
    Design an event recommendation algorithm that determines how many possible sequences of n consecutive social events can be suggested, where each event must have at least double the engagement potential of the previous event and cannot exceed the platform's maximum engagement threshold m. The sequence should optimize for growing social impact while respecting platform limitations.
    

    
def get_total_number_of_sequences(m, n):
    """
    Design an event recommendation algorithm that determines how many possible sequences of n consecutive social events can be suggested, where each event must have at least double the engagement potential of the previous event and cannot exceed the platform's maximum engagement threshold m. The sequence should optimize for growing social impact while respecting platform limitations.
    

    """
def get_total_number_of_sequences(m, n):
    """
    Design an event recommendation algorithm that determines how many possible sequences of n consecutive social events can be suggested, where each event must have at least double the engagement potential of the previous event and cannot exceed the platform's maximum engagement threshold m. The sequence should optimize for growing social impact while respecting platform limitations.
    

    """
    T = [[0 for i in range(n + 1)] for i in range(m + 1)]
    for i in range(m + 1):
        for j in range(n + 1):
            if i == 0 or j == 0:
                T[i][j] = 0
            elif i < j:
                T[i][j] = 0
            elif j == 1:
                T[i][j] = i
            else:
                T[i][j] = T[i - 1][j] + T[i // 2][j - 1]
    return T[m][n]