Food safety policies have gained considerable importance in recent years, food safety being one of the indicators that illustrates the standard of living and quality of life within a nation state. In order to assess food security, we analyzed the Global Food Security Index (GFSI) that, economically, is based on GDP, degree of poverty and agricultural production, extending also to areas such as government and public policies, which are usually not directly included in food safety indicators or generating factors. Considering the importance and impact of food safety, starting from the theoretical concepts, from the current state of food safety in Europe, presented by the means of GFSI and its components, we developed a set of measures based on the grouping (correlation) of states following the analysis of hierarchical ranking of clusters. To analyse clusters hierarchical ranking the food safety indicators were used as input, dependent data. As an independent variable, with a strong influence on all the others, determined by means of multiple linear regression, we considered GDP/inhabitant at the level of each analysed state. The design of the set of measures considered the correlation that can be established among the various GFSI indicators that influence and generate the current state of food security in different European countries and the influence these indicators can have on maintaining or improving this state.

Abstract. A relevant application of the stochastic convex order is the well-known weighted Hermite-Hadamard inequality, where the weight is provided by a given probability distribution. Our goal is to show that, starting from such a fixed weight, we can fill the whole space between the Hermite-Hadamard bounds by highlighting some parametric families of probability distributions. Thus, we propose two alternative constructions based on the convex ordering properties.Mathematics subject classification (2010): 26A51, 26B25, 26D10.

This paper deals with the problem of estimating the deviation of the values of a function from its mean value. We consider the following special cases: (i) the case of random variables (attached to arbitrary probability fields); (ii) the comparison is performed additively or multiplicatively; (iii) the mean value is attached to a multiplicative averaging process.

No abstract

In this paper we consider a three-dimensional nonlinear system which models the dynamics of a population during an epidemic disease. The considered model is a SIS-type system in which a recovered individual automatically becomes a susceptible one. We take into account the births and deaths, and we also consider that susceptible individuals are divided into two groups: non-vaccinated and vaccinated. In addition, we assume a medical scenario in which vaccinated people take a special measure to quarantine their newborns. We study the stability of the considered system. Numerical simulations point out the behavior of the considered population.