentina). 23. Slide. 24. Habitus.
FIGURES 25–28 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 25–28. Cremnomymar sagittifer, female (Luján, Buenos Aires, Argentina). 25. Habitus. 26. Antenna. 27. Head, frontal. 28. Mesosoma.
FIGURES 15–20 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 15–20. Cremnomymar nahuelbutae sp. n., female (holotype). 15. Slide. 16. Antenna. 17. Head, frontal. 18. Prosternum (seen through mesosoma). 19. Mesosoma, dorsal. 20. Metasoma, lateral.
FIGURES 11–14 in Review of Cremnomymar species (Hymenoptera: Mymaridae) in mainland South America, with a new generic synonymy
FIGURES 11–14. Cremnomymar fidalgoi sp. n., male (paratypes). 11. Habitus (Pucará, Parque Nacional Lanín, Neuquén, Argentina). 12. Mesosoma, dorsal (Puerto Arrayán, Parque Nacional Nahuel Huapi, Neuquén). 13. Genitalia (Puerto Arrayán). 14. Wings (Terao, Isla Grande de Chiloé, Los Lagos, Chile).
FIGURE 1 in Two new generic synonyms in Palearctic Ciinae (Coleoptera: Ciidae)
FIGURE 1. Species of Paraxestocis Miyatake, 1954, sensu novo. A–D. Paraxestocis unicornis Miyatake, 1954, male holotype. Dorsal view, with arrow showing the pronotum pointed anteriorly (A), lateral view (B), ventral view (C) and labels (D). The type locality "Naose" was a small village on the foot of Mt. Ishizumi, about 500–700 m of altitude (33º42'N, 132º57'E), "Kuma" is now the city of "Kumakogen-cho" and "IYO" is now Ehime Prefecture, Shikoku. E. Paraxestocis denticollis (Nakane & Nobuchi, 1955), new combination, male from Chitose, Hokkaido, Japan. F. Paraxestocis wagae (Wankowiez, 1869), new combination, male from Bialowieska Forest, Poland. Scale bars: 0.5 mm.
Impact of the unimodal molar mass distribution on the mechanical behavior of polymer nanocomposites below the glass transition temperature: A generic, coarse-grained molecular dynamics study - dataset
<p>Abstract:<br>from [1]</p> <p>Polymer nanocomposites (PNCs) have shown great potential to meet the ever-growing requirements of modern engineering applications. Nowadays, molecular dynamics (MD) simulations are increasingly employed to complement experimental work and thereby gain a deeper understanding of the complex structure–property relations of PNCs. However, with respect to the thermoplastic’s mechanical behavior, the role of its average molar mass is rarely addressed, and many MD studies only consider uniform (monodispersed) polymers. Therefore, this contribution investigates the impact that and the dispersity Đ have on the stiffness and strength of PNCs through coarse-grained MD. To this end, we employed a Kremer–Grest bead–spring model and observed the expected increase in the mechanical performance of the neat polymer for larger . Our results indicated that the unimodal molar mass distribution does not impact the mechanical behavior in the investigated dispersity range Đ. For the PNC, we obtained the same -dependence and Đ-independence of the mechanical properties over a wide range of filler sizes and contents. This contribution proves that even simple MD models can reproduce the experimentally well researched effect of the molar mass. Hence, this work is an important step in understanding the complex structure–property relations of PNCs, which is essential to unlock their full potential.</p> <p>Contact:</p> <p>Maximilian Ries<br>Institute of Applied Mechanics<br>Friedrich-Alexander-Universität Erlangen-Nürnberg<br>Egerlandstr. 5<br>91058 Erlangen</p> <p>Software:</p> <p>All MD simulations were performed with LAMMPS [2,3], version: 23 Oct 2022 / 20220623</p> <p>Compiled with<br>Compiler: GNU C++ 11.2.0 with OpenMP not enabled<br>C++ standard: C++11</p> <p>Active compile time flags:<br>-DLAMMPS_GZIP<br>-DLAMMPS_SMALLBIG</p> <p>Installed packages:<br>CLASS2 DPD-BASIC EXTRA-DUMP INTEL KSPACE MANYBODY MC MISC MOLECULE MOLFILE MPIIO NETCDF OPT PERI</p> <p>Polymer and polymer composite samples generated with self-avoiding random-walk algorithm [4]</p> <p>Post-processing Matlab R2019b</p> <p>License:</p> <p>Creative Commons Attribution 4.0 International</p> <p>Context:</p> <p>Data set supplementing journal paper:</p> <p>[1] M. Ries, L. Laubert, P. Steinmann, & S. Pfaller, “Impact of the unimodal molar mass distribution on the mechanical behavior of polymer nanocomposites below the glass transition temperature: A generic, coarse-grained molecular dynamics study,” European Journal of Mechanics - A/Solids, vol. 107, p. 105 379, 2024.</p> <p>Content:</p> <p>structure of data set:</p> <p> -01_neat <br> containing the neat polymer simulations<br> -01_uniform<br> containing samples with uniform chain lengths<br> -02_distributed<br> containing samples with distributed chain lengths<br> -100-dist<br> samples with mean molar mass 100<br> -200-dist<br> samples with mean molar mass 200<br> -02_PNC<br> containing the polymer nanocomposite simulations<br> -01_uniform<br> containing samples with uniform chain lengths<br> -T_0.2<br> simulations at temperature 0.2<br> -T_0.3<br> simulations at temperature 0.3<br> -T_0.4<br> simulations at temperature 0.4<br> -02_distributed<br> containing samples with distributed chain lengths<br> -T_0.2<br> simulations at temperature 0.2<br> -T_0.3<br> simulations at temperature 0.3<br> -T_0.4<br> simulations at temperature 0.4<br> </p> <p>naming convention for simulation folders</p> <p> - neat polymer simulations<br> example: GTP_UT_num_chains-80_num_beads_per_chain-500-8<br> * num_chains: number of polymer chains<br> * num_beads_per_chain: molar mass (chain length)<br> * distribution: standard deviation of gauss distribution govering dispersity<br> * "trailing number": batch number of sample<br> <br> - polymer nanocomposite simulations<br> example: GTP_rF-5_nF-10_chainlen-5_7-T_0.2<br> * rF: nanofiller radius<br> * nF: number of nanofillers<br> * chainlen: molar mass (chain length)</p> <p> </p> <p>Each simulation directory contains:</p> <p> lammps input file (*.in) of the specific simulation</p> <p> data file (*.data) containing the initial sample configuration</p> <p> input.prm: input parameters of the specific simulation (read by the input file)</p> <p> meta.info: meta data of the specific simulation run</p> <p> LAMMPS_out:<br> simulation results (lammps thermo_out) in tabulated form, an overview of columns is given below</p> <p> thermo_out.Dat: raw output </p> <p> thermo_out_SG.Dat: smoothed output (Savitzky-Golay filter)</p> <p> thermo_out_STD.Dat: standard deviation of raw output</p> <p>Output quantities (columns of *.Dat files):<br>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].</p> <p> Step: time step </p> <p> Time: time </p> <p> TotEng: total energy </p> <p> PotEng: potential energy</p> <p> KinEng: kinetic energy </p> <p> E_pair: pair energy </p> <p> E_bond: bond energy </p> <p> E_angle: angle energy </p> <p> E_dihed: dihedral energy </p> <p> Temp: temperature</p> <p> Press: hydrostatic pressure</p> <p> Pxx: xx component of pressure tensor </p> <p> Pyy: yy component of pressure tensor </p> <p> Pzz: zz component of pressure tensor </p> <p> Pxy: xy component of pressure tensor</p> <p> Pxz: xz component of pressure tensor</p> <p> Pyz: yz component of pressure tensor</p> <p> Volume: volume of simulation box </p> <p> Lx: box length in x direction </p> <p> Ly: box length in y direction </p> <p> Lz: box length in z direction </p> <p> Density: density </p> <p> c_RG: radius of gyration scalar </p> <p> c_RG[1]: squared radius of gyration tensor (xx component) </p> <p> c_RG[2]: squared radius of gyration tensor (yy component) </p> <p> c_RG[3]: squared radius of gyration tensor (zz component) </p> <p> c_RG[4]: squared radius of gyration tensor (xy component) </p> <p> c_RG[5]: squared radius of gyration tensor (xz component) </p> <p> c_RG[6]: squared radius of gyration tensor (yz component) </p> <p> c_bondave[1]: bond energy averaged over all atoms </p> <p> c_bondave[2]: bond distance averaged over all atoms </p> <p> c_bondave[3]: squared bond distance averaged over all atoms </p> <p> c_angleave[1]: angle energy averaged over all atoms </p> <p> c_angleave[2]: angle averaged over all atoms degree</p> <p> c_angleave[3]: cosine of angle </p> <p> c_angleave[4]: squared cosine of angle </p> <p> c_MSD[1]: mean squared displacement x-direction </p> <p> c_MSD[2]: mean squared displacement y-direction </p> <p> c_MSD[3]: mean squared displacement z-direction </p> <p> c_MSD[4]: total mean squared displacement </p> <p> c_COM[1]: x coordinate of center of mass </p> <p> c_COM[2]: y coordinate of center of mass </p> <p> c_COM[3]: z coordinate of center of mass </p> <p> v_strain_xx: xx component of engineering strain tensor </p> <p> v_strain_yy: yy component of engineering strain tensor </p> <p> v_strain_zz: zz component of engineering strain tensor </p> <p> v_vMisesequivstress: von Mises equivalent stress </p> <p> v_Cauchy_xx: xx component of stress tensor </p> <p> v_Cauchy_yy: yy component of stress tensor</p> <p> v_Cauchy_zz: zz component of stress tensor</p> <p> v_Cauchy_xy: xy component of stress tensor </p> <p> v_Cauchy_xz: xz component of stress tensor </p> <p> v_Cauchy_yz: yz component of stress tensor </p> <p> v_strain_xy: xy component of engineering strain tensor </p> <p> v_strain_xz: xz component of engineering strain tensor </p> <p> v_strain_yz: yz component of engineering strain tensor </p> <p>References:</p> <p>[1] M. Ries, L. Laubert, P. Steinmann, & S. Pfaller, “Impact of the unimodal molar mass distribution on the mechanical behavior of polymer nanocomposites below the glass transition temperature: A generic, coarse-grained molecular dynamics study,” European Journal of Mechanics - A/Solids, vol. 107, p. 105 379, 2024.</p> <p>[2] S. Plimpton, “Fast parallel algorithms for short-range molecular dynamics,” Journal of computational physics, 1995, 117, 1-19.</p> <p>[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.</p> <p>[4] J. Roksvaag, M.Ries . “A fast self-avoiding random walk algorithm (SARW) for generic thermoplastic polymers and nanocomposites”, manuscript in preparation</p>
FIGURE 5 in More cautionary tales: family, generic and species synonymies of recently published taxa of ghost and mud shrimps (Decapoda: Axiidea and Gebiidea)
FIGURE 5. Paracalliax bollorei de Saint Laurent, 1979, SMF 44114, female holotype of Paracalliax stenophthalmus. A, front in dorsal vieW (A1/1–3: first to third antennular peduncular articles); B, pleomeres 5, 6, telson and left uropods in dorsal vieW. Scale bar = 1 mm.
FIGURE 3 in More cautionary tales: family, generic and species synonymies of recently published taxa of ghost and mud shrimps (Decapoda: Axiidea and Gebiidea)
FIGURE 3. Callianassa subterranea (Montagu, 1808). Relationship betWeen the lengths of male pleopods 1 and 2 and carapace length.
FIGURE 2 in More cautionary tales: family, generic and species synonymies of recently published taxa of ghost and mud shrimps (Decapoda: Axiidea and Gebiidea)
FIGURE 2. Callianassa subterranea (Montagu, 1808). A, NHMW 25024 (male, 2.4 mm), pleomeres 2 and 3, ventral aspect; B, NHMW 25641 (male, 4.3 mm), pleomeres 1–3, lateral aspect; C, NHMW 25023 (male, 10.3 mm), Plp2, ventral aspect. Scale bar = 1 mm.
FIGURE 4 in More cautionary tales: family, generic and species synonymies of recently published taxa of ghost and mud shrimps (Decapoda: Axiidea and Gebiidea)
FIGURE 4. Callianopsis mauritana (Sakai, Türkay, Beuck & FreiWald, 2015). A–E, holotype of Phaetoncalliax mauritana, F, paratype of P. mauritana, SMF 44111. A, carapace in lateral vieW; B, same in dorsal vieW; C, D, left pleopod, posterior vieW; E, same, anterior vieW; F, left and right pleopods 1 in situ, arroW points to pleuron 1 spine. Scale bar = 1 mm.
FIGURE 1 in More cautionary tales: family, generic and species synonymies of recently published taxa of ghost and mud shrimps (Decapoda: Axiidea and Gebiidea)
FIGURE 1. Guyanacaris caespitosa (Squires, 1979). SMF 31563, male (holotype of Neoaxius nicoyaensis). A, pleomeres 1–5 in ventral vieW; B, detail of pleopod 1 from frame in A; C, carapace in dorsal vieW (photo: S. M. Schnedl), arroWs point to spines behind cervical groove. Scale bar: A, C = 10 mm; B = 1 mm.
FIGURE 6 in More cautionary tales: family, generic and species synonymies of recently published taxa of ghost and mud shrimps (Decapoda: Axiidea and Gebiidea)
FIGURE 6. Upogebia balmaorum Ngoc-Ho, 1990. A, B, C, female holotype of Kuwaitupogebia nithyanandan, SMF 48913; D, male paratype of K. nithyanandan (3.4 mm); E, female paratype of K. nithyanandan (3.6 mm), SMF 48914; A, D, E, front, dorsal aspect; B, front, lateral aspect; C, uropods, arroW points to proXimal spine on eXopod. Scale bar = 1 mm.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.