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This formula allows us to work out the day with the highest 'depression factor' which you can then use as a focus for making things better, booking your holiday etc...".
Moreover, the formula allows us to write.
For the case of, the matrix inversion formula allows us to instead write (35).
An explicit formula allows us to define the parameters of a regulator guaranteeing weak dependence of the escape rate on the noise strength.
The formula allows us to determine which trees to plant between buildings in that we can predict the effects of future tree growth on building daylighting.
This formula allows us to make rigorous a well known heuristic connection between Euler Poisson equations and classical Hamilton Jacobi equations.
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The parametric g-formula allows us to estimate effects of such hypothetical interventions using observed data.
Generic propositional formulas allow us to define constraints and dependencies among features, such as "features A and B imply not C".
Feeding this software with various molecular formulae allowed us to gather as many non-equivalent structures as necessary (for an example of molecular formulae used with counts of generated structures, and a structure generation software screenshot, see Additional file 1: Table S1 and Additional file 1: Figure S1).
Common formulae allow us to calculate further determinants of the cardiovascular system (e.g. systemic vascular resistance, pulmonary vascular resistance, right ventricular stroke work, and left ventricular stroke work).
Then, formula (1) allows us to represent any linear combination of input variables.
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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