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35 results for “Layered materials”
Organic Matter, Geochemical, Visible Spectrocolorimetric Properties, Radiocesium Properties, and Grain Size of Potential Source Material, Target Sediment Core Layers and Laboratory Mixtures for Conducting Sediment Fingerprinting Approaches in the Mano Dam Reservoir (Hayama Lake) Catchment, Fukushima Prefecture, Japan
<p>The current dataset was compiled to study sediment fingerprintings practices, i.e tracer selection and contribution modelling. Organic matter, elemental geochemistry, visible difuse spectrocolorimetric properties, radiocesium properties, and grain size were analysed were analysed in potential source material that may supply sediment to coastal rivers, here the upper part of the Mano river, draining the main Fukushima radioactive pollution plume (Japan). Four potential soil source materials (<em>n</em> = 68) were considered: undecontaminated cropland (<em>n</em> = 24), as non-decontaminated soil before the application of local decontamination policies, remediated cropland (<em>n</em> = 10), as decontaminated soil after the application of local decontamination policies, forest soils (n = 24) and subsurface material originating from channel bank collapse or landslides (<em>n</em> = 10; referred to as subsoil). A sediment core was collected in the Mano Dam lake (Hayama lake) on the 6th June 2021 and was sectionned into 1-cm layers (<em>n</em> = 38). Laboratory mixtures (<em>n</em> = 27) were made to assess different contribution levels from the sources.</p> <p>The current dataset comprises four .csv files including data and metadata information and their respective descriptions of variables. The data set is composed of soil samples, sediment core layer and laboratory mixtures. Laboratory mixtures were prepared to provide a dataset to calibrate/validate un-mixing models implemented to address this research question and analysed in the same conditions and using the same equipment as the source/target material.</p> <p>Recommended encoding format: <strong>latin1</strong></p>
Global restoration opportunities in tropical rainforest landscapes - Supplementary Materials - Spatial Data Layers
<p><strong>Global restoration opportunities in tropical rainforest landscapes</strong></p> <p><strong>Sci Adv 5 (7), eaav3223</strong></p> <p><strong>DOI: 10.1126/sciadv.aav3223</strong></p> <p><strong><a href="https://advances.sciencemag.org/content/5/7/eaav3223">https://advances.sciencemag.org/content/5/7/eaav3223</a></strong></p> <p><strong>Supplementary Materials</strong></p> <p><strong><a href="https://advances.sciencemag.org/content/suppl/2019/07/01/5.7.eaav3223.DC1">https://advances.sciencemag.org/content/suppl/2019/07/01/5.7.eaav3223.DC1</a></strong></p> <p><strong>Spatial Data layers:</strong></p> <p><strong><a href="https://doi.org/10.5281/zenodo.3233495">https://doi.org/10.5281/zenodo.3233495</a></strong></p> <p><strong>_OutR10:</strong></p> <p><strong>r_10.img → Global restoration opportunity score (ROS)</strong></p> <p><strong>r_10_sc.img → Global restoration opportunity score (ROS) – rescaled 0-1</strong></p> <p><strong>r_10_nt_sc.img → Neo Tropic restoration opportunity score (ROS) – rescaled 0-1</strong></p> <p><strong>r_10_aa_sc.img → Australiasia restoration opportunity score (ROS) – rescaled 0-1</strong></p> <p><strong>r_10_at_sc.img → Afro Tropic restoration opportunity score (ROS) – rescaled 0-1</strong></p> <p><strong>r_10_im_sc.img → Indo Malay restoration opportunity score (ROS) – rescaled 0-1</strong></p> <p><strong>r_10_nt_sc.img → Neo Tropic restoration opportunity score (ROS) – rescaled 0-1</strong></p> <p> </p> <p><strong>_OutBasics:</strong></p> <p><strong>r_1.img → Study Area</strong></p> <p><strong>r_2.img → Restorable Area</strong></p> <p><strong>r_3.img → Restoration Benefits</strong></p> <p><strong>r_4.img → Restoration feasibility</strong></p> <p><br> <strong>_OutCountry:</strong></p> <p><strong>r_10_XXX_sc.tif → restoration opportunity score (ROS) for country XXX – rescaled 0-1</strong></p> <p><br> <strong>_OutHotspots:</strong></p> <p><strong>r_10_hotspot_XXX_hotspot_area_sc.tif → restoration opportunity score (ROS) for conservation hotspot area XXX – rescaled 0-1</strong></p> <p><strong>r_10_hotspots_upper60.img → Areas with restoration opportunity score (ROS) above 0.6 in conservation hotspots</strong></p> <p><br> <strong>_OutKBA:</strong></p> <p><strong>r_10_XXX_sc.tif → restoration opportunity score (ROS) for Key Biodiversity Area XXX – rescaled 0-1</strong></p> <p><strong>r_10_kba_upper60.img → Areas with restoration opportunity score (ROS) above 0.6 in Key Biodiversity Areas</strong></p> <p><br> <strong>_OutAichi:</strong></p> <p><strong>r_10_aichi_XXX.tif → Top 15% area of with highest restoration opportunity score (ROS) in country XXX</strong></p> <p><strong>r_10_aichi.img → Top 15% area of with highest restoration opportunity score (ROS) global</strong></p> <p><br> <strong>_OutBonn:</strong></p> <p><strong>r_10_XXX_Bonn.img → Area with highest restoration opportunity score (ROS) in country XXX according to their Bonn Challenge commitments</strong></p> <p> </p> <p><strong>_OutParis:</strong></p> <p><strong>r_10_at_paris.img → Area with highest restoration opportunity score (ROS) in Afro Tropic Nationally Determined Contributions to the Paris Climate Agreement</strong></p> <p><strong>r_10_im_paris.img → Area with highest restoration opportunity score (ROS) in Indo Malay Nationally Determined Contributions to the Paris Climate Agreement</strong></p> <p><strong>r_10_nt_paris.img → Area with highest restoration opportunity score (ROS) in Neo Tropic Nationally Determined Contributions to the Paris Climate Agreement</strong></p> <p><br> <strong>_OutTEOW:</strong></p> <p><strong>r_10_ECOREGION_XXX_sc.tif → restoration opportunity score (ROS) for Ecoregion XXX – rescaled 0-1</strong></p> <p><strong>r_10_ECOREGION_upper60.img → Areas with restoration opportunity score (ROS) above 0.6 in Ecoregions</strong></p> <p> </p> <p><strong>_OutAll</strong></p> <p><strong>alltargets.img → Area with highest restoration opportunity score (ROS) according to all targets (excluded from the paper)</strong></p> <p> </p>
Simulated shielding performance of 1024 five-layer permutations of four satellite and radiation shielding materials against trapped particles on GTO
<p>The 5Layer.csv file contains ionizing dose results of simulating the shielding performance of all 1024 five-layer permutations of four satellite and radiation shielding materials against trapped particles on GTO.<br> The materials are the aluminium alloy 7075 (Al_7075), polyethylene (G4_POLYETHYLENE), tungsten (G4_W) and the circuit board composite material FR4 (FR4).<br> The particle spectra used for this simulation are provided in the files AE9500keV.mac and AP910MeV.mac.<br> The simulated geometry is provided in the file 5Layer.gdml.</p> <p>The particle spectra were generated with the AE9/AP9 models on SPENVIS, with electron energies starting at 500 keV and proton energies starting at 10 MeV.<br> The simulation was performed with GRAS / Geant4 with the FTFP_BERT physics model using 1.4e+11 electrons and 3.1e+09 protons directed against slabs of shielding materials of 1.5 g/cm2 total depth with each of the five layers being 0.3 g/cm2 in depth.<br> The ionizing dose is recorded in 0.5mm thick silicon plates behind the shielding plates.<br> <br> Column A: ID of the material combination<br> Column B: Name of the top layer material.<br> Column C: Name of the second layer material.<br> Column D: Name of the third layer material.<br> Column E: Name of the fourth layer material.<br> Column F: Name of the bottom layer material.<br> Column G: Ionizing dose due to electrons in units of kRad per month.<br> Column H: Absolute statistical error in the electron dose in kRad per month.<br> Column I: Ionizing dose due to protons in kRad per month.<br> Column J: Absolute statistical error in the proton dose in kRad per month. <br> Column K: Total ionizing dose from electrons and protons in kRad per month.<br> Column L: Absolute statistical error in the total ionizing dose in kRad per month. <br> Column M: Relative statistical error of the total ionizing dose in per cent.<br> Column N: Rank of the material combination sorted from lowest total ionizing dose to highest.<br> Column O: Rank of the material combination sorted from lowest electron dose to highest.<br> Column P: Rank of the material combination sorted from lowest proton dose to highest.</p> <p>All dose values are rounded according to their uncertainty.</p>
Simulated shielding performance of 1296 four-layer permutations of six common satellite and radiation shielding materials against trapped particles on GTO
<p>The 4Layer.csv file contains ionizing dose results of simulating the shielding performance of all 1296 four-layer permutations of six common satellite and radiation shielding materials against trapped particles on GTO.<br> The materials are the aluminium alloy 7075 (Al_7075), polyethylene (G4_POLYETHYLENE), kevlar (G4_KEVLAR), tungsten (G4_W), stainless steel (G4_STAINLESS_STEEL) and the circuit board composite material FR4 (FR4).<br> The particle spectra used for this simulation are provided in the files AE9500keV.mac and AP910MeV.mac.<br> The simulated geometry is provided in the file 4Layer.gdml.</p> <p>The particle spectra were generated with the AE9/AP9 models on SPENVIS, with electron energies starting at 500 keV and proton energies starting at 10 MeV.<br> The simulation was performed with GRAS / Geant4 with the FTFP_BERT physics model using 6.6e+10 electrons and 3.8e+09 protons directed against slabs of shielding materials of 1.5 g/cm2 total depth with each of the four layers being 0.375 g/cm2 in depth.<br> The ionizing dose is recorded in 0.5mm thick silicon plates behind the shielding plates.<br> <br> Column A: ID of the material combination<br> Column B: Name of the top layer material.<br> Column C: Name of the second layer material.<br> Column D: Name of the third layer material.<br> Column E: Name of the bottom layer material.<br> Column F: Ionizing dose due to electrons in units of kRad per month.<br> Column G: Absolute statistical error in the electron dose in kRad per month.<br> Column H: Ionizing dose due to protons in kRad per month.<br> Column I: Absolute statistical error in the proton dose in kRad per month. <br> Column J: Total ionizing dose from electrons and protons in kRad per month.<br> Column K: Absolute statistical error in the total ionizing dose in kRad per month. <br> Column L: Relative statistical error of the total ionizing dose in per cent.<br> Column M: Rank of the material combination sorted from lowest total ionizing dose to highest.<br> Column N: Rank of the material combination sorted from lowest electron dose to highest.<br> Column O: Rank of the material combination sorted from lowest proton dose to highest.</p> <p>All dose values are rounded according to their uncertainty.</p>
Supplementary Material: A Large-Eddy Simulation Study of Vertical Axis Wind Turbine Wakes in the Atmospheric Boundary Layer
<p>Supplementary material for <em>Energies</em> <strong>2016</strong>, <em>9</em>, 366; doi:10.3390/en9050366:</p> <p><strong>Video S1:</strong> Normalized instantaneous streamwise velocity field both on a vertical plane (<em>x</em>-<em>z</em>) going through the center of the turbine and on a horizontal plane at the equator height of the turbine (Note: the physical time corresponding to this video is 1 minute and 17 seconds, and the size of the blades is magnified for illustration purposes).</p> <p><strong>Video S2:</strong> Normalized instantaneous streamwise velocity field on a horizontal plane at the equator height of the turbine for two cases: when the turbine starts to operate (top) and when the flow has reached statistically steady condition (bottom) (Note: the physical time corresponding to both videos is 1 minute and 17 seconds, and the size of the blades is magnified for illustration purposes).</p>
Dataset of the publication: Liquid‐Phase Fabrication of Janus 2D Materials: Defect‐Rich MoS2 Ultrathin Layers Asymmetrically Decorated with Au Nanoparticles. Small 2024, 2406599
<p>Dataset of the publication: Liquid‐Phase Fabrication of Janus 2D Materials: Defect‐Rich MoS2 Ultrathin Layers Asymmetrically Decorated with Au Nanoparticles</p> <p>N. V. Vassilyeva, A. Forment-Aliaga, E. Coronado, <em>Small</em> <strong>2024</strong>, e2406599.</p> <p>doi: 10.1002/smll.202406599</p>
The Data Set for the Publication "Laboratory Testing of Small Scale Solar Facade Module with Phase Change Material and Adjustable Insulation Layer"
<p>In the scope of the ambitious EU goals of carbon neutrality in 2050, building energy efficiency is one of the crucial segments. To ensure a faster energy transition process, innovations are needed at various built environment-related sectors - starting from building components up to urban level energy management advancements.</p> <p>Phase change material (PCM) enriched building components allow to shift the existing paradigm - to make a switch from the static building components to dynamic ones able to take an active part in building energy balance by ensuring energy storage in the building thermal envelope.</p> <p>The data set presented here supports the paper "Laboratory Testing of Small Scale Solar Facade Module with Phase Change Material and Adjustable Insulation Layer". The design of the façade module, experimental setup, used equipment, the plan of the experiment, and obtained results are described in the paper. The provided data set provides heat-flux and average temperature (in PCM) measurements.</p>
Figure 4: Spectro°uorimetric spectra of TiO2/CdS composites samples with a di®erent mass proportion-PREPARATION AND CHARACTERIZATION OF TIO2/CDS LAYERS AS POTENTIAL PHOTOELECTROCATALYTIC MATERIALS
<p>Fig. 4 illustrates the fluorescence emission spectra of TiO2/CdS nanostructured ¯lm at the exciting<br> wavelength of 340 nm. The curves for TC 1, TC 2, TC 3 and TC 4 exhibited<br> the clear photoemission peaks at about 375 nm, and compared with emission of<br> bulk CdS (520 nm), 145 nm of blue shift was observed. These features indicate<br> the quantum-con¯ned e®ect of the TiO2/CdS nanocomposite ¯lms [25].</p>
PREPARATION AND CHARACTERIZATION OF TIO2/CDS LAYERS AS POTENTIAL PHOTOELECTROCATALYTIC MATERIALS-Figure 2: The FT/IR microscopy images of the TiO2/CdS composites
<p>The microstructural properties of the deposited TiO2/CdS layers depend<br> on the mass proportions of TiO2:CdS. The proportion of CdS phase is di-<br> rect proportional with the CdS powder used in the preparation process. The<br> FT/IR microscopy images of the TiO2/CdS composites upon annealing at high<br> temperatures, are shown in Fig.2<br> The micrograph shows agglomerates with irregular morphology and size<br> ranging from few micrometers down to hundreds of nanometer.</p>
Figure 1: X-ray di®raction pattern for TiO2/CdS composites samples-PREPARATION AND CHARACTERIZATION OF TIO2/CDS LAYERS AS POTENTIAL PHOTOELECTROCATALYTIC MATERIALS
<p>Fig. 1 shows the X-ray di®raction pattern for TiO2/CdS<br> composites (sample TC 1, TC 2, TC 3 and TC 4). The di®raction pattern of<br> the TiO2/CdS composites exhibits the di®raction peaks owning to CdS phase<br> (hexagonal and cubic). TiO2 (rutile and anatase) phases were also detected.</p>
Figure 3: Absorption spectra of TiO2/CdS composites samples with a di®erent mass proportion-PREPARATION AND CHARACTERIZATION OF TIO2/CDS LAYERS AS POTENTIAL PHOTOELECTROCATALYTIC MATERIALS
<p>Optical properties of TiO2/CdS semi-<br> conductor composites have been investigated using optical absorption and pho-<br> toluminescence spectroscopy. UV-VIS absorption spectra of the as-prepared<br> photocatalysts were taken on a JASCO V-550 spectrometer. The °uorescence<br> spectra were obtained using an ABL&Jasco V 6500 spectro°uorimeter with<br> xenon lamp. The optical studies of the TiO2/CdS composites were performed<br> using the absorption spectra observed in the wavelength range 200-900 nm.<br> Fig. 3 shows the UV-Vis spectra of TiO2/CdS samples.</p>
Рис. 5. Морские двустворчатые моллюски иЗ раскопов памЯтника Константиновка-1: A–D, G–K – Anadara talmiensis Kalishevich, 1976 (A, B – раскоп 3, постройка № 40, пласт 6, квадрат Ж.3-10, длина раковины 49.3 мм; C, D – раскоп 3, постройка № 40, квадрат Ж.3-10, длина фрагмента 40.8 мм; G, H – раскоп 3, постройка № 40, квадрат Ж.3-10, длина фрагмента 41.6 мм; I–K – раскоп 1, пласт 1, квадрат Б2, длина фрагмента 35.8 мм; E, F – Crenomytilus grayanus (Dunker, 1853), подъемный материал, длина фрагмента 100.7 мм. Fig. 5. Marine bivalves from the Konstantinovka-1 site excavations: A–D, G–K – Anadara talmiensis Kalishevich, 1976 (A, B – excavation 3, construction N 40, layer 6, square Ж.3-10, shell length 49.3 mm; C, D – excavation 3, construction N 40, square Ж.3-10, fragment length 40.8 mm; G, H – excavation 3, construction N 40, square Ж.3-10, fragment length 41.6 mm; I–K – excavation 1, formation 1, square B2, fragment length 35.8 mm); E, F – Crenomytilus grayanus (Dunker, 1853), lifting material, fragment length 100.7 mm. in Mollusks from the archaeological site Konstantinovka-1 in Primorye (Russian Far East)
Рис. 5. Морские двустворчатые моллюски иЗ раскопов памЯтника Константиновка-1: A–D, G–K – Anadara talmiensis Kalishevich, 1976 (A, B – раскоп 3, постройка № 40, пласт 6, квадрат Ж.3-10, длина раковины 49.3 мм; C, D – раскоп 3, постройка № 40, квадрат Ж.3-10, длина фрагмента 40.8 мм; G, H – раскоп 3, постройка № 40, квадрат Ж.3-10, длина фрагмента 41.6 мм; I–K – раскоп 1, пласт 1, квадрат Б2, длина фрагмента 35.8 мм; E, F – Crenomytilus grayanus (Dunker, 1853), подъемный материал, длина фрагмента 100.7 мм. Fig. 5. Marine bivalves from the Konstantinovka-1 site excavations: A–D, G–K – Anadara talmiensis Kalishevich, 1976 (A, B – excavation 3, construction N 40, layer 6, square Ж.3-10, shell length 49.3 mm; C, D – excavation 3, construction N 40, square Ж.3-10, fragment length 40.8 mm; G, H – excavation 3, construction N 40, square Ж.3-10, fragment length 41.6 mm; I–K – excavation 1, formation 1, square B2, fragment length 35.8 mm); E, F – Crenomytilus grayanus (Dunker, 1853), lifting material, fragment length 100.7 mm.
Text-fig. 7. Enamel microstructure in the molars of (a) Allosorex stenodus (KOE-4196 / Z 28207 – OF 6512) and (b) Blarina brevicauda (KOE-1435). SEM photos showing transverse sections of the paralophid in a lower molar. The schmelzmuster of Allosorex is one-layered and formed exclusively from radial enamel (RE), whereas the schmelzmuster of Blarina is two-layered, with an inner enamel of laterally inclined radial enamel with distinct interrow sheets (REIS). The radial enamel of the outer layer is heavily pigmented and therefore poorly etched. The pigmentation does not affect the schmelzmuster. in Allosorex Stenodus Fejfar, 1966 (Eulipotyphla, Soricidae): Re-Description Of Type Material And Re-Interpretation Of Its Fossil Record
Text-fig. 7. Enamel microstructure in the molars of (a) Allosorex stenodus (KOE-4196 / Z 28207 – OF 6512) and (b) Blarina brevicauda (KOE-1435). SEM photos showing transverse sections of the paralophid in a lower molar. The schmelzmuster of Allosorex is one-layered and formed exclusively from radial enamel (RE), whereas the schmelzmuster of Blarina is two-layered, with an inner enamel of laterally inclined radial enamel with distinct interrow sheets (REIS). The radial enamel of the outer layer is heavily pigmented and therefore poorly etched. The pigmentation does not affect the schmelzmuster.
Supplementary material for the paper "Paleoenvironment Implications of Layered Ejecta Craters in Chryse Planitia, Mars"
<p>The compressed file contains the spatial crater count (scc) files for crater dating, results of randomness analysis tests and derived model ages with different chronology systems.</p> <p>Table S1 lists all the identified layered ejecta craters in the Chryse Planitia, with a 5-m-per-pixel high resolution context camera (CTX) mosaic as a base map. </p> <p>Table S2 lists all the dating results for selected layered ejecta craters in the Chryse Planitia.</p>
Supporting Data for: Resolving high potential structural deterioration in Ni-rich layered cathode materials for lithium-ion batteries operando
<p>The following file contains supporting data for "Resolving high potential structural deterioration in Ni-rich layered cathode materials for lithium-ion batteries operando" manuscript.</p>
FIGURE. View of medullary hyphae in R. subcalcarata covered by a thin layer of secreted material, probably glycoproteins. The presence of small, elongated and electron-dense nodules is also observed. Scale = 12 µm. in The genus Ramalina Acharius (Ascomycota, Lecanoromycetes, Ramalinaceae) in northern South America
FIGURE. View of medullary hyphae in R. subcalcarata covered by a thin layer of secreted material, probably glycoproteins. The presence of small, elongated and electron-dense nodules is also observed. Scale = 12 µm.
Simulated shielding performance of 1728 three-layer permutations of 12 common satellite and radiation shielding materials against trapped particles on GTO
<p>The 3Layer.csv file contains ionizing dose results of simulating the shielding performance of all 1728 three-layer permutations of twelve common satellite and radiation shielding materials against trapped particles on GTO.<br> The materials are pure aluminium (G4_Al), the aluminium alloy 7075 (Al_7075), polyethylene (G4_POLYETHYLENE), kevlar (G4_KEVLAR), lead (G4_Pb), tungsten (G4_W), stainless steel (G4_STAINLESS_STEEL), pure carbon fibre (CarbonFibre), the circuit board composite material FR4 (FR4), tantalum (G4_Ta), Teflon (G4_TEFLON) and the titanium alloy 6Al-4V (Ti_6AL_4V).<br> The particle spectra used for this simulation are provided in the files AE9500keV.mac and AP910MeV.mac.<br> The simulated geometry is provided in the file 3Layer.gdml.</p> <p>The particle spectra were generated with the AE9/AP9 models on SPENVIS, with electron energies starting at 500 keV and proton energies starting at 10 MeV.<br> The simulation was performed with GRAS / Geant4 with the FTFP_BERT physics model using 3.9e+10 electrons and 4.7e+09 protons directed against slabs of shielding materials of 1.5 g/cm2 total depth with each of the three layers being 0.5 g/cm2 in depth.<br> The ionizing dose is recorded in 0.5mm thick silicon plates behind the shielding plates.<br> <br> Column A: ID of the material combination<br> Column B: Name of the top layer material.<br> Column C: Name of the middle layer material.<br> Column D: Name of the bottom layer material.<br> Column E: Ionizing dose due to electrons in units of kRad per month.<br> Column F: Absolute statistical error in the electron dose in kRad per month.<br> Column G: ionizing dose due to protons in kRad per month.<br> Column H: Absolute statistical error in the proton dose in kRad per month. <br> Column I: Total ionizing dose from electrons and protons in kRad per month.<br> Column J: Absolute statistical error in the total ionizing dose in kRad per month. <br> Column K: Relative statistical error of the total ionizing dose in per cent.<br> Column L: Rank of the material combination sorted from lowest total ionizing dose to highest.<br> Column M: Rank of the material combination sorted from lowest electron dose to highest.<br> Column N: Rank of the material combination sorted from lowest proton dose to highest.</p> <p>All dose values are rounded according to their uncertainty.</p>
MATERIALS OF ARCHAEOLOGICAL RESEARCH OF THE ARCHAEOLOGICAL HERITAGE OBJECT CULTURAL LAYER OF VORONEZH ON THE TERRITORY OF THE LAND PLOT AT 1, KLUBNAYA STREET AND 30D, 20-LETIYA OKTYABRYA STREET
<p>Archaeological research on the land plot at the address: Voronezh, 1, Klubnaya Street, and 30d, 20-letiya Oktyabrya Street, was carried out as part of the implementation of the section of project documentation to ensure the safety of the identified cultural heritage site "Cultural layer of the city of Voronezh". As a result of the work, additional information was obtained on the history of the coastal part of the city in the XIX-th-XX-th centuries.</p>
Effects of hot-wet storage aging, CNT-integration and damping layer interposition on static and fatigue interlaminar shear response of a UD Graphite/Epoxy material system
<p>The present work aims at experimental quantification of the effect of hot-wet storage aging on the static and<br> fatigue interlaminar shear response of three UD Graphite-Epoxy based material systems: a control laminate, a<br> CNT-treated laminate and a lamination including an embedded damping veil. In this context, specimens have<br> been fabricated and tested for determination of the interlaminar shear strength (ILSS) according to the relevant<br> ASTM standard, and the effects of the above mentioned constituents on the response of non-aged (RT) and aged<br> (HW) specimens have been investigated. The experimental data, presented in batch mode, indicated that aging<br> leads to severe degradation of the interlaminar shear strength and relevant fatigue endurance of all material<br> systems, whereas the CNT-treated laminate appeared to be the most sensitive configuration. In the case of nonaged specimens, CNT-treatment led to larger failure strains and a clear bilinear response, while all three material<br> systems exhibited similar values of interlaminar shear strength.</p>
Supplementary material 4 from: Beltrán LC, Aguilar-Dorantes KM, Howe HF (2020) Effects of a recalcitrant understory fern layer in an enclosed tropical restoration experiment. NeoBiota 59: 99-118. https://doi.org/10.3897/neobiota.59.51906
Fern data from quadrat study
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.