On the nonlinear stability of a continuous duopoly model with constant conjectural variation

The paper concerns a continuous model governed by a ODE system originated by a discrete duopoly model with bounded rationality, based on constant conjectural variation. The aim of the paper is to show (i) the existence of an absorbing set in the phase space; (ii) linear stability analysis of the critical points of the system; (iii) nonlinear, global asymptotic stability of equilibrium of constant conjectural variation.

Eugenio Elia Levi, normalista e volontario e caduto nella grande guerra

Eugenio Elia Levi (1883-1917) fu uno dei più grandi matematici italiani del 900, come del resto il fratello Beppo. La sua produzione scientifica fu tanto profonda quanto differenziata, venne immediatamente apprezzata negli ambienti matematici internazionali e, a distanza di un secolo, conserva grande attualità in diversi campi della matematica. Momento importantissimo per la sua formazione fu la permanenza nella Scuola Normale Superiore di Pisa.

An Integrated Decision Support System to Solve Multi-Criteria Orienteering Problem

In this work we proposed an integrated support system combining a meta-heuristic algorithm and a multicriteria decision analysis method to solve an orienteering problem applied to car-pooling system. For this purpose a Genetic Algorithm (GA), an Analytical Hierarchy Process (AHP) are implemented. The research is based on the awareness that decision makers (DMs) often face situations in which different conflicting viewpoints (goals or criteria) are to be considered. Current car-pooling web platforms are focused on the exchange of information among potential users and drivers.

Source modelling of ElectroCorticoGraphy data: stability analysis and spatial filtering

ElectroCOrticoGraphy (ECoG) is an invasive neuroimaging technique that measures electrical potentials produced by brain currents via an electrode grid implanted on the cortical surface. A full interpretation of ECoG data is difficult because it requires solving the inverse problem of reconstructing the spatio-temporal distribution of neural currents responsible of the recorded ECoG signals, which is ill-posed. Only in the last few years novel computational methods to solve this inverse problem have been developed. This study describes a beamformer method for ECoG source modeling.

Source modelling of ElectroCorticoGraphy (ECoG) data: stability analysis and spatial filtering

Electrocorticography (ECoG) is a neurophysiological modality that measures the distribution of electrical potentials, associated with either spontaneous or evoked neural activity, by means of electrodes grids implanted close to the cortical surface. A full interpretation of ECoG data, however, requires solving the ill-posed inverse problem of reconstructing the spatio-temporal distribution of neural currents responsible for the recorded signals.

Bayesian estimation of multiple static dipoles from EEG time series: validation of an SMC sampler

Source modeling of EEG data is an important tool for both neuroscience and clinical applications, such as epilepsy. Despite their simplicity, multiple dipole models remain highly desirable to explain neural sources. However, estimating dipole models from EEG time-series remains a difficult task, mainly due to the ill-posedness of the inverse problem and to the fact that the number of dipoles is usually not known a priori.

A GENETIC ALGORITHM TO DESIGN TOURISTIC ROUTES IN A BIKE SHARING

The aim of this paper is to study a Bike Sharing Touring (BST) applying a mathematical model known in operation research as Orienteering Problem (OP). Several European Cities are developing BST in order to reduce the exhaust emissions and to improve the sustainability in urban areas. The authors offer a Decision Support Tool useful for the tourist and the service's manager to organize the tourists' paths on the basis of tourists' desires, subject to usable time, place of interest position and docking station location.

IMSP schemes for spatially explicit models of cyclic populations and metapopulation dynamics

We examine spatially explicit models described by reaction-diffusion partial differential equations for the study of predator-prey population dynamics. The numerical methods we propose are based on the coupling of a finite difference/element spatial discretization and a suitable partitioned Runge-Kutta scheme for the approximation in time. The RK scheme here implemented uses an implicit scheme for the stiff diffusive term and a partitioned RK symplectic scheme for the reaction term (IMSP schemes).

Error bounds for Gauss-Jacobi quadrature rules

Gaussian quadrature has been extensively studied in literature and several error estimates have been proved under dierent smoothness assumptions of the integrand function. In this talk we are going to state a general error estimate for Gauss-Jacobi quadrature, based on the weighted moduli of smoothness introduced by Z. Ditzian and V. Totik in [1]. Such estimate improves a previous result in [1, Theorem 7.4.1] and it includes several error bounds from literature as particular cases.

The Stein and Chen-Stein methods for functionals of non-symmetric Bernoulli processes

Based on a new multiplication formula for discrete multiple stochastic integrals with respect to non-symmetric Bernoulli random walks, we extend the results of Nourdin et al. (2010) on the Gaussian approximation of symmetric Rademacher sequences to the setting of possibly non-identically distributed independent Bernoulli sequences. We also provide Poisson approximation results for these sequences, by following the method of Peccati (2011).