Ulisses Dias

A preservação do patrimônio histórico-cultural enfrenta o desafio da disseminação do conhecimento e da ampliação do acesso à informação. Este estudo tem como objetivo desenvolver um aplicativo móvel em Realidade Aumentada (RA) para promover a valorização e conservação da Ilha Anchieta, unidade de conservação no litoral de Ubatuba (SP), por meio da visualização de modelos 3D, imagens 360° e recursos interativos. A metodologia adotada foi um estudo de caso com abordagem qualitativa, combinando pesquisa histórica, levantamento geográfico, modelagem tridimensional e desenvolvimento em Flutter com integração ao Unity. Os resultados incluem um aplicativo funcional que oferece navegação por mapa interativo, visualização em RA do antigo presídio da ilha e outros pontos turísticos, linha do tempo histórica e quiz educativo. Os testes indicaram elevado engajamento e imersão dos usuários. Como contribuição, o projeto propõe uma nova forma de sensibilização para o patrimônio, utilizando tecnologias digitais acessíveis para apoiar práticas de educação, turismo e preservação cultural.

In comparative genomics, evolutionary distance can be estimated by determining a minimum sequence of genome rearrangements required to transform one genome into another. The length of this sequence is called the rearrangement distance. Traditionally, most studies assumed that compared genomes shared the same set of genes, with only their relative gene order being used for comparison. Recent studies indicate that incorporating intergenic region sizes leads to more accurate distance estimates when analyzing real genomes. Furthermore, they started to consider genomes having a distinct set of genes. In this work, we investigate genome rearrangement problems by incorporating additional information and complexity into the models, in order to achieve more realistic practical results that can benefit several scientific fields.

One of the challenges in the Comparative Genomics field is to infer how close two organisms are based on the similarities and differences between their genetic materials. Recent advances in DNA sequencing have made complete genomes increasingly available. That said, several new algorithms trying to infer the distance between two organisms based on genome rearrangements have been proposed in the literature. However, given the diversity of approaches, the diversity of genome rearrangement events, or even how each work models the genomes and what assumptions are made by each of them, finding the ideal algorithm for each situation or simply knowing the range of applicable approaches can be challenging. In this work, we review these approaches having the algorithmic and combinatorial advances since 2010 as our main focus. This survey aims to organize the recently published papers using a concise notation and to indicate the gaps filled by each of them in the literature. This makes it easier to understand what still needs to be done and what has room for enhancement.

The most common way to calculate the rearrangement distance between two genomes is to use the size of a minimum length sequence of rearrangements that transforms one of the two given genomes into the other, where the genomes are represented as permutations using only their gene order, based on the assumption that genomes have the same gene content. With the advance of research in genome rearrangements, new works extended the classical models by either considering genomes with different gene content (unbalanced genomes) or including more genomic characteristics to the mathematical representation of the genomes, such as the distribution of intergenic regions sizes. In this study, we study the Reversal, Transposition, and Indel (Insertion and Deletion) Distance using intergenic information, which allows comparing unbalanced genomes, because indels are included in the rearrangement model (i.e., the set of possible rearrangements allowed when we compute the distance). For the particular case of transpositions and indels on unbalanced genomes, we present a 4-approximation algorithm, improving a previous 4.5 approximation. This algorithm is extended so as to deal with gene orientation and to maintain the 4-approximation factor for the Reversal, Transposition, and Indel Distance on unbalanced genomes. Furthermore, we evaluate the proposed algorithms using experiments on simulated data.

Genome rearrangement events are widely used to estimate a minimum-size sequence of mutations capable of transforming a genome into another. The length of this sequence is called distance, and determining it is the main goal in genome rearrangement distance problems. Problems in the genome rearrangement field differ regarding the set of rearrangement events allowed and the genome representation. In this work, we consider the scenario where the genomes share the same set of genes, gene orientation is known or unknown, and intergenic regions (structures between a pair of genes and at the extremities of the genome) are taken into account. We use two models, the first model allows only conservative events (reversals and moves), and the second model includes non-conservative events (insertions and deletions) in the intergenic regions. We show that both models result in NP-hard problems no matter if gene orientation is known or unknown. When the information regarding the orientation of genes is available, we present for both models an approximation algorithm with a factor of 2. For the scenario where this information is unavailable, we propose a 4-approximation algorithm for both models.