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Simplified models for azeotropic design that rely on parameters derived from distillation simulations involving rigorous thermodynamic models are developed.
Nonlinear models that utilize the proposed damping formulations are found to be superior to those that solely rely on parameters from a quasi-static experiment.
In the instantaneous mixture case, where each observation consists of a sum of sources with different signal intensity in presence of noise, the sparseness-based methods introduced in[12 17], among others, rely on parameters that are chosen empirically.
Both methods are problematic since they rely on parameters that are localised and therefore have a strong dependency on the gradient of the stress strain diagram in the plastic region.
Both OCRA and ULRA rely on parameters that define the upper limb posture, force and duration of each activity.
Similarly, the score-based learning methods such as the penalized maximum likelihood estimation [ 13] rely on parameters controlling the penalization as a function of complexity.
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Here, we cannot obtain such estimates, hence we rely on parameter estimates from other empirical studies.
Many studies rely on parameter estimation to link models and data, and to tailor predictions and counterfactuals to specific settings.
The advantage of our approach is that it is based on physical descriptions of atomic interactions, and does not rely on parameter training with available experimental protein stability data.
The ability of the DNA-relay model to reproduce the experimental results is particularly remarkable given that the model was grounded on experimentally measured data (Table 2) and did not rely on parameter optimization.
To prevent convergence issues due to erroneous derivative values we use, in the last optimization steps, Powell's multi-dimensions algorithm, which does not rely on parameter derivatives [ 26].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com