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Biomass characteristics are taken into account by considering two morphological classes for biofilm.
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Our study has shown that, by considering just two tumour morphological features that could potentially be reported at the time of diagnostic pathology, and one aspect of family history of breast cancer, it is feasible to establish a simple way to identify those young women with breast cancer who are most likely to carry a BRCA1 germline mutation.
The impact of these two parameters may be explained by considering the morphological evolution of the pores upon sintering and, in particular, the disappearance of interconnections between the porous seed and the bulk as well as the enlargement of pores near the surface.
For example, by considering both morphological and molecular characteristics and the distribution of calcium oxalate crystals in some taxa, Rudall and Chase (1996) have shown that the genera formerly included in Xanthorrhoeaceae sensu lato may belong to three different families: Xanthorrhoeaceae sensu stricto, Lomandraceae and Dasypogonaceae (Prychid and Rudall 1999).
But today, via advances in genetics and morphological studies, they are considered two separate species, with at least three reproductively distinct subspecies.
The image-extracted edges are obtained by evaluating two morphological operations [6] in parallel.
In T. rubrum, conidial germination is accompanied by two morphological transitions, swelling and germ tube emergence.
Dissolution characteristics of the alloys are discussed by considering their potential dependency and the morphological changes of the dissolving surface.
Next, we specifically looked for genes potentially related to morphological variation, by considering retained and lost genes with orthologs in both A. thaliana and T. halophila.
FG objects are considered as detected if the segmentation yields two morphological connected objects, i.e., a FG object surrounded by BG volume.
By considering a heterogeneous set of features, e.g., statistical descriptors, spectral measures, and morphological descriptors, AdaBoost classifier based on intensity channel achieves the best average performance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com