New distance measure for comparing protein using cellular automata image.

One of the first steps in protein sequence analysis is comparing sequences to look for similarities. We propose an information theoretical distance to compare cellular automata representing protein sequences, and determine similarities. Our approach relies in a stationary Hamming distance for the evolution of the automata according to a properly chosen rule, and to build a pairwise similarity matrix and determine common ancestors among different species in a simpler and less computationally demanding computer codes when compared to other methods.

Analysis of intermunicipal journeys for cardiac surgery in Brazilian Unified Health System (SUS): an approach based on network theory.

Introduction: The transformation of data into information is important to support decision making and, thus, to induce improvements in healthcare services. The regionalized organization of healthcare systems is necessary to ensure the integrity of citizen care. From this perspective, the creation of mechanisms to guide and assess the behavior of a healthcare services network becomes necessary.

Conservation in the Amazon rainforest and Google searches: A DCCA approach.

In this paper we analyze the descriptive statistics of the Google search volume for the terms related to the National Reserve of Copper and Associates (RENCA), a Brazilian mineral reserve in the Amazon of 4.6 million hectares, before and after the government signed the decree releasing it for exploration. First, we analyze the volume of searches for expressions related to RENCA in Google Trends using descriptive statistics; second, we assess the cross-correlation coefficient ρDCCA, which measures the cross-correlation between two nonstationary time series across different time scales.

Retrospective Cohort Study of COVID-19 in Patients of the Brazilian Public Health System with SARS-CoV-2 Omicron Variant Infection.

Several vaccines against COVID-19 are now available, based on different techniques and made by different laboratories spread around the world. With the roll out of the vaccination process in an advanced stage in many countries, the reduced risk of hospitalization due to the Omicron variant relative to the Delta variant infection, despite the higher transmission risk of Omicron, may lead to a misinterpretation of the results, as infection by Omicron is associated with a significant reduction in severe outcomes and shorter hospitalization time than the Delta variant. We compared the in-hospital mortality due to the Omicron (Jan-Mar 2022) with Gamma (Jan 2021) and Delta (Oct-Dec 2021) variants of patients in the Brazilian public health system.

Graph-based feature extraction: A new proposal to study the classification of music signals outside the time-frequency domain.

Most feature extraction algorithms for music audio signals use Fourier transforms to obtain coefficients that describe specific aspects of music information within the sound spectrum, such as the timbral texture, tonal texture and rhythmic activity. In this paper, we introduce a new method for extracting features related to the rhythmic activity of music signals using the topological properties of a graph constructed from an audio signal. We map the local standard deviation of a music signal to a visibility graph and calculate the modularity (Q), the number of communities (Nc), the average degree (〈k〉), and the density (Δ) of this graph.

A Model for Improving the Learning Curves of Artificial Neural Networks.

In this article, the performance of a hybrid artificial neural network (i.e. scale-free and small-world) was analyzed and its learning curve compared to three other topologies: random, scale-free and small-world, as well as to the chemotaxis neural network of the nematode Caenorhabditis Elegans.