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The aims of this study were: (1) to validate a device specifically designed to study the kinetics of particle exhalation and the percentage of airway particle deposition (%DEP) in polluted indoor environments (welding fumes, environmental tobacco smoke – ETS) and (2) to assess the intra- and inter-subject variability of the signal.
As observed in Fig. 5, variability of the signal around MPL also depends on the propagation conditions and polarisation.
A statistical analysis of the signal components in the CP and XP channels implies that the higher attenuation and greater variability of the signal is associated with the latter, as indicated by parameter values of the mean path loss model and distributions of fading components.
This is expected, since variability of the signal in static scenarios comes merely from dynamics of objects in the propagation environment and elliptically polarised MPCs associated with reflections from lossy materials, whereas in the dynamic scenario the on-body antenna is moving, rotating and tilting as the user moves.
The ROI time-courses were standardized, so that beta weights reflected the BOLD response amplitude of one condition relative to the variability of the signal.
Fundamental for understanding the evolution of communication systems is both the variation in a signal and how this affects the behavior of receivers, as well as variation in preference functions of receivers, and how this affects the variability of the signal.
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Bland-Altman plots should be used as a first step in the analysis as they may be helpful in better understanding the dependence of variability on the signal strength as well as potential bias between test and retest measurements.
In addition, the higher values of transition probabilities, the faster the modes switch (N B,N O, are smaller) due to the time variability of the signals.
For each SM, the Mutation Score is calculated from the signal on the array and the underlying variability of that signal in a large reference of samples negative for that SM.
We suggest that this is due to larger variations in oligodendrocyte abundance, as reflected in the larger variability of the oligodendrocyte signal compared to other reference signals (Additional file 2: Figure S1).
Furthermore, from each measured signal, information on the variability of the acceleration signal (motility, which is related to the intensity of body-segment movements) will be obtained.
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