Abrams and Fung [ 12] studied the IGP module in which the IGpredator exhibits partial preference while this study focused on individual variation (difference between partial preference and individual variation is discussed above), and both studies show that sub-optimal adaptive behavior can increase coexistence possibilities.
In 19 patients undergoing the implantation of a biventricular pacing/defibrillator device under general anesthesia, dynamic blood pressure regulation was assessed during right ventricular and biventricular pacing in the frequency domain (power spectral analysis) and in the time domain (PP variation: difference between the maximal and minimal PP values, normalized by the mean value).
Accordingly, variability can be attributed to differences between devices (inter-instrument variation), differences over time (intra-instrument variation), differences between subjects (between-subject variation) and interactions between these different sources of variation.
Variation in the risk associated with blood measures could be explained by the first type of variation (that is, true population differences) or the third type of variation (differences between centres in the care provided to patients with different blood results).
This introduces the evolutionary process as the consequence of three components that structure the lesson: replication (the inheritance of parental traits by offspring), variation (differences between parent and offspring and among siblings), and selection (nonrandom differential survival of offspring).
Based on our estimates of multivariate effect size, allometry provided the most important explanatory source, with fragmentation status representing the second most important source of variation; differences between species and islands were slightly smaller in magnitude.
The maximum percent difference measured between subsets was used as a threshold to establish the percentage of random variation: Differences between genotypes higher than the threshold values were considered as relevant, that is, not related to random sampling of the reads.
It is apparent that there are significant (though it is borderline at 785 nm during μa variation) differences between the measuring (DB-dynamic) and assuming (DB-mid) variables; DB-dynamic is more accurate (with less measurement errors, see Table 2) than DB-mid.
Aside from the differences in the flavonoid levels due to diverse environmental conditions of growing and to the specific variations, differences between tissues can be expected as the result of the differential regulation of the genic expression in well differentiated cells.
Results are presented in figures and tables to visualize measurement variations, differences between expected and obtained values, and the optical property influences on DCS flow indices.
Aside from species dependent variations, differences between physiological and pathophysiological states appear to be important determinants of the effects of AVP on cutaneous microcirculatory flow.
