Problem:
Score : 400 points

Problem Statement

You are given a tree with N vertices.

Here, a tree is a kind of graph, and more specifically, a connected undirected graph with N-1 edges, where N is the number of its vertices.

The i-th edge (1≤i≤N-1) connects Vertices a_i and b_i, and has a length of c_i.

You are also given Q queries and an integer K. In the j-th query (1≤j≤Q):

find the length of the shortest path from Vertex x_j and Vertex y_j via Vertex K.

Constraints

3≤N≤10^5

1≤a_i,b_i≤N (1≤i≤N-1)

1≤c_i≤10^9 (1≤i≤N-1)

The given graph is a tree.

1≤Q≤10^5

1≤K≤N

1≤x_j,y_j≤N (1≤j≤Q)

x_j≠y_j (1≤j≤Q)

x_j≠K,y_j≠K (1≤j≤Q)

Input

Input is given from Standard Input in the following format:

N
a_1 b_1 c_1
:
a_{N-1} b_{N-1} c_{N-1}
Q K
x_1 y_1
:
x_{Q} y_{Q}

Output

Print the responses to the queries in Q lines.

In the j-th line j(1≤j≤Q), print the response to the j-th query.

Sample Input 1

5
1 2 1
1 3 1
2 4 1
3 5 1
3 1
2 4
2 3
4 5

Sample Output 1

3
2
4

The shortest paths for the three queries are as follows:

Query 1: Vertex 2 → Vertex 1 → Vertex 2 → Vertex 4 : Length 1+1+1=3

Query 2: Vertex 2 → Vertex 1 → Vertex 3 : Length 1+1=2

Query 3: Vertex 4 → Vertex 2 → Vertex 1 → Vertex 3 → Vertex 5 : Length 1+1+1+1=4

Sample Input 2

7
1 2 1
1 3 3
1 4 5
1 5 7
1 6 9
1 7 11
3 2
1 3
4 5
6 7

Sample Output 2

5
14
22

The path for each query must pass Vertex K=2.

Sample Input 3

10
1 2 1000000000
2 3 1000000000
3 4 1000000000
4 5 1000000000
5 6 1000000000
6 7 1000000000
7 8 1000000000
8 9 1000000000
9 10 1000000000
1 1
9 10

Sample Output 3

17000000000

Solution in Python (3.4.3) (judge verdict: Time Limit Exceeded)

from collections import defaultdict
from heapq import heappop, heappush

class Graph(object):
    def __init__(self):
        self.graph = defaultdict(list)

    def __len__(self):
        return len(self.graph)

    def add_edge(self, src, dst, weight=1):
        self.graph[src].append((dst, weight))

    def get_nodes(self):
        return self.graph.keys()


class Dijkstra(object):
    def __init__(self, graph, start):
        self.g = graph.graph
        self.dist = defaultdict(lambda: float('inf'))
        self.dist[start] = 0
        self.prev = defaultdict(lambda: None)
        self.Q = []
        heappush(self.Q, (self.dist[start], start))

        while self.Q:
            dist_u, u = heappop(self.Q)
            if self.dist[u] < dist_u:
                continue
            for v, weight in self.g[u]:
                alt = dist_u + weight
                if self.dist[v] > alt:
                    self.dist[v] = alt
                    self.prev[v] = u
                    heappush(self.Q, (alt, v))

    def shortest_distance(self, goal):
        return self.dist[goal]

    def shortest_path(self, goal):
        path = []
        node = goal
        while node is not None:
            path.append(node)
            node = self.prev[node]
        return path[::-1]


n = int(input())
g = Graph()
for _ in range(n-1):
  a, b, c = map(int, input().split())
  g.add_edge(a-1, b-1, c)
  g.add_edge(b-1, a-1, c)

q, k = map(int, input().split())
for _ in range(q):
  x, y = map(int, input().split())
  d1 = Dijkstra(g, x-1)
  dist_1 = d1.shortest_distance(k-1)
  d2 = Dijkstra(g, k-1)
  dist_2 = d2.shortest_distance(y-1)
  print(dist_1 + dist_2)