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2,214 results for “Strength”
Appendix from: Understanding challenges and strengths in the post-dairy farm surplus calf value chain: An interview study
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Body size mediates trophic interaction strength of novel fish assemblages under climate change
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Dependence of tropical cyclone weakening rate in response to an imposed moderate environmental vertical wind shear on the warm-core strength and height of the initial vortex
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Data from: A meta-analysis of factors influencing the strength of mate choice copying in animals
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Sex differences in fearful personality traits are explained by facultative calibration to physical strength
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Fig. 9 in Fused and vaulted nasals of tyrannosaurid dinosaurs: Implications for cranial strength and feeding mechanics
Fig. 9. Comparison of theropod nasal strengths at multiple transverse sections. Horizontal (Iy) and vertical (Iz) second moments of area of nasal cross−sections of Allosaurus fragilis (upper two graphs) and tyrannosaurids (lower two graphs). Second moments of area are proportional to lateral (Iy) and vertical (Iz) bending strengths. X−axes of graphs show relative position of slices along the long axes of the bones: 0.0 is posterior and 1.0 anterior.
Fig. 6 in Fused and vaulted nasals of tyrannosaurid dinosaurs: Implications for cranial strength and feeding mechanics
Fig. 6. Geometry used to compute the area, centroid, and second moments of area of a nasal cross−section (from middle region of fused Tyrannosaurus rex nasals: TMP 98.86.01; cast of BHI 2033). A. Decomposition of the cross−section to compute area by summing areas of triangles. Small "+"s are centroids of individual triangles. Large "+" is the centroid for the complete section. B. Cross−section partitioned into horizontal and vertical strips of known area and position, used to calculate second moments of area.
Fig. 5 in Fused and vaulted nasals of tyrannosaurid dinosaurs: Implications for cranial strength and feeding mechanics
Fig. 5. CT cross sections and reconstructions of Allosaurus fragilis nasals: A, largest (UUVP 1663/UMNH VP 9146); B, midsize (UUVP 1913/ UMNH VP 9144); and C, smallest (UUVP 10854/UMNHVP 7784). Anterior is to the right. Cross sections are from the strongly pneumatized regions of the nasals, at positions indicated by the dashed lines. The slices are normalized to the same size to show the relative degree of pneumatic excavation, evident despite mineral infilling in some sections. Reconstructions are in lateral views and in dorsal views with single left or right specimens mirrored to replicate complete pairs. Specimen B is broken over the posterior part of the external nares. Scale bar 10 cm.
Fig. 4 in Fused and vaulted nasals of tyrannosaurid dinosaurs: Implications for cranial strength and feeding mechanics
Fig. 4. CT reconstructions of tyrannosaurid nasals in side and top views. Anterior is to the right. A. Tyrannosaurus rex (TMP 98.86.01; cast of BHI 2033). B. Daspletosaurus torosus (TMP 98.48.1). C. Albertosaurus sarcophagus (TMP 2000.12.1). D. Adult Gorgosaurus libratus (TMP 86.64.1). E. Juvenile Gorgosaurus libratus (TMP 86.144.1). Scale bars 15 cm.
Fig. 1 in Fused and vaulted nasals of tyrannosaurid dinosaurs: Implications for cranial strength and feeding mechanics
Fig. 1. Comparison of cranial and nasal morphology of: A, the tyrannosaurid Tyrannosaurus rex (TMP 98.86.01; cast of BHI 2033) and B, the carnosaur Allosaurus fragilis (UUVP 1663/UMNH VP 9146; mirrored to depict a complete pair). Scale axes for crania are in meters. Nasals in their life positions are highlighted in lateral and dorsal cranial views, and rendered in oblique view (not to scale). The T. rex nasals are tall, vaulted, and fused, while the A. fragilis nasals are lower and unfused.
Data and code for publication "The role of history and strength of the oceanic forcing in sea level projections from Antarctica with the Parallel Ice Sheet Model"
<p>Data and code underlying the publication <a href="https://tc.copernicus.org/preprints/tc-2019-330/">"The role of history and strength of the oceanic forcing in sea level projections from Antarctica with the Parallel Ice Sheet Model"</a>.</p> <p>Journal: The Cryosphere</p> <p>Authors: <em>Ronja Reese<sup>1*</sup></em><em>, Anders Levermann</em><sup><em>1,2,3</em></sup><em>, Torsten Albrecht</em><sup><em>1</em></sup><em>, Hélène Seroussi<sup>4</sup></em><em>, Ricarda Winkelmann<sup>1,2 </sup></em></p> <p>(1) Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany</p> <p>(2) Institute of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany</p> <p>(3) LDEO, Columbia University, New York, USA</p> <p>(4) Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA</p> <p>(*) email ronja.reese@pik-potsdam.de</p> <p>Abstract:<br> Mass loss from the Antarctic Ice Sheet constitutes the largest uncertainty in projections of future sea level rise. Ocean-driven melting underneath the floating ice shelves and subsequent acceleration of the inland ice streams is the major reason for currently observed mass loss from Antarctica and is expected to become more important in the future. Here we show that for projections of future mass loss from the Antarctic Ice Sheet, it is essential (1) to better constrain the sensitivity of sub-shelf melt rates to ocean warming and (2) to include the historic trajectory of the ice sheet. In particular, we find that while the ice sheet response in simulations using the Parallel Ice Sheet Model is comparable to the median response of models in three Antarctic Ice Sheet Intercomparison projects – initMIP, LARMIP-2 and ISMIP6 – conducted with a range of ice sheet models, the projected 21st century sea level contribution differs significantly depending on these two factors. For the highest emission scenario RCP8.5, this leads to projected ice loss ranging from 1.4 to 4.0 cm of sea level equivalent in the ISMIP6 simulations where the sub-shelf melt sensitivity is comparably low, opposed to a likely range of 9.2 to 35.9 cm using the exact same initial setup, but emulated from the LARMIP-2 experiments with a higher melt sensitivity based on oceanographic studies. Furthermore, using two initial states, one with and one without a previous historic simulation from 1850 to 2014, we show that while differences between the ice sheet configurations in 2015 are marginal, the historic simulation increases the susceptibility of the ice sheet to ocean warming, thereby increasing mass loss from 2015 to 2100 by about 50 %. Our results emphasize that the uncertainty that arises from the forcing is of the same order of magnitude as the ice dynamic response for future sea level projections.</p> <p>Large zip files contain data, small zip file python notebooks for data analysis and PISM code. Please contact ronja.reese@pik-potsdam.de if you have any further questions.</p>
Fig. 11 in Fused and vaulted nasals of tyrannosaurid dinosaurs: Implications for cranial strength and feeding mechanics
Fig. 11. Top and side views of theropod crania used to reconstruct crosssectional shapes, and oblique views of reconstructed plinge cross−sections for each cranium. Second moments of area of the plinges were calculated as indices of bending and torsional cranium strengths. A–D, carnosaurs; E–G, tyrannosaurids.
Fig. 7 in Fused and vaulted nasals of tyrannosaurid dinosaurs: Implications for cranial strength and feeding mechanics
Fig. 7. CT−scanned cross−sections of fused tyrannosaurid nasals, showing greater vaulting and higher cross−sectional areas of bone in larger individuals. A. Gorgosaurus libratus (juvenile: TMP 86.144.1). B. Gorgosaurus libratus (subadult: TMP 86.64.1). C. Daspletosaurus torosus (adult: TMP 98.48.1). Numbers 1–4: cross−sections at topologically similar positions, from posterior to anterior.
Fig. 3 in Fused and vaulted nasals of tyrannosaurid dinosaurs: Implications for cranial strength and feeding mechanics
Fig. 3. Comparisons of mediolateral (A, B) and anteroposterior (C, D) strengths of tyrannosaurid and non−tyrannosaurid theropod maxillary teeth, plotted against skull length. Regressions are by least squares, on log transformed data for the tyrannosaurids. Trend lines are allometric in the tyannosaurids but linear in non−tyrannosaurids. Tooth strengths of Tyrannosaurus rex are much higher than in any other examined taxon. Starting points of the small arrows indicate the position of the juvenile T. rex (TrJ). See Appendix 1 for other specimen labels.
Fig. 8 in Fused and vaulted nasals of tyrannosaurid dinosaurs: Implications for cranial strength and feeding mechanics
Fig. 8. Average strengths of nasal cross−sections in tyrannosaurids and Allosaurus fragilis, plotted against nasal length. A. Cross−sectional areas, proportional to compression strengths. B. Second moment of area, proportional to vertical bending strength. C. Second moment of area, proportional to lateral bending strength. Values for the A. fragilis nasals are uncorrected for the hollowness of the sections, which would reduce their strengths. Lines fitted to the tyrannosaurid values are derived from log transformed data. See Appendix 1 for labels.
Variation in the strength of allometry drives rates of evolution in primate brain shape - Supplementary Material
<p>Large brains are a defining feature of primates, as is a clear allometric trend</p> <p>between body mass and brain size. However, important questions on the</p> <p>macroevolution of brain shape in primates remain unanswered. Here we</p> <p>address two: (i), does the relationship between the brain size and its shape</p> <p>follow allometric trends and (ii), is this relationship consistent over evolutionary</p> <p>time? We employ three-dimensional geometric morphometrics and</p> <p>phylogenetic comparative methods to answer these questions, based on a</p> <p>large sample representing 151 species and most primate families. We found</p> <p>two distinct trends regarding the relationship between brain shape and</p> <p>brain size. Hominoidea and Cercopithecinae showed significant evolutionary</p> <p>allometry, whereas no allometric trends were discernible for Strepsirrhini,</p> <p>Colobinae or Platyrrhini. Furthermore,we found that in the taxa characterized</p> <p>by significant allometry, brain shape evolution accelerated, whereas for taxa in</p> <p>which such allometrywas absent, the evolution of brain shape decelerated.We</p> <p>conclude that although primates in general are typically described as largebrained,</p> <p>strong allometric effects on brain shape are largely confined to the</p> <p>order's representatives that display more complex behavioural repertoires.</p>
Moisture alone is sufficient to impart strength but not weathering resistance to termite mound soil
<p>Soil is used for construction of structures by many animals, at times admixed with endogenous secretions. These additives, along with soil components, are suggested to have a role in biocementation. However, the relative contribution of endogenous and exogenous materials to soil strength has not been adequately established. Termite mounds are earthen structures with exceptional strength and durability including weathering resistance to wind and rain. With <i>in-situ</i> and lab-based experiments we demonstrate that the fungus-farming termite <i>Odontotermes obesus</i> which builds soil nest mounds, when given a choice, prefers soil close to its liquid limit for construction. At this moisture content, the soil–water mixture alone even in the absence of termite handling undergoes self-weight consolidation and upon drying attains a monolithic, densely packed structure with compressive strength comparable to the <i>in-situ</i> strength of the mound soil; however, the soil–water mixture alone has lower resistance to water erosion than the <i>in-situ</i> mound samples suggesting that termite secretions impart weathering resistance and thereby long-term stability to the mound. Therefore, weathering resistance and compressive strength are conferred by different aspects of termite soil manipulation. Our work provides novel insights into termite mound construction and strength correlates for earthen structures built by animals.</p>
Dynamic Compressive Strength and Fragmentation in Felsic Crystalline Rocks
<p>Complete data for "Dynamic Compressive Strength and Fragmentation in Crystalline Rocks" by Rae et al.</p>
Individual differences determine the strength of ecological interactions
<p>Biotic interactions are central to both ecological and evolutionary dynamics. In the vast majority of empirical studies, the strength of intraspecific interactions is estimated by using simple mea- sures of population size. Biologists have long known that these are crude metrics, with experiments and theory suggesting that interactions between individuals should depend on traits, such as body size. Despite this, it has been difficult to estimate the impact of traits on competitive ability from ecological field data, and this explains why the strength of biotic interactions has empirically been treated in a simplistic manner. Using long-term observational data from four different populations, we show that large Trinidadian guppies impose a significantly larger competitive pressure on conspecifics than individuals that are smaller; in other words, competition is asymmetric. When we incorporate this asymmetry into integral projection models, the predicted size structure is much closer to what we see in the field compared with models where competition is independent of body size. This difference in size structure translates into a twofold difference in reproductive output. This demonstrates how the nature of ecological interactions drives the size structure, which, in turn, will have important implications for both the ecological and evolutionary dynamics.</p>
Data from: Positive relationships between association strength and phenotypic similarity characterize the assembly of mixed-species bird flocks worldwide
Competition theory predicts that communities at small spatial scales should consist of species more dissimilar than expected by chance. We find a strikingly different pattern in a multi-continent dataset (55 presence-absence matrices from 24 locations) on the composition of mixed-species bird flocks, important subunits of local bird communities the world over. Using null models and randomization tests followed by meta-analysis, we find the association strength of species in flocks to be strongly related to similarity in body size and foraging behavior, and higher for congeneric compared with non-congeneric species pairs. Given the small spatial scale of our individual analyses, differences in habitat preferences of species are unlikely to have caused these association patterns; therefore, the patterns are most likely the outcome of species interactions. Extending group-living and social information use theory to a heterospecific context, we discuss potential behavioral mechanisms leading to positive interactions among similar species in flocks as well as ways in which competition costs are reduced. Our findings highlight the need to consider positive interactions along with competition when seeking to explain community assembly.
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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.