Sentence examples for morphology and variability from inspiring English sources

The EIA, characterized for two crests in the ionospheric F-region plasma density at either side of the magnetic dip equator (around ∼15° 20°), is one of the most studied phenomena, and the understanding of its morphology and variability is of great interest to improve regional ionospheric models.

We therefore encourage studies of geographical variation in sperm morphology and variability within passerine species with known population differences in extrapair paternity rates.

Henneberger et al. (2005) found that ambient particle levels were associated with changes in repolarization duration, morphology, and variability, which could produce the type of ST-segment changes that we observed.

This study provides evidence suggesting an immediate effect of air pollution on repolarization duration, morphology, and variability representing myocardial substrate and vulnerability, key factors in the mechanisms of cardiac death.

Two panel studies of patients with cardiovascular disease, which were conducted in East Germany, showed evidence of an immediate effect of air pollution on ventricular repolarization duration, morphology, and variability (Henneberger et al. 2005; Yue et al. 2007).

Thus, the spatial dynamic between virus and host defines episode morphology, and explains variability in shedding severity in an individual over periods of hours to weeks.

The present approach can be used in the future to appraise the significance of inter-subject lung morphology and breathing physiology variability for PM deposition and dose calculations.

These findings lead to the hypothesis that the immediate effects in T-wave morphology and heart rate variability might lead 2 days later to a manifestation expressing in ST-segment depression or cardiac arrhythmia.

Combination of the analytical techniques brought the knowledge about the morphology of the grains and variability of the use of the lead tin yellows in the Bohemian panel paintings.

The study was designed (1) to characterize particulate matter (PM) by examination of size, surface area, and volume distribution, chemical composition as a function of size and on a single particle basis, morphology, and temporal and spatial variability in the Pittsburgh region; (2) to quantify the impact of the various sources (transportation, power plants, biogenic sources, etc).

The question of synthesizing key-poses with variability from our representation model can be potentially solved by, at every metric class, stochastically generating joint coordinates/rotations that would satisfy both kinematic constraints and their respective spherical distributions; preserving both body morphology and the represented spatiotemporal variability.