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Our findings further demonstrate that the 'optimal' model fit to the data was achieved by shortening the odorant 'ON' period to approximately 6 s.
An improved global fit to the data was achieved through applying a unique technique utilizing the Fokker-Plank equation with a non-linear rigidity-dependent diffusion coefficient.
In most cases, a satisfying description of the data was achieved via a one-parameter fit according to the Gordon-Taylor equation.
The best fit for the data was achieved with Virtual Cell simulations with a two-component system.
Saturation of the data was achieved.
A fit to the data was achieved with a one component fluorescence recovery model.
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The curves show that a good fit to the data is achieved at convergence.
Clustering of the data is achieved through the minimization of the objective function J HKM = ∑ n = 1 N ∑ θ ( k, l ) ∈ C n D n ( k, l ), (15).
A generally good description of the data is achieved adding confidence to the use of FLUKA for the design of shielding for high-energy electron accelerators.
For discrete ill-conditioned problems, this plot displays an 'L-shape' with a corner point, where a certain balance between the regularized solution and fit to the data is achieved (Hansen et al. 2007).
Measures of model fit for the multivariate three-level linear growth models show that the best fit of the data is achieved by modelling context effects of mathematics, grade, structure and task analysis.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com