from collections import defaultdict
import numpy as np
from scipy.sparse.csgraph import dijkstra
from scipy.sparse import csr_matrix

N, M, L = map(int, input().split())
L -= 1  # 0-indexed
T = np.array(list(map(int, input().split())), dtype=np.int64)
nonzero = np.nonzero(T)[0]
d = defaultdict(lambda: 2 * 10 ** 6)
for _ in range(M):
    a, b, c = map(int, input().split())
    a -= 1
    b -= 1
    d[(a, b)] = min(d[(a, b)], c)
frm, to, length = [], [], []
for (a, b), c in d.items():
    frm.append(a)
    to.append(b)
    length.append(c)

if len(nonzero) == 1:
    print(0)
    exit()

matr = csr_matrix((length, (frm, to)), shape=(N, N))
way = dijkstra(matr, directed=False).astype(np.int64)
ans = np.inf
for target in range(N):
    tmp = np.sum(way[target] * 2 * T)
    first = np.max(way[target][nonzero] - way[L][nonzero])
    tmp -= first
    ans = min(ans, tmp)
print(ans)