
    Given hourly patient arrival counts in an emergency room, determine the maximum possible patient influx scenario by rearranging these counts to form the highest possible number, helping administrators prepare for worst-case capacity requirements. The arrangement will represent the most challenging possible distribution of patient arrivals that the emergency room must be equipped to handle, with each digit representing the number of patients arriving in a single hour.
    

    
def find_Max_Num(arr):
    """
    Given hourly patient arrival counts in an emergency room, determine the maximum possible patient influx scenario by rearranging these counts to form the highest possible number, helping administrators prepare for worst-case capacity requirements. The arrangement will represent the most challenging possible distribution of patient arrivals that the emergency room must be equipped to handle, with each digit representing the number of patients arriving in a single hour.
    

    """
def find_Max_Num(arr):
    """
    Given hourly patient arrival counts in an emergency room, determine the maximum possible patient influx scenario by rearranging these counts to form the highest possible number, helping administrators prepare for worst-case capacity requirements. The arrangement will represent the most challenging possible distribution of patient arrivals that the emergency room must be equipped to handle, with each digit representing the number of patients arriving in a single hour.
    

    """
    n = len(arr)
    arr.sort(reverse=True)
    num = arr[0]
    for i in range(1, n):
        num = num * 10 + arr[i]
    return num