def simulate_shipments(n, departures, cars_needed, initial_cars):
    # Initialize number of cars available at each station to cars_needed
    available_cars = cars_needed.copy()

    # Initialize number of cars sent from each station to 0
    sent_cars = [0] * n

    # Iterate over stations in increasing order of departure times
    for i in range(n):
        # Check if station i has enough cars available to make its shipment
        if available_cars[i] >= cars_needed[i]:
            # Station i can make its shipment using its own cars
            available_cars[i] -= cars_needed[i]
            available_cars[departures[i]-1] += cars_needed[i]
            sent_cars[i] = cars_needed[i]
        else:
            # Station i needs additional cars to make its shipment
            deficit = cars_needed[i] - available_cars[i]
            available_cars[i] = 0
            available_cars[departures[i]-1] += deficit
            sent_cars[i] = available_cars[i]
            available_cars[i] = 0

    # Return True if all shipments can be performed, False otherwise
    return all(sent_cars[i] >= cars_needed[i] for i in range(n))

def find_minimum_cars(n, departures, cars_needed):
    # Initialize search range to [0, sum(Ci)]
    lo, hi = 0, sum(cars_needed)

    # Binary search for minimum number of cars needed
    while lo < hi:
        mid = (lo + hi) // 2
        if simulate_shipments(n, departures, cars_needed, [mid] * n):
            hi = mid
        else:
            lo = mid + 1

    # Return the minimum number of cars needed
    return lo

# Read input
t = int(input())
for i in range(1, t+1):
    n = int(input())
    departures = list(map(int, input().split()))
    cars_needed = list(map(int, input().split()))

    # Find minimum number of cars needed for initial supplies
    min_cars = find_minimum_cars(n, departures, cars_needed)

    # Print output
    print("Case #{}: {}".format(i, min_cars))