Does education protect families' well-being in times of crisis? Measurement issues and empirical findings from IT-SILC data

This study analyses the relationship between education and material well-being from a longitudinal perspective using the European Survey on Income and Living Conditions (EU-SILC) data collected in Italy in four waves (2009-2012). It has two main aims: (i) to measure household material well-being on the basis of householders' responses to multiple survey items (addressed to gather information on the household availability of material resources) by advancing indexes, which can account for global and relative divergences in households' material well-being across survey waves; (ii) to assess how education and other sociodemographic characteristics affect absolute well-being and its variation (i.e. relative well-being) in the time span considered. Both aims are pursued, combining measuring and explanatory modelling approaches. That is, the use of the Multilevel Item Response Theory model allows to measure the global household material well-being and its yearly variation (i.e. relative material well-being) in the four waves. Meanwhile, the use of a multivariate (and multivariate multilevel) regression model allows to assess the effects of education and other sociodemographic characteristics on both components (absolute and relative well-being), controlling for the relevant sources of heterogeneity in the data. The value added to using the proposed methodologies with the main findings and economic implications are discussed

SPACE-TIME ESTIMATION AND PREDICTION UNDER FIXED-DOMAIN ASYMPTOTICS WITH COMPACTLY SUPPORTED COVARIANCE FUNCTIONS

We study the estimation and prediction of Gaussian processes with spacetime covariance models belonging to the dynamical generalized Wendland (DGW) family, under fixed-domain asymptotics. Such a class is nonseparable, has dynamical compact supports, and parameterizes differentiability at the origin similarly to the space-time Matern class.Our results are presented in two parts. First, we establish the strong consistency and asymptotic normality for the maximum likelihood estimator of the microergodic parameter associated with the DGW covariance model, under fixed-domain asymptotics. The second part focuses on optimal kriging prediction under the DGW model and an asymptotically correct estimation of the mean squared error using a misspecified model. Our theoretical results are, in turn, based on the equivalence of Gaussian measures under some given families of space-time covariance functions, where both space or time are compact. The technical results are provided in the online Supplementary material

Unifying compactly supported and Matern covariance functions in spatial statistics

The Matern family of covariance functions has played a central role in spatial statistics for decades, being a flexible parametric class with one parameter determining the smoothness of the paths of the underlying spatial field. This paper proposes a family of spatial covariance functions, which stems from a reparameterization of the generalized Wendland family. As for the Matern case, the proposed family allows for a continuous parameterization of the smoothness of the underlying Gaussian random field, being additionally compactly supported.More importantly, we show that the proposed covariance family generalizes the Matern model which is attained as a special limit case. This implies that the (reparametrized) Generalized Wendland model is more flexible than the Matern model with an extra-parameter that allows for switching from compactly to globally supported covariance functions.Our numerical experiments elucidate the speed of convergence of the proposed model to the Matern model. We also inspect the asymptotic distribution of the maximum likelihood method when estimating the parameters of the proposed covariance models under both increasing and fixed domain asymptotics. The effectiveness of our proposal is illustrated by analyzing a georeferenced dataset of mean temperatures over a region of French, and performing a re-analysis of a large spatial point referenced dataset of yearly total precipitation anomalies. (C) 2022 Published by Elsevier Inc

Solvent recovery system for a CO2-MEA reactive absorption-stripping plant

The solvent recovery section from the exhaust gas represents an important auxiliary part for an industrial CO2 post-combustion capture plant by the reactive absorption-stripping process. In this work, a partial condenser and a water-wash section configuration were designed to reach 1 ppm of solvent in the exhaust gas, and compared using the Total Annual Cost (TAC) as economic index. Both the configurations ensured the required recovery performance. The results highlighted that the partial condenser alternative is more convenient in terms of capital annualized costs and water make-up, but at the same time it is strongly penalized by the high operating costs for the cooling water. Therefore, the configuration in which the absorber is equipped with the water-wash section resulted the option with the minimum TAC

Self-propagating reactions for environmental protection: Treatment of wastes containing asbestos

A thermochemical process based on the occurrence of self-propagating reactions that is able to convert asbestos fibers into harmless, nonfibrous species is proposed. Specifically, a mixture consisting of a waste (containing about 85 wt % of chrysotile), ferric oxide, and magnesium is able, once locally ignited by a thermal source, to generate a self-propagating reaction that travels through the mixture without requiring additional energy. The process is accompanied by a dramatic change in the material from both the chemical and microstructural points of view. In addition, front velocity and maximum combustion temperature decrease as the amount of waste in the starting mixture increases, with the self-propagating character being maintained if the waste content is equal to or below 60 wt %. It is also observed that, when nonasbestos (nontoxic) materials, i.e., sepiolite and glass fibers, are used instead of the hazardous waste, the front velocity, combustion temperature, propagation limits, and apparent activation energies are found to be very similar to those observed in the case of asbestos

Extreme Peripheral Blood Plasmacytosis Mimicking Plasma Cell Leukemia as a Presenting Feature of Angioimmunoblastic T-Cell Lymphoma (AITL).

Angioimmunoblastic T-cell lymphoma (AITL) is one of four major subtypes of nodal peripheral T cell lymphoma, characterized by its cell of origin, the follicular helper T-cell (TFH). Patients typically present with prominent constitutional (B) symptoms, generalized lymphadenopathy, hepatosplenomegaly, cytopenias, and rash. Here we present a case of a 62-year-old male with progressive cervical adenopathy, fevers and weight loss presenting with extreme polyclonal plasmacytosis and high plasma EBV viral load. While the initial presentation appeared to mimic plasma cell leukemia or severe infection, lymph node biopsy and bone marrow biopsy confirmed a diagnosis of AITL. This case highlights the heterogeneity of the clinical presentation of AITL to enable physicians to more promptly recognize, diagnose and initiate treatment

Stein hypothesis and screening effect for covariances with compact support

In spatial statistics, the screening effect historically refers to the situation when the observations located far from the predictand receive a small (ideally, zero) kriging weight. Several factors play a crucial role in this phenomenon: among them, the spatial design, the dimension of the spatial domain where the observations are defined, the mean-square properties of the underlying random field and its covariance function or, equivalently, its spectral density. The tour de force by Michael L. Stein provides a formal definition of the screening effect and puts emphasis on the Matérn covariance function, advocated as a good covariance function to yield such an effect. Yet, it is often recommended not to use covariance functions with a compact support. This paper shows that some classes of covariance functions being compactly supported allow for a screening effect according to Stein’s definition, in both regular and irregular settings of the spatial design. Further, numerical experiments suggest that the screening effect under a class of compactly supported covariance functions is even stronger than the screening effect under a Matérn model