deletions | additions       diff --git a/2-Memory.tex b/2-Memory.tex  index 52e3192..f330ea8 100644  --- a/2-Memory.tex  +++ b/2-Memory.tex 
...
While this method is efficient, it is poorly suited to exploratory analysis where the proper refinement criterion may not be know {\it{a priori}}.  However, when additional fields are loaded into an existing \code{PartType} dataframe that has been manually refined, particles not in the existing data are dropped.  This allows for the incremental refinement along several axes of the data kept in memory.  As fields are loaded additional Additional  cuts can be made, made as subsequent fields are loaded,  resulting in the selection of a precisely targeted primary dataset from whichsubsequent  derived properties (e.g., temperature)  may be calculated, serving to reduce computational overhead as well.