The protection of a popular program developed by one of IT City companies is organized the following way. After installation it outputs a random five digit number which should be sent in SMS to a particular phone number. In response an SMS activation code arrives.

A young hacker Vasya disassembled the program and found the algorithm that transforms the shown number into the activation code. Note: it is clear that Vasya is a law-abiding hacker, and made it for a noble purpose — to show the developer the imperfection of their protection.

The found algorithm looks the following way. At first the digits of the number are shuffled in the following order <first digit><third digit><fifth digit><fourth digit><second digit>. For example the shuffle of 12345 should lead to 13542. On the second stage the number is raised to the fifth power. The result of the shuffle and exponentiation of the number 12345 is 455 422 043 125 550 171 232. The answer is the 5 last digits of this result. For the number 12345 the answer should be 71232.

Vasya is going to write a keygen program implementing this algorithm. Can you do the same?

Input

The only line of the input contains a positive integer five digit number for which the activation code should be found.

Output

Output exactly 5 digits without spaces between them — the found activation code of the program.

Examples

Input

12345


Output

71232
#########			##	##     ##    	  ####  #####  ##     #  ##     #		##
	#			   # #	# #   # #		 #	  #	#	#  # #    #  # #    #	   # #
	#			  #  #	#  ###  #	    #		#	#  #  #   #  #  #   #	  #  #
	#			 #####	#	#	#	   #    ###	#	#  #   #  #  #   #  #    #####
	#			#    #	#		#	   #    # #	#	#  #	# #  #	  # #   #    #  
######### 	   #     # 	#		#		##### #	#####  #	 ##  #	   ##  #     #

"""

PPPPPPP       RRRRRRR		    OOOO	  VV        VV    EEEEEEEEEE
PPPPPPPP      RRRRRRRR         OOOOOO     VV       VV	  EE
PPPPPPPPP     RRRRRRRRR       OOOOOOOO    VV      VV	  EE
PPPPPPPP      RRRRRRRR        OOOOOOOO    VV     VV    	  EEEEEE
PPPPPPP       RRRRRRR         OOOOOOOO    VV    VV        EEEEEEE
PP  		  RRRR			  OOOOOOOO    VV   VV         EEEEEE
PP			  RR  RR          OOOOOOOO    VV  VV          EE
PP			  RR    RR         OOOOOO     VV VV           EE
PP			  RR      RR        OOOO      VVVV            EEEEEEEEEE

"""



"""
 Perfection is achieved not when there is nothing more to add, but rather when there is nothing more to take away.
"""
import sys
input = sys.stdin.readline
# from bisect import bisect_left as lower_bound;
# from bisect import bisect_right as upper_bound;
# from math import ceil, factorial;
 
def ceil(x):
    if x != int(x):
        x = int(x) + 1
    return x
 
def factorial(x, m):
	val = 1
	while x>0:
		val = (val * x) % m
		x -= 1
	return val

def fact(x):
	val = 1
	while x > 0:
		val *= x
		x -= 1
	return val
    
# swap_array function
def swaparr(arr, a,b):
    temp = arr[a];
    arr[a] = arr[b];
    arr[b] = temp;
 
## gcd function
def gcd(a,b):
    if b == 0:
        return a;
    return gcd(b, a % b);

## lcm function
def lcm(a, b):
	return (a * b) // gcd(a, b)
 
## nCr function efficient using Binomial Cofficient
def nCr(n, k): 
	if k > n:
		return 0
	if(k > n - k):
		k = n - k
	res = 1
	for i in range(k):
		res = res * (n - i)
		res = res / (i + 1)
	return int(res)
 
## upper bound function code -- such that e in a[:i] e < x;
def upper_bound(a, x, lo=0, hi = None):
    if hi == None:
        hi = len(a);
    while lo < hi:
        mid = (lo+hi)//2;
        if a[mid] < x:
            lo = mid+1;
        else:
            hi = mid;
    return lo;
 
## prime factorization
def primefs(n):
    ## if n == 1    ## calculating primes
    primes = {}
    while(n%2 == 0 and n > 0):
        primes[2] = primes.get(2, 0) + 1
        n = n//2
    for i in range(3, int(n**0.5)+2, 2):
        while(n%i == 0 and n > 0):
            primes[i] = primes.get(i, 0) + 1
            n = n//i
    if n > 2:
        primes[n] = primes.get(n, 0) + 1
    ## prime factoriazation of n is stored in dictionary
    ## primes and can be accesed. O(sqrt n)
    return primes
 
## MODULAR EXPONENTIATION FUNCTION
def power(x, y, p): 
    res = 1
    x = x % p  
    if (x == 0) : 
        return 0
    while (y > 0) : 
        if ((y & 1) == 1) : 
            res = (res * x) % p 
        y = y >> 1      
        x = (x * x) % p 
    return res 
 
## DISJOINT SET UNINON FUNCTIONS
def swap(a,b):
    temp = a
    a = b
    b = temp
    return a,b;
 
# find function with path compression included (recursive)
# def find(x, link):
#     if link[x] == x:
#         return x
#     link[x] = find(link[x], link);
#     return link[x];
 
# find function with path compression (ITERATIVE)
def find(x, link):
    p = x;
    while( p != link[p]):
        p = link[p];
    
    while( x != p):
        nex = link[x];
        link[x] = p;
        x = nex;
    return p;
 
 
# the union function which makes union(x,y)
# of two nodes x and y
def union(x, y, link, size):
    x = find(x, link)
    y = find(y, link)
    if size[x] < size[y]:
        x,y = swap(x,y)
    if x != y:
        size[x] += size[y]
        link[y] = x
 
## returns an array of boolean if primes or not USING SIEVE OF ERATOSTHANES
def sieve(n): 
    prime = [True for i in range(n+1)] 
    prime[0], prime[1] = False, False
    p = 2
    while (p * p <= n): 
        if (prime[p] == True): 
            for i in range(p * p, n+1, p):
                prime[i] = False
        p += 1
    return prime
 
#### PRIME FACTORIZATION IN O(log n) using Sieve ####
MAXN = int(1e5 + 5)
def spf_sieve():
    spf[1] = 1;
    for i in range(2, MAXN):
        spf[i] = i;
    for i in range(4, MAXN, 2):
        spf[i] = 2;
    for i in range(3, ceil(MAXN ** 0.5), 2):
        if spf[i] == i:
            for j in range(i*i, MAXN, i):
                if spf[j] == j:
                    spf[j] = i;
    ## function for storing smallest prime factors (spf) in the array
 
################## un-comment below 2 lines when using factorization #################
spf = [0 for i in range(MAXN)]
# spf_sieve();
def factoriazation(x):
    res = []
    for i in range(2, int(x ** 0.5) + 1):
    	while x % i == 0:
    		res.append(i)
    		x //= i
    if x != 1:
   		res.append(x)
    return res
    ## this function is useful for multiple queries only, o/w use
    ## primefs function above. complexity O(log n)
 
## taking integer array input
def int_array():
    return list(map(int, input().strip().split()));
 
def float_array():
    return list(map(float, input().strip().split()));
 
## taking string array input
def str_array():
    return input().strip().split();
 
#defining a couple constants
MOD = int(1e9)+7;
CMOD = 998244353;
INF = float('inf'); NINF = -float('inf');
 
################### ---------------- TEMPLATE ENDS HERE ---------------- ###################
 
from itertools import permutations
import math

from bisect import bisect_left


def solve():
	s = input()
	s = s[0] + s[2] + s[4] + s[3] + s[1]
	n = int(s)
	# print(n)
	y = n ** 5 % 10 ** 5
	print(str(y) + '0'*(len(s) - len(str(y))))
if __name__ == '__main__':
	for _ in range(1):
		solve()
	# fin_time = datetime.now()
# 	print("Execution time (for loop): ", (fin_time-init_time))
