Write a program which manipulates a sequence A = {a1, a2, . . . , an} with the following operations:

* add(s, t, x): add x to as, as+1, ..., at.
* get(i): output the value of ai.



Note that the initial values of ai (i = 1, 2, . . . , n) are 0.

Constraints

* 1 ≤ n ≤ 100000
* 1 ≤ q ≤ 100000
* 1 ≤ s ≤ t ≤ n
* 1 ≤ i ≤ n
* 0 ≤ x ≤ 1000

Input


n q
query1
query2
:
queryq


In the first line, n (the number of elements in A) and q (the number of queries) are given. Then, ith query queryi is given in the following format:


0 s t x


or


1 t


The first digit represents the type of the query. '0' denotes add(s, t, x) and '1' denotes get(i).

Output

For each get operation, print the value.

Examples

Input

3 5
0 1 2 1
0 2 3 2
0 3 3 3
1 2
1 3


Output

3
5


Input

4 3
1 2
0 1 4 1
1 2


Output

0
1
import sys
input = sys.stdin.readline

class LazyPropSegmentTree:
    def __init__(self, lst, op, apply, comp, e, identity):
        self.n = len(lst)
        self.depth = (self.n - 1).bit_length()
        self.N = 1 << self.depth
        self.op = op # binary operation of elements
        self.apply = apply # function to apply to an element
        self.comp = comp # composition of functions
        self.e = e # identity element w.r.t. op
        self.identity = identity # identity element w.r.t. comp
        self.v = self._build(lst) # self.v is set to be 1-indexed for simplicity
        self.lazy = [self.identity] * (2 * self.N)
    
    def __getitem__(self, i):
        return self.fold(i, i+1)
    
    def _build(self, lst):
        # construction of a tree
        # total 2 * self.N elements (tree[0] is not used)
        tree = [self.e] * (self.N) + lst + [self.e] * (self.N - self.n)
        for i in range(self.N - 1, 0, -1): tree[i] = self.op(tree[i << 1], tree[(i << 1)|1])
        return tree
    
    def _indices(self, l, r):
        left = l + self.N; right = r + self.N
        left //= (left & (-left)); right //= (right & (-right))
        left >>= 1; right >>= 1
        while left != right:
            if left > right: yield left; left >>= 1
            else: yield right; right >>= 1
        while left > 0: yield left; left >>= 1
    
    # propagate self.lazy and self.v in a top-down manner
    def _propagate_topdown(self, *indices):
        identity, v, lazy, apply, comp = self.identity, self.v, self.lazy, self.apply, self.comp
        for k in reversed(indices):
            x = lazy[k]
            if x == identity: continue
            lazy[k << 1] = comp(lazy[k << 1], x)
            lazy[(k << 1)|1] = comp(lazy[(k << 1)|1], x)
            v[k << 1] = apply(v[k << 1], x)
            v[(k << 1)|1] = apply(v[(k << 1)|1], x)
            lazy[k] = identity # propagated

    # propagate self.v in a bottom-up manner
    def _propagate_bottomup(self, indices):
        v, op = self.v, self.op
        for k in indices: v[k] = op(v[k << 1], v[(k << 1)|1])

    # update for the query interval [l, r) with function x
    def update(self, l, r, x):
        *indices, = self._indices(l, r)
        self._propagate_topdown(*indices)
        
        N, v, lazy, apply, comp = self.N, self.v, self.lazy, self.apply, self.comp
        
        # update self.v and self.lazy for the query interval [l, r)
        left = l + N; right = r + N
        if left & 1: v[left] = apply(v[left], x); left += 1
        if right & 1: right -= 1; v[right] = apply(v[right], x)
        left >>= 1; right >>= 1
        while left < right:
            if left & 1:
                lazy[left] = comp(lazy[left], x)
                v[left] = apply(v[left], x)
                left += 1
            if right & 1:
                right -= 1
                lazy[right] = comp(lazy[right], x)
                v[right] = apply(v[right], x)
            left >>= 1; right >>= 1
        self._propagate_bottomup(indices)
    
    # returns answer for the query interval [l, r)
    def fold(self, l, r):
        self._propagate_topdown(*self._indices(l, r))
        
        e, N, v, op = self.e, self.N, self.v, self.op
        
        # calculate the answer for the query interval [l, r)
        left = l + N; right = r + N
        L = R = e
        while left < right:
            if left & 1: # self.v[left] is the right child
                L = op(L, v[left])
                left += 1
            if right & 1: # self.v[right-1] is the left child
                right -= 1
                R = op(v[right], R)
            left >>= 1; right >>= 1
        return op(L, R)

N, Q = map(int, input().split())
op = lambda x, y: x+y
apply = lambda x, f: x+f
comp = lambda f, g: f+g
e = 0
identity = 0
A = [e] * N
lpsg = LazyPropSegmentTree(A, op, apply, comp, e, identity)
ans = []
for _ in range(Q):
    t, *arg, = map(int, input().split())
    if t == 0:
        s, t, x = arg
        lpsg.update(s-1, t, x)
    else:
        ans.append(lpsg[arg[0]-1])
print('\n'.join(map(str, ans)))
