THRBL - Catapult that ball

Bob has unusual problem. In Byteland we can find a lot of hills and cities. King of Byteland ordered Bob to deliver magic balls from one city to another. Unfortunately, Bob has to deliver many magic balls, so walking with them would take too much time for him. Bob came up with great idea - catapulting them.

Byteland is divided into intervals. Each interval contains city and hill.

Bob can catapult magic ball accurately from city A to city B, if between them there isn't higher hill than A's hill.

Input

Every test case contains N and M (N ≤ 50000, M ≤ 50000), number of intervals and number of balls.

In next line there's N numbers H (H ≤ 109) separated by one space.

In next M lines numbers A and B (1 ≤ A, B ≤ N), number of city from which we want to catapult the ball and number of city to which we want to catapult the ball.

Output

Write one number - number of magic balls that Bob can catapult successfully.

Example

Input:
7 3
2 3 5 4 2 1 6
3 5
2 5
4 6

Output:
2

Explanation

Bob can catapult balls numbered 1 and 3.


Added by:Krzysztof Lewko
Date:2011-05-25
Time limit:1s
Source limit:50000B
Memory limit:1536MB
Cluster: Cube (Intel G860)
Languages:All except: ASM64

hide comments
2021-01-08 21:26:14
AC with Sparse Table. You can use Segment Tree or Binary Indexed Tree to solve this problem.
2020-10-27 05:13:07
AC using stack
2020-08-23 20:37:17
Can be done using Sparse Table.
Quick Remainder - take extra care for edge cases, when A = B and B - A = 1.
Also, it's (A, B) not [A, B].
2020-08-20 19:31:13
Plain basic minimum range query required. 0.05 s using sparse table algorithm
2020-08-07 14:22:06
took me 5 tries look for edge cases
2020-04-01 13:31:46
Not always (A<B) can be (B < A).
2020-01-24 16:42:27
between means after A and before B
(A,B) not [A,B]

Last edit: 2020-01-24 16:49:31
2019-07-29 05:45:59 Vinod Kollipara
is anybody able to submit sparse table based solution in java
2019-05-29 05:14:33
Accepted, but how to solve this with binary concept?
2019-05-25 12:13:13
AC in one go using sparse table
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