Sentence examples similar to optimized assumptions from inspiring English sources

Moreover, the growth-optimized assumptions that constraint-based models often rely on do not hold when studying stationary or persistor cell populations.

Flux balance analysis (FBA), as one of the most prominent of the MFA methods, is based on linear programming (LP) whereby a given objective function (e.g., biomass yield) is optimized under the assumption that the system operates at steady state under the constraints given by the stoichiometric matrix [ 11, 13- 16].

Creating a model of a soil leads to complexity problems: a soil is a multi-scale heterogeneous, three-dimensional and dynamic environment that cannot be modelled and simulated without defining a suitable and optimized representation and taking assumptions about the studied system.

The objective function maximized by ReML, as shown in Friston et al. [ 2002, 2007], is identical to the (negative) variational free-energy, F. For such linear models under Gaussian assumptions, the optimized free-energy provides a tight lower bound on the marginal log-likelihood of the generative model, or its "log-evidence," In, where the model is defined fully by L and.

Thus, the model is developed from these assumptions and parameters are optimized with respect to experimental values for one case and subsequently validated for others; a very good agreement is obtained.

The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity.

Figure 12 and Figure 13 show the optimized simulations under this set of assumptions for: women and men.

FBA relies on the strong assumption that bacteria have optimized their growth performance in a subset of possible environments during their evolution, thereby making the maximization of biomass production a driving principle for metabolic operation (Varma & Palsson, 1994b).

Both screening and the optimization procedures were conducted under the assumption that the parameter being optimized (dependent variable) is the sum of chromatographic peak areas for all analytes.

The optimized confidence level is based on the assumption that the mean edge weight in GR depends mainly on the edge distance le.

The algorithm makes no assumption of the function to be optimized and for biomedical experiments like those presented here, PSO typically finds the optimal solutions in a few seconds of CPU time on a garden-variety laptop.