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.

class Graph:

    def __init__(self, n_vertices, edges, directed=True):
        self.n_vertices = n_vertices
        self.edges = edges
        self.directed = directed

    @property
    def adj(self):
        try:
            return self._adj
        except AttributeError:
            adj = [[] for _ in range(self.n_vertices)]
            if self.directed:
                for u,v in self.edges:
                    adj[u].append(v)
            else:
                for u,v in self.edges:
                    adj[u].append(v)
                    adj[v].append(u)
            self._adj = adj
            return adj

class RootedTree(Graph):
    def __init__(self, n_vertices, edges, root_vertex=0):
        self.root = root_vertex
        super().__init__(n_vertices, edges, False)

    @property
    def parent(self):
        try:
            return self._parent
        except AttributeError:
            adj = self.adj
            parent = [None]*self.n_vertices
            parent[self.root] = -1
            stack = [self.root]
            for _ in range(self.n_vertices):
                v = stack.pop()
                for u in adj[v]:
                    if parent[u] is None:
                        parent[u] = v
                        stack.append(u)
            self._parent = parent
            return parent

    @property
    def children(self):
        try:
            return self._children
        except AttributeError:
            children = [None]*self.n_vertices
            for v,(l,p) in enumerate(zip(self.adj,self.parent)):
                children[v] = [u for u in l if u != p]
            self._children = children
            return children

    @property
    def dfs_order(self):
        try:
            return self._dfs_order
        except AttributeError:
            order = [None]*self.n_vertices
            children = self.children
            stack = [self.root]
            for i in range(self.n_vertices):
                v = stack.pop()
                order[i] = v
                for u in children[v]:
                    stack.append(u)
            self._dfs_order = order
            return order



from functools import reduce
from itertools import accumulate,chain
def rerooting(rooted_tree, merge, identity, finalize):
    N = rooted_tree.n_vertices
    parent = rooted_tree.parent
    children = rooted_tree.children
    order = rooted_tree.dfs_order

    # from leaf to parent
    dp_down = [None]*N
    for v in reversed(order):
        dp_down[v] = finalize(reduce(merge,
            (dp_down[c] for c in children[v]),
            identity), parent[v], v)

    # from parent to leaf
    dp_up = [None]*N
    dp_up[0] = identity
    for v in order:
        if len(children[v]) == 0:
            continue
        temp = (dp_up[v],)+tuple(dp_down[u] for u in children[v])+(identity,)
        left = accumulate(temp[:-2],merge)
        right = tuple(accumulate(reversed(temp[2:]),merge))
        for u,l,r in zip(children[v],left,reversed(right)):
            dp_up[u] = finalize(merge(l,r), u, v)

    res = [None]*N
    for v,l in enumerate(children):
        res[v] = reduce(merge,
                    (dp_down[u] for u in children[v]),
                    identity)
        res[v] = finalize(merge(res[v], dp_up[v]), -1, v)
    return res,dp_up,dp_down

import sys
read = sys.stdin.buffer.read
readline = sys.stdin.buffer.readline

if __name__ == '__main__':
    n = int(readline())
    color = tuple(map(int,readline().split()))
    temp = map(lambda x:int(x)-1, read().split())
    edges = zip(temp,temp)

    min2 = lambda x,y: x if x < y else y
    t = RootedTree(n, edges)

    def merge(x,y):
        b1, w1, s1 = x
        b2, w2, s2 = y
        return b1+b2, w1+w2, s1+s2

    def finalize(x,u,v):
        b, w, s = x
        if color[v]:
            w += 1
        else:
            b += 1
        if u >= 0 and w-b < s:
            s = w-b
        return (b,w,s)


    e = sum(color)*2 - n

    res,_,_ = rerooting(t, merge, (0,0,0), finalize)
    print(*(e-s for _,_,s in res))
