This work aims to study the effects on mental health and brain structure of the time spent by children in different activities in front of a screen. Associations were found through the use of statistical models fitted on data from Adolescent Brain Cognitive Development longitudinal study, a US representative sample of almost 120000 children in age 8-12.
The idea of this work is to automatize the process of analysis and description of the SARS-CoV-2 virus starting from a sample of its genome and to be able to assign a group of samples to the correct variant. By using a clustering algorithm, in the end, it’s also possible to distinguish a new variant and obtain a description of its most common mutations.
Application of implicit neural representation with periodic activation function for Single Image Super-Resolution