Can someone explain the binary tree part of the O(NlogN) solution for problem B 
to me? Why do we need a binary search tree here? The purpose of the tree is to 
help find the nearest activity or find out the limits? I understand the 
solution in this way: we need to find the nearest activity that has been 
considered and find out the limits it imposed. So can we make the activity 
array into an object array, each array element will contain the limits (how 
many it needs and how many it will leave unspent) when we find the nearest 
activity that has been considered. 

(We copy the array first and make it into another object array so that each of 
them contain the original position, then sort it to determine which one we 
should consider next so we will always consider the highest values unconsidered 
activity.)

Hope I made the question clear

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