Sentence examples for integration of above from inspiring English sources

With integration of above equation, we have first-order kinetic equation: {text{Ln}}frac{{left[ {4{text{-CP}}} right]_{0} }}{{left[ {4{text{-CP}}} right]_{t} }} = K_{text{app}} t, (18 where [4-CP]0 and [4-CP] are the concentrations of 4-CP at the beginning and time t, respectively.

The integration of above equations under the boundary conditions that n 1, n el 1, n eh 1, v x 1, v y 1, v z 1, φ 1 → 0 as ξ → ∞ yields the following phase velocity relations λ 0 = v x 0 sin θ + v z 0 ± 1 + 2 T i T eff - n d 0 n el 0 + n eh0 - 1 Φ i 0 1 - Φ i 0 1 + T i / T eff 1 - Φ i 0 - 1 1 + n d 0 n el 0 + n eh 0 - 1 Φ i 0 1 - Φ i 0 1 + T i / T eff 1 - Φ i 0 cos θ. (22).

Thus, on the basis of smart integration of the above nanocomposites and the detection of H2O2 generated by ChO enzymatic reactions under the optimal conditions, the obtained ECL biosensor for choline showed wide linear range from 3 nM to 1.12 mM with detection limit (signal-to-noise ratio of 3) of 1 nM.

On the basis of this principle and smart integration of the above nanocomposites under the optimal conditions, the resulting ECL biosensor for ATCl showed wide linear range from 6.7 nM to 0.92 mM with detection limit (signal-to-noise ratio of 3) of 2.2 nM.

This is obtained from forward time integration of the above governing equations.

The state of robot in time t could be calculate by the integration of the above formula.

An integration of the above inequality over ([0,t]) leads to x t)=x 0)+ int_{0}^{t}y(s),ds.

Integration of the above equation yields as follows: ln dye 0 / dye = k app t Open image in new window.

From the integration of the above two factors, risk diagram of the danger is resulted which combines the factors in the tables of the consequence and the probability in order to provide a proper device for estimating acceptable level of the risk.

Integration of the above equation yields the following relations used to calculate the coordinates of any point of the clothoid at a distance ℓ away from its starting point [3] x = ℓ − ℓ 5 40 A 4 + ℓ 9 3456 A 8 − ℓ 13 599040 A 12 ⋯ (8) y = ℓ 3 6 A 2 − ℓ 7 336 A 6 + ℓ 11 42240 A 10 − ℓ 15 9676800 A 14 ⋯ (9).

Finally, data integration of the above showed that saturations based on Archie are prone to higher uncertainties if compared to those derived from the MICP, Sigma log, Dean Stark, and SCAL, in the pay intervals, due to a relatively low resistivity measured by the electrical log.