{'fraction_non_alphanumeric': 0.013458950201884253, 'fraction_numerical': 0.0, 'mean_word_length': 5.702702702702703, '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}}
Set Membership (In) Validation of nonlinear positive models for biological systems

The complexity of biology needs quantitative tools in order to support and validate biologists intuition and traditional qualitative descriptions. In this paper, nonlinear positive models with constraints for biological systems are validated/invalidated in a worst-case deterministic setting. These models are useful for the analysis of the DNA and RNA evolution and for the description of the population dynamics of viruses and bacteria. The conditional central estimate and the uncertainty intervals are determined in order to validate/invalidate the model. The effectiveness of the proposed procedure has been illustrated by means of simulation experiments