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+34 946 567 842
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+34 946 567 842
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dbarros@bcamath.org
Information of interest
- Orcid: 0000-0002-7762-8862
Postdoctoral Fellow at BCAM.
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Biphasic changes in hippocampal granule cells after traumatic brain injury
Danielewicz, J.
; Llamosas, N.; Durá, I.; Barros de Souza, D.; Rodrigues, S.; Encinas, J.M.; Mateos, D.M. (2025-08-01)
Traumatic brain injury (TBI) leads to a wide range of long-lasting physical and cognitive impairments. Changes in neuronal excitability and synaptic functions in the hippocampus have been proposed to underlie cognitive ...
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Efficient set-theoretic algorithms for computing high-order Forman-Ricci curvature on abstract simplicial complexes
Barros de Souza, D.; Teodomiro, J.; A N Santos, F.; Jost, J.; Rodrigues, S. (2024-11-19)
Forman-Ricci curvature (FRC) is a potent and powerful tool for analysing empirical networks, as the distribution of the curvature values can identify structural information that is not readily detected by other geometrical ...
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The Euler characteristic as a topological marker for outbreaks in vector-borne disease
Barros de Souza, D.; Figueiroa dos Santos, E.; A N Santos, F. (2022-12-01)
Abstract. Epidemic outbreaks represent a significant concern for the current state of global health, particularly in Brazil, the epicentre of several vector-borne disease outbreaks and where epidemic control is still a ...
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Fock-space approach to stochastic susceptible-infected-recovered models
Barros de Souza, D.; Araújo, H.; Duarte-Fillho, G.; Gaffney, E.; Nóbrega Santos, F.; Raposo, E. (2022-07-25)
We investigate the stochastic susceptible-infected-recovered (SIR) model of infectious disease dynamics in the Fock-space approach. In contrast to conventional SIR models based on ordinary differential equations for the ...
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Using discrete Ricci curvatures to infer COVID-19 epidemic network fragility and systemic risk
Barros de Souza, D.; Da Cunha, J.; Figueroa dos Santos, E.; Correia, J.; P. da Silva, H.; De Lima Filho, J.L.; Alburquerque, J.; Santos, F. (2021)
The damage of the novel Coronavirus disease (COVID-19) is reaching unprecedented scales. There are numerous classical epidemiology models trying to quantify epidemiology metrics. Usually, to forecast epidemics, classical ...