Problem: A string is called diverse if it contains consecutive (adjacent) letters of the Latin alphabet and each letter occurs exactly once. For example, the following strings are diverse: "fced", "xyz", "r" and "dabcef". The following string are not diverse: "az", "aa", "bad" and "babc". Note that the letters 'a' and 'z' are not adjacent.

Formally, consider positions of all letters in the string in the alphabet. These positions should form contiguous segment, i.e. they should come one by one without any gaps. And all letters in the string should be distinct (duplicates are not allowed).

You are given a sequence of strings. For each string, if it is diverse, print "Yes". Otherwise, print "No".

Input

The first line contains integer n (1 ≤ n ≤ 100), denoting the number of strings to process. The following n lines contains strings, one string per line. Each string contains only lowercase Latin letters, its length is between 1 and 100, inclusive.

Output

Print n lines, one line per a string in the input. The line should contain "Yes" if the corresponding string is diverse and "No" if the corresponding string is not diverse. You can print each letter in any case (upper or lower). For example, "YeS", "no" and "yES" are all acceptable.

Example

Input


8
fced
xyz
r
dabcef
az
aa
bad
babc


Output


Yes
Yes
Yes
Yes
No
No
No
No

Solution (in PYTHON3):

Solution:
''' CODED WITH LOVE BY SATYAM KUMAR '''

from sys import stdin, stdout
import cProfile, math
from collections import Counter,defaultdict
from bisect import bisect_left,bisect,bisect_right
import itertools
from copy import deepcopy
from fractions import Fraction
import sys, threading
import operator as op
from functools import reduce
sys.setrecursionlimit(10**6) # max depth of recursion
threading.stack_size(2**27)  # new thread will get stack of such size
fac_warmup = False
printHeap = str()
memory_constrained = False
P = 10**9+7
import sys

class merge_find:
    def __init__(self,n):
        self.parent = list(range(n))
        self.size = [1]*n
        self.num_sets = n
        self.lista = [[_] for _ in range(n)]
    def find(self,a):
        to_update = []
        while a != self.parent[a]:
            to_update.append(a)
            a = self.parent[a]
        for b in to_update:
            self.parent[b] = a
        return self.parent[a]
    def merge(self,a,b):
        a = self.find(a)
        b = self.find(b)
        if a==b:
            return
        if self.size[a]<self.size[b]:
            a,b = b,a
        self.num_sets -= 1
        self.parent[b] = a
        self.size[a] += self.size[b]
        self.lista[a] += self.lista[b]
    def set_size(self, a):
        return self.size[self.find(a)]
    def __len__(self):
        return self.num_sets

def display(string_to_print):
    stdout.write(str(string_to_print) + "\n")

def primeFactors(n): #n**0.5 complex 
    factors = dict()
    for i in range(2,math.ceil(math.sqrt(n))+1):  
        while n % i== 0: 
            if i in factors:
                factors[i]+=1
            else: factors[i]=1
            n = n // i 
    if n>2:
        factors[n]=1
    return (factors)

def fibonacci_modP(n,MOD):
    if n<2: return 1
    #print (n,MOD)
    return (cached_fn(fibonacci_modP, (n+1)//2, MOD)*cached_fn(fibonacci_modP, n//2, MOD) + cached_fn(fibonacci_modP, (n-1) // 2, MOD)*cached_fn(fibonacci_modP, (n-2) // 2, MOD)) % MOD

def factorial_modP_Wilson(n , p): 
    if (p <= n): 
        return 0
    res = (p - 1) 
    for i in range (n + 1, p): 
        res = (res * cached_fn(InverseEuler,i, p)) % p 
    return res 

def binary(n,digits = 20):
    b = bin(n)[2:]
    b = '0'*(20-len(b))+b
    return b

def isprime(n):
    """Returns True if n is prime."""
    if n < 4:
        return True
    if n % 2 == 0:
        return False
    if n % 3 == 0:
        return False
    i = 5
    w = 2
    while i * i <= n:
        if n % i == 0:
            return False
        i += w
        w = 6 - w
    return True
factorial_modP = []
def warm_up_fac(MOD):
    global factorial_modP,fac_warmup
    if fac_warmup: return
    factorial_modP= [1 for _ in range(fac_warmup_size+1)]
    for i in range(2,fac_warmup_size):
        factorial_modP[i]= (factorial_modP[i-1]*i) % MOD
    fac_warmup = True

def InverseEuler(n,MOD):
    return pow(n,MOD-2,MOD)

def nCr(n, r, MOD):
    global fac_warmup,factorial_modP
    if not fac_warmup:
        warm_up_fac(MOD)
        fac_warmup = True
    return (factorial_modP[n]*((pow(factorial_modP[r], MOD-2, MOD) * pow(factorial_modP[n-r], MOD-2, MOD)) % MOD)) % MOD

def test_print(*args):
    if testingMode:
        print(args)

def display_list(list1, sep=" "):
    stdout.write(sep.join(map(str, list1)) + "\n")

def display_2D_list(li):
    for i in li:
        print(i)
def prefix_sum(li):
    sm = 0
    res = []
    for i in li:
        sm+=i
        res.append(sm)
    return res

def get_int():
    return int(stdin.readline().strip())

def get_tuple():
    return map(int, stdin.readline().split())

def get_list():
    return list(map(int, stdin.readline().split()))
import heapq,itertools
pq = []                         # list of entries arranged in a heap
entry_finder = {}               # mapping of tasks to entries
REMOVED = '<removed-task>' 
def add_task(task, priority=0):
    'Add a new task or update the priority of an existing task'
    if task in entry_finder:
        remove_task(task)
    count = next(counter)
    entry = [priority, count, task]
    entry_finder[task] = entry
    heapq.heappush(pq, entry)

def remove_task(task):
    'Mark an existing task as REMOVED.  Raise KeyError if not found.'
    entry = entry_finder.pop(task)
    entry[-1] = REMOVED

def pop_task():
    'Remove and return the lowest priority task. Raise KeyError if empty.'
    while pq:
        priority, count, task = heapq.heappop(pq)
        if task is not REMOVED:
            del entry_finder[task]
            return task
    raise KeyError('pop from an empty priority queue')
memory = dict()
def clear_cache():
    global memory
    memory = dict()
def cached_fn(fn, *args):
    global memory
    if args in memory:
        return memory[args]
    else:
        result = fn(*args)
        memory[args] = result
        return result

def ncr (n,r):
    return math.factorial(n)/(math.factorial(n-r)*math.factorial(r))
def binary_serach(i,li):
    #print("Search for ",i)
    fn = lambda x: li[x]-x//i
    x = -1
    b = len(li)
    while b>=1:
        #print(b,x)
        while b+x<len(li) and fn(b+x)>0: #Change this condition 2 to whatever you like
            x+=b
        b=b//2
    return x

# -------------------------------------------------------------- MAIN PROGRAM
TestCases = True
testingMode = False
fac_warmup_size = 10**5+100
optimiseForReccursion = True #Can not be used clubbed with TestCases # WHen using recursive functions, use Python 3
from math import factorial


def main():
    st = list(input())
    st.sort()
    a = ord(st[0])-1
    for i in st:
        if ord(i)!=a+1:
            print("NO")
            return
        a+=1
    print("YES")
    
    
# --------------------------------------------------------------------- END=


if TestCases: 
    for _ in range(get_int()): 
        cProfile.run('main()') if testingMode else main() 
else: (cProfile.run('main()') if testingMode else main()) if not optimiseForReccursion else threading.Thread(target=main).start()