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
inf = float('inf')
# ベルマンフォード法 計算量(VE)
# [引数]: 隣接リスト, 始点, 終点
class Bellmanford:
    def __init__(self, to:list, start:int, goal:int):
        self.N = len(to)
        self.to = [s[:] for s in to]
        self.start = start
        self.goal = goal
        self.dist = [inf] * self.N
        self.dist[start] = 0
        self.exists_negative_cycle = False
        self.exists_negative_cycle_stog = False
        self.is_updated = [False] * self.N

    # distを更新
    def update(self) -> None:
        for _ in range(self.N - 1):
            for v, s in enumerate(self.to):
                if not s: continue
                for nv, w in s:
                    if self.dist[nv] > self.dist[v] + w:
                        self.dist[nv] = self.dist[v] + w

    # グラフの負閉路検出
    def detection(self) -> bool:
        for v, s in enumerate(self.to):
            if not s: continue
            for nv, w in s:
                if self.dist[nv] > self.dist[v] + w:
                    self.dist[nv] = self.dist[v] + w
                    self.exists_negative_cycle = True
        return self.exists_negative_cycle

    # スタートからゴールまでのパスの負閉路検出
    def detection_stog(self) -> bool:
        for _ in range(self.N):
            for v, s in enumerate(self.to):
                if not s: continue
                for nv, w in s:
                    if self.dist[nv] > self.dist[v] + w:
                        self.dist[nv] = self.dist[v] + w
                        self.is_updated[nv] = True
                    if self.is_updated[v] is True:
                        self.is_updated[nv] = True
        self.exists_negative_cycle_stog = self.is_updated[self.goal]
        return self.exists_negative_cycle_stog

N, M, r = map(int,input().split())
to = [[] for _ in range(N)]
for _ in range(M):
    s, t, d = map(int,input().split())
    to[s].append((t, d))

BF = Bellmanford(to, r, -1)
BF.update()

if BF.detection():
    print("NEGATIVE CYCLE")
else:
    for d in BF.dist:
        if d == inf:
            print("INF")
        else:
            print(d)
