{'fraction_non_alphanumeric': 0.013725490196078431, 'fraction_numerical': 0.0, 'mean_word_length': 5.468354430379747, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Stochastic flow networks: How component criticality changes with component reliability

Consider a directed flow network whose arcs have random two-state capacities. The paper describes how a single Monte Carlo experiment allows one to estimate the sensitivity of the probability that a particular cutset is critical, given that the maximum flow between a pair of nodes takes values in an interval, in response to varying arc reliabilities. The technique improves considerably on alternative potential methods.