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A rich variety of morphological patterns are predicted and analyzed.
This algorithm explores the lexicon, keeping track of which morphological patterns are statistically most reliable in different phonological environments.
These morphological patterns are beyond the reach of the classical phenomenological theory of martensitic crystallography (PTMC).
No special self-accommodating morphological patterns are observed on the (0001)α2 plane, which is very different from the pattern formation predicted for the coherent hexagonal → O-phase transformations.
Morphological patterns are focal and diffuse.
Furthermore, morphological patterns are not concordant with the molecular patterns observed.
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The most representative morphological patterns were chosen to conduct this work.
The intensities of these phenological events were estimated using the semi-quantitative scale of Fournier (Fournier 1974) and identification of the morphological patterns was made according to the classification proposed by Newstrom (Newstrom et al. 1994).
These morphological patterns were attributed to mutualist coevolutionary processes with flowers.
The morphological patterns were almost identical between AI-Ste5p ste2Δ and AI-Ste5p sst2Δ (Figure 6C), suggesting that the ability to form multiple projections in AI-Ste5p ste2Δ was because of elevated basal heterotrimeric G-protein activity [25], which also led to an enhanced transcriptional response.
Neuropathological assessment of six cases with the C9ORF72 repeat expansion demonstrated a heterogeneous profile, in that both FTLD-TDP type A and type B morphological patterns were represented.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com