
    In a busy emergency room, administrators need to predict how the patient queue diminishes over time blocks when multiple patients are processed simultaneously. Starting with an initial count of waiting patients at peak hours, the system processes patients in decreasing batch sizes, where each subsequent time block handles 2 fewer patients than the previous block. Calculate the total number of patients that can be processed across all time blocks, continuing until no complete batch can be formed (when remaining patients are less than or equal to 0). This calculation will help determine staffing requirements and estimate total processing time for the current queue of waiting patients.
    

    
def sum_series(n):
    """
    In a busy emergency room, administrators need to predict how the patient queue diminishes over time blocks when multiple patients are processed simultaneously. Starting with an initial count of waiting patients at peak hours, the system processes patients in decreasing batch sizes, where each subsequent time block handles 2 fewer patients than the previous block. Calculate the total number of patients that can be processed across all time blocks, continuing until no complete batch can be formed (when remaining patients are less than or equal to 0). This calculation will help determine staffing requirements and estimate total processing time for the current queue of waiting patients.
    

    """
def sum_series(n):
    """
    In a busy emergency room, administrators need to predict how the patient queue diminishes over time blocks when multiple patients are processed simultaneously. Starting with an initial count of waiting patients at peak hours, the system processes patients in decreasing batch sizes, where each subsequent time block handles 2 fewer patients than the previous block. Calculate the total number of patients that can be processed across all time blocks, continuing until no complete batch can be formed (when remaining patients are less than or equal to 0). This calculation will help determine staffing requirements and estimate total processing time for the current queue of waiting patients.
    

    """
    if n < 1:
        return 0
    else:
        return n + sum_series(n - 2)