from heapq import heappop, heappush, heapify class MinCostFlow(): def __init__(self, n): self.n = n self.graph = [[] for _ in range(n)] self.pos = [] def add_edge(self, fr, to, cap, cost): #assert 0 <= fr < self.n #assert 0 <= to < self.n m = len(self.pos) self.pos.append((fr, len(self.graph[fr]))) self.graph[fr].append([to, len(self.graph[to]), cap, cost]) self.graph[to].append([fr, len(self.graph[fr]) - 1, 0, -cost]) return m def get_edge(self, idx): #assert 0 <= idx < len(self.pos) to, rev, cap, cost = self.graph[self.pos[idx][0]][self.pos[idx][1]] rev_to, rev_rev, rev_cap, rev_cost = self.graph[to][rev] return self.pos[idx][0], to, cap + rev_cap, rev_cap, cost def edges(self): for i in range(len(self.pos)): yield self.get_edge(i) def dual_ref(self, s, t): dist = [2**63 - 1] * self.n dist[s] = 0 vis = [0] * self.n self.pv = [-1] * self.n self.pe = [-1] * self.n queue = [] heappush(queue, (0, s)) while queue: k, v = heappop(queue) if vis[v]: continue vis[v] = True if v == t: break for i in range(len(self.graph[v])): to, rev, cap, cost = self.graph[v][i] if vis[to] or cap == 0: continue cost += self.dual[v] - self.dual[to] if dist[to] - dist[v] > cost: dist[to] = dist[v] + cost self.pv[to] = v self.pe[to] = i heappush(queue, (dist[to], to)) if not vis[t]: return False for v in range(self.n): if not vis[v]: continue self.dual[v] -= dist[t] - dist[v] return True def flow(self, s, t): return self.flow_with_limit(s, t, 2**63 - 1) def flow_with_limit(self, s, t, limit): return self.slope_with_limit(s, t, limit)[-1] def slope(self, s, t): return self.slope_with_limit(s, t, 2**63 - 1) def slope_with_limit(self, s, t, limit): #assert 0 <= s < self.n #assert 0 <= t < self.n #assert s != t flow = 0 cost = 0 prev_cost = -1 res = [(flow, cost)] self.dual = [0] * self.n while flow < limit: if not self.dual_ref(s, t): break c = limit - flow v = t while v != s: c = min(c, self.graph[self.pv[v]][self.pe[v]][2]) v = self.pv[v] v = t while v != s: to, rev, cap, _ = self.graph[self.pv[v]][self.pe[v]] self.graph[self.pv[v]][self.pe[v]][2] -= c self.graph[v][rev][2] += c v = self.pv[v] d = -self.dual[s] flow += c cost += c * d if prev_cost == d: res.pop() res.append((flow, cost)) prev_cost = cost return res N = int(input()) S = input() V = list(map(int, input().split())) MAX = 10**15 mcf = MinCostFlow(N + 2) s = N t = N + 1 for i in range(N): if S[i] == 'y': mcf.add_edge(s, i, 1, 0) if S[i] == 'i': mcf.add_edge(i, t, 1, MAX - V[i]) for i in range(N - 1): for j in range(i + 1, N): if (S[i], S[j]) in {('y', 'u'), ('u', 'k'), ('k', 'i')}: mcf.add_edge(i, j, 1, MAX - V[i]) flow, cost = mcf.flow(s, t) print(MAX * flow * 4 - cost)