import numpy as np

def convolve(f, g):
    tf = np.array(f, np.int64)
    tg = np.array(g, np.int64) 
    fft_len = 1
    while 2 * fft_len < len(tf) + len(tg) - 1:
        fft_len *= 2
    
    fft_len *= 2

    # フーリエ変換
    Ff = np.fft.rfft(tf, fft_len)
    Fg = np.fft.rfft(tg, fft_len)

    # 各点積
    Fh = Ff * Fg

    # フーリエ逆変換
    h = np.fft.irfft(Fh, fft_len)

    # 小数になっているので、整数にまるめる
    h = np.rint(h).astype(np.int64)

    return h[:len(f) + len(g) - 1]

def convolve2(f,g,p):
    
    
    f1,f2 = np.divmod(f,1<<15)
    g1,g2 = np.divmod(g,1<<15)
    
    a = convolve(f1,g1)%p
    c = convolve(f2,g2)%p
    b = (convolve(f1+f2,g1+g2) - a - c)%p
    h = (a<<30) + (b<<15) + c
    return h%p
    
def convolve_pow(f,n,p):
    nbit = list(str(bin(n))[2:])
    nbit = [int(i) for i in nbit]
    N = len(f)
    C = [1] + [0]*(N-1)
    
    B = f

        
    for i in range(len(nbit)):
        if nbit[-1-i] == 1:
            C = convolve2(C,B,p)
        
        B = convolve2(B,B,p)
    
    return C

T = int(input())
a,b,c,d,e = map(int,input().split())
a = abs(a)
b = abs(b)
c = abs(c)
mod = 10**9 + 7

M = max(a,b,c)

X = [0]*(2*M+1)
X[M+a] += 1
X[M-a] += 1
X[M+b] += 1
X[M-b] += 1
X[M+c] += 1
X[M-c] += 1
print(sum(convolve_pow(X,T,mod)[max(d+M*T,0):e+M*T+1])%mod)