Fashion and democracy in Europe, 1860-1960

The article deals with the interaction between fashion and political systems

Quantile mixed graphical models with an application to mass public shootings in the United States

Over the last fifty years, the United States have experienced hundreds of mass public shootings that resulted in thousands of victims. Characterized by their frequent occurrence and devastating nature, mass shootings have become a major public health hazard that dramatically impact safety and well-being of individuals and communities. Given the epidemic traits of this phenomenon, there have been concerted efforts to understand the root causes that lead to public mass shootings in order to implement effective prevention strategies. We propose a quantile mixed graphical model for investigating the intricacies of inter- and infra-domain relationships of this complex phenomenon, where conditional relations between discrete and continuous variables are modeled without stringent distributional assumptions using Parzen's definition of mid-quantile. To retrieve the graph structure and recover only the most relevant connections, we consider the neighborhood selection approach in which conditional mid-quantiles of each variable in the network are modeled as a sparse function of all others. We propose a two-step procedure to estimate the graph where, in the first step, conditional mid-probabilities are obtained semi-parametrically and, in the second step, the model parameters are estimated by solving an implicit equation with a LASSO penalty

Dilated Cardiomyopathy. From Genetics to Clinical Management

The current definition of dilated cardiomyopathy (DCM) is relatively simple: it is a heart muscle disease characterized by left ventricular (LV) or biventricular dilation and systolic dysfunction in the absence of either pressure or volume overload or coronary artery disease sufficient enough to explain the dysfunction. In the last 30 years, prognosis of patients with DCM has dramatically been improved with few similarities in the history of cardiology and medicine. Typically, in the 1980s, the average survival rate was approximately 50% in a 5-year follow-up. Nowadays, at 10 years of follow-up, the survival/free from heart transplant rate is far beyond 85%, and the projection of this improvement is significantly better for those who have had DCM diagnosed in the late 2010s. This improvement in outcomes is fundamentally due to a better characterization of etiological factors, medical management for heart failure, and device treatment, like the implantable cardioverter defibrillator (ICD), for sudden cardiac death prevention. However, other milestones should be recognized for the improvement in the survival rate, namely, the early diagnosis due to familial and sport-related screening, which allow detection of DCM at a less severe stage, and the uninterrupted, active, and individualized long-term follow-up with continuous reevaluation of the disease and re-stratification of the risk

Standardizing the role of endomyocardial biopsy in current clinical practice worldwide

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Automating the simulation of SME processes through a discrete event parametric model

At the factory level, the manufacturing system can be described as a group of processes governed by complex weaves of engineering strategies and technologies. Decision- making processes involve a lot of information, driven by managerial strategies, technological implications and layout constraints. Many factors affect decisions, and their combination must be carefully managed to determine the best solutions to optimize performances. In this way, advanced simulation tools could support the decisional process of many SMEs. The accessibility of these tools is limited by knowledge, cost, data availability and development time. These tools should be used to support strategic decisions rather than specific situations. In this paper, a novel approach is proposed that aims to facilitate the simulation of manufacturing processes by fast modelling and evaluation. The idea is to realize a model that is able to be automatically adapted to the user’s specific needs. The model must be characterized by a high degree of flexibility, configurability and adaptability in order to automatically simulate multiple/heterogeneous industrial scenarios. In this way, even a SME can easily access a complex tool, perform thorough analyses and be supported in taking strategic decisions. The parametric DES model is part of a greater software platform developed during COPERNICO EU funded project

The VESPA Project: Virtual Reality Interventions for Neurocognitive and Developmental Disorders

VESPA is a financed project supported by the Sicilian Regional Research and Development funds, and it is structured by the development, research and validation of Virtual Reality (VR) based application for the diagnosis and treatment of neurocognitive conditions. In particular, this article presents its characteristics, referred to as the first (2013-2015) and second (2021-ongoing) generations of VESPA, with particular reference to literature regarding the VR technology application and development, the VR treatment of neurocognitive conditions and prior versions of this intervention. Through a comprehensive review of the research conducted over the last 5 years, evidence has emerged supporting VESPA’s aim and scopes, highlighting how the application of VR can be considered to add value to typical rehabilitation/therapeutic paths. VESPA project generations are then presented in detail, including specific session/task battery characteristics, 2.5D, 3D and 5D typologies, system usability and architecture and pathological domain-based dynamics and features. The discussion about VESPA will highlight the current advantages along with limitations and future directions