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These coefficients relate the time and frequency average energies of the subsystems to the subsystem input powers.
In order to relate the time scales of structural and rheological changes, we measured time-resolved small-angle light scattering (SALS) and transmittance properties in a single experimental run, which then was repeated in an optical microscope for direct observation of growth of large-scale structures, and in a rheometer for mechanical spectroscopy.
Using spectral data obtained with both clear solutions and suspensions, the calibration of the in situ infrared sensor was performed to relate the time variations of the concentrations of the main product and of its main impurity, in the presence of both pH and temperature variations.
A major interest of the two-dimensional model lies in its ability to relate the time variations of the crystal habit: the particles lengthen in the first moments of their growth and then progressively get thicker until the end of the process.
If the frequency response on subcarrier k and antenna n is denoted by hn,k, we can then relate the time domain channel h ~ n, m through Parseval's theorem s n = ∑ k = 0 K − 1 | h n, k | 2 N 0 = ∑ m = 0 M − 1 | h ~ n, m | 2 N 0 = ∑ m = 0 M − 1 γ n, m (10).
The inability to relate the time of neurosurgical interventions is problematic due to the effect such procedures could have on ICP.
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By assuming sinusoidal wave motion, expressions are developed which relate the time-averaged power transmission to the travelling wave amplitudes.
Several equations are proposed which relate the time-average energy of a forced vibrating linear structure to the structure input impedance and mobility.
We relate the time-dependent standard deviation of price changes volatility to two microscopic quantities: the number of transactions N t) in Δt and the variance W2 t) of the price changes for all transactions in Δt.
We relate the time-dependent standard deviation of price fluctuations – volatility – to two microscopic quantities: the number of transactions NΔt in Δt and the variance WΔt2 of the price changes for all transactions in Δt.
Specify the Courant factor S which relates the time step size to the spatial discretization: cΔt = SΔx.
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