1,721,001 research outputs found
Identification and Simulation of a Spatial Ecological Model in a Lake with Fractal Boundary
No full textWe propose a 2D ecological model of phytoplankton dynamics accounting for the distribution and the evolution of algae in a large basin located in the Amazonian region. The model is described by a set of reaction-drift-diffusion equations and is driven by several exogenous inputs, such as wind velocity and direction, water temperature and solar radiation. Due to the roughness of the domain, a preliminary boundary extraction with a curvelet algorithm is performed. Then, the model is simulated in an approximated domain, where the contour has been reconstructed by estimating a set of Recurrent Fractal Interpolation Functions, aimed at preserving its fractal structure. Simulations are combined with time and space chlorophyll-a data in order to estimate the parameters of the model. The proposed algorithm is based on an iterative two-step identification procedure, where reaction parameters are recovered first and then used for estimating diffusion and transport parameters. Comparison results at different accuracy approximations and before and after the algorithm implementation are presented and discussed
Identification and Control of Game-Based Epidemic Models
Full text linkThe effectiveness of control measures against the diffusion of the COVID-19 pandemic is grounded on the assumption that people are prepared and disposed to cooperate. From a strategic decision point of view, cooperation is the unreachable strategy of the Prisoner’s Dilemma game, where the temptation to exploit the others and the fear of being betrayed by them drives the people’s behavior, which eventually results in a fully defective outcome. In this work, we integrate a standard epidemic model with the replicator equation of evolutionary games in order to study the interplay between the infection spreading and the propensity of people to be cooperative under the pressure of the epidemic. The developed model shows high performance in fitting real measurements of infected, recovered and dead people during the whole period of COVID-19 epidemic spread, from March 2020 to September 2021 in Italy. The estimated parameters related to cooperation result to be significantly correlated with vaccination and screening data, thus validating the model. The stability analysis of the multiple steady states present in the proposed model highlights the possibility to tune fundamental control parameters to dramatically reduce the number of potential dead people with respect to the non-controlled case
Evolutionary game theoretic insights on the SIRS model of the CoviD-19 pandemic
Full text linkThe effectiveness of control measures against the diffusion of the COVID-19 pandemic is grounded on the assumption that people are prepared and disposed to cooperate. From a strategic decision point of view, cooperation is the unreachable strategy of the prisoner's dilemma game, where the temptation to exploit the others and the fear to be betrayed by them drives the people behavior, which eventually results fully defective. In this work, we integrate the SIRS epidemic model with the replicator equation of evolutionary games in order to study the interplay between the infection spreading and the propensity of people to become cooperative under the pressure of the epidemic. We find that the developed model possesses several steady states, including fully or partially cooperative ones and that the presence of such states allows to take the disease under control. Moreover, assuming a seasonal variation of the infection rate, the system presents rich dynamics, including chaotic behavior and epidemic extinction
Decision Making in Networks: A Model of Awareness Raising
Full text linkThis work investigates how interpersonal interactions among individuals could affect the dynamics of awareness raising. Even though previous studies on mathematical models of awareness in the decision making context demonstrate how the level of awareness results from self-observation impinged by optimal decision selections and external uncertainties, an explicit accounting of interaction among individuals is missing. Here we introduce for the first time a theoretical mathematical framework to evaluate the effect on individual awareness exerted by the interaction with neighbor agents. This task is performed by embedding the single agent model into a graph and allowing different agents to interact by means of suitable coupling functions. The presence of the network allows, from a global point of view, the emergence of diffusion mechanisms for which the population tends to reach homogeneous attractors, and, among them, the one with the highest level of awareness. The structural and behavioral patterns, such as the initial levels of awareness and the relative importance the individual assigns to their own state with respect to others’, may drive real actors to stress effective actions increasing individual and global awareness
Lumping evolutionary game dynamics on networks
No full textWe study evolutionary game dynamics on networks (EGN), where players reside in the vertices of a graph, and games are played between neighboring vertices. The model is described by a system of ordinary differential equations which depends on players payoff functions, as well as on the adjacency matrix of the underlying graph. Since the number of differential equations increases with the number of vertices in the graph, the analysis of EGN becomes hard for large graphs. Building on the notion of lumpability for Markov chains, we identify conditions on the network structure allowing to reduce the original graph. In particular, we identify a partition of the vertex set of the graph and show that players in the same block of a lumpable partition have equivalent dynamical behaviors, whenever their payoff functions and initial conditions are equivalent. Therefore, vertices belonging to the same partition block can be merged into a single vertex, giving rise to a reduced graph and consequently to a simplified system of equations. We also introduce a tighter condition, called strong lumpability, which can be used to identify dynamical symmetries in EGN which are related to the interchangeability of players in the system
A Markov Decision Process with Awareness and Present Bias in Decision-Making
Full text linkWe propose a Markov Decision Process Model that blends ideas from Psychological research and Economics to study decision-making in individuals with self-control problems. We have borrowed a dual-process of decision-making with self-awareness from Psychological research, and we introduce present bias in inter-temporal preferences, a phenomenon widely explored in Economics. We allow for both an exogenous and endogenous, state-dependent, present bias in inter-temporal decision-making and explore, by means of numerical simulations, the consequences on well-being emerging from the solution of the model. We show that, over time, self-awareness may mitigate present bias and suboptimal choice behaviour
Generalized Recurrence Plots for the analysis of images from spatially distributed systems
No full textWe propose a new method for the analysis of images showing patterns emerging from the evolution of spatially distributed systems. The generalized recurrence plot (GRP) and the generalized recurrence
quantification analysis (GRQA) are exploited for the investigation of such patterns.
We focus on snapshots of spatio-temporal processes such as the formation of Turing structures and traveling waves in the Belousov-Zhabotinsky reaction, satellite images of spatial chlorophyll distribution in seas and oceans (similar to turbulent flows), colonies of Dyctiostelium discoideum, fractals, and noise.
The method is based on the GRP and GRQA and particularly on the measures determinism (DET) and entropy (ENT), providing a new criterion for the assessment and classification of images based on the
simultaneous evaluation of their global and local structure.
The DET-ENT diagram is introduced and compared with the classical image analysis entropy defined on the pixels' values. The method proposed provides appealing performances in the case of images
showing complex spatial patterns
Modeling pluralism and self-regulation explains the emergence of cooperation in networked societies
Full text linkUnderstanding the dynamics of cooperative behavior of individuals in complex societies represents a fundamental research question which puzzles scientists working in heterogeneous fields. Many studies have been developed using the unitary agent assumption, which embeds the idea that when making decisions, individuals share the same socio-cultural parameters. In this paper, we propose the ECHO-EGN model, based on Evolutionary Game Theory, which relaxes this strong assumption by considering the heterogeneity of three fundamental socio-cultural aspects ruling the behavior of groups of people: the propensity to be more cooperative with members of the same group (Endogamic cooperation), the propensity to cooperate with the public domain (Civicness) and the propensity to prefer connections with members of the same group (Homophily). The ECHO-EGN model is shown to have high performance in describing real world behavior of interacting individuals living in complex environments. Extensive numerical experiments allowing the comparison of real data and model simulations confirmed that the introduction of the above mechanisms enhances the realism in the modelling of cooperation dynamics. Additionally, theoretical findings allow us to conclude that endogamic cooperation may limit significantly the emergence of cooperation
Kinetic analysis and comparison of models of xylose metabolism by Klebsiella planticola
No full textA model for the degradation of xylose and ethanol production by Klebsiella planticola is proposed and compared with the exponential and Michaelis-Menten approaches. This model is based on the energy system diagrams and it is a simplified version of a previous model developed for the glucose and ethanol kinetics of the yeast Saccharomices cerevisiae. In this model the dynamics of the substrate and of the final product are strictly related by means of the cellular activity. This model shows superior performances with respect to the two alternatives, behaving better along the whole dynamics. (C) 1996 Academic Press, Inc
Mathematical modelling and parameter estimation of the Serra da Mesa basin
No full textThis work concerns the development and calibration of several classes of mathematical models describing ecological and bio-geochemical aspects of aquatic systems. We focus our experimental analysis on the Serra da Mesa lake in Brazil, from which the biological information is extracted by real online measurements provided by the SIMA monitoring program of the Brazilian Institute for Space Research (INPE).
A preliminary analysis is carried out so as to define the input-output data to be accounted for by the models. Furthermore, several classes of mathematical models are considered for fitting real data of biological processes. In order to do that, a two-step parameter identification/validation procedure is applied: the first step uses the integrals of the differential equations to reduce the nonlinear estimation problem to a linear least squares one. The parameter vector resulting from the first step is used for initializing a nonlinear minimization procedure. The results are discussed to assess the fitting performances of the physical and black-box models proposed in the paper. Several simulations are presented that could be used for developing scenario analysis and managing the real system
- …
