The large H2020 project ECOPOTENTIAL (2015-2019, 47 partners, contributing to GEO and GEOSS http://www.ecopotential-project.eu/) is devoted to making best use of remote sensing and in situ data to improve future ecosystem benefits, adopting the view of ecosystems as one physical system with their environment, focusing on geosphere-biosphere interactions, Earth Critical Zone dynamics, Macrosystem Ecology and cross-scale interactions, the effect of extreme events and using Essential (Climate, Biodiversity and Ocean) Variables as descriptors of change. In ECOPOTENTIAL, remote sensing and in situ data are collected, processed and used for a betterunderstandingoftheecosystemdynamics,analysingandmodellingtheeffectsofglobalchangesonecosystem functions and services, over an array of different ecosystem types, including mountain, marine, coastal, arid and semi-arid ecosystems. The project focuses on a network of Protected Areas of international relevance, that is representative of the range of environmental and biogeographical conditions characterizing Europe. Some of the activitiesoftheprojectaredevotedtodetectandquantifythechangestakingplaceintheProtectedAreas,through the analysis of remote sensing observations, in-situ data and gridded climatic datasets. Likewise, the project aims atprovidingestimatesofthefutureecosystemconditionsindifferentclimateandenvironmentalchangescenarios. In all such endeavours, one is faced with cross-scale issues: downscaling of climate information to drive ecosystem response, and upscaling of local ecosystem changes to larger scales. So far, the analysis has been conducted mainly by using traditional methods, but there is wide room for improvement by using more refined approaches. In particular, a crucial question is how to upscale the information gained at single-site scale to larger, regional or continental scale, an issue that could benefit from using, for example, complex network analysis.

A model consisting of a kinetic equation for \run-and-tumble" biased bacteria motion, coupled with two reaction-diusion equations for chemical signals, is studied. It displays time- asymptotic propagation at constant velocity, i.e., aggregated travelling (exponential) layers. To capture them for various parameters, a well-balanced setup is based on both \Case's elementary solutions" and L-spline reconstruction. Far from the diusive regime, waves travelling at dierent velocities (bistability) are proved to coexist. Numerics suggest that they are locally asymptotically stable, so that the resulting bifurcation diagram shows counterintuitive features.

The emergencies management in industrial plants is an issue widely discussed in the literature and in the European legislative framework. Despite the large interest shown by the different actors involved in emergencies management, neither scientific nor in industrial field, have developed intelligent tools to support the decisions in these particular contexts. This work, realized inside an Italian financed project (DIEM-SSP), faces the problem to evacuate the greater number of persons from a risky area and transfer them in a unique destination outside from this area using the available and limited resources. Supposing that these persons have problem of mobility, the problem to solve becomes this: collect the highest number of persons from several origins and bring them into a unique destination, using a limited number of capacitated vehicles respecting a time limit. This problem has been modelled as a Multi origins Capacitated Team Orienteering Problem (Mo-CTOP) and solved implementing Ants Colony Optimization algorithm (ACOa). Results and tests are given in order to validate the proposed model and to offer a solution for a real case treaty into the abovementioned project.

We investigate the effects of nanoparticles on the onset of varicose and whipping instabilities in the dynamics of electrified jets. In particular, we show that the non-linear interplay between the mass of the nanoparticles and electrostatic instabilities, gives rise to qualitative changes of the dynamic morphology of the jet, which in turn, drastically affect the final deposition pattern in electrospinning experiments. It is also shown that even a tiny amount of excess mass, of the order of a few percent, may more than double the radius of the electrospun fiber, with substantial implications for the design of experiments involving electrified jets as well as spun organic fibers. Copyright (C) EPLA, 2017

We investigate the effects of high solvated-methane concentration on methane-hydrate nucleation at 250 K and 500 atm. We consider solutions at four levels of methane molar fraction in the initial H2O-CH4 solution, ?CH4 = 0.038, 0.044, 0.052, and 0.058, which are higher than (metastable) bulk supersaturation. ?CH4 is controlled independently of the temperature and pressure thanks to the use of special simulation techniques [Phys. Chem. Chem. Phys. 2011, 13, 13177]. These conditions mimic a possible increase of local methane concentration beyond supersaturation induced, for example, by freeze concentration or thermal fluctuations. The nucleation mechanism and kinetics are investigated using the dynamical approach to nonequilibrium molecular dynamics. We demonstrate a hydrate-forming/-ordering process of solvated methane and water molecules in a manner consistent with both the "blob" hypothesis and "cage adsorption hypothesis": the system initially forms an amorphous nucleus at high methane concentration, which then gets ordered, forming the clathrate crystallite. We evaluate nucleation rates using both the methods of the mean first-passage time, i.e., the curve of the average time the system takes to reach a crystalline nucleus of given size, and survival probability, i.e., probability that up to a given time the system has not nucleated yet. We found a dependence of the nucleation rate on initial methane concentration of a form consistent with the dependence of classical nucleation theory rate on supersaturation and determined the relevant parameters of this relation. We found a very rapid increase of nucleation rate with solvated-methane concentration, proving that methane molar fraction, even beyond bulk supersaturation, is key at triggering the homogeneous nucleation of clathrate. We derive a kinetic equation that allows for estimation of the nucleation rate over a wide range of concentration conditions.

We present a multi-layer mathematical model to describe the transdermal drug release from an iontophoretic system. The Nernst-Planck equation describes the basic convection-diffusion process, with the electric potential obtained by solving the Laplace's equation. These equations are complemented with suitable interface and boundary conditions in a multi-domain. The stability of the mathematical problem is discussed in different scenarios and a finite-difference method is used to solve the coupled system. Numerical experiments are included to illustrate the drug dynamics under different conditions.

The expansion of biological species in natural environments is usually described as the combined effect individual spatial dispersal and growth. In the case of aquatic ecosystems flow transport can also be extremely relevant as an extra, advection induced, dispersal factor. We designed and assembled a dedicated microfluidic device to control and quantify the expansion of populations of E. coli bacteria under both co-flowing and counter-flowing conditions, measuring the front speed at varying intensity of the imposed flow. At variance with respect to the case of classic advective-reactive-diffusive chemical fronts, we measure that almost irrespective of the counter-flow velocity, the front speed remains finite at a constant positive value. A simple model incorporating growth, dispersion and drift on finite-size hard beads allows to explain this finding as due to a finite volume effect of the bacteria. This indicates that models based on the Fisher-Kolmogorov-Petrovsky-Piscounov equation (FKPP) that ignore the finite size of organisms may be inaccurate to describe the physics of spatial growth dynamics of bacteria.

Understanding and modeling the dynamics of pedestrian crowds can help with designing and increasing the safety of civil facilities. A key feature of a crowd is its intrinsic stochasticity, appearing even under very diluted conditions, due to the variability in individual behaviors. Individual stochasticity becomes even more important under densely crowded conditions, since it can be nonlinearly magnified and may lead to potentially dangerous collective behaviors. To understand quantitatively crowd stochasticity, we study the real-life dynamics of a large ensemble of pedestrians walking undisturbed, and we perform a statistical analysis of the fully resolved pedestrian trajectories obtained by a yearlong high-resolution measurement campaign. Our measurements have been carried out in a corridor of the Eindhoven University of Technology via a combination of Microsoft Kinect 3D range sensor and automatic head-tracking algorithms. The temporal homogeneity of our large database of trajectories allows us to robustly define and separate average walking behaviors from fluctuations parallel and orthogonal with respect to the average walking path. Fluctuations include rare events when individuals suddenly change their minds and invert their walking directions. Such tendency to invert direction has been poorly studied so far, even if it may have important implications on the functioning and safety of facilities. We propose a model for the dynamics of undisturbed pedestrians, based on stochastic differential equations, that provides a good agreement with our field observations, including the occurrence of rare events.

integral(R) A(vertical bar f' (x)vertical bar h(f(x))) dx <= C-1 integral(R) A(C-2 (p) root vertical bar Mf"(x)T-h,T-p (f,x)vertical bar. h(f(x))dx, Given a N-function A and a continuous function h satisfying certain assumptions, we derive the inequality [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], with constants [C.sub.1], [C.sub.2] independent of f, where f [greater than or equal to] 0 belongs locally to the Sobolev space [W.sup.2,1] (R), f' has compact support, p 1 is smaller than the lower Boyd index of A, [T.sub.h,p] (*) is certain nonlinear transform depending of h but not of A and M denotes the Hardy-Littlewood maximal function. Moreover, we show that when h [equivalent to] 1, then Mf" can be improved by f". This inequality generalizes a previous result by the third author and Peszek, which was dealing with p = 2.

Il volume introdotto da un lungo saggio è la trascrizione del memoriale di Cesare Gamba conservato al Centro di Servizio Bibliotecario di Architettura "Nino Carboneri" della Facoltà di Architettura dell'Università degli Studi di Genova. Gamba fu un abile ingegnere, un sensibile architetto ed uno degli ultimi seguaci della scuola classica. Il suo nome è oggi legato alla sua opera maggiore che fu la progettazione e la costruzione di via XX Settembre a Genova. Personaggio polivalente, Gamba fu anche un industriale, un impresario teatrale e molto altro. Durante la sua vita conobbe e frequentò figure storiche di grande rilievo, nel memoriale sono riportati i suoi ricordi degli incontri che ebbe con Garibaldi, Verdi, Puccini, Sarah Bernhardt e tanti altri. Il volume può essere letto come un romanzo storico o un intimo diario biografico, in entrambi i casi la lettura scorre piacevole ed avvincente.

The exploration and analysis of Web graphs has flourished in the recent past, producing a large number of relevant and interesting research results. However, the unique characteristics of the Tor network limit the applicability of standard techniques and demand for specific algorithms to explore and analyze it. The attention of the research community has focused on assessing the security of the Tor infrastructure (i.e., its ability to actually provide the intended level of anonymity) and on discussing what Tor is currently being used for. Since there are no foolproof techniques for automatically discovering Tor hidden services, little or no information is available about the topology of the Tor Web graph. Even less is known on the relationship between content similarity and topological structure. The present article aims at addressing such lack of information. Among its contributions: A study on automatic Tor Web exploration/data collection approaches; the adoption of novel representative metrics for evaluating Tor data; a novel in-depth analysis of the hidden services graph; a rich correlation analysis of hidden services' semantics and topology. Finally, a broad interesting set of novel insights/considerations over the TorWeb organization and content are provided.

With black-box access to the cipher being its unique requirement, Dinur and Shamir's cube attack is a flexible cryptanalysis technique which can be applied to virtually any cipher. However, gaining a precise understanding of the characteristics that make a cipher vulnerable to the attack is still an open problem, and no implementation of the cube attack so far succeeded in breaking a real-world strong cipher. In this paper, we present a complete implementation of the cube attack on a GPU/CPU cluster able to improve state-of-the-art results against the Trivium cipher. In particular, our attack allows full key recovery up to 781 initialization rounds without brute-force, and yields the first ever maxterm after 800 initialization rounds. The proposed attack leverages a careful tuning of the available resources, based on an accurate analysis of the offline phase, that has been tailored to the characteristics of GPU computing. We discuss all design choices, detailing their respective advantages and drawbacks. Other than providing remarkable results, this paper shows how the cube attack can significantly benefit from accelerators like GPUs, paving the way for future work in the area.

As services steadily migrate to the Cloud, the availability of an overarching identity framework has become a stringent need. Moreover, such an identity framework is now critical in the Internet of Things. To address this problem, identification solutions have been proposed in the past leveraging software or hardware properties of devices. While those solutions proved feasible, their root of trust was based either within the device or in a remote server. In this paper, we overcome the above paradigm and star investigating novel perspectives offered by an overarching identity framework that is not based on client/server properties, but on the network latency of their communications. The core idea behind our approach is to leverage cloud client/server interactions' latency patterns over the network to derive unique and unpredictable identity factors. Such factors can be used to design and implement effective identification schemes especially suitable for cloud-based services. To the best of our knowledge, our approach is the first one ensuring unclonability and unpredictability properties, relying on neither trusted computing bases (TCBs) nor on classical pseudo-random number generators (PRNGs). The experimental tests presented in this paper, conducted on worst case conditions, show that the network latency (generated between two interacting devices) can produce random values with properties close to the ones generated by most of the well-known PRNGs, that are an ideal fit for providing unique identifiers. Peer-review under responsibility of the Conference Program Chairs.

Effectively protecting the WindowsTM OS is a challenging task, since most implementation details are not publicly known. Windows OS has always been the main target of malware that have exploited numerous bugs and vulnerabilities exposed by its implementations. Recent trusted boot and additional integrity checks have rendered the Windows OS less vulnerable to kernel-level rootkits. Nevertheless, guest Windows Virtual Machines are becoming an increasingly interesting attack target. In this work we introduce and analyze a novel Hypervisor-Based Introspection System (HyBIS) we developed for protecting Windows OSes from malware and rootkits. The HyBIS architecture is motivated and detailed, while targeted experimental results show its effectiveness. Comparison with related work highlights main HyBIS advantages such as: effective semantic introspection, support for 64-bit architectures and for recent Windows versions ( >=>= win 7), and advanced malware disabling capabilities. We believe the research effort reported here will pave the way to further advances in the security of WindowsTM OSes.

This paper presents a chemo-mechano-biological framework for arterialphysiopathology. The model accounts for the fine remodelling in the multi-scale hierarchical arrangement of tissue constituents and for the diffusion of molecular species involved in cell-cell signalling pathways. Effects in terms of alterations in arterial compliance are obtained. A simple instructive example is introduced. Although oversimplified with respect to realistic case studies, the proposed application mimics the biochemical activity of matrix metallo- proteinases, transforming growth factors beta and interleukins on tissue remodelling. Effects of macrophage infiltration, of intimal thickening and of a healing phase are investigated, highlighting the corresponding influence on arterial compliance. The obtained results show that the present approach is able to capture changes in arterial mechanics as a consequence of the alterations in tissue biochemical environment and cellular activity, as well as to incorporate the protective role of both autoimmune responses and pharmacological treatments.

ThŒis paper is focused on the comparison of results obtained by the resolution of the capacitated vehicle routing problem. A modi€ed algorithm of classical arti€cial bee colony (ABC) is described and implemented in this article, in particular, a new type of neighborhood operator is introduced. Œe idea on the base of ABC is creating an algorithm of Swarm - Intelligence which mimics the behavior of a honey bee swarm. Œe performance of the proposed metaheuristic is evaluated on two sets of standard benchmark instances and is compared with the well-known results obtained by savings algorithm of Clarke and Wright and with those calculated using ABC-enhanced by Szeto et al. Œe computational results show that the proposed ABC outperforms the Saving algorithm and that it can produce good solutions when compared with the ABC-enhanced.

ThŒe emergencies management in industrial plants is an issue widely discussed in the literature and in the European legislative framework. Despite the large interest shown by the di‚erent actors involved in emergencies management, neither scienti€c nor in industrial €eld, have developed intelligent tools to support the decisions in these particular contexts. Œiswork, realized inside an Italian €nanced project (DIEM-SSP), faces the problem to evacuate the greater number of persons from a risky area and transfer them in a unique destination outside from this area using the available and limited resources. Supposing that these persons have problem of mobility, the problem to solve becomes this: collect the highest number of persons from several origins and bring them into a unique destination or multiple destination using a limited number of capacitated vehicles respecting a time limit. Œis problem has been modelled as a Multi origins Capacitated Team Orienteering Problem (Mo-CTOP) and solved implementing Optimization algorithm. At the same time the potentiality of multi-destination are explored in order to analyse the bene€ts in a real application. So that a €rst design a solution approach for a Multi origins and Multi destination Capacitated Team Orienteering Problem (Mo-Md-CTOP) is given. Œe team characteristic of the problem is due to need of simultaneous optimization of multi recovery vehicles. Results and tests are given on simple instances in order to validate the proposed model. Future research could explore the opportunities o‚ered by this tool if implemented in smartphone and tablet application. In this case in fact, the computational time could represent an important constraint to considerer in the algorithm€s design. Heuristics and metaheuristics approaches could be explored to give sub-optimal solutions to the problem in short time of computation. In this way the designed algorithm could be used also in real time situation in mobile applications available for rescue teams.

The present investigation focuses on the effects of the stern appendages and the propulsion system on the hydro-loads generated by the propeller during off-design conditions, with particular emphasis on the in-plane components. Recent experimental investigations carried out by free running model tests [7,8] and CFD analysis [5] for a modern twin screw model, highlighted that maneuvers at small drift angles and yaw rates might be as critical as the tighter ones due to complex propeller-wake interactions. Therefore, design criteria should take into account also these operative conditions, in order to reduce the effects of propeller-wake interaction phenomena that degrade the overall propulsive efficiency, induce shaft/hull structural vibration and increase noise emission. In the present study we analyze the effects of geometric and propulsive modifications with respect to the twin screw configuration studied in [5]. In particular, the effect of the centreline skeg, propeller direction of rotation and control strategies of the propulsion plant on the propeller bearing loads have been investigated from the analysis of the nominal wake in maneuvring conditions, computed by unsteady RANSE simulations coupled with a propeller model based on Blade Element Theory. The considered test cases were turning circle maneuvers with different rudder angles at FN = 0.265.

In this paper we propose a method to couple two or more explicit numerical schemes approximating the same time-dependent PDE, aiming at creating a new scheme which inherits 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.