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Return losses were evaluated using equations representing a structure with a single-layer absorber terminated by a layer of perfect conductor.
Temperature dependence was then evaluated using equations 20 and 21 (Figure 10) and extrapolated to 175°C, because the highly linear and limited data set at this temperature did not allow contributions of homogeneous and defect-assisted nucleation to be constrained.
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The sum rate is evaluated using Equation 10 for a given number of mobile terminals.
RHEED intensities of simulated thin films are also evaluated using Equation 5, and results are shown in Figure 3.
Figure 2 shows a test of varying the SPH particle number, N, based on the amount of mass lost from the companion star (evaluated using Equation 5).
The time tR is evaluated using Equation 4 assuming the chloride concentration C x, t) as known at a given position x inside the concrete.
In the recognition phase, the features of an observed object are computed, and class conditional likelihoods are evaluated using Equation 18 for explicit shape model or Equation 19 for implicit shape model.
The absorption of the incident light by the Si can be evaluated using Equation (5): Figure 4 The SEM of the Si surface (a), and (b) the schematic presentation of Ag dissociation in the solution.
Thus, the out-of-plane thermal conductivity of the thin films can generally be evaluated using Equation 3, provided ΔT s+f and ΔT s are measured separately using the 3-ω method in the 20 to 300 K temperature range.
The prediction performances of the 100 classification random forest models were evaluated using Equation (3).
The quality of identified M/E sites were evaluated using Equation 1 to excluding the probability of being random sequencing errors.
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