Gini estimation under infinite variance

We study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index $\alpha\in(1,2)$). We show that, in such a case, the Gini coefficient cannot be reliably estimated using conventional nonparametric methods, because of a downward bias that emerges under fat tails. This has important implications for the ongoing discussion about economic inequality. We start by discussing how the nonparametric estimator of the Gini index undergoes a phase transition in the symmetry structure of its asymptotic distribution, as the data distribution shifts from the domain of attraction of a light-tailed distribution to that of a fat-tailed one, especially in the case of infinite variance. We also show how the nonparametric Gini bias increases with lower values of $\alpha$. We then prove that maximum likelihood estimation outperforms nonparametric methods, requiring a much smaller sample size to reach efficiency. Finally, for fat-tailed data, we provide a simple correction mechanism to the small sample bias of the nonparametric estimator based on the distance between the mode and the mean of its asymptotic distribution

Upgrading Italy's Industrial Capacity: Industry 4.0 across Regions and Sectors

How are Industry 4.0 investments distributed across Italian regions and sectors? Which are the main drivers of diffusion? To address these questions, in this study we exploit rich firm survey data on the adoption of the new digital technologies and examine their adoption patterns. On the one hand, we produce novel insights into the drivers of structural change in the Italian economy, and on the other, we provide evidence on the technological upgrading of Italy's production capacity that is relevant for policy. The results of econometric tests on region-sector pairs indicate that corporate governance characteristics, innovation patterns and type of industrial relations are significant predictors of the uneven regional and sectoral distribution of Industry 4.0 investments

Operative and nonoperative management for renal trauma. Comparison of outcomes. A systematic review and meta-analysis

INTRODUCTION: Preservation of kidney and renal function is the goal of nonoperative management (NOM) of renal trauma (RT). The advantages of NOM for minor blunt RT have already been clearly described, but its value for major blunt and penetrating RT is still under debate. We present a systematic review and meta-analysis on NOM for RT, which was compared with the operative management (OM) with respect to mortality, morbidity, and length of hospital stay (LOS). METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-analyses statement was followed for this study. A systematic search was performed on Embase, Medline, Cochrane, and PubMed for studies published up to December 2015, without language restrictions, which compared NOM versus OM for renal injuries. RESULTS: Twenty nonrandomized retrospective cohort studies comprising 13,824 patients with blunt (2,998) or penetrating (10,826) RT were identified. When all RT were considered (American Association for the Surgery of Trauma grades 1-5), NOM was associated with lower mortality and morbidity rates compared to OM (8.3% vs 17.1%, odds ratio [OR] 0.471; 95% confidence interval [CI] 0.404-0.548; P<0.001 and 2% vs 53.3%, OR 0.0484; 95% CI 0.0279-0.0839, P<0.001). Likewise, NOM represented the gold standard treatment resulting in a lower mortality rate compared to OM even when only high-grade RT was considered (9.1% vs 17.9%, OR 0.332; 95% CI 0.155-0.708; P=0.004), be they blunt (4.1% vs 8.1%, OR 0.275; 95% CI 0.0957-0.788; P=0.016) or penetrating (9.1% vs 18.1%, OR 0.468; 95% CI 0.398-0.0552; P<0.001). CONCLUSION: Our meta-analysis demonstrated that NOM for RT is the treatment of choice not only for AAST grades 1 and 2, but also for higher grade blunt and penetrating RT

Hollow viscus injuries. Predictors of outcome and role of diagnostic delay

INTRODUCTION: Hollow viscus injuries (HVIs) are uncommon but potentially catastrophic conditions with high mortality and morbidity rates. The aim of this study was to analyze our 16-year experience with patients undergoing surgery for blunt or penetrating bowel trauma to identify prognostic factors with particular attention to the influence of diagnostic delay on outcome. METHODS: From our multicenter trauma registry, we selected 169 consecutive patients with an HVI, enrolled from 2000 to 2016. Preoperative, intraoperative, and postoperative data were analyzed to assess determinants of mortality, morbidity, and length of stay by univariate and multivariate analysis models. RESULTS: Overall mortality and morbidity rates were 15.9% and 36.1%, respectively. The mean length of hospital stay was 23±7 days. Morbidity was independently related to an increase of white blood cells (P=0.01), and to delay of treatment >6 hours (P=0.033), while Injury Severity Score (ISS) (P=0.01), presence of shock (P=0.01), and a low diastolic arterial pressure registered at emergency room admission (P=0.02) significantly affected postoperative mortality. CONCLUSION: There is evidence that patients with clinical signs of shock, low diastolic pressure at admission, and high ISS are at increased risk of postoperative mortality. Leukocytosis and delayed treatment (>6 hours) were independent predictors of postoperative morbidity. More effort should be made to increase the preoperative detection rate of HVI and reduce the delay of treatment

Food insecurity as a determinant of international migration: evidence from Sub-Saharan Africa

In this paper, we examined how food insecurity can affect international migration aspirations and subsequent actions taken in preparation to move internationally from Sub-Saharan Africa. Drawing on a conceptual framework of the determinants of migration, we developed a three-stage regression model and tested it using data from the 2014 Gallup World Poll. The results indicate that multiple determinants play different roles in the migration decision process, which is characterized by aspirations, planning and final decision to migrate. Specifically, food insecurity is an important determinant of both the desire and the decision to migrate: food insecurity raises the probability of desiring to migrate internationally, with the probability of the desire increasing along with the severity of food insecurity. However, the probability of actually deciding to migrate internationally decreased as food insecurity worsened. These findings are in line with migration literature stating that the very poor, despite wishing to migrate, face tremendous constraints in transforming this desire into concrete decisions. Our results suggest that removing or reducing constraints to migration will benefit the poorest/most food insecure and highlight the need for an increased and effective coordination between food security and international migration policy agendas

Diagnostic accuracy of short-time inversion recovery sequence in Graves' ophthalmopathy before and after prednisone treatment

Introduction: In Graves' Ophthalmopathy, it is important to distinguish active inflammatory phase, responsive to immunosuppressive treatment, from fibrotic unresponsive inactive one. The purpose of this study is, first, to identify the relevant orbital magnetic resonance imaging signal intensities before treatment, so to classify patients according to their clinical activity score (CAS), discriminating inactive (CAS3) subjects and, second, to follow post-steroid treatment disease. Methods: An observational study was executed on 32 GO consecutive patients in different phases of disease, based on clinical and orbital Magnetic Resonance Imaging parameters, compared to 32 healthy volunteers. Orbital Magnetic Resonance Imaging was performed on a 1.5 tesla Magnetic Resonance Unit by an experienced neuroradiologist blinded to the clinical examinations. Results: In pre-therapy patients, compared to controls, a medial rectus muscle statistically significant signal intensity ratio (SIR) in short-time inversion recovery (STIR) (long TR/TE) sequence was found, as well as when comparing patients before and after treatment, both medial and inferior rectus muscle SIR resulted significantly statistically different in STIR. These increased outcomes explain the inflammation oedematous phase of disease, moreover after steroid administration, compared to controls; patients presented lack of that statistically significant difference, thus suggesting treatment effectiveness. Conclusion: In our study, we proved STIR signal intensities increase in inflammation oedematous phase, confirming STIR sequence to define active phase of disease with more sensibility and reproducibility than CAS alone and to evaluate post-therapy involvement. © 2014 Springer-Verlag

Gini estimation under infinite variance

We study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index α∈(1,2)). We show that, in such a case, the Gini coefficient cannot be reliably estimated using conventional nonparametric methods, because of a downward bias that emerges under fat tails. This has important implications for the ongoing discussion about economic inequality. We start by discussing how the nonparametric estimator of the Gini index undergoes a phase transition in the symmetry structure of its asymptotic distribution, as the data distribution shifts from the domain of attraction of a light-tailed distribution to that of a fat-tailed one, especially in the case of infinite variance. We also show how the nonparametric Gini bias increases with lower values of α. We then prove that maximum likelihood estimation outperforms nonparametric methods, requiring a much smaller sample size to reach efficiency. Finally, for fat-tailed data, we provide a simple correction mechanism to the small sample bias of the nonparametric estimator based on the distance between the mode and the mean of its asymptotic distribution

Differences between computed tomoghaphy and surgical findings in acute complicated diverticulitis

Summary Background/Objective: A preoperative reliable classification system between clinical and computed tomography (CT) findings to better plan surgery in acute complicated diverticulitis (ACD) is lacking. We studied the inter-observer agreement of CT scan data and their concordance with the preoperative clinical findings and the adherence with the intraoperative status using a new classification of diverticular disease (CDD). Methods: 152 patients operated on for acute complicated diverticulitis (ACD) were retrospectively enrolled. All patients were studied with CT scan within 24 h before surgery and CT images were blinded reanalyzed by 2 couples of radiologists (A/B). Kappa value evaluated the inter-observer agreement between radiologists and the concordance between CDD, preoperative clinical findings and findings at operation. Univariate and multivariate analysis were used to evaluate the predicting values of CT classification and CDD stage at surgery on postoperative outcomes. Results: Overall inter-observer agreement for the CDD was high, with a kappa value of 0.905 (95% CI Z 0.850e0.960) for observers A and B, while the concordance between radiologica

A Continuum Model for Morphology Formation from Interacting Ternary Mixtures: Simulation Study of the Formation and Growth of Patterns

Our interest lies in exploring the ability of a coupled nonlocal system of two quasilinear parabolic partial differential equations to produce phase separation patterns. The obtained patterns are referred here as morphologies. Our target system is derived in the literature as the rigorous hydrodynamic limit of a suitably scaled interacting particle system of Blume--Capel--type driven by Kawasaki dynamics. The system describes in a rather implicit way the interaction within a ternary mixture that is the macroscopic counterpart of a mix of two populations of interacting solutes in the presence of a background solvent. Our discussion is based on the qualitative behavior of numerical simulations of finite volume approximations of smooth solutions to our system and their quantitative postprocessing in terms of two indicators (correlation and structure factor calculations). Our results show many similar features compared to what one knows at the level of the stochastic Blume--Capel dynamics with three interacting species. The properties of the obtained morphologies (shape, connectivity, and so on) can play a key role in, e.g., the design of the active layer for efficient organic solar cells

Editorial: Glial cells, maladaptive plasticity, and neurodegeneration: Mechanisms, targeted therapies, and future directions

Understanding the biological complexity of the central nervous system (CNS) is a frontier in neuroscience. Morphological organization of the CNS represents the basis for its functional properties underlying higher brain functions; therefore, efforts are needed to boost the comprehension of the organization of the CNS, from the ultrastructural to the functional-networks level.To date, two highly integrated and interconnected cellular networks substantiate the anatomofunctional organization of CNS: neurons and non-neuronal cells, namely glial cells. Glial cells, including astrocytes, oligodendrocytes, and microglia, actively participate in many complex functions within the CNS (immunity surveillance and inflammatory response, metabolic and synaptic homeostasis, modulation of blood-brain barrier?BBB) (Volterra and Meldolesi, 2005). Moreover, interaction with the elements of the extracellular matrix (ECM), an active player for long-term plasticity and circuit maintenance, adds another level of complexity to the modern model of the synapse structure (tetrapartite synapse) (Song and Dityatev, 2018). Therefore, if on one hand glial cells allow adaptive synaptic plasticity of CNS in several physiological conditions modulating synaptic transmission, homeostasis, and neural pathways signaling, then on the other, when activated, they boost inflammatory response and perturb neuroglial interactions, synaptic circuitry, and plasticity. This new condition, called maladaptive synaptic plasticity, may represent an early stage of neuroinflammatory processes in neurodegenerative disorders (Papa et al., 2014). Recently, it has been hypothesized that the morpho-functional heterogeneity of astrocytes in different brain regions might explain the regional diversity of astrocytic response to an external injury and the selectivity of neuronal degeneration (Cragnolini et al., 2018, 2020). Therefore, the comprehension of these mechanisms is relevant for the development of targeted therapies for clinical management of neurodegenerative disorders. Only through unraveling the complex interactions between the different cell types at the synapse, we will truly understand synaptic plasticity, higher brain functions, and how perturbations of these interactions contribute to brain diseases with dramatic clinical impact.Fil: Korai, Sohaib Ali. Università degli Studi della Campania "Luigi Vanvitelli"; ItaliaFil: Sepe, Giovanna. Università degli Studi della Campania "Luigi Vanvitelli"; ItaliaFil: Luongo, Livio. Università degli Studi della Campania "Luigi Vanvitelli"; ItaliaFil: Cragnolini, Andrea Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; ArgentinaFil: Cirillo, Giovanni. Università degli Studi della Campania "Luigi Vanvitelli"; Itali