The absence of biomarkers poses a significant challenge to
the early diagnosis of Autism Spectrum Disorders (ASDs) in children,
particularly during routine newborn examinations. Consequently, post-birth
years often rely on identifying difficulties in social interaction and other
emerging factors to evaluate ASD in children. This study presents numerical
findings examining social interaction and repetitive behaviors in both ASD and
non-ASD cohorts. To illustrate these interactions, we employ two sets of random
walkers, each representing distinct characteristics. One set, akin to children
with autism, exhibits persistent and resistant dynamics, while the other,
labeled as healthy, demonstrates diffusive behavior resembling the Elephant
Random Walks (ERW) model. We analyze the influence of these two sets on each
other's entropy variations using an information entropy framework. By examining
paired interactions between walkers, we assess how these interactions impact
the entropy fluctuations within each set. Surprisingly, our findings reveal
that variations in the strength of interaction, represented by probability f,
do not induce entropy changes in the group of random walkers simulating
children with autism.
Author(s) Details
Silvério Sirotheau
Faculty of Engineering, Federal University of Pará (UFPA),
Brazil.
José Leão de Luna
Faculty of
Engineering, Federal University of Pará (UFPA), Brazil.
Thiago R. S. Moura
Faculty of Physics, Federal University of Pará (UFPA),
Brazil.
Please see the link:- https://doi.org/10.9734/bpi/mria/v10/938
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