Constraints

* 1 ≤ |V| ≤ 1000
* 0 ≤ |E| ≤ 2000
* -10000 ≤ di ≤ 10000
* There are no parallel edges
* There are no self-loops

Input

An edge-weighted graph G (V, E) and the source r.


|V| |E| r
s0 t0 d0
s1 t1 d1
:
s|E|-1 t|E|-1 d|E|-1


|V| is the number of vertices and |E| is the number of edges in G. The graph vertices are named with the numbers 0, 1,..., |V|-1 respectively. r is the source of the graph.

si and ti represent source and target vertices of i-th edge (directed) and di represents the cost of the i-th edge.

Output

If the graph contains a negative cycle (a cycle whose sum of edge costs is a negative value) which is reachable from the source r, print


NEGATIVE CYCLE


in a line.

Otherwise, print


c0
c1
:
c|V|-1


The output consists of |V| lines. Print the cost of the shortest path from the source r to each vertex 0, 1, ... |V|-1 in order. If there is no path from the source to a vertex, print "INF".

Examples

Input

4 5 0
0 1 2
0 2 3
1 2 -5
1 3 1
2 3 2


Output

0
2
-3
-1


Input

4 6 0
0 1 2
0 2 3
1 2 -5
1 3 1
2 3 2
3 1 0


Output

NEGATIVE CYCLE


Input

4 5 1
0 1 2
0 2 3
1 2 -5
1 3 1
2 3 2


Output

INF
0
-5
-3
from collections import defaultdict
import heapq

vertice,edge,source = map(int,input().split(" "))
link = defaultdict(dict)
weight = defaultdict(dict)
cost = [float("inf") for n in range(vertice)]
cost[source] = 0
for e in range(edge):
    i,j,w = map(int,input().split(" "))
    link[i] = link.get(i,set()) | {j}
    weight[i].update({j:w})

vertice_cnt = 0
while True:
    if vertice_cnt >= vertice:
        print("NEGATIVE CYCLE")
        break
    update = False
    for k,val in link.items():
        for v in val:
            if cost[v] > cost[k] + weight[k][v]:
                cost[v] = cost[k] + weight[k][v]
                update = True
    if not(update):
        for c in cost:
            print(c if c != float("inf") else "INF")
        break
    vertice_cnt += 1