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6,175 results for “Composite”

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zenodo32/100

FIGURE 4 in Composition of the genus Loricella (Mollusca: Polyplacophora: Loricidae) and the description of two new species

FIGURE 4. Loricella profundior, New Zealand, southern Kermadec Ridge, (NMNZ M.319774), BL 18.0 mm. A. Dorsal scales, marginal spicules and ventral scales on edge of caudal incision; B. Part of radula; C. Dorsal scales and bristles; D. Central, first lateral and major lateral teeth of radula.

opennotspecifiedJun 2021View details →
zenodo32/100

FIGURE 3 in Composition of the genus Loricella (Mollusca: Polyplacophora: Loricidae) and the description of two new species

FIGURE 3. Loricella profundior, New Zealand, southern Kermadec Ridge, (NMNZ M.319774), BL 18.0 mm. A. Dorsal and ventral scales; B, D. Dorsal scales; C. Dorsal scales and marginal spicules.

opennotspecifiedJun 2021View details →
zenodo32/100

FIGURE 5 in Composition of the genus Loricella (Mollusca: Polyplacophora: Loricidae) and the description of two new species

FIGURE 5. Loricella profundior, Tonga Islands, (MNHN-IM-2013-59983), BL 11.0 mm. A. Valve I, dorsal view; B. Valve V, dorsal view; C. Valve VIII, dorsal view; D. Valve IV, ventral view; E. Valve V, detail of tegmentum in central and lateral areas; F. Valve V, rostral view; G. Valve VIII, lateral view.

opennotspecifiedJun 2021View details →
zenodo32/100

FIGURE 2 in Composition of the genus Loricella (Mollusca: Polyplacophora: Loricidae) and the description of two new species

FIGURE 2. Loricella profundior, New Zealand, southern Kermadec Ridge, (NMNZ M.319774), BL 18.0 mm. A. Valve VII, dorsal view; B. Valve VIII, dorsal view; C. Valve VII, rostral view; D. Valve VII, detail of tegmentum in central and lateral areas; E. Valve VIII, lateral view.

opennotspecifiedJun 2021View details →
zenodo32/100

FIGURE 1 in Composition of the genus Loricella (Mollusca: Polyplacophora: Loricidae) and the description of two new species

FIGURE 1. Complete specimens of selected species of the genus Loricella. A, B. L. neoguinensis n. sp. Papua New Guinea, holotype (MNHN-IM-2013-45614), BL 16.0 mm; C, D. L. profundior, Tonga Islands, (MNHN-IM-2013-59980), BL 11.5 mm; E-G. L. vanbellei, New Caledonia, (MNHN-IM-2013-69525) BL 16.0 mm; A, C, G. Dorsal view; B, E. Ventral view; D, F. Lateral view. m.f.—mantle fold.

opennotspecifiedJun 2021View details →
zenodo32/100

FIGURE 6 in Composition of the genus Loricella (Mollusca: Polyplacophora: Loricidae) and the description of two new species

FIGURE 6. Loricella profundior, Tonga Islands, (MNHN-IM-2013-59983), BL 11.0 mm. A. Dorsal and ventral scales; B. Dorsal scales and marginal spicules; C. Dorsal scales; D. Ventral scales.

opennotspecifiedJun 2021View details →
zenodo32/100

DINEOF reconstructed MODIS-terra 8-day composite of surface chlorophyll data

<p>Sea surface chlorophyll data&nbsp;are the 8&ndash;day composite of MODIS&ndash;terra chlorophyll products from 2001 to 2019. The L3 data with a 4 km spatial resolution were extracted from 42&deg;N-44.5&deg;N and 65.5&deg;W-71&deg;W and interpolated spatially onto a 0.025&deg;*0.025&deg;&nbsp;grid.&nbsp;Cloud&ndash;free chlorophyll data were reconstructed using the Data INterpolation Empirical Orthogonal Function (DINEOF) method, which has been applied to fill the spatial gaps of satellite products without lowering their qualities. The original 8&ndash;day composite of MODIS&ndash;terra chlorophyll products are available at&nbsp;https://oceancolor.gsfc.nasa.gov.&nbsp;Only those spatial points without data due to clouds or&nbsp;sun glint&nbsp;are constructed using the DINEOF.&nbsp;chl_GOM_origin_and_DINEOF.mat is the surface chlorophyll data.&nbsp;lon_GOM_2D.mat and&nbsp;lat_GOM_2D.mat are&nbsp;longitude and latitude information. The data can be loaded directly using MATLAB (.mat file).</p>

opencc-by-4.0Jul 2021View details →
dryad32/100

Behavioral and chemical composition data for: Maternal and personal information mediates the use of social cues about predation risk

<p></p><p>Organisms can gain information about predation risks from their parents, their own personal experience, and their conspecifics and adjust their behavior to alleviate these risks. These different sources of information can, however, provide conflicting information due to spatial and temporal variation of the environment. This raises the question of how these cues are integrated to produce adaptive antipredator behavior. We investigated how common lizards (Zootoca vivipara) adjust the use of conspecific cues about predation risk depending on whether the information is maternally or personally acquired. We experimentally manipulated the presence of predator scent in gestating mothers and their offspring in a full-crossed design. We then tested the consequences for social information use by monitoring offspring social response to conspecifics previously exposed to predator cues or not. Lizards were more attracted to the scent of conspecifics having experienced predation cues when they had themselves no personal information about predation risk. In contrast, they were more repulsed by conspecific scent when they had personally obtained information about predation risk. However, the addition of maternal information about predation risk canceled out this interactive effect between personal and social information: lizards were slightly more attracted to conspecific scent when these two sources of information about predation risk were in agreement. A chemical analysis of lizard scent revealed that exposure to predator cues modified the chemical composition of lizard scents, a change that might underlie lizards' use of social information. Our results highlight the importance of considering multiple sources of information while studying antipredator defenses.</p><p></p>

opencc-zeroJul 2021View details →
dryad32/100

Data from: Similar hybrid composition among different age and sex classes in the Myrtle–Audubon's warbler hybrid zone

Hybrid zones provide a key natural context within which to study the barriers between incipient species. In some avian hybrid zones, there is indirect evidence of selection against hybrid offspring, yet the source of that selection is often unclear. We examined the frequency distribution of hybrids between Myrtle Warblers (Setophaga coronata coronata) and Audubon's Warblers (S. c. auduboni), using data to quantify—for the first time at a genomic scale—the composition of hybrids in this hybrid zone. We sampled birds during the breeding season and during fall migration and compared the frequencies of hybrids of different sex and age classes. Specifically, we tested for evidence of early-generation hybrids being significantly under- or over-represented in any of these classes, as would be expected if hybrids have lower or higher fitness than non-hybrids. We found that the genomic composition of birds in the hybrid zone spans the full ancestry spectrum. Across all our sampling periods, we found an excess of birds that had more Audubon's ancestry, with a stronger bias toward Audubon's ancestry in fall migrants than in breeding birds, consistent with asymmetric introgression. Notably, we did not find any differences in hybrid frequencies between juvenile and adult age classes or between males and females. Therefore, our results do not support large differences in viability between male and female hybrids or between different age classes of hybrids.

opencc-zeroDec 2017View details →
zenodo32/100

Supplemental videos for "Composition and decomposition of visuomotor maps during manual tracking", by Bernier et al.,

<p>The videos depict representative trials&nbsp;in Baseline, as well as for the first (1) and last (50) trials of each mapping.</p>

opencc-by-4.0Jan 2021View details →
dryad32/100

Cell wall thickness and composition are involved in photosynthetic limitation

<p><span><span><span><span><span><span><span><span><span><span><span>The key role of cell walls in setting mesophyll conductance to CO<sub>2</sub> (<i>g</i><sub>m</sub>) and, consequently, photosynthesis, is reviewed. First, the theoretical properties of cell walls that can affect <i>g</i><sub>m</sub> are presented. Then, we focus on cell wall thickness (<i>T</i><sub>cw</sub>) reviewing empirical evidence showing that <i>T</i><sub>cw</sub> varies strongly among species and phylogenetic groups in a way that correlates with <i>g</i><sub>m</sub> and photosynthesis i.e. the thicker the mesophyll cell walls, the lower <i>g</i><sub>m</sub> and photosynthesis. Potential interplays of <i>g</i><sub>m</sub>, <i>T</i><sub>cw</sub>, dehydration tolerance and hydraulic properties of leaves are also discussed. Dynamic variations of <i>T</i><sub>cw</sub> in response to the environment and their implications in the regulation of photosynthesis are discussed, and recent evidence suggesting an influence of cell wall composition on <i>g</i><sub>m</sub> are presented. We then propose a hypothetical mechanism for the influence of cell walls on photosynthesis, combining the effects of thickness and composition, particularly pectins. Finally, we discuss the prospects for using biotechnology for enhancing photosynthesis by means of altering cell wall-related genes.</span></span></span></span></span></span></span></span></span></span></span></p>

opencc-zeroMar 2022View details →
dryad32/100

Growth-defense tradeoffs shape the genetic composition of aspen forests

<p><span><span><span><span><span><span><span><span><span><span><span>All organisms experience fundamental conflicts between divergent metabolic processes. In plants, a pivotal conflict occurs between allocation to growth, which accelerates resource acquisition, and to defense, which protects existing tissue against herbivory. Tradeoffs between growth and defense traits are not universally observed, and a fundamental prediction of plant evolutionary ecology is that context-dependence of these tradeoffs contributes to the maintenance of intraspecific variation in defense. This prediction has rarely been tested, however, and the evolutionary consequences of growth-defense tradeoffs in different environments are poorly understood. Here we show that intraspecific trait tradeoffs interact with competitive environment to drive natural selection of tree genotypes corresponding to their growth-defense phenotypes. Our results show for the first time that a functional trait tradeoff, when coupled with environmental variation, causes real-time divergence in the genetic architecture of forest stands. Specifically, competitive selection for faster growth resulted in dominance by fast-growing tree genotypes that were poorly defended against natural enemies. This outcome is a signature example of eco-evolutionary dynamics: competitive interactions affected microevolutionary trajectories on a timescale relevant to subsequent ecological interactions. Eco-evolutionary drivers of tree growth and defense are thus critical to stand-level trait variation, which structures communities and ecosystems over expansive spatiotemporal scales.</span></span></span></span></span></span></span></span></span></span></span></p>

opencc-zeroAug 2021View details →
zenodo32/100

Figure 11 in Morphology and composition of the internal axis in two morphologically contrasting deep-water sea pens (Cnidaria: Octocorallia)

Figure 11. Axis composition in the sea pens Umbellula encrinus and Anthoptilum grandiflorum: average proportion of axis components (a–b), carbonate proportion in relation to distance from base (c–d), and carbonate proportion at base and tip for each colony (e–f). The vertical arrows in (c) and (d) indicate maximum peduncle length among the studied colonies.

opennotspecifiedMar 2018View details →
zenodo32/100

Figure 10 in Morphology and composition of the internal axis in two morphologically contrasting deep-water sea pens (Cnidaria: Octocorallia)

Figure 10. Anthoptilum grandiflorum: whole colony and its extracted axis before being sectioned, showing position of cross sections (arrows) along the axis, and in relation to the peduncle (p).

opennotspecifiedMar 2018View details →
zenodo32/100

Figure 9 in Morphology and composition of the internal axis in two morphologically contrasting deep-water sea pens (Cnidaria: Octocorallia)

Figure 9. Cross sections of the internal axis of eight Anthoptilum grandiflorum colonies along a gradient (every 5 cm) from the base to the distal tip. Cross sections were photographed under UV light. Scale bar = 2 mm.

opennotspecifiedMar 2018View details →
zenodo32/100

Figure 7 in Morphology and composition of the internal axis in two morphologically contrasting deep-water sea pens (Cnidaria: Octocorallia)

Figure 7. Radial growth rates in relation to distance from base in five colonies of Umbellula encrinus.

opennotspecifiedMar 2018View details →
zenodo32/100

Figure 6 in Morphology and composition of the internal axis in two morphologically contrasting deep-water sea pens (Cnidaria: Octocorallia)

Figure 6. Axis radius in each of the four lobes in five colonies of Umbellula encrinus. Colour codes for lobes are: top right = blue, top left = green, bottom right = black, bottom left = red.

opennotspecifiedMar 2018View details →
zenodo32/100

Figure 3 in Morphology and composition of the internal axis in two morphologically contrasting deep-water sea pens (Cnidaria: Octocorallia)

Figure 3. Pieces of axis showing surface texture at different sections of a same specimen of Umbellula encrinus (a, sample ID 052) and Anthoptilum grandiflorum (b) from base to distal tip. Pencil marking can be seen in red. Scale bars = 5 cm.

opennotspecifiedMar 2018View details →
zenodo32/100

Figure 5 in Morphology and composition of the internal axis in two morphologically contrasting deep-water sea pens (Cnidaria: Octocorallia)

Figure 5. The internal axes from five Umbellula encrinus colonies (042–052) seen as cross sections along a gradient (every 10 cm) from base to tip. Changes in the position of red dots indicate changes in lobe position due to axis twisting. *Cracked samples. Cross sections were photographed under UV light. Scale bar = 2 mm.

opennotspecifiedMar 2018View details →
zenodo32/100

Figure 2 in Morphology and composition of the internal axis in two morphologically contrasting deep-water sea pens (Cnidaria: Octocorallia)

Figure 2. Umbellula encrinus: (a) whole colony in situ, (b) whole colony, (c) piece of stem and corresponding extracted axis. Anthoptilum grandiflorum: (d) whole colony in situ, (e) whole colony and extracted axis. au: autozooids, p: peduncle, s: stalk, r: rachis. (a–c) and (d–e) are not the same colonies. Colony in (a) measures ~81 cm. Size not available for (d). Photo credits: ArcticNet-CSSF-DFO (a) and ROPOS-DFO (d).

opennotspecifiedMar 2018View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

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