To ensure the cyclic aging predictor was trained on data free from the influence of calendar aging, it is necessary to remove the effects of calendar aging from the cyclic dataset. This is achieved by subtracting the corresponding values from the calendar aging dataset, thus isolating the cyclic aging effects. This process resulted in a pure cyclic dataset, essential for the precise training of the cyclic aging predictor.