
# slower version:

s = input()
for i in range(len(s)):
  if i%2 == 0:
    print(s[i], end = '')


# optimized version of the same code:

s = input()
ans = ''
for i in range(len(s)):
  if i % 2 == 0:
    ans += s[i]
print(ans)



# slower version:

import copy

from functools import lru_cache

import numpy as np

from numba import njit



#@njit

# @njit('(i8[::1],)', cache=True)

# def func(A):

#     N = len(A)

#     B = np.zeros_like(A)

#     for i in range(N):

#         l = max(0, i - A[i])

#         r = min(i + A[i], N-1)

#         B[l] += 1

#         if r+1 < N:

#             B[r+1] -= 1



#     B = np.cumsum(B)

#     return B



def resolve():

    N, K = list(map(int, input().split()))

    A = np.array(list(map(int, input().split())))



    # N = 2 * 10**5

    # K = 2 * 10**5

    # A = np.array([0] *  N)



    @njit

    def func(A):

        #N = len(A)

        B = np.zeros_like(A)

        for i in range(N):

            l = max(0, i - A[i])

            r = min(i + A[i], N-1)

            B[l] += 1

            if r+1 < N:

                B[r+1] -= 1



        B = np.cumsum(B)

        return B



    for k in range(K):

        #print(k)

        A = func(A)

        if k >= 50:

            break



    print((" ".join(map(str, A))))



if __name__ == "__main__":

    resolve()

# optimized version of the same code:

import copy

from functools import lru_cache

#import numpy as np

#from numba import njit



def resolve():

    N, K = list(map(int, input().split()))

    #A = np.array(list(map(int, input().split())))

    A = list(map(int, input().split()))



    #N = 2 * 10**5

    #K = 2 * 10**5

    #A = np.array([0] *  N)



    def func(A):

        B = [0] * N

        for i in range(N):

            l = max(0, i - A[i])

            r = min(i + A[i], N-1)

            B[l] += 1

            if r+1 < N:

                B[r+1] -= 1



        for i in range(1, N):

            B[i] += B[i-1]

        return B



    for k in range(K):

        #print(k)

        A = func(A)

        if k >= 50:

            break



    print((" ".join(map(str, A))))



if __name__ == "__main__":

    resolve()
import copy
from functools import lru_cache
import numpy as np
from numba import njit

# @njit
# @njit('(i8[::1],)', cache=True)
# def func(A):
#     N = len(A)
#     B = np.zeros_like(A)
#     for i in range(N):
#         l = max(0, i - A[i])
#         r = min(i + A[i], N-1)
#         B[l] += 1
#         if r+1 < N:
#             B[r+1] -= 1
#     B = np.cumsum(B)
#     return B
def resolve():
    N, K = list(map(int, input().split()))
    A = np.array(list(map(int, input().split())))
    # N = 2 * 10**5
    # K = 2 * 10**5
    # A = np.array([0] *  N)
    @njit
    def func(A):
        # N = len(A)
        B = np.zeros_like(A)
        for i in range(N):
            l = max(0, i - A[i])
            r = min(i + A[i], N - 1)
            B[l] += 1
            if r + 1 < N:
                B[r + 1] -= 1
        B = np.cumsum(B)
        return B

    for k in range(K):
        # print(k)
        A = func(A)
        if k >= 50:
            break
    print((" ".join(map(str, A))))


if __name__ == "__main__":
    resolve()

import copy
from functools import lru_cache

# import numpy as np
# from numba import njit
def resolve():
    N, K = list(map(int, input().split()))
    # A = np.array(list(map(int, input().split())))
    A = list(map(int, input().split()))
    # N = 2 * 10**5
    # K = 2 * 10**5
    # A = np.array([0] *  N)
    def func(A):
        B = [0] * N
        for i in range(N):
            l = max(0, i - A[i])
            r = min(i + A[i], N - 1)
            B[l] += 1
            if r + 1 < N:
                B[r + 1] -= 1
        for i in range(1, N):
            B[i] += B[i - 1]
        return B

    for k in range(K):
        # print(k)
        A = func(A)
        if k >= 50:
            break
    print((" ".join(map(str, A))))


if __name__ == "__main__":
    resolve()

-import numpy as np -from numba import njit -# @njit -# @njit('(i8[::1],)', cache=True) -# def func(A): -#     N = len(A) -#     B = np.zeros_like(A) -#     for i in range(N): -#         l = max(0, i - A[i]) -#         r = min(i + A[i], N-1) -#         B[l] += 1 -#         if r+1 < N: -#             B[r+1] -= 1 -#     B = np.cumsum(B) -#     return B +# import numpy as np +# from numba import njit -    A = np.array(list(map(int, input().split()))) +    # A = np.array(list(map(int, input().split()))) +    A = list(map(int, input().split())) -    @njit -        # N = len(A) -        B = np.zeros_like(A) +        B = [0] * N -        B = np.cumsum(B) +        for i in range(1, N): +            B[i] += B[i - 1]