Blended numerical schemes for the advection equation and conservation laws

In this paper we propose a method to couple two or more explicit numerical schemes approximating the same time-dependent PDE, aiming at creating new schemes which inherit advantages of the original ones. We consider both advection equations and nonlinear conservation laws. By coupling a macroscopic (Eulerian) scheme with a microscopic (Lagrangian) scheme, we get a new kind of multiscale numerical method

Calibration of Soil Amplification Factors for Real-Time Ground-Motion Scenarios in Italy

This study deals with the calibration of soil amplification factors to be used for generating site-specific, real-time (or quasi real-time) ground-motion scenarios in Italy. To this end, the ground response of 100 soil profiles is studied through 1-dimensional (1D) equivalent-linear numerical simulations. Several real, rock ground-motion time histories, grouped into different peak ground acceleration (PGA) classes, are driven through the models of the soil columns. Soil amplification factors are then calculated using different definitions, either as the ratio of the spectral acceleration at the surface to the spectral acceleration at the rock outcrop or by dividing the (acceleration or pseudo-velocity) response spectrum intensity at the surface to the reference response spectrum intensity. Finally, regression analyses are performed to derive empirical equations that relate the amplification factor to different soil parameters, such as the average shear wave velocity VS,30 in the top 30 m of a soil profile and the soil fundamental frequency, f0. The reliability of the amplification factors here calculated is verified through comparison with experimental data recorded during the April 6, 2009 L’Aquila earthquake (Mw = 6.3)

Topographic Effects in Probabilistic Seismic Hazard Analysis: The Case of Narni, Central Italy

This study presents a probabilistic method for estimating the ground motion hazard at sites presenting topographic irregularities. This method is applicable to topographic crests or ridges which may affect site response, producing 2D (or 3D) amplification effects. The method is based on a set of 2D numerical analyses that are carried out using multiple accelerograms from worldwide weak and strong earthquakes recorded on rock. Numerical analyses are performed to compute site-specific frequency-dependent amplification factors to be included into the ground motion prediction equation used in the seismic hazard computation. The hazard at the top of the ridge is then assessed by running a conventional probabilistic seismic hazard analysis (PSHA) with the attenuation relationship modified to include the site response. An application to the case study of Narni (Central Italy) is presented in this work

The impact of NFT profile pictures within social network communities

This paper presents an analysis of the role of social media, specifically Twitter, in the context of non-fungible tokens, better known as NFTs. Such emerging technology framing the creation and exchange of digital object, started years ago with early projects such as "CryptoPunks" and since early 2021, has received an increasing interest by a community of people creating, buying, selling NFT's and by the media reporting to the general public. In this work it is shown how the landscape of one class of projects, specifically those used as social media profile pictures, has become mainstream with leading projects such as "Bored Ape Yacht Club", "Cool Cats" and "Doodles". This work illustrates how heterogeneous data was collected from the Ethereum blockchain and Twitter and then analysed using algorithms and state-of-art metrics related to graphs. The initial results show that from a social network perspective, the collections of most popular NFTs can be considered as a single community around NFTs. Thus, while each project has its own value and volume of exchange, on a social level all of them are primarily influenced by the evolution of values and trades of "Bored Ape Yacht Club" collection.Comment: In Proceedings of the ACM International Conference on Information Technology for Social Good (GoodIT'22), September 07--09, 2022, Cypru

The impact of NFT profile pictures within social network communities

This paper presents an analysis of the role of social media, specifically Twitter, in the context of non-fungible tokens, better known as NFTs. Such emerging technology framing the creation and exchange of digital object, started years ago with early projects such as ”CryptoPunks” and since early 2021, has received an increasing interest by a community of people creating, buying, selling NFTs and by the media reporting to the general public. In this work it is shown how the landscape of one class of projects, specifically those used as social media profile pictures, has become mainstream with leading projects such as ”Bored Ape Yacht Club”, ”Cool Cats” and ”Doodles”. This work illustrates how heterogeneous data was collected from the Ethereum blockchain and Twitter and then analysed using algorithms and state-of-art metrics related to graphs. The initial results show that from a social network perspective, the collections of most popular NFTs can be considered as a single community around NFTs. Thus, while each project has its own value and volume of exchange, on a social level all of them are primarily influenced by the evolution of values and trades of ”Bored Ape Yacht Club” collection

Effects of dislocation density on injection and temperature sensitivity of InGaN LED emission spectra: a combined experimental and simulation approach

The aim of this paper is to describe a combined simulation and characterization activity carried out on blue LEDs grown on templates with different threading dislocation densities (TDDs)

Long-range dependence in earthquake-moment release and implications for earthquake occurrence probability

Since the beginning of the 1980s, when Mandelbrot observed that earthquakes occur on 'fractal' self-similar sets, many studies have investigated the dynamical mechanisms that lead to self-similarities in the earthquake process. Interpreting seismicity as a self-similar process is undoubtedly convenient to bypass the physical complexities related to the actual process. Self-similar processes are indeed invariant under suitable scaling of space and time. In this study, we show that long-range dependence is an inherent feature of the seismic process, and is universal. Examination of series of cumulative seismic moment both in Italy and worldwide through Hurst's rescaled range analysis shows that seismicity is a memory process with a Hurst exponent H 48 0.87. We observe that H is substantially space-and time-invariant, except in cases of catalog incompleteness. This has implications for earthquake forecasting. Hence, we have developed a probability model for earthquake occurrence that allows for long-range dependence in the seismic process. Unlike the Poisson model, dependent events are allowed. This model can be easily transferred to other disciplines that deal with self-similar processe