Testing Gravity with Quasi Periodic Oscillations from accreting Black Holes: the Case of Einstein-Dilaton-Gauss-Bonnet Theory

Quasi-Periodic Oscillations (QPOs) observed in the X-ray flux emitted by accreting black holes, are associated to phenomena occurring near the horizon. Future very large area X-ray instruments will be able to measure QPO frequencies with very high precision, thus probing this strong-field region. By using the relativistic precession model, we show the way in which QPO frequencies could be used to test general relativity against those alternative theories of gravity which predict deviations from the classical theory in the strong-field regime. We consider one of the best motivated strong-curvature corrections to general relativity, namely the Einstein-Dilaton-Gauss-Bonnet theory, and show that a detection of QPOs with the expected sensitivity of the proposed ESA M-class mission LOFT would set the most stringent constraints on the parameter space of this theory.Comment: 10 pages, 5 figures, 1 table; minor changes to match the version appearing on Ap

Bio-Inspired Collective Decision-Making in Game Theoretic Models and Multi-Agent Systems

Collective decision-making can be investigated in a variety of different contexts, from opinion dynamics to swarm robotics. In the context of honeybee swarms, the evolutionary dynamics corresponding to the honeybee consensus problem can be studied via game theoretic tools. Evolutionary game theory provides the necessary tools to capture the relevant aspects for the decision-making process, whereas mean-field game theory serves well as a framework to analyse the optimal response of a large number of interacting players, even in the case of adversarial disturbance, where the aim is to ensure the robustness of the system to worst-case deterministic perturbations. The interactions among players, often originating in the corresponding real system from a social or physical structure, e.g. humans or animals for social and nodes of a power network for physical, can be captured by means of a network. In this thesis, the model originating in the context of bio-inspired collective decision-making is formulated in a game theoretic framework. The study of the corresponding consensus problem is carried out by analysing the stability property of the system and the corresponding optimal strategies in the presence of an adversarial disturbance. A threshold is identified to prevent a situation of deadlock, which happens when the population is stuck in a scenario where no option has predominantly taken over. The analysis is then extended to compartmental models, which share similarities with the original system and gives insight on asymmetric evolutions of the system. Through this link, other relevant applications are considered, such as duopolistic competition in marketing and virus propagation in smart grids. Finally, structured environments are explored as an extension to the original model, and the structure is captured by means of undirected graphs or of the Barabási-Albert scale-free (SF) complex network model

Evolutionary Game Dynamics for Crowd Behavior in Emergency Evacuations

This paper studies the problem of a large group of individuals that has to get to a safety exit in the context of high-stress emergency evacuations. We model this problem as a discrete-state continuous-time game, where the players update their strategies to reach the exit within a defined time horizon, whilst avoiding undesirable situations such as congestion and being trampled. The proposed model builds on crowd dynamics in a two-strategy game theoretic context, which we extend to include aspects of crowd behavior originating in sociology and psychology, and in the analogous studies performed in immersive virtual environments. The main contribution of this paper is threefold: i) we propose a novel game formulation of the model in terms of the population distribution across three strategies, and provide a link with prospect theory; ii) we study the equilibria of the system and their stability via Lyapunov stability theory of nonlinear systems; iii) we extend the model to a multi-population setting, where each population represents the group of players at a certain distance from the exit

A Multi-Agent Reinforcement Learning Approach to Promote Cooperation in Evolutionary Games on Networks with Environmental Feedback

A prominent feature of biological organization in many species of social animals is the ability to achieve cooperation. However, despite its predominance in natural evolution, cooperative behaviors come at a cost, typically in the form of do ut des mechanisms (e.g., reciprocal altruism in vampire bats) with given thresholds for sharing resources or communication efforts. In this paper, we investigate the conditions of cooperation through the evolutionary dynamics of the prisoner's dilemma (PD) game as well as the learning dynamics resulting from the corresponding multi-agent reinforcement learning (MARL) model. In both cases, the interactions in the population are captured by a regular network and the impact of the players' actions is reflected through the evolution of an environmental resource, which also acts as a feedback on the dynamics. The following is a list of contributions: i) we provide a full characterization of the stability properties of the networked feedback-evolving PD game; ii) we determine a set of threshold values below which cooperation is promoted; iii) we develop the corresponding cross-learning model, which is a stateless MARL model, and we show that this model is equivalent to the networked PD game with environmental feedback.</p

Cascading Failures in the Global Financial System: A Dynamical Model

In this paper, we propose a dynamical model to capture cascading failures among interconnected organizations in the global financial system. Failures can take the form of bankruptcies, defaults, and other insolvencies. The network that underpins the financial interdependencies between different organizations constitutes the backbone of the financial system. A failure in one or more of these organizations can lead the propagation of the financial collapse onto other organizations in a domino effect. Paramount importance is therefore given to the mitigation of these failures. Motivated by the relevance of this problem and recent prominent events connected to it, we develop a framework that allows us to investigate under what conditions organizations remain healthy or are involved in the propagation of the failures in the network. The contribution of this paper is the following: i) we develop a dynamical model that describes the equity values of financial organizations and their evolution over time given an initial condition; ii) we characterize the equilibria for this model by proving the existence and uniqueness of these equilibria, and by providing an explicit expression for them; and iii) we provide a computational method via sign-space iteration to analyze the propagation of failures and the attractive equilibrium point

The Role of Asymptomatic Individuals in the COVID-19 Pandemic via Complex Networks

Recent seroprevalence studies have tried to estimate the real number of asymptomatic cases affected by COVID-19. It is of paramount importance to understand the impact of these infections in order to prevent a second wave. This study aims to model the interactions in the population by means of a complex network and to shed some light on the effectiveness of localised control measures in Italy in relation to the school opening in mid-September. The formulation of an epidemiological predictive model is given: the advantage of using this model lies in that it discriminates between asymptomatic and symptomatic cases of COVID-19 as the interactions with these two categories of infected individuals are captured separately, allowing for a study on the impact of asymptomatic cases. This model is then extended to a structured nonhomogeneous version by means of the Watts-Strogatz complex network, which is adopted widely to model societal interactions as it holds the small world property. Finally, a case study on the situation in Italy is given: first the homogeneous model is used to compare the official data with the data of the recent seroprevalence study from Istat; second, in view of the return to school in mid-September, a study at regional level is conducted. The results of this study highlight the importance of coordinating the deployment of appropriate control measures that take into account the role of asymptomatic infections, especially in younger individuals, and inter-regional connectivity in Italy.Comment: 38 pages, journa

Nanostructured delivery systems with improved leishmanicidal activity: a critical review

Natascia Bruni,1 Barbara Stella,2 Leonardo Giraudo,1 Carlo Della Pepa,2 Daniela Gastaldi,3 Franco Dosio2 1Candioli Pharmaceutical Institute Srl, Beinasco, Italy; 2Department of Drug Science and Technology, University of Turin, Turin, Italy; 3Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy Abstract: Leishmaniasis is a vector-borne zoonotic disease caused by protozoan parasites of the genus Leishmania, which are responsible for numerous clinical manifestations, such as cutaneous, visceral, and mucocutaneous leishmaniasis, depending on the site of infection for particular species. These complexities threaten 350 million people in 98 countries worldwide. Amastigotes living within macrophage phagolysosomes are the principal target of antileishmanial treatment, but these are not an easy target as drugs must overcome major structural barriers. Furthermore, limitations on current therapy are related to efficacy, toxicity, and cost, as well as the length of treatment, which can increase parasitic resistance. Nanotechnology has emerged as an attractive alternative as conventional drugs delivered by nanosized carriers have improved bioavailability and reduced toxicity, together with other characteristics that help to relieve the burden of this disease. The significance of using colloidal carriers loaded with active agents derives from the physiological uptake route of intravenous administered nanosystems (the phagocyte system). Nanosystems are thus able to promote a high drug concentration in intracellular mononuclear phagocyte system (MPS)-infected cells. Moreover, the versatility of nanometric drug delivery systems for the deliberate transport of a range of molecules plays a pivotal role in the design of therapeutic strategies against leishmaniasis. This review discusses studies on nanocarriers that have greatly contributed to improving the efficacy of antileishmaniasis drugs, presenting a critical review and some suggestions for improving drug delivery. Keywords: amphotericin B, drug delivery systems, drug targeting, human leishmaniasis, polymeric nanoparticl