import sys
import numpy as np
from numba import njit

read = sys.stdin.buffer.read
readline = sys.stdin.buffer.readline
readlines = sys.stdin.buffer.readlines

A = 2

# ノード、重さ→価値
@njit('(i4,i4[:],i4[:])', cache=True)
def precompute(N, V, W):
    U = 10**5 + 10
    dp = np.zeros((A, U), np.int32)
    for v in range(1, min(A, N)):
        p = v // 2
        dp[v] = dp[p]
        dp[v, W[v]:] = np.maximum(dp[v, W[v]:], dp[p, :-W[v]] + V[v])
        for i in range(1, U):
            dp[v][i] = max(dp[v][i], dp[v][i - 1])
    return dp

@njit('(i4,i4[:],i4[:],i4[:],i4[:])', cache=True)
def main(N, V, W, v, L):
    dp = precompute(N, V, W)
    values = np.empty(1024, np.int32)
    weights = np.empty(1024, np.int32)

    def solve(i, lim, values, weights):
        if i < A:
            return dp[i][lim]
        values[0] = 0
        weights[0] = 0
        p = 0
        while i >= A:
            for j in range(1 << p):
                values[j + (1 << p)] = values[j] + V[i]
                weights[j + (1 << p)] = weights[j] + W[i]
            p += 1
            i >>= 1
        best = 0
        for n in range(1 << p):
            if weights[n] > lim:
                continue
            x = dp[i][lim - weights[n]] + values[n]
            best = max(best, x)
        return best

    Q = len(v)
    for i in range(Q):
        x = solve(v[i], L[i], values, weights)
        print(x)

N = int(readline())
stdin = np.array(read().split(), np.int32)
V = np.zeros(N + 1, np.int32)
W = np.zeros(N + 1, np.int32)
V[1:] = stdin[:N + N:2]
W[1:] = stdin[1:N + N:2]
query = stdin[N + N + 1:]
v, L = query[::2], query[1::2]

main(N, V, W, v, L)

### FIXED CODE ###

import sys
import numpy as np
from numba import njit

read = sys.stdin.buffer.read
readline = sys.stdin.buffer.readline
readlines = sys.stdin.buffer.readlines

# ノード、重さ→価値
@njit('(i4,i4[:],i4[:])', cache=True)
def precompute(N, V, W):
    U = 10**5 + 10
    dp = np.zeros((1024, U), np.int32)
    for v in range(1, min(1024, N + 1)):
        p = v // 2
        dp[v] = dp[p]
        dp[v, W[v]:] = np.maximum(dp[v, W[v]:], dp[p, :-W[v]] + V[v])
        for i in range(1, U):
            dp[v][i] = max(dp[v][i], dp[v][i - 1])
    return dp

@njit('(i4,i4[:],i4[:],i4[:],i4[:])', cache=True)
def main(N, V, W, v, L):
    dp = precompute(N, V, W)
    values = np.empty(1024, np.int32)
    weights = np.empty(1024, np.int32)

    def solve(i, lim, values, weights, dp):
        if i < 1024:
            return dp[i][lim]
        values[0] = 0
        weights[0] = 0
        p = 0
        while i >= 1024:
            for j in range(1 << p):
                values[j + (1 << p)] = values[j] + V[i]
                weights[j + (1 << p)] = weights[j] + W[i]
            p += 1
            i >>= 1
        best = 0
        for n in range(1 << p):
            if weights[n] > lim:
                continue
            x = dp[i][lim - weights[n]] + values[n]
            best = max(best, x)
        return best

    Q = len(v)
    for i in range(Q):
        x = solve(v[i], L[i], values, weights, dp)
        print(x)

N = int(readline())
stdin = np.array(read().split(), np.int32)
V = np.zeros(N + 1, np.int32)
W = np.zeros(N + 1, np.int32)
V[1:] = stdin[:N + N:2]
W[1:] = stdin[1:N + N:2]
query = stdin[N + N + 1:]
v, L = query[::2], query[1::2]

main(N, V, W, v, L)