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The approximating functions are based on one- and two-dimensional integrals of Legendre polynomials, allowing accurate simulation of three-dimensional behavior.
These scoring functions are based on knowledge-based atom-pair potentials which can be used in an additive manner (PMF-Score) to score protein-ligand complexes.
First of all, the model structure and value functions are based on value-based MCDA [ 3, 7].
Cerebral functions are based on the functional interactions between multiple distinct specialized regions of the brain.
These algorithms are associated with the method of normalized functions, are based on a combination of formal and heuristic procedures, and allow one to obtain quasi-optimal solutions after a small number of steps, thus overcoming the computational complexity posed the NP-completeness of discrete optimization problems.
These functions are based on the following criteria.
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Wherever possible, these functions were based on known (evidence-based) regional or national impact models.
These functions were based on Euclidean distance function.
The first linear utility functions were based on these representative transfer variables.
The ranking for all the functions were based on its contributions to the total ESVS.
Both functions were based on a set of experimental results using the technique of experimental design.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com