Evolutionary Games on Networks
The research topic concerns the development of new mathematical models, grounded on evolutionary game equations, able to embed a social network among the players.
In this way we can describe decision mechanisms under selection pressure and social influence. Besides its theoretical impact, the model has also been applied
to model the formation of
networks among the members of a microbial population as a response to hostile environments.
D. Madeo, A. Talarico, A. Pascual-Leone, C. Mocenni end E. Santarnecchi, "An Evolutionary Game Theory Model of Spontaneous Brain Functioning", Scientific Reports Vol. 7, Article number: 15978, 2017.
G. Iacobelli, D. Madeo and C. Mocenni, "Lumping evolutionary game dynamics on networks", Journal of Theoretical Biology, Vol. 407, pp. 328–338, 2016.
D. Madeo and C. Mocenni, "Game interactions and dynamics on networked populations",
IEEE Transactions on Automatic Control, Vol. 60, N. 7, pp. 1801-1810, 2015.
D. Madeo, L.R. Comolli and C. Mocenni, "Emergence of microbial networks as response to hostile
environments", Frontiers in Microbiology, Vol. 5, N. 407, 2014.
Modeling, Analysis and Identification of Biological Systems
This research deals with development and identification of dynamic
models of biological systems. After the modeling phase, two
main approaches are followed: the first one consists in the estimation
of the model parameters through an identification procedure based on
real data. The second one deals with the application of nonlinear
analysis methods for modeling and analyzing their complex behavior.
With this aim, one of the main objectives is to make an effort for
bridging the identification stage with the qualitative analysis of the
model dynamics, in order to gain a better understanding of system
behavior and obtain reliable estimates for the model parameters and
exogenous inputs. Several applications have been investigated, such as metabolic modeling of microorganisms and biogeochemical
modeling of lagoon ecosystems and kinetic. In the last case, homogenization and multiple scale techniques have also been applied to take into account
the presence of roughness in the boundaries.
C. Rossi, P. Madl, A. Foletti and C. Mocenni, "Equilibrium and far-from equilibrium states", in
Fields of the Cell, D. Fels, M. Cifra and F. Scholkmann eds., Research Signpost Press, (Kerala,
India), pp. 71-94, 2015.
C. Mocenni, E. Sparacino, J. P. Zubelli, "Effective rough boundary parametrization for reaction diffusion systems",
Applicable Analysis and Discrete Mathematics, Vol. 8, pp. 33-5, 2014.
A. Boianelli, A. Bidossi, L. Gualdi, L. Mulas, C. Mocenni, G. Pozzi, A. Vicino, M. R. Oggioni,
"A Non-Linear Deterministic Model for Regulation of Diauxic Lag on Cellobiose by the Pneumococcal
Multidomain Transcriptional Regulator CelR", PLOS ONE, vol. 7 (10), 2012.
C. Mocenni, D. Madeo, and E. Sparacino, "Linear least squares
parameter estimation of nonlinear reaction diffusion equations", Mathematics and Computers in Simulation, Vol. 81, pp. 2244-2257, 2011.
A. Facchini and C. Mocenni, "Filling gaps in ecological time series by means of twin surrogates",
International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, Vol. 21, N. 4, pp.
The research topic concerns the application of nonlinear time series
analysis to the reconstruction of embedded state spaces and detection
of critical regimes in complex systems. In particular, the main
contribution in this field consists in extending measures usually applied to time
series to PDEs, such as reaction-diffusion equations. The methodology allowed the identification of
structurally different regimes, e.g. stable and unstable spiral waves,
in the Complex Ginzburg-Landau equation and in biological and
biochemical reaction-diffusion systems undergoing Turing instabilities.
Stochastic simulation and control of reactio-diffusion equations with Turing instabilities is under development.
A. Facchini, C. Mocenni, "Recurrence methods for the identication of morphogenetic patterns",
Plos ONE, Vol. 8, N.9, pp. e73686, 2013.
C. Mocenni, A. Facchini, and A. Vicino, "Comparison of recurrence quantification methods for the analysis of temporal and spatial chaos",
Mathematical and Computer Modelling, Vol. 53, pp. 1535-1545, 2011.
C. Mocenni, A. Facchini, A. Vicino, "Identifying the dynamics of complex
spatio-temporal systems by spatial recurrence properties",
Proceedings of the National Academy of Sciences of USA Vol. 107, N. 18, pp. 8097-8102, 2010.
Brain Dynamics and Behavior
The research topic concerns the application of nonlinear time series
analysis to the analysis of brain patterns with particular attention to the level of hypnotizability of subjects.
The study is conducted by analyzing the EEG time series recorded in several regions of the scalpo of resting state, not hypnotized subjects.
The application of evolutionary game equations to the modeling of brain dynamics is under development.
D. Madeo, E. Castellani, C. Mocenni and E.L. Santarcangelo, "Pain perception and EEG dynamics:
Does hypnotizability account for the ecacy of the suggestions of analgesia?", Physiology and
Behavior, Vol. 145, pp. 57-63, 2015.
R. Chiarucci, D. Madeo, M.I. Loredo, E. Castellani, E.L. Santarcangelo and C. Mocenni, "Crossevidence
for hypnotic susceptibility through nonlinear measures on EEGs of non-hypnotized subjects",
Scientic Report, 4:5610, 2014.
D. Madeo, E. Castellani, E.L. Santarcangelo, C. Mocenni, "Hypnotic assessment based on the
Recurrence Quantication Analysis of EEG recorded in the ordinary state of consciousness', Brain
and Cognition, Vol. 83, N. 2, pp. 227-233, 2013.
Decision Support Systems
This research deals with the development of tools for the correct
management of coastal areas with anthropic exploitation, which is a
difficult task for local authorities. Socio-economic interests and
environment preservation are typically contrasting objectives between
which a suitable trade-off must be achieved. The solution to this
problem requires the development of interdisciplinary and multicriteria
approaches. Decision support systems are suitable tools for integrating
the different kinds of mathematical and analytical models, such as
biogeochemical, hydrodynamic, ecological, socio-economic models. A
Decision Support System has been developed for the management of
eutrophication and aquaculture in the Sacca di Goro Lagoon (Italy).
M. Casini, C. Mocenni, S. Paoletti, M. Pranzo, "Decision support system development for integrated
management of European coastal lagoons", Environmental Modelling & Software, Vol. 64,
pp. 47-57, 2015.
A. Newton, J. Icely, S. Cristina, A. Brito, A. C. Cardoso, F. Colijn, S. Dalla Riva, F. Gertz, J.
W. Hansen, M. Holmer, K. Ivanova, E. Leppakoski, D. Melaku Canu, C. Mocenni, S. Mudge,
N. Murray, M. Pejrup, A. Razinkovas, S. Reizopoulou, A. Perez-Ruzafa, G. Schernewski, H.
Schubert, L. Carr, C. Solidoro, P. Viaroli and J.M. Zaldivar, "An overview of ecological status,
vulnerability and future perspectives of European large shallow, semi-enclosed coastal systems,
lagoons and transitional waters", Estuarine, Coastal and Shelf Science, Vol. 140, pp. 95-122, 2014.
P. Viaroli, G. Giordani, C. Mocenni, E. Sparacino, S. Lovo, S. Bencivelli, "The Sacca di Goro:
a cooperative decision making experiment for a sustainable lagoon exploitation, In: Carlo Sessa. Sustainable Water Ecosystems Management in Europe.
p. 83-96, IWA Publishing, 2012.