Sentence examples for inclusion density from inspiring English sources

Host mineral strain by crystal-plastic processes in relatively weak minerals such as calcites can alter the fluid inclusion density in ways that render homogenization temperature data difficult to use (Roedder, [1984]), for example, fluid-inclusion stretching during heating (Prezbindowski and Larese, [1987]).

An analysis of neocortical regions based solely on the density of NCIs yielded similar results in that the three cases of aFTLD-U exhibited more neocortical NCIs than the two BIBD cases, and so the difference in FUS inclusion density was not due to differences in inclusion type or localization (data not shown).

For all r>0, the first and second-order unit inclusion densities are positive, allowing for unbiased estimators of variance.

In our previous analyses, Unc119 inclusions were more prominent in regions affected by prominent neurodegeneration in three C9orf72 mutation patients, but staining intensity and inclusions density varied considerably between patients.

Thus, in FD children podocyte, but not endothelial, inclusion volume density increases progressively with age, along with the foot process width, which correlates with proteinuria [ 17].

The two aforementioned approaches differ in their typical treatment of stochasticity, inclusion of density dependence, and assumption of demographics prior to the onset of drug treatment (equilibrium versus exponential growth; cost of resistance).

The inclusion of density-dependent somatic growth is a particularly relevant extension, because it is known to play a critical role in determining the effectiveness of a reserve under conditions of crowding (Gårdmark et al. 2006).

The SEM images of polycarbonate:M1 and polycarbonate:M4 composite films show beside the large dimension inclusions, a significant density of inclusions of smaller dimension, <100 nm (Fig. 5d, h).

The inclusion of the density term has little effect on the predicted results.

Inclusion of stand density determined from plot measurements was found to be superior to the use of LiDAR metrics that approximate this quantity (e.g. PCveg).

In this study we consciously selected the Chave et al. [25] models as they fulfill several key criteria (the inclusion of wood density, representation of a large DBH range, and development from a large sample size).