Problem: You are given a tree consisting of n vertices. A tree is a connected undirected graph with n-1 edges. Each vertex v of this tree has a color assigned to it (a_v = 1 if the vertex v is white and 0 if the vertex v is black).

You have to solve the following problem for each vertex v: what is the maximum difference between the number of white and the number of black vertices you can obtain if you choose some subtree of the given tree that contains the vertex v? The subtree of the tree is the connected subgraph of the given tree. More formally, if you choose the subtree that contains cnt_w white vertices and cnt_b black vertices, you have to maximize cnt_w - cnt_b.

Input

The first line of the input contains one integer n (2 ≤ n ≤ 2 ⋅ 10^5) — the number of vertices in the tree.

The second line of the input contains n integers a_1, a_2, ..., a_n (0 ≤ a_i ≤ 1), where a_i is the color of the i-th vertex.

Each of the next n-1 lines describes an edge of the tree. Edge i is denoted by two integers u_i and v_i, the labels of vertices it connects (1 ≤ u_i, v_i ≤ n, u_i ≠ v_i).

It is guaranteed that the given edges form a tree.

Output

Print n integers res_1, res_2, ..., res_n, where res_i is the maximum possible difference between the number of white and black vertices in some subtree that contains the vertex i.

Examples

Input


9
0 1 1 1 0 0 0 0 1
1 2
1 3
3 4
3 5
2 6
4 7
6 8
5 9


Output


2 2 2 2 2 1 1 0 2 


Input


4
0 0 1 0
1 2
1 3
1 4


Output


0 -1 1 -1 

Note

The first example is shown below:

<image>

The black vertices have bold borders.

In the second example, the best subtree for vertices 2, 3 and 4 are vertices 2, 3 and 4 correspondingly. And the best subtree for the vertex 1 is the subtree consisting of vertices 1 and 3.

Solution (in PYTHON3):

Solution:
class WhiteSubtree:
    def __init__(self, vertex_is_white, edges, root=1):
        self.vertex_is_white = vertex_is_white
        self.root = root
        self.adj = self.__build_adj_list__(edges)

        self.subtree_best_polarity = self.__compute_subtree_best_polarity__()
        self.score_at_nodes = self.__compute_final_score_at_nodes__()

    def __build_adj_list__(self, edges):
        n = len(self.vertex_is_white) - 1
        adj = [[] for _ in range(n + 1)]
        adj[0] = None
        for v1, v2 in edges:
            adj[v1].append(v2)
            adj[v2].append(v1)
        return adj

    def __compute_subtree_best_polarity__(self):
        n = len(self.vertex_is_white) - 1
        subtree_best_polarity = [None for _ in range(n + 1)]
        visited = [False for _ in range(n + 1)]
        stack = [(self.root, None)]

        while len(stack) > 0:
            u, up = stack[-1]
            if not visited[u]:
                for v in self.adj[u]:
                    if v != up:
                        stack.append((v, u))
                visited[u] = True
            else:
                node_score = 1 if self.vertex_is_white[u] else -1
                for v in self.adj[u]:
                    if v != up:
                        node_score += max(0, subtree_best_polarity[v])
                subtree_best_polarity[u] = node_score
                stack.pop()
        return subtree_best_polarity

    def __compute_final_score_at_nodes__(self):
        subtree_best_polarity = self.subtree_best_polarity
        n = len(self.vertex_is_white) - 1
        score_at_nodes = [None for _ in range(n + 1)]
        stack = [(self.root, None, 0)]
        while len(stack) > 0:
            u, up, contrib_from_parent = stack.pop()
            score_at_nodes[u] = subtree_best_polarity[u] + contrib_from_parent
            for v in self.adj[u]:
                if v != up:
                    contrib_to_parent = max(subtree_best_polarity[v], 0)
                    stack.append((v, u, max(score_at_nodes[u] - contrib_to_parent, 0)))
        return score_at_nodes


def construct_tree():
    n = int(input())
    vertex_is_white = [int(elm.strip()) == 1 for elm in input().split()]
    vertex_is_white = [[]] + vertex_is_white
    edges = []
    for _ in range(n - 1):
        v1, v2 = [int(elm.strip()) for elm in input().split()]
        edges.append((v1, v2))
    return WhiteSubtree(vertex_is_white, edges)


tree = construct_tree()
scores = tree.score_at_nodes[1: ]
print(' '.join([str(elm) for elm in scores]))