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Your search keyword '"Corso, Gilberto"' showing total 34 results
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34 results on '"Corso, Gilberto"'

1. Bayesian Time-Lapse Full Waveform Inversion using Hamiltonian Monte Carlo

Author

de Lima, Paulo Douglas S., Ferreira, Mauro S., Corso, Gilberto, and de Araújo, João M.

Subjects
Physics - Geophysics, Condensed Matter - Statistical Mechanics, Physics - Data Analysis, Statistics and Probability
Abstract

Time-lapse images carry out important information about dynamic changes in Earth's interior which can be inferred using different Full Waveform Inversion (FWI) schemes. The estimation process is performed by manipulating more than one seismic dataset, associated with the baseline and monitors surveys. The time-lapse variations can be so minute and localised that quantifying the uncertainties becomes fundamental to assessing the reliability of the results. The Bayesian formulation of the FWI problem naturally provides confidence levels in the solution, but evaluating the uncertainty of time-lapse seismic inversion remains a challenge due to the ill-posedness and high dimensionality of the problem. The Hamiltonian Monte Carlo (HMC) can be used to effectively sample over high dimensional distributions with affordable computational efforts. In this context, we propose a probabilistic Bayesian sequential approach for time-lapse FWI using the HMC method. Our approach relies on the integration of the baseline survey information as prior knowledge in the monitor estimation. We compare the proposed methodology with a parallel scheme in perfect and perturbed acquisition geometry scenarios. We also investigate the correlation effect between baseline and monitor samples in the propagated uncertainties. The results show that our strategy provides accurate times-lapse estimates with errors of similar magnitude to the parallel methodology., Comment: 12 pages, 6 figures

Published
2023
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3. Acoustic Full Waveform Inversion with Hamiltonian Monte Carlo Method

Author

de Lima, Paulo D. S., Corso, Gilberto, Ferreira, Mauro S., and de Araújo, João M.

Subjects
Physics - Geophysics, Condensed Matter - Statistical Mechanics
Abstract

Full-Waveform Inversion (FWI) is a high-resolution technique used in geophysics to evaluate the physical parameters and construct subsurface models in a noisy and limited data scenario. The ill-posed nature of the FWI turns this a challenging problem since more than one model can match the observations. In a probabilistic way, solving the FWI problem demands efficient sampling techniques to infer information on parameters and to estimate the uncertainties in high-dimensional model spaces. We investigate the feasibility of applying the Hamiltonian Monte Carlo (HMC) method in the acoustic FWI by a reflection setup containing different noise level data. We propose a new strategy for tuning the mass matrix based on the acquisition geometry of the seismic survey. Our methodology significantly improves the ability of the HMC method in reconstructing reasonable seismic models with affordable computational efforts., Comment: 10 pages, 6 figures

Published
2022
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5. Generalized statistics: applications to data inverse problems with outlier-resistance

Author

de Lima, João V. T., da Silva, Sérgio Luiz E. F., de Araújo, João M., Corso, Gilberto, and Lima, Gustavo Z. dos Santos

Subjects
Statistics - Methodology, Condensed Matter - Statistical Mechanics, Mathematics - Statistics Theory, Physics - Computational Physics, Physics - Geophysics
Abstract

The conventional approach to data-driven inversion framework is based on Gaussian statistics that presents serious difficulties, especially in the presence of outliers in the measurements. In this work, we present maximum likelihood estimators associated with generalized Gaussian distributions in the context of R\'enyi, Tsallis and Kaniadakis statistics. In this regard, we analytically analyse the outlier-resistance of each proposal through the so-called influence function. In this way, we formulate inverse problems by constructing objective functions linked to the maximum likelihood estimators. To demonstrate the robustness of the generalized methodologies, we consider an important geophysical inverse problem with high noisy data with spikes. The results reveal that the best data inversion performance occurs when the entropic index from each generalized statistic is associated with objective functions proportional to the inverse of the error amplitude. We argue that in such a limit the three approaches are resistant to outliers and are also equivalent, which suggests a lower computational cost for the inversion process due to the reduction of numerical simulations to be performed and the fast convergence of the optimization process., Comment: 17 pages, 14 figures

Published
2022

6. An outlier-resistant $\kappa$-generalized approach for robust physical parameter estimation

Author

da Silva, Sérgio Luiz E. F., Silva, R., Lima, Gustavo Z. dos Santos, de Araújo, João M., and Corso, Gilberto

Subjects
Condensed Matter - Statistical Mechanics, Physics - Data Analysis, Statistics and Probability, Physics - Geophysics
Abstract

In this work we propose a robust methodology to mitigate the undesirable effects caused by outliers to generate reliable physical models. In this way, we formulate the inverse problems theory in the context of Kaniadakis statistical mechanics (or $\kappa$-statistics), in which the classical approach is a particular case. In this regard, the errors are assumed to be distributed according to a finite-variance $\kappa$-generalized Gaussian distribution. Based on the probabilistic maximum-likelihood method we derive a $\kappa$-objective function associated with the finite-variance $\kappa$-Gaussian distribution. To demonstrate our proposal's outlier-resistance, we analyze the robustness properties of the $\kappa$-objective function with help of the so-called influence function. In this regard, we discuss the role of the entropic index ($\kappa$) associated with the Kaniadakis $\kappa$-entropy in the effectiveness in inferring physical parameters by using strongly noisy data. In this way, we consider a classical geophysical data-inverse problem in two realistic circumstances, in which the first one refers to study the sensibility of our proposal to uncertainties in the input parameters, and the second is devoted to the inversion of a seismic data set contaminated by outliers. The results reveal an optimum $\kappa$-value at the limit $\kappa \rightarrow 2/3$, which is related to the best results., Comment: 37 pages, 23 figures

Published
2021
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15. Cycling reduces the entropy of neuronal activity in the human adult cortex.

Author

Ferré, Iara Beatriz Silva, Corso, Gilberto, dos Santos Lima, Gustavo Zampier, Lopes, Sergio Roberto, Leocadio-Miguel, Mario André, França, Lucas G. S., de Lima Prado, Thiago, and Araújo, John Fontenele

Subjects
*CEREBRAL dominance, *ENTROPY, *ELECTROENCEPHALOGRAPHY, *ADULTS, *ELECTRODES
Abstract

Brain Complexity (BC) have successfully been applied to study the brain electroencephalographic signal (EEG) in health and disease. In this study, we employed recurrence entropy to quantify BC associated with the neurophysiology of movement by comparing BC in both resting state and cycling movement. We measured EEG in 24 healthy adults and placed the electrodes on occipital, parietal, temporal and frontal sites on both the right and left sides of the brain. We computed the recurrence entropy from EEG measurements during cycling and resting states. Entropy is higher in the resting state than in the cycling state for all brain regions analysed. This reduction in complexity is a result of the repetitive movements that occur during cycling. These movements lead to continuous sensorial feedback, resulting in reduced entropy and sensorimotor processing. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Camera trap surveys of Atlantic Forest mammals: A data set for analyses considering imperfect detection (2004–2020)

Author

Franceschi, Ingridi Camboim, primary, Dornas, Rubem Augusto da Paixão, additional, Lermen, Isabel Salgueiro, additional, Coelho, Artur Vicente Pfeifer, additional, Vilas Boas, Ademir Henrique, additional, Chiarello, Adriano Garcia, additional, Paglia, Adriano Pereira, additional, de Souza, Agnis Cristiane, additional, Borsekowsky, Alana Rafaela, additional, Rocha, Alessandro, additional, Bager, Alex, additional, de Souza, Alexander Zaidan, additional, Lopes, Alexandre Martins Costa, additional, de Moura, Aloysio Souza, additional, Ferreira, Aluane Silva, additional, García‐Olaechea, Alvaro, additional, Delciellos, Ana Cláudia, additional, Bacellar, Ana Elisa de Faria, additional, Campelo, Ana Kellen Nogueira, additional, Paschoal, Ana Maria Oliveira, additional, Rolim, Anderson Claudino, additional, da Silva, André Luiz Ferreira, additional, Lanna, Andre Monnerat, additional, da Silva, André Pereira, additional, Guimarães, Andresa, additional, Cardoso, Ângela, additional, Cassol, Angelica Soligo, additional, da Costa‐Pinto, Anna Ludmilla, additional, do Nascimento, Ariel Guilherme Santos, additional, Fernandes, Arthur Soares, additional, Clyvia, Aryanne, additional, Santos, Aureo Banhos dos, additional, Lima‐Silva, Barbara, additional, Beisiegel, Beatriz de Mello, additional, Luciano, Beatriz Fernandes Lima, additional, Leopoldo, Bernardo de Faria, additional, Krobel, Bruna Nunes, additional, Kubiak, Bruno Busnello, additional, Saranholi, Bruno Henrique, additional, Correa, Bruno Senna, additional, Sant Anna Teixeira, Caio, additional, Ayroza, Camila Rezende, additional, Cassano, Camila Righetto, additional, Benitez‐Riveros, Camilo, additional, Gestich, Carla Cristina, additional, Tedesco, Carla Denise, additional, Gheler‐Costa, Carla, additional, Hegel, Carla Grasiele Zanin, additional, Evangelista Junior, Carlito da Silva, additional, Ferreira, Carlos Eduardo Morando Faria, additional, Grelle, Carlos Eduardo Viveiros, additional, Esteves, Carolina Franco, additional, Espinosa, Caroline da Costa, additional, Leuchtenberger, Caroline, additional, Sanchéz‐Lalinde, Catalina, additional, Machado, Cauanne Iglesias Campos, additional, Andreazzi, Cecilia, additional, Bueno, Cecília, additional, Cronemberger de Faria, Cecilia, additional, Novaes, Claudio, additional, Widmer, Cynthia Elisa, additional, Santos, Cyntia Cavalcante, additional, Ferraz, Daniel da Silva, additional, Galiano, Daniel, additional, Bôlla, Daniela Aparecida Savariz, additional, Behs, Daniela, additional, Rodrigues, Daniele Pereira, additional, de Melo, Danielle Picão, additional, Ramos, Déborah Maria Soares, additional, de Mattia, Denise Lidório, additional, Pavei, Diego Dias, additional, Loretto, Diogo, additional, Huning, Douglas da Silva, additional, Dias, Douglas de Matos, additional, Paetzhold, Éder Ricardo, additional, Rios, Elaine, additional, Setz, Eleonore Zulnara Freire, additional, Cazetta, Eliana, additional, Cafofo Silva, Emanuel Giovani, additional, Pasa, Emanuelle, additional, Saito, Erica Naomi, additional, de Aguiar, Erick Francisco Silva, additional, Castro, Érika Paula, additional, Viveiros de Castro, Ernesto Bastos, additional, Pedó, Ezequiel, additional, Pereira, Fabiane de Aguiar, additional, Bolzan, Fábio, additional, Roque, Fábio de Oliveira, additional, Mazim, Fábio Dias, additional, Comin, Fábio Henrique, additional, Maffei, Fábio, additional, Peters, Felipe Bortolotto, additional, Fantacini, Felipe Moreli, additional, da Silva, Felipe Pessoa, additional, Machado, Felipe Santana, additional, Vélez‐Garcia, Felipe, additional, Lage, Fernanda Stussi Duarte, additional, Perini, Fernando Araújo, additional, Passos, Fernando Camargo, additional, Carvalho, Fernando, additional, de Azevedo, Fernando Cesar Cascelli, additional, Ferreira, Fernando, additional, de Pinho, Fernando Ferreira, additional, Chaves, Flávia Guimarães, additional, Miranda, Flavia Regina, additional, Rodrigues, Flavio Henrique Guimarães, additional, Ubaid, Flávio Kulaif, additional, Gabriel, Francisco Homem, additional, de Souza, Franco Leandro, additional, de Oliveira, Fred Victor, additional, Cupolillo, Gabriel, additional, Moreira, Gabriela de Araújo Pires, additional, Mette, Gabriela, additional, Duarte, Gabriela Teixeira, additional, Beca, Gabrielle, additional, Corso, Gilberto, additional, Perbiche‐Neves, Gilmar, additional, Souto, Glauber Henrique Borges de Oliveira, additional, Vilarroel, Glenda Jéssica da Silva, additional, Batista, Graziele O., additional, Ferreira, Guilherme Braga, additional, Toledo, Gustavo Alves da Costa, additional, Senger, Gustavo, additional, Bergallo, Helena de Godoy, additional, dos Santos, Hellen Cristina Pinheiro, additional, Gazola, Humberto Angelo, additional, Melo, Isabel, additional, Brack, Ismael Verrastro, additional, Veríssimo, Iuri, additional, Viana, Ivan Réus, additional, Laurentino, Izabela Costa, additional, Diehl, Jaime Luis, additional, Zocche, Jairo José, additional, Martins‐Silva, Jimi, additional, Just, João Paulo Gava, additional, Cherem, Jorge José, additional, Nascimento, Jorge Luiz, additional, Marinho, Jorge Reppold, additional, Dantas, José Oliveira, additional, de Matos, Jose Roberto, additional, Pires, José Salatiel Rodrigues, additional, Cerveira, Josi Fernanda, additional, Ruiz‐Esparza, Juan, additional, da Silva, Juliana Paulo, additional, Bogoni, Juliano André, additional, Molina, Karina Theodoro, additional, Pereira, Karla Dayane de Lima, additional, Ceron, Karoline, additional, de Vleeschouwer, Kristel, additional, Lautenschlager, Laís, additional, Bailey, Larissa, additional, Fornitano, Larissa, additional, Rampim, Lilian Elaine, additional, Sforza, Lorena, additional, Bissa, Luan Gonçalves, additional, Santucci, Luca Mattos, additional, da Silva, Lucas Gonçalves, additional, Perillo, Lucas Neves, additional, Correa, Lucas Ribeiro, additional, Hufnagel, Ludmila, additional, Alberti, Luis Fernando, additional, Recalde Mello, Luis Jose, additional, Bernardo, Luis Renato Rezende, additional, Oliveira‐Santos, Luiz Gustavo Rodrigues, additional, Guimarães, Luiza Neves, additional, Benchimol, Maíra, additional, Twardowschy, Manuela Catharina, additional, Ferreira‐Riveros, Marcela, additional, da Silva, Marcelo, additional, Jardim, Márcia Maria de Assis, additional, Fontes, Marco Aurélio Leite, additional, Tortato, Marcos Adriano, additional, do Nascimento, Marcos Tadeu, additional, Sekiama, Margareth Lumy, additional, Nascimento‐Costa, Maria Clara, additional, dos Santos, Maria Ester Bueno, additional, Morini, Maria Santina de Castro, additional, Nagy‐Reis, Mariana Baldy, additional, Kaizer, Mariane da Cruz, additional, Sant'Anna, Mariano José Ribeiro da Silva, additional, Hartmann, Marilia Teresinha, additional, Favarini, Marina Ochoa, additional, Olivo, Marina Oliveira, additional, Montes, Martín Alejandro, additional, Alvaréz, Martin Roberto del Valle, additional, Haddad, Matheus Feldstein, additional, Costa, Maurício Djalles, additional, Graipel, Maurício Eduardo, additional, Konzen, Mauricio Quoos, additional, Galetti, Mauro, additional, Almeida, Meyline de Oliveira Souza, additional, Faria, Michel Barros, additional, Luiz, Micheli Ribeiro, additional, Baptista, Michelle Noronha da Matta, additional, Marini, Miguel Ângelo, additional, Ribeiro, Milton Cezar, additional, Olifiers, Natalie, additional, de Albuquerque, Natasha Moraes, additional, Cantero, Nicolás, additional, Peroni, Nivaldo, additional, Zanella, Noeli, additional, Mendonça‐Furtado, Olívia, additional, Pays, Olivier, additional, Ferretti, Orlando Ednei, additional, Rocha‐Barbosa, Oscar, additional, Santos, Paloma Marques, additional, de Farias, Patrícia Menegaz, additional, da Rocha, Patrício Adriano, additional, Colas‐Rosas, Paul François, additional, Ribeiro‐Souza, Paula, additional, Ferracioli, Paula, additional, Hartmann, Paulo Afonso, additional, Antas, Paulo de Tarso Zuquim, additional, Ribeiro, Paulo, additional, Tomasi Sarti, Paulo, additional, Mônico, Paulo Ivo, additional, de Castilho, Pedro Volkmer, additional, Pereira, Peônia Brito de Moraes, additional, Crawshaw, Peter Gransden, additional, Renaud, Pierre‐Cyril, additional, Romagna, Rafael Spilere, additional, de Sousa, Rafael Turíbio Moraes, additional, Spagnol, Raíssa Soares, additional, Beltrão‐Mendes, Raone, additional, Mariano, Ravi Fernandes, additional, Rocha, Renata Reinoso, additional, Sousa‐Lima, Renata, additional, Pagotto, Renata Valls, additional, de Faria, Rhayssa Terra, additional, Arrais, Ricardo Corassa, additional, Moratelli, Ricardo, additional, Sartorello, Ricardo, additional, Bianchi, Rita de Cassia, additional, Guimarães, Roberto de Carvalho, additional, Massara, Rodrigo Lima, additional, Costa, Romulo Theodoro, additional, Marques, Rosane Vera, additional, Nunes, Ruan Márcio Ruas, additional, Hartz, Sandra Maria, additional, Silvestre de Sousa, Saulo Meneses, additional, Lima, Saulo Ramos, additional, Barbosa, Sergio Lutz, additional, Godoy, Silvia Neri, additional, Ferrari, Stephen Francis, additional, de Araújo‐Piovezan, Talita Guimarães, additional, Góes, Talita Laura, additional, Trigo, Tatiane Campos, additional, de Freitas, Thales R. O., additional, Maccarini, Thiago Bernardes, additional, de Castro, Thiago Marcial, additional, Bella, Thiago Ribas, additional, de Oliveira Junior, Tonny Marques, additional, Cunha, Uslaine Maciel, additional, Kanaan, Vanessa Tavares, additional, Pfannerstill, Vera, additional, Pimentel, Victor Siqueira, additional, Picinatto Filho, Vilmar, additional, Alves, Vinícius Nunes, additional, Rojas‐Bonzi, Viviana, additional, Mottin, Viviane, additional, Rocha, Vlamir José, additional, Kindel, Andreas, additional, and Coelho, Igor Pfeifer, additional

Published
2024
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19. Thermal effects and ephaptic entrainment in Hodgkin–Huxley model.

Author

de Sousa, Matheus Phellipe Brasil, Cunha, Gabriel Moreno, Corso, Gilberto, and dos Santos Lima, Gustavo Zampier

Subjects
NEURAL physiology, ACTION potentials, EPILEPSY, BIOLOGICAL systems, INFLAMMATION, MOTOR unit
Abstract

The brain is understood as an intricate biological system composed of numerous elements. It is susceptible to various physical and chemical influences, including temperature. The literature extensively explores the conditions that influence synapses in the context of cellular communication. However, the understanding of how the brain's global physical conditions can modulate ephaptic communication remains limited due to the poorly understood nature of ephapticity. This study proposes an adaptation of the Hodgkin and Huxley (HH) model to investigate the effects of ephaptic entrainment in response to thermal changes (HH-E). The analysis focuses on two distinct neuronal regimes: subthreshold and suprathreshold. In the subthreshold regime, circular statistics are used to demonstrate the dependence of phase differences with temperature. In the suprathreshold regime, the Inter-Spike Interval are employed to estimate phase preferences and changes in the spiking pattern. Temperature influences the model's ephaptic interactions and can modify its preferences for spiking frequency, with the direction of this change depending on specific model conditions and the temperature range under consideration. Furthermore, temperature enhance the anti-phase differences relationship between spikes and the external ephaptic signal. In the suprathreshold regime, ephaptic entrainment is also influenced by temperature, especially at low frequencies. This study reveals the susceptibility of ephaptic entrainment to temperature variations in both subthreshold and suprathreshold regimes and discusses the importance of ephaptic communication in the contexts where temperature may plays a significant role in neural physiology, such as inflammatory processes, fever, and epileptic seizures. [ABSTRACT FROM AUTHOR]

Published
2024
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31. A direct method to detect deterministic and stochastic properties of data

Author

Prado, Thiago, Boaretto, Bruno, Corso, Gilberto, Dos Santos Lima, Gustavo Zampier, Kurths, Jürgen, Lopes, Sergio Roberto, Prado, Thiago, Boaretto, Bruno, Corso, Gilberto, Dos Santos Lima, Gustavo Zampier, Kurths, Jürgen, and Lopes, Sergio Roberto

Abstract

A fundamental question of data analysis is how to distinguish noise corrupted deterministic chaotic dynamics from time-(un)correlated stochastic fluctuations when just short length data is available. Despite its importance, direct tests of chaos vs stochasticity in finite time series still lack of a definitive quantification. Here we present a novel approach based on recurrence analysis, a nonlinear approach to deal with data. The main idea is the identification of how recurrence microstates and permutation patterns are affected by time reversibility of data, and how its behavior can be used to distinguish stochastic and deterministic data. We demonstrate the efficiency of the method for a bunch of paradigmatic systems under strong noise influence, as well as for real-world data, covering electronic circuit, sound vocalization and human speeches, neuronal activity, heart beat data, and geomagnetic indexes. Our results support the conclusion that the method distinguishes well deterministic from stochastic fluctuations in simulated and empirical data even under strong noise corruption, finding applications involving various areas of science and technology. In particular, for deterministic signals, the quantification of chaotic behavior may be of fundamental importance because it is believed that chaotic properties of some systems play important functional roles, opening doors to a better understanding and/or control of the physical mechanisms behind the generation of the signals., Financiadora de Estudos e Projetoshttps://doi.org/10.13039/501100004809, Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorhttps://doi.org/10.13039/501100002322, Conselho Nacional de Desenvolvimento Científico e Tecnológicohttps://doi.org/10.13039/501100003593, Peer Reviewed

Published
2022

33. Scale-free distribution of silences

Author

de Sousa, Ivandson P., primary, dos Santos Lima, Gustavo Zampier, additional, Oliveira, Eliziane G., additional, Duarte, Marina Henriques Lage, additional, Alves-Gomes, José A., additional, Lopes, Lara C., additional, Ferreira, Luane S., additional, Sousa-Lima, Renata S., additional, and Corso, Gilberto, additional

Published
2022
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