Comparing and generating Latin Hypercube designs in Kriging models

In Computer Experiments (CE), a careful selection of the design points is essential for predicting the system response at untried points, based on the values observed at tried points. In physical experiments, the protocol is based on Design of Experiments, a methodology whose basic principles are questioned in CE. When the responses of a CE are modeled as jointly Gaussian random variables with their covariance depending on the distance between points, the use of the so called space-filling designs (random designs, stratified designs and Latin Hypercube designs) is a common choice, because it is expected that the nearer the untried point is to the design points, the better is the prediction. In this paper we focus on the class of Latin Hypercube (LH) designs. The behavior of various LH designs is examined according to the Gaussian assumption with exponential correlation, in order to minimize the total prediction error at the points of a regular lattice. In such a special case, the problem is reduced to an algebraic statistical model, which is solved using both symbolic algebraic software and statistical software. We provide closed-form computation of the variance of the Gaussian linear predictor as a function of the design, in order to make a comparison between LH designs. In principle, the method applies to any number of factors and any number of levels, and also to classes of designs other than LHs. In our current implementation, the applicability is limited by the high computational complexity of the algorithms involved.     

The flower intersection problem for Kirkman triple systems

The flower at a point x in a Steiner triple system is the set of all triples containing x. Denote by I_R^*[r] the set of all integers k such that there exists a pair of KTS(2r+1) having k+r triples in common, r of them being the triples of a common flower. In this article we determine the set I_R^*[r] for any positive integer r≡1 (mod 3) (only nine cases are left undecided for r=7,13,16,19), and establish that I_R^*[r]=J[r] for r≡1 (mod 3) and r22 where J[r]={0,1,…,2r(r−1)/3−6,2r(r−1)/3−4,2r(r−1)/3}.     

L'évolution du tissu social – entre nouvelles technologies et tendances socio‐économiques anciennes

Nos sociétés vivent‐elles aujourd'hui une nouvelle révolution industrielle? Les auteurs s'efforcent de répondre à cette question à partir d'une évaluation des conséquences des changements technologiques sur le tissu socio‐économique actuel, notamment sous l'angle de l'emploi, des inégalités, des conditions de travail et des relations professionnelles. Ils avancent que les processus d'innovation et la diffusion de «l'automatisation intelligente» risquent de renforcer des schémas de répartition des revenus et des rapports de force inéquitables (certains préexistants à l'arrivée des technologies et d'autres apparus au cours des trente à quarante dernières années). Ils détaillent les implications de ces évolutions sur les politiques à mettre en ?uvre.     

Restarting “Normal” Life after Covid-19 and the Lockdown: Evidence from Spain,the United Kingdom,and Italy

Social Indicators Research - In this article, we examine the expectations of the economic outlook, fear of the future, and behavioural change during the first Covid-19 wave, for three European...     

Component Criticality in Failure Cascade Processes of Network Systems

In this work, specific indicators are used to characterize the criticality of components in a network system with respect to their contribution to failure cascade processes. A realistic‐size network is considered as reference case study. Three different models of cascading failures are analyzed, differing both on the failure load distribution logic and on the cascade triggering event. The criticality indicators are compared to classical measures of topological centrality to identify the one most characteristic of the cascade processes considered.     

Robust design of adaptive control charts for manual manufacturing/inspection workstations

Often the manufacturing and the inspection workstations in a manufacturing process can coincide: thus, in these workstations the statistical process control (SPC) procedure of collecting sample statistics related to a critical-to-quality parameter is a task required to be done by the same worker who has to complete the working operations on a part. The aim of this study is to design a local SPC inspection procedure implementing an adaptive Shewhart control chart locally managed by the worker within the manufacturing workstation: the economic design of the inspection procedure is constrained by the expected number of false alarms issued and is restricted to those designs feasible with respect to the available shared labour resource. Furthermore, a robust approach that models the shift of the controlled parameter mean as a random variable is taken into account. The numerical analysis allows the most influencing environmental process factors to be captured and commented upon. The obtained results show that a few process operating parameters drive the choice of performing a robust optimization and the selection of the optimal SPC adaptive procedure.     

Citalopram-Associated Gambling: A Case Report

Pathological gambling behaviour is a side effect of dopaminergic drugs used in Parkinson’s disease, but has seldom been reported with selective serotonin reuptake inhibitors. A 58-years-old woman with somatisation disorder since the age of 20 and recent-onset major depression (at 54 years) received 40 mg/day intravenous citalopram, thereafter switching to the same dose of oral citalopram to treat her comorbid psychiatric disorders after showing poor response to paroxetine for one year. Her anxious and depressive symptoms were moderately reduced after 7 months of oral citalopram, but simultaneously, the patient admitted gambling. We gradually discontinued citalopram and introduced pregabalin and alprazolam; this was followed by a reduction of gambling compulsions, but the somatisation and depressive symptoms did not further improve. Pathological gambling may be mediated by an interplay of 5-HT_1A serotonergic and D₂ dopaminergic mechanisms. Citalopram affects both these mechanisms in areas that were shown to be involved in gambling behaviour, but while dopaminergic effects of citalopram appear to be consistent with the induction of gambling, its serotonergic mechanisms are rather inconsistent. In our patient, mood destabilisation induced by citalopram may have contributed to the first onset of pathological gambling.     

Financial Instruments for Mitigation of Flood Risks: The Case of Florence

This article analyzes the mechanisms and effects of innovative financial instruments that a central public administration (CPA) may adopt to minimize the flood risk in particularly exposed regions. The pattern we suggest assumes that in risky areas the CPA can issue two financial instruments, called project options and CAT‐bonds, producing a dynamic interaction among three types of agents: the CPA itself, the local public administrations, and private investors. We explore the possible scenarios of such interaction and the conditions under which the CPA's goal of maximal risk reduction is attained. This pattern is proposed for flood risk mitigation in the city of Florence, where the model dynamics are tested assuming parameters obtained from engineering studies.     

Gender wage differentials in Italy: a structural estimation approach

This paper studies gender wage differentials by providing a maximum likelihood structural estimation of the frictional parameters of an equilibrium search model with on-the-job search and firm heterogeneity. In a second step, I also consider the role of discrimination. Results indicate higher level of search frictions for women; this result is confirmed by various robustness checks and by different specification and estimation strategies. I also find that the resulting mapping from productivity to wages for men is highly non-linear, while for women it is almost linear. Search, productivity and discrimination play different roles in shaping the gender differential depending on the specification and estimation of the model.