A code for square permutations and convex permutominoes

In this article we consider square permutations, a natural subclass of permutations defined in terms of geometric conditions, that can also be described in terms of pattern avoiding permutations, and convex permutoninoes, a related subclass of polyominoes. While these two classes of objects arised independently in various contexts, they play a natural role in the description of certain random horizontally and vertically convex grid configurations. We propose a common approach to the enumeration of these two classes of objets that allows us to explain the known common form of their generating functions, and to derive new refined formulas and linear time random generation algorithms for these objects and the associated grid configurations.Comment: 18 pages, 10 figures. Revision according to referees' remark

Sensible debt buybacks for highly indebted countries

Previous studies indicate that debt buybacks at market prices benefit lenders the most because the lack of a seniority structure in sovereign lending distorts secondary market prices upward. The author examines whether welfare-improving buybacks would arise at the"fair"price. If so, policy intervention is needed to remove the distortion. In a model of intertemporal consumption smoothing, buybacks at the fair price are desirable if the country experiences unusually heavy export earnings and if large reserve holdings tend to increase transfers to creditors in default states. Concerted agreements in which debt repurchases are linked to cuts in interest rates or new money requirements can make buybacks at the fair price viable, while preventing the free-rider problem among lenders.Economic Theory&Research,Banks&Banking Reform,Environmental Economics&Policies,Financial Intermediation,Strategic Debt Management

I piani settoriali a scala urbana

Il contributo propone un focus su alcuni strumenti di settore che affrontano specifiche tematiche alla scala urbana, con particolare riferimento agli strumenti per la tutela della qualità ambientale e per il governo della mobilità. Si evidenziano, in entrambi i casi, le significative interrelazioni tra problematiche ambientali e scelte relative all’evoluzione/trasformazione dei contesti urbani e al governo della mobilità e la conseguente necessità di una più stretta integrazione tra strumenti generali e settoriali, difficilmente conseguibile attraverso il solo coordinamento a posteriori tra strumenti elaborati separatamente e sulla base di approcci settoriali

The subgrid-scale scalar variance under supercritical pressure conditions

To model the subgrid-scale (SGS) scalar variance under supercritical-pressure conditions, an equation is first derived for it. This equation is considerably more complex than its equivalent for atmospheric-pressure conditions. Using a previously created direct numerical simulation (DNS) database of transitional states obtained for binary-species systems in the context of temporal mixing layers, the activity of terms in this equation is evaluated, and it is found that some of these new terms have magnitude comparable to that of governing terms in the classical equation. Most prominent among these new terms are those expressing the variation of diffusivity with thermodynamic variables and Soret terms having dissipative effects. Since models are not available for these new terms that would enable solving the SGS scalar variance equation, the adopted strategy is to directly model the SGS scalar variance. Two models are investigated for this quantity, both developed in the context of compressible flows. The first one is based on an approximate deconvolution approach and the second one is a gradient-like model which relies on a dynamic procedure using the Leonard term expansion. Both models are successful in reproducing the SGS scalar variance extracted from the filtered DNS database, and moreover, when used in the framework of a probability density function (PDF) approach in conjunction with the β-PDF, they excellently reproduce a filtered quantity which is a function of the scalar. For the dynamic model, the proportionality coefficient spans a small range of values through the layer cross-stream coordinate, boding well for the stability of large eddy simulations using this model

Classification Problem in a Quantum Framework

The aim of this paper is to provide a quantum counterpart of the well known minimum-distance classifier named Nearest Mean Classifier (NMC). In particular, we refer to the following previous works: i) in Sergioli et al. 2016, we have introduced a detailed quantum version of the NMC, named Quantum Nearest Mean Classifier (QNMC), for two-dimensional problems and we have proposed a generalization to abitrary dimensions; ii) in Sergioli et al. 2017, the n-dimensional problem was analyzed in detail and a particular encoding for arbitrary n-feature vectors into density operators has been presented. In this paper, we introduce a new promizing encoding of arbitrary n-dimensional patterns into density operators, starting from the two-feature encoding provided in the first work. Further, unlike the NMC, the QNMC shows to be not invariant by rescaling the features of each pattern. This property allows us to introduce a free parameter whose variation provides, in some case, an improvement of the QNMC performance. We show experimental results where: i) the NMC and QNMC performances are compared on different datasets; ii) the effects of the non-invariance under uniform rescaling for the QNMC are investigated.Comment: 11 pages, 2 figure