Opinion formation models based on game theory

A way to simulate the basic interactions between two individuals with different opinions, in the context of strategic game theory, is proposed. Various games are considered, which produce different kinds of opinion formation dynamics. First, by assuming that all individuals (players) are equals, we obtain the bounded confidence model of continuous opinion dynamics proposed by Deffuant et al. In such a model a tolerance threshold is defined, such that individuals with difference in opinion larger than the threshold can not interact. Then, we consider that the individuals have different inclinations to change opinion and different abilities in convincing the others. In this way, we obtain the so-called ``Stubborn individuals and Orators'' (SO) model, a generalization of the Deffuant et al. model, in which the threshold tolerance is different for every couple of individuals. We explore, by numerical simulations, the dynamics of the SO model, and we propose further generalizations that can be implemented.Comment: 18 pages, 4 figure

Microstructure and chemical composition of Roman orichalcum coins emitted after the monetary reform of Augustus (23 B.C.)

A collection of ancient Roman orichalcum coins, i.e., a copper-zinc alloy, minted under the reigns from Caesar to Domitianus, have been characterised using scanning electron microscopy (SEM-EDS) and electron microprobe analysis (EMPA). We studied, for the first time, coins emitted by Romans after the reforms of Augustus (23 B.C.) and Nero (63-64 A.D). These coins, consisting of asses, sestertii, dupondii and semisses, were analysed using non- and invasive analyses, aiming to explore microstructure, corrosive process and to acquire quantitative chemical analysis. The results revealed that the coins are characterized by porous external layers, which are affected by dezincification and decuprification processes. As pictured by the X-ray maps, the elemental distribution of Cu and Zn shows patterns of depletion that in some cases penetrate in deep up to 1 mm. The composition of the un-corroded nucleus is a Cu-Zn alloy containing up to 30% of Zn, typical of coins produced via cementation process

Development of a quantitative descriptive sensory honey analysis: application to eucalyptus and clover honeys

Sensory analysis of bee honey is an important tool for determining its floral origin, for subsequent quality control practices and which ultimately will determine consumer preferences towards this product. A procedure for the selection, training and monitoring of assessors was applied. Unifloraleucalyptus and clover honeys produced in Argentine were assessed using descriptive quantitative analysis. The sensory profiles differentiated clover honey (light, fruity and floral flavor with low intensity) from eucalyptus honey (more intense flavors, vegetable notes, aromatic, warm, small crystals with a high tendency to quick crystallization in mass). The analysis by principal components showed higher intensities of sweetness and smell for eucalyptus honeys and graininess for clover honeys. These appropriate indicators of quality provide a differentiating tool to increase the added value of these honeys.Fil: Ciappini, Maria Cristina. Universidad del Centro Educativo Latinoamericano; ArgentinaFil: Di Vito, M. V.. Universidad del Centro Educativo Latinoamericano; ArgentinaFil: Gatti, M. B.. Universidad del Centro Educativo Latinoamericano; ArgentinaFil: Calviño, Amalia Mirta. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Metabolismo del Fármaco. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Metabolismo del Fármaco; Argentin

Calibrating chemical multisensory devices for real world applications: An in-depth comparison of quantitative Machine Learning approaches

Chemical multisensor devices need calibration algorithms to estimate gas concentrations. Their possible adoption as indicative air quality measurements devices poses new challenges due to the need to operate in continuous monitoring modes in uncontrolled environments. Several issues, including slow dynamics, continue to affect their real world performances. At the same time, the need for estimating pollutant concentrations on board the devices, espe- cially for wearables and IoT deployments, is becoming highly desirable. In this framework, several calibration approaches have been proposed and tested on a variety of proprietary devices and datasets; still, no thorough comparison is available to researchers. This work attempts a benchmarking of the most promising calibration algorithms according to recent literature with a focus on machine learning approaches. We test the techniques against absolute and dynamic performances, generalization capabilities and computational/storage needs using three different datasets sharing continuous monitoring operation methodology. Our results can guide researchers and engineers in the choice of optimal strategy. They show that non-linear multivariate techniques yield reproducible results, outperforming lin- ear approaches. Specifically, the Support Vector Regression method consistently shows good performances in all the considered scenarios. We highlight the enhanced suitability of shallow neural networks in a trade-off between performance and computational/storage needs. We confirm, on a much wider basis, the advantages of dynamic approaches with respect to static ones that only rely on instantaneous sensor array response. The latter have been shown to be best choice whenever prompt and precise response is needed

Host-parasite relationships in root-knot disease of white mulberry

Severe infections of white mulberry feeder roots and heavy soil infestations by Meloidogyne arenaria race 2 were found in southern Spain. This is the first record of M. arenaria on white mulberry in Europe. Morphometric observations, analysis of the esterase electrophoretic pattern, and artificial inoculations of race differentials were used to characterize nematodes. Nematode-induced mature galls were spherical and usually contained one or more females, males, and egg masses with eggs. Feeding sites were characterized by the development of giant cells that contained granular cytoplasm and many hypertrophied nuclei. Giant cell cytoplasm was aggregated along a thickened cell wall. Vascular tissues within galls appeared disorganized. The relationship between the initial nematode population density (Pi) in a series from 0 to 1,024 eggs and juveniles/cm3 soil and growth of white mulberry seedlings was tested in the greenhouse. A Seinhorst model was fitted to plant height and top fresh weight. Tolerance limits of white mulberry to M. arenaria race 2 for plant height and top fresh weight were, respectively, 1.1 and 1.38 eggs and juveniles/cm3 soil. The minimum relative values for plant height and top fresh weight were 0 at Pi > 64 and Pi > 128 eggs and juveniles/cm3 soil, respectively. Maximum nematode reproduction rate was 435-fold at the lowest Pi. Additional keywords: histopathology, Morus alba, pathogenicity, threshold limitPeer reviewe