Despite advances in the reliability of sensory devices used by drones, the integrity of information from some devices is still considered an obstacle to ensuring successful flight plans. It is widely known that GNSS can suffer attacks or lose the signal from satellites, which can cause the drone to fail to complete its flight plan. In this context, we propose SiaN-VO, a Siamese network for visual odometry prediction. In our initial studies, this approach proved satisfactory for flights in static conditions (speed and height). Although interesting, these conditions do not reflect real flight conditions. In this sense, we have advanced our studies to propose the SiaN-VO, which fuses data from different sensors to enable displacement predictions to be made in dynamic flight conditions.

Runs of homozygosity (ROH) are contiguous homozygous segments occurring throughout the genome. ROH's number and size heavily depend upon shared parental ancestry, particularly relevant in the context of parental consanguinity. Homozygosity mapping, a valuable technique for the identification of genes associated with human genetic diseases, is based on the presence of ROH. Next-generation sequencing (NGS) improved this process by allowing simultaneous homozygosity mapping and detection of disease-causing variants. In this work, we present the methodology to automate the creation of personalized multigene panels based on whole-exome sequencing (WES) data using ROH (identified by combining two different algorithms: ROHMMCLI and HomozygosityMapper) and/or Human Phenotype Ontology (HPO) terms, and its integration in a Django Web application. The new resources’ applicability and impact on diagnostics are demonstrated through the genetic characterization of two siblings affected by a recessive disease. Resorting to a sample of 3,941 patients generated in this work, we provide an extensive analysis of ROH at a genomic scale for the first time in the Portuguese population. This work also describes the development of a new classification approach based on ROH features. In summary, this research advances ROH analysis from WES data, emphasizing its diagnostic potential and significance in population genetics’ characterization.