Sulla genesi della città nell’Italia preromana. Economia, sociologia, urbanistica: il caso dell’insediamento dell’Accesa

The paper opens with a series of passages from ancient historiographic sources on the concept of cities in pre-Roman Italy, on the rite of foundation and on internal urban organization, apart from the vast bibliography. We then focus on the case of the settlement of Accesa (Municipality of Massa Marittima, GR). This is one of several settlements located E and N of Vetulonia, controlled by this same city and connected through by river valleys to areas of mining interest in the district of the Colline Metallifere and the Tyrrhenian coast. Unlike other settlements, where only tombs mostly dating to the Archaic period have been discovered, Accesa has tombs and houses included in a period that ranges from the recent Villanovan to the Archaic. Its main characteristic is the division into distinct neighborhoods, functionalized in the operations that were conducted there: exploitation of mines and metallurgical activity. Their genesis is linked to a number of economic and sociological factors that, integrated together, find an eloquent expression in the urban structure

Investigation of a passive control system for limiting cavitation inside turbomachinery under different operating conditions

Abstract Herein, a new passive control system for limiting cavitation inside turbomachinery has been applied to a NACA0009 hydrofoil. The basic idea is to introduce slots nearby its leading edge, connecting pressure and suction sides of the hydrofoil, in order to increase locally the pressure on its suction side and to prevent cavitation from developing. The cavitating flow developed around a two-dimensional hydrofoil is here considered since it is an archetype of cavitation nearby the leading edges of the impeller vanes. Thus, the flow field developed at the leading edge of both the original and modified hydrofoil has been studied at different angles of attack in order to reproduce a wide range of operating conditions that occur inside turbomachinery. Eventually, a comparison of their performance in terms of polars (C L and C D ) and vapour volume fractions (α v ) is performed

A gray-box model for a probabilistic estimate of regional ground magnetic perturbations: Enhancing the NOAA operational Geospace model with machine learning

We present a novel algorithm that predicts the probability that the time derivative of the horizontal component of the ground magnetic field $dB/dt$ exceeds a specified threshold at a given location. This quantity provides important information that is physically relevant to Geomagnetically Induced Currents (GIC), which are electric currents { associated to} sudden changes in the Earth's magnetic field due to Space Weather events. The model follows a 'gray-box' approach by combining the output of a physics-based model with machine learning. Specifically, we combine the University of Michigan's Geospace model that is operational at the NOAA Space Weather Prediction Center, with a boosted ensemble of classification trees. We discuss the problem of re-calibrating the output of the decision tree to obtain reliable probabilities. The performance of the model is assessed by typical metrics for probabilistic forecasts: Probability of Detection and False Detection, True Skill Statistic, Heidke Skill Score, and Receiver Operating Characteristic curve. We show that the ML enhanced algorithm consistently improves all the metrics considered.Comment: under revie

Multi-modal/multi-resolution 3d data acquisition and processing for a new understanding of the historical city of Siena (Italy)

The paper presents the acquisition and data processing approach for the Ground Penetrating Radar (GPR) and laser scanner surveys carried out within the SOS project (the acronym comes from ‘SOtto Siena’, in English ‘Beneath Siena’). SOS is a program aimed to overcome some of the problems and limitations currently present in the study of cities with long-term continuity of life, responding in particular to the need for a better understanding of the city’s ancient fabric and hence to improvements in its conservation by: GPR city survey full coverage (of all the public spaces, streets, squares, courtyards, gardens, etc.), GIS data entry of the historical-archaeological and geoarchaeological knowledge and the development of a 3D Archaeological WEBGIS. The paper discusses the procedure for the creation of a 3D viewer within an already active WEBGIS platform, specifically created for the visualisation and management of archaeological data. The GPR data, once acquired, were exported in 3D in the form of point clouds and subjected to a procedure of cleaning and filtering from noise, so as to eliminate geometries not referable to anomalies and therefore to the presence of buried structures or cavities, and then transformed into mesh to meet the needs of the subsequent process of semantic enrichment. The GPR survey of the underground was flanked by laser scanning of some of the most significant structures in the historic centre (e.g. the cathedral). All 3D geometries were then inserted into the new visualiser via a pipeline using open-source tools and libraries

The Challenge of Machine Learning in Space Weather Nowcasting and Forecasting

The numerous recent breakthroughs in machine learning (ML) make imperative to carefully ponder how the scientific community can benefit from a technology that, although not necessarily new, is today living its golden age. This Grand Challenge review paper is focused on the present and future role of machine learning in space weather. The purpose is twofold. On one hand, we will discuss previous works that use ML for space weather forecasting, focusing in particular on the few areas that have seen most activity: the forecasting of geomagnetic indices, of relativistic electrons at geosynchronous orbits, of solar flares occurrence, of coronal mass ejection propagation time, and of solar wind speed. On the other hand, this paper serves as a gentle introduction to the field of machine learning tailored to the space weather community and as a pointer to a number of open challenges that we believe the community should undertake in the next decade. The recurring themes throughout the review are the need to shift our forecasting paradigm to a probabilistic approach focused on the reliable assessment of uncertainties, and the combination of physics-based and machine learning approaches, known as gray-box.Comment: under revie

A catalogue of observed geo-effective CME/ICME characteristics

One of the goals of Space Weather studies is to achieve a better understanding of impulsive phenomena, such as Coronal Mass Ejections (CMEs), in order to improve our ability to forecast them and mitigate the risk to our technologically driven society. The essential part of achieving this goal is to assess the performance of forecasting models. To this end, the quality and availability of suitable data are of paramount importance. In this work, we have merged already publicly available data of CMEs from both in-situ and remote instrumentation in order to build a database of CME properties. To evaluate the accuracy of such a database and confirm the relationship between in-situ and remote observations, we have employed the drag-based model (DBM) due to its simplicity and inexpensive cost of computational resources. In this study, we have also explored the parameter space for the drag parameter and solar wind speed using a Monte Carlo approach to evaluate how well the DBM determines the propagation of CMEs for the events in the dataset. The dataset of geoeffective CMEs constructed as a result of this work provides validation of the initial hypothesis about DBM, and solar wind speed and also yields further insight into CME features like arrival time, arrival speed, lift-off time, etc. Using a data-driven approach, this procedure allows us to present a homogeneous, reliable, and robust dataset for the investigation of CME propagation. On the other hand, possible CME events are identified where DBM approximation is not valid due to model limitations and higher uncertainties in the input parameters, those events require more thorough investigation

ViDA: a VlasovDArwin solver for plasma physics at electron scales

We present a Vlasov–DArwin numerical code (ViDA) specifically designed to address plasma physics problems, where small-scale high accuracy is requested even during the nonlinear regime to guarantee a clean description of the plasma dynamics at fine spatial scales. The algorithm provides a low-noise description of proton and electron kinetic dynamics, by splitting in time the multi-advection Vlasov equation in phase space. Maxwell equations for the electric and magnetic fields are reorganized according to the Darwin approximation to remove light waves. Several numerical tests show that ViDA successfully reproduces the propagation of linear and nonlinear waves and captures the physics of magnetic reconnection. We also discuss preliminary tests of the parallelization algorithm efficiency, performed at CINECA on the Marconi-KNL cluster. ViDA will allow the running of Eulerian simulations of a non-relativistic fully kinetic collisionless plasma and it is expected to provide relevant insights into important problems of plasma astrophysics such as, for instance, the development of the turbulent cascade at electron scales and the structure and dynamics of electron-scale magnetic reconnection, such as the electron diffusion region

Flow non-normality-induced transient growth in superposed Newtonian and non-Newtonian fluid layers

In recent years non-normality and transient growths have attracted much interest in fluid mechanics. Here, we investigate these topics with reference to the problem of interfacial instability in superposed Newtonian and non-Newtonian fluid layers. Under the hypothesis of the lubrication theory, we demonstrate the existence of significant transient growths in the parameter space region where the dynamical system is asymptotically stable, and show how they depend on the main physical parameters. In particular, the key role of the density ratio is highlighte

The Role of Histone H4 Biotinylation in the Structure of Nucleosomes

Background: Post-translational modifications of histones play important roles in regulating nucleosome structure and gene transcription. It has been shown that biotinylation of histone H4 at lysine-12 in histone H4 (K12Bio-H4) is associated with repression of a number of genes. We hypothesized that biotinylation modifies the physical structure of nucleosomes, and that biotin-induced conformational changes contribute to gene silencing associated with histone biotinylation. Methodology/Principal Findings: To test this hypothesis we used atomic force microscopy to directly analyze structures of nucleosomes formed with biotin-modified and non-modified H4. The analysis of the AFM images revealed a 13% increase in the length of DNA wrapped around the histone core in nucleosomes with biotinylated H4. This statistically significant (p,0.001) difference between native and biotinylated nucleosomes corresponds to adding approximately 20 bp to the classical 147 bp length of nucleosomal DNA. Conclusions/Significance: The increase in nucleosomal DNA length is predicted to stabilize the association of DNA with histones and therefore to prevent nucleosomes from unwrapping. This provides a mechanistic explanation for the gene silencing associated with K12Bio-H4. The proposed single-molecule AFM approach will be instrumental for studying the effects of various epigenetic modifications of nucleosomes, in addition to biotinylation