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The influence of source-zone management on site remediation was evaluated by conducting two predictive simulations, one for which the source zones were controlled and one for which they were not.
In order to illustrate this difference, we set up two simulations, one for the method of [8] and one for our method.
We perform two simulations, one for the PDE with a rotation rate of (Omega _{rm{PDE}}= 1) (left( dfrac{hbox {rotation}}{hbox {days}}right)) and a second one for the TLE with a rotation rate of (Omega_{mathrm{TLE}}= dfrac{1}{365}) (left( dfrac{hbox {rotation}}{hbox {days}}right)).
This enabled us to run many simulations – one for each individual – and to predict the amounts of VEGF and Semaphorin signaling complexes in a patient-specific manner.
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We conducted two types of simulation, one for the branching-process regime and another for a finite island population with Wright Fisher random drift.
Three computers running Microsoft Windows 7 operating system (Microsoft, Inc., WA) were used to control the simulation, one for the calculation and the control of the dynamic scenario, and two for the graphics.
It can be observed that the analytic results are similar to the simulation ones for both cases.
I also found surprising the set-up of the simulations: one molecule looking for a single target in the nucleus.
For simulations one needs to specify L, nseg, diam, Ra, and connectivity.
Logistic regression models were also run for Simulation set 1B (results not shown) and again KWII and logistic models were powered within 2% of one another for all simulations; one approach was not consistently better than another.
For each simulation, one value for each of the four parameters was randomly selected from a uniform distribution over pre-specified plausible ranges, creating a unique natural history parameter set.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com