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The USV trajectory planning problem is characterized by the presence of large and somewhat stochastic forces due to ocean waves, which can cause significant deviations in their motion.
The variable phenotype of fil-9 flowers suggested that the severity of the effect of the mutation was somewhat stochastic.
Furthermore, the k-means algorithm itself is somewhat stochastic in nature, and so it is likely that repeated analyses of the same dataset might lead to the estimation of partitioning schemes with very minor differences.
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These distributions correspond to somewhat different stochastic processes [e.g. 21], [ 22], so distinguishing between them may be important.
The results are shown in figure 7. The symmetric but slightly U-shaped distributions in figure 7 E and 7 F suggest that synonymous variation in ORFs is distributed very similarly to that in non-ORFans, and differs only in having somewhat greater stochastic variance, as expected given that ORFans are approximately three-fourth the size of non-ORFans (fig. 4 A).
A standard, though somewhat simple approach to obtain stochastic versions consists of adding (small) noise to the deterministic equations.
In carbonate reef sediments at Dry Tortugas, O2 based bioirrigation coefficients calculated using the stochastic model are somewhat larger than values found through diagenetic modeling.[15] However, if the irrigation coefficients are corrected for inefficient flushing, using an estimate of the time-averaged value of Cb, the agreement is better.
The correlations between the values obtained by the measurements and the stochastic model were somewhat higher than the correlations between the measured values and the dispersion values.
It is now appreciated that the general biochemical 'state' of all cells is somewhat plastic, because transcription occurs in stochastic bursts.
With parameter values as in Fig. 6, specifically with D a =0.1 μm/s (central inverted cup in Fig. 9), we observe a somewhat more stringent condition in the stochastic wave-pinning regime, 22≤ than, than predicted by Fig. 3 (arrow indicates default value T=22.68).
The techniques and methods involved in stochastic modeling are explained in somewhat more detail, as they are newer and less known than those used for the deterministic modeling.
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