Sentence examples for model include i from inspiring English sources

Obvious imperfections that should be taken into account in our model include: (i) fluctuations of the doping density, (ii) fluctuations in (d_{B}) and (d_{W}), (iii) fluctuations in (V_{B}).

Main characteristics of the model include: i) grain size-dependent diffusion and particle density, ii) a vertically stratified wind, iii) particle diffusion within the risingrain size-dependentling velocities that includiffusionions in the Reynolds number depending on whether pandicles follow a laminar or turbulent flow regime.

Important new features of this model include: (i) the simulation of AR in multiple tissue compartments (i.e., brain, liver, and gonad); (ii) AR binding and its effects upon the HPG axis; and (iii) free androgen effects on brain AR concentration.

Advantages of such a model include (i) consideration of probe-probe variation, (ii) easily interpretable confidence of the detections and (iii) straight forward false discovery rate (FDR) control/estimate [ 18, 19].

Examples of settings with a two-variance components model include (i) a null model that contains a background kernel to correct for confounding factors (owing to, for example, family relatedness and population structure) (Listgarten et al., 2013), and (ii) gene gene interaction tests where the null model contains a background kernel for the additive gene terms (Li and Cui, 2012).

The kinetic model included (i) steady-state scheme; (ii) reversible inhibition of the enzyme by alcohols; and (iii) aggregation of water W + W ↔ WW.

The stage-gate model includes (I) General vision and investment strategy definition; (II) Venture search, screening and rapid pre-evaluation; (III) Due diligence and negotiation of terms; (IV) Portfolio management, evaluation, and exit.

The model includes: (i) charge reactions and electric bias according to the local Fermi-level; (ii) pairing and break-up reactions involving charged particles; (iii) clustering-related dopant deactivation; and (iv) Fermi level-dependent solubility.

So, our multi-objective model includes (i) the minimization of the sum of current investment costs and the expected future processing, transportation, shortage and capacity expansion costs, (ii) the minimization of the variance of the total cost and (iii) the minimization of the financial risk or the probability of not meeting a certain budget.

k is derived from a multivariate regression model including (i) Langewouter's aortic compliance [ 19], (ii) mean arterial pressure (MAP), (iii) variance, (iv) skewness and (v) kurtosis of the pressure curve.

The general model included (i) common time constants: τ1 for Model-1Comp, τ1 and τ2 for Model-2Comp, and τ1, τ2, and τ3 for Model-3Comp; (ii) a subject-specific intercept p(0); and (iii) subject-specific multiplying factors for each component: k1 for Model-1Comp, k1 and k2 for Model-2Comp, and k1, k2 0), and k3 for Model-3Comp.