As you know, an undirected connected graph with n nodes and n - 1 edges is called a tree. You are given an integer d and a tree consisting of n nodes. Each node i has a value ai associated with it.

We call a set S of tree nodes valid if following conditions are satisfied:

  1. S is non-empty.
  2. S is connected. In other words, if nodes u and v are in S, then all nodes lying on the simple path between u and v should also be presented in S.
  3. <image>.



Your task is to count the number of valid sets. Since the result can be very large, you must print its remainder modulo 1000000007 (109 + 7).

Input

The first line contains two space-separated integers d (0 ≤ d ≤ 2000) and n (1 ≤ n ≤ 2000).

The second line contains n space-separated positive integers a1, a2, ..., an(1 ≤ ai ≤ 2000).

Then the next n - 1 line each contain pair of integers u and v (1 ≤ u, v ≤ n) denoting that there is an edge between u and v. It is guaranteed that these edges form a tree.

Output

Print the number of valid sets modulo 1000000007.

Examples

Input

1 4
2 1 3 2
1 2
1 3
3 4


Output

8


Input

0 3
1 2 3
1 2
2 3


Output

3


Input

4 8
7 8 7 5 4 6 4 10
1 6
1 2
5 8
1 3
3 5
6 7
3 4


Output

41

Note

In the first sample, there are exactly 8 valid sets: {1}, {2}, {3}, {4}, {1, 2}, {1, 3}, {3, 4} and {1, 3, 4}. Set {1, 2, 3, 4} is not valid, because the third condition isn't satisfied. Set {1, 4} satisfies the third condition, but conflicts with the second condition.
def read_two_ints():
    a = raw_input()
    d, n = a.split(" ")
    n1 = int(d)
    n2 = int(n)
    return n1, n2

def read_int_list():
    lst = raw_input()
    lst = lst.split(" ")
    lst = [int(x) for x in lst]
    return lst


import collections

MOD = 1000000007

# Modified DFS. The third parameter prevents double counting
def explore_graph(minWeight, maxWeight, maxIdxInTie, weights, ady, idx, parent):
#    print idx
    includingOthers = 0
    for neighbor in ady[idx]:
        if neighbor == parent:
            continue
        if weights[neighbor] < minWeight or weights[neighbor] > maxWeight or \
                (weights[neighbor] == maxWeight and neighbor > maxIdxInTie):
            continue
        # Options we have re:going down that way, including not going down
        numAdy = explore_graph(minWeight, maxWeight, maxIdxInTie, weights, ady, neighbor,
                               idx) + 1
        if includingOthers > 0:
            includingOthers *= numAdy
            includingOthers = includingOthers % MOD
        else:
            includingOthers = numAdy
    if includingOthers == 0:
        includingOthers = 1
    return includingOthers % MOD

# Read the graph
d, n = read_two_ints()
weights = read_int_list()
verts = collections.defaultdict(list)
for _i in xrange(n - 1):
    v1, v2 = read_two_ints()
    v1 -= 1
    v2 -= 1
    verts[v1].append(v2)
    verts[v2].append(v1)

res = 0
for i in xrange(n):
    numGraphs = explore_graph(weights[i] - d, weights[i], i, weights, verts, i, None)
    res += numGraphs
#    print i, res
    res = res % MOD

print res