Phoenix has a string s consisting of lowercase Latin letters. He wants to distribute all the letters of his string into k non-empty strings a_1, a_2, ..., a_k such that every letter of s goes to exactly one of the strings a_i. The strings a_i do not need to be substrings of s. Phoenix can distribute letters of s and rearrange the letters within each string a_i however he wants.

For example, if s =  baba and k=2, Phoenix may distribute the letters of his string in many ways, such as: 

  * ba and ba
  * a and abb
  * ab and ab
  * aa and bb



But these ways are invalid: 

  * baa and ba
  * b and ba
  * baba and empty string (a_i should be non-empty) 



Phoenix wants to distribute the letters of his string s into k strings a_1, a_2, ..., a_k to minimize the lexicographically maximum string among them, i. e. minimize max(a_1, a_2, ..., a_k). Help him find the optimal distribution and print the minimal possible value of max(a_1, a_2, ..., a_k).

String x is lexicographically less than string y if either x is a prefix of y and x ≠ y, or there exists an index i (1 ≤ i ≤ min(|x|, |y|)) such that x_i < y_i and for every j (1 ≤ j < i) x_j = y_j. Here |x| denotes the length of the string x.

Input

The input consists of multiple test cases. The first line contains an integer t (1 ≤ t ≤ 1000) — the number of test cases. Each test case consists of two lines.

The first line of each test case consists of two integers n and k (1 ≤ k ≤ n ≤ 10^5) — the length of string s and the number of non-empty strings, into which Phoenix wants to distribute letters of s, respectively.

The second line of each test case contains a string s of length n consisting only of lowercase Latin letters.

It is guaranteed that the sum of n over all test cases is ≤ 10^5.

Output

Print t answers — one per test case. The i-th answer should be the minimal possible value of max(a_1, a_2, ..., a_k) in the i-th test case.

Example

Input


6
4 2
baba
5 2
baacb
5 3
baacb
5 3
aaaaa
6 4
aaxxzz
7 1
phoenix


Output


ab
abbc
b
aa
x
ehinopx

Note

In the first test case, one optimal solution is to distribute baba into ab and ab. 

In the second test case, one optimal solution is to distribute baacb into abbc and a.

In the third test case, one optimal solution is to distribute baacb into ac, ab, and b.

In the fourth test case, one optimal solution is to distribute aaaaa into aa, aa, and a.

In the fifth test case, one optimal solution is to distribute aaxxzz into az, az, x, and x.

In the sixth test case, one optimal solution is to distribute phoenix into ehinopx.
#########			##	##     ##    	  ####  #####  ##     #  ##     #		##
	#			   # #	# #   # #		 #	  #	#	#  # #    #  # #    #	   # #
	#			  #  #	#  ###  #	    #		#	#  #  #   #  #  #   #	  #  #
	#			 #####	#	#	#	   #    ###	#	#  #   #  #  #   #  #    #####
	#			#    #	#		#	   #    # #	#	#  #	# #  #	  # #   #    #  
######### 	   #     # 	#		#		##### #	#####  #	 ##  #	   ##  #     #

"""

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
read = lambda: map(int, input().split())
read_float = lambda: map(float, input().split())
# 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) // math.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;

 
## 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

# Euler's Toitent Function phi
def phi(n) : 
  
    result = n 
    p = 2
    while(p * p<= n) : 
        if (n % p == 0) : 
            while (n % p == 0) : 
                n = n // p 
            result = result * (1.0 - (1.0 / (float) (p))) 
        p = p + 1
    if (n > 1) : 
        result = result * (1.0 - (1.0 / (float)(n))) 
   
    return (int)(result) 

def is_prime(n):
	if n == 0:
		return False
	if n == 1:
		return True
	for i in range(2, int(n ** (1 / 2)) + 1):
		if not n % i:
			return False
 
	return True
 
#### 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)

def factors(n):
	res = []
	for i in range(1, int(n ** 0.5) + 1):
		if n % i == 0:
			res.append(i)
			res.append(n // i)
	return list(set(res))
 
## 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();

def binary_search(low, high, w, h, n):
	while low < high:
		mid = low + (high - low) // 2
		# print(low, mid, high)
		if check(mid, w, h, n):
			low = mid + 1
		else:
			high = mid
	return low

## for checking any conditions
def check(councils, a, k):
	summ = 0
	for x in a:
		summ += min(x, councils)
	return summ // councils >= k
	

 
#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
import bisect as bis
import random
import sys

def contains(s):
	s = list(s)
	c = 0
	for i in range(len(s) - 6):
		if "".join(s[i: i + 7]) == 'abacaba':
			c += 1
	return c

def process(s):
	ans = ""
	for x in s:
		if x == '?':
			ans = ans + 'd'
		else:
			ans = ans + x
	return ans

def solve():
	n, k = read()
	s = input().rstrip()
	news = "".join(list(sorted(s)))
	# print(ans)
	if news[0] != news[k - 1]:
		print(news[k - 1])
	elif k < n and news[k] == news[-1]:
		print(news[0] + news[k] * ((n - k) // k + (((n - k) % k) > 0)))
	else:
		print(news[0] + news[k:])
	

if __name__ == '__main__':
	for _ in range(int(input())):
		solve()
	# fin_time = datetime.now()
# 	print("Execution time (for loop): ", (fin_time-init_time))
