Please solve these 10 true or false questions. No need to give a detailed explanation on why, brief explanations are fine.

For each subproblem below, state whether the statement is true or false ( 2 points each) (a) We currently know that every problem in P can also be solved in O(poly(n)) work and O(polylog(n)) depth (let n be the input size). (b) If some algorithm, for an input of size n has work n and depth n, then it is highly parallelizable. (c) A strongly NP-complete problem is a problem that remains NP-complete even when all of its numerical parameters (e.g., the magnitude of a capacity, or the size of a bin) are bounded by a polynomial of the input size. (d) The Ford-Fulkerson algorithm always runs in polynomial time. (e) Given a graph G(V,E) and s,tV, a source and a target and a maximum flow f assigning flows to edges, we can compute the minimum s,t-cut in O(E+V) time. (f) Consider an undirected graph G(V,E) and consider it as a directed graph G^ where each edge (u,v) appears in both directions as (u,v) and (v,u). The number of strongly connected components of G^ is equal to the number of connected components G. (g) A maximum matching is always a maximal matching. (recall that a matching M is maximal if no edge in E\M can be added to M to obtain a larger matching.) (h) If a data structure ensures that some operation op on it runs in O(f(n)) amortized time, then every call to op runs in O(f(n)) time. (i) There is a polynomial time algorithm for solving the global min-cut problem (i.e., to figure out the value of the smallest minimum cut in an undirected weighted graph G ). (j) The maximum flow on a weighted graph G with n vertices and m weighted edges, where the graph can be represented in O( poly (n)) space cannot be computed in polynomial time since the flow value can be super-polyomial, e.g., (2n) or larger