A5068511125- Complex Network Analysis Techniques
- Graph theory and applications
- Communication and COVID-19 Impact
- Business, Innovation, and Economy
- Knowledge Societies in the 21st Century
- Functional Brain Connectivity Studies
- Advanced Clustering Algorithms Research
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Synthesis and Properties of Aromatic Compounds
- Time Series Analysis and Forecasting
- Advanced Neuroimaging Techniques and Applications
- COVID-19 Clinical Research Studies
- Random Matrices and Applications
- Interconnection Networks and Systems
- Heart Rate Variability and Autonomic Control
- Early Childhood Education and Development
- Graph Theory and Algorithms
- Genetics and Neurodevelopmental Disorders
- Stochastic processes and statistical mechanics
- Mental Health Research Topics
- ECG Monitoring and Analysis
- VLSI and FPGA Design Techniques
- Gene Regulatory Network Analysis
- Advanced MRI Techniques and Applications
Universidade de São Paulo
2018-2024
Universidade Federal do Rio Grande do Norte
2022
National University of Saint Anthony the Abbot in Cuzco
2021
Graphs have become widely used to represent and study social, biological, technological systems. Statistical methods analyze empirical graphs were proposed based on the graph's spectral density. However, their running time is cubic in number of vertices, precluding direct application large instances. Thus, efficient algorithms calculate density necessary. For sparse graphs, cavity method can efficiently approximate locally treelike undirected directed graphs. it does not apply most because...
This paper reports the methods and preliminary findings of Germina, an ongoing cohort study to identify biomarkers trajectories executive functions language development in first 3 years life. 557 mother-infant dyads (mean age mothers 33.7 years, 65.2% white, 48.7% male infants) have undergone baseline are currently collecting data for other timepoints. A linear regression was used predict Bayley-III using scores derived from data-driven sparse partial least squares utilizing a multiple...
Initial studies using resting-state functional magnetic resonance imaging on the trajectories of brain network from childhood to adulthood found evidence integration and segregation over time. The comprehension how healthy individuals’ occur is crucial enhance our understanding possible deviations that may lead disorders. Recent approaches have focused framework wherein organized into spatially distributed modules been associated with specific cognitive functions. Here, we tested hypothesis...
Abstract Many natural phenomena are the results of interactions different components. For example, an organism’s phenotype from genes, proteins and environment. The characteristics our society shaped by how people relate to each other. internet is product billions interconnected computers, electronic devices users. To understand systems, we represent them using networks, that is, random graphs. A critical inferential step estimate parameters these networks. Often analytical likelihood...
Abstract The network Laplacian spectral density calculation is critical in many fields, including physics, chemistry, statistics, and mathematics. It highly computationally intensive, limiting the analysis to small networks. Therefore, we present two efficient alternatives: one based on network’s edges another degrees. former gives exact of locally tree-like networks but requires iterative edge-based message-passing equations. In contrast, latter obtains an approximation using only degree...
La falta de base datos para tomar decisiones en acciones rápidas durante la pandemia ocasionada por el COVID-19 mostró necesidad usar nuevas tecnologías agilizar proceso captura información descentralizada. Este artículo presenta un asistente virtual (chatbot) denominado SaminBot, como una alternativa recolectar y brindar del COVID-19. chatbot se aplicó región Cusco, Perú, con conversaciones las áreas salud, economía educación entre enero agosto 2020. SaminBot inicia recolección función área...
Abstract Graphs have become crucial for representing and examining biological, social technological interactions. In this context, the graph spectrum is an exciting feature to be studied because it encodes structural dynamic characteristics of graph. Hence, becomes essential efficiently compute graph’s spectral distribution (eigenvalue’s density function). Recently, some authors proposed degree-based methods obtain locally tree-like networks in linear time. The bottleneck their approach that...
Abstract Estimating the number of eigenvalues $\mu_{[a,b]}$ a network’s adjacency matrix in given interval $[a,b]$ is essential several fields. The straightforward approach consists calculating all $O(n^3)$ (where $n$ nodes network) and then counting ones that belong to $[a,b]$. Another use Sylvester’s law inertia, which also requires $O(n^3)$. Although both methods provide exact $[a,b]$, their application for large networks computationally infeasible. Sometimes, an approximation enough. In...
Abstract Methods for controlling machines using physiological signals have been the focus of much research over last decades. One natural approach is to use brain decoding subject-driven cognitive states. However, brain-based approaches often require costly, challenging handle, and uncomfortable devices inadequate daily use. We propose an alternative method decode states based on heart rate (HR). Although HR capable classifying general conditions (e.g., level physical activities, stress,...