Stochastic macromodeling for hierarchical uncertainty quantification of nonlinear electronic systems

A hierarchical stochastic macromodeling approach is proposed for the efficient variability analysis of complex nonlinear electronic systems. A combination of the Transfer Function Trajectory and Polynomial Chaos methods is used to generate stochastic macromodels. In order to reduce the computational complexity of the model generation when the number of stochastic variables increases, a hierarchical system decomposition is used. Pertinent numerical results validate the proposed methodology

Agritourism flows to Italy: an analysis of determinants using the gravity model approach

Tourism represents one of the most important income sources for Italy. In recent years, apart from “traditional” destinations, tourism supply is widely changing in order to satisfy the customers “love for variety” and valorise marginal resources, then new formulas are emerging (e.g. agritourism). This work aims to elaborate and estimate an econometric model able to adequately explain the size of agritourists flows to Italy from main partner countries using the gravity model approach that has been broadly applied to the analysis of international flows. In this work, the “basic” model has been enlarged and improved with the introduction of other explicative variables. The results has allowed to confirm empirical validity of the gravity model in studying international flows of any nature. Furthermore, the estimated econometric model represents a useful analytical instrument to describe, and, eventually, predict demand of foreign visitors for agritourist vacations in Italy.Gravity Model, Agritourism, Rural tourism, Tourism flows, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy,

Unraveling the Origin of Social Bursts in Collective Attention

In the era of social media, every day billions of individuals produce content in socio-technical systems resulting in a deluge of information. However, human attention is a limited resource and it is increasingly challenging to consume the most suitable content for one's interests. In fact, the complex interplay between individual and social activities in social systems overwhelmed by information results in bursty activity of collective attention which are still poorly understood. Here, we tackle this challenge by analyzing the online activity of millions of users in a popular microblogging platform during exceptional events, from NBA Finals to the elections of Pope Francis and the discovery of gravitational waves. We observe extreme fluctuations in collective attention that we are able to characterize and explain by considering the co-occurrence of two fundamental factors: the heterogeneity of social interactions and the preferential attention towards influential users. Our findings demonstrate how combining simple mechanisms provides a route towards complex social phenomena.Comment: 14 pages, 10 figure

analysis of dynamic instabilities in bridges under wind action through a simple friction based mechanical model

Abstract In the field of stability of structures under nonconservative loads, the concept of follower force has long been debated by scientists due to the lack of actual experimental evidence. Bigoni and Noselli's work [2] aimed to investigate flutter and divergence instability phenomena through a purely mechanical model with Coulomb friction represents a praiseworthy attempt to shed light on this issue. A two-degree-of-freedom (DOF) system, conceived as a variant of the Ziegler column, was set up experimentally. The follower load was induced by a frictional force acting on a wheel mounted at the column end, so that the rolling friction vanishes and the sliding frictional force keeps always coaxial to the column, thus representing a tangential follower force. Along this research line, in this contribution a model is elaborated that stems from the analysis of an elastically supported rigid plate that represents the behaviour of a bridge deck suspended on springs and subjected to a wind-induced force. The wind force has been simulated by a Coulomb friction force acting on a wheel mounted on the plate aerodynamic centre, so that the sliding friction force keeps perpendicular to the plate axis throughout the system motion, thus representing a follower force. To properly reproduce the wind force, the friction force is applied to the wheel by a lever mechanism wherein one of the two lever arms involves the plate rotation via a particular circular guide. The corresponding equations of motion of the bridge deck are derived in a completely dimensionless form. Depending on the mechanical characteristics of the plate and the magnitude of the friction force, stability, flutter or divergence phenomena may occur. The occurrence of these phenomena is numerically investigated by integration of the equations of motion. The development of an experimental framework of the model to corroborate these intuitions is the object of an ongoing research

Machine-learning-enhanced variable-angle truss model to predict the shear capacity of RC elements with transverse reinforcement

This contribution presents a numerical model for the shear capacity prediction of reinforced concrete (RC) elements with transverse reinforcement. The proposed model originates from one of the most popular mechanical models adopted in building codes, namely the variable-angle truss model. Starting from the formulation proposed in the Eurocode 2, two empirical coefficients governing the concrete contribution (i.e., the shear capacity ascribed to crushing of compressed struts) are adjusted and enriched through machine learning, in such a way to improve the predictive efficiency of the model against experimental results. More specifically, genetic programming is used to derive closed-form expressions of the two corrective coefficients, thus facilitating the use of this model for practical purposes. The proposed expressions are validated by comparison with a wide set of experimental results collected from the literature concerning RC beams and columns failing in shear under both monotonic and cyclic loading conditions, respectively. It is demonstrated that the proposed formulation, thanks to the two novel corrective coefficients, not only attains higher accuracy than the original Eurocode 2 formulation, but also outperforms many other existing design code provisions while preserving a sound mechanical basis

Microfluidic cartridge with integrated array of amorphous silicon photosensors for chemiluminescence detection of viral DNA

Portable and simple analytical devices based on microfluidics with chemiluminescence detection are particularly attractive for point-of-care applications, offering high detectability and specificity in a simple and miniaturized analytical format. Particularly relevant for infectious disease diagnosis is the ability to sensitively and specifically detect target nucleic acid sequences in biological fluids. To reach the goal of real-life applications for such devices, however, several technological challenges related to full device integration are still to be solved, one key aspect regarding on-chip integration of the chemiluminescence signal detection device. Nowadays, the most promising approach is on-chip integration of thin-film photosensors. We recently proposed a portable cartridge with microwells aligned with an array of hydrogenated amorphous silicon (a-Si:H) photosensors, reaching attomole level limits of detection for different chemiluminescence model reactions. Herein, we explore its applicability and performance for multiplex and quantitative detection of viral DNA. In particular, the cartridge was modified to accommodate microfluidic channels and, upon immobilization of three oligonucleotide probes in different positions along each channel, each specific for a genotype of Parvovirus B19, viral nucleic acid sequences were captured and detected. With this system, taking advantage of oligoprobes specificity, chemiluminescence detectability, and photosensor sensitivity, accurate quantification of target analytes down to 70 pmol L-1 was obtained for each B19 DNA genotype, with high specificity and multiplexing ability. Results confirm the good detection capabilities and assay applicability of the proposed system, prompting the development of innovative portable analytical devices with enhanced sensitivity and multiplexed capabilities

Key factors affecting the compressive strength of foamed concrete

This contribution aims to highlight, from an experimental point of view, the key factors affecting the compressive strength of foamed concrete. An experimental campaign has been conducted on a broad group of cubic specimens made of foamed concrete under compression tests at 28 days. In addition to the obvious influence of the density on the achievement of the compressive strength, other factors have been studied. In particular, three different curing conditions, three foaming agents with either synthetic or protein nature, two different cement types, and three water/cement ratios have been included in this experimental investigation. As a result of this experimental campaign, it has been found that the not only the density, but also the foaming agent and the water/cement ratio play a major role in the strength achievement of the foamed concrete. It is also demonstrated that the combination of the foaming agent with a particular water/cement ratio is a crucial parameter affecting the compressive strength of this material

Informed assessment of structural health conditions of bridges based on free-vibration tests

consolidated procedure for the evaluation of current structural health con-ditions in bridges consists in the comparison between estimated modal features from in-situ tests and numerical values. This strategy allows making informed decisions for existing bridge structures to ensure structural safety or serviceability. Free vibration tests are common in bridges monitoring since they allow a quick and cost-effective determination of dynamic infor-mation about the structure, using a sparse network of few sensors and avoid long-lasting monitoring campaigns. Exploiting an identification method based on a tuned version of Vari-ational Mode Decomposition and an area-ratio based approach, modal parameters are deter-mined from free vibration tests. This technique is applied to the dynamic identification of cables in a stay-cabled bridge assumed as case study: the obtained results prove reliability of the adopted method as a useful tool for objective dynamic identification purposes, with focus on the structural health conditions of bridges

Hidden geometric correlations in real multiplex networks

Real networks often form interacting parts of larger and more complex systems. Examples can be found in different domains, ranging from the Internet to structural and functional brain networks. Here, we show that these multiplex systems are not random combinations of single network layers. Instead, they are organized in specific ways dictated by hidden geometric correlations between the individual layers. We find that these correlations are strong in different real multiplexes, and form a key framework for answering many important questions. Specifically, we show that these geometric correlations facilitate: (i) the definition and detection of multidimensional communities, which are sets of nodes that are simultaneously similar in multiple layers; (ii) accurate trans-layer link prediction, where connections in one layer can be predicted by observing the hidden geometric space of another layer; and (iii) efficient targeted navigation in the multilayer system using only local knowledge, which outperforms navigation in the single layers only if the geometric correlations are sufficiently strong. Our findings uncover fundamental organizing principles behind real multiplexes and can have important applications in diverse domains.Comment: Supplementary Materials available at http://www.nature.com/nphys/journal/v12/n11/extref/nphys3812-s1.pd