We survey recent results on determinantal processes

Robust Design Optimization (RDO) represents a really interesting opportunity when the specifications of the design are careful and accurate: the possibility to optimize an industrial object for the real usage situation, improving the overall performances while reducing the risk of occurrence of off-design con- ditions, strictly depends on the availability of the information about the probability of occurrence of the various operative conditions during the lifetime of the design. Those data are typically not available prior than the production of a prototype. However, once the design has been produced and is operative, navigation data can be collected and utilized for the modification (refitting) of the current design, possibly in an early stage of its lifetime, in order to adapt the design to the real operative conditions at a time when the lifetime is still long enough to allow the payback of the cost of the modification by the obtained savings. In the present paper, five sister ships have been observed for a time period of two months, recording their operative data. Statistical distribution of speed and displacement are derived. An optimization framework is then applied, and some modifications of a small portion of the hull are proposed in order to increase significantly the performances of the hull, decreasing the operative cost of the ship. Dedicated numerical techniques are adopted in order to reduce the time required for the re-design activities.

By using direct numerical simulations (DNS) at unprecedented resolution, we study turbulence under rotation in the presence of simultaneous direct and inverse cascades. The accumulation of energy at large scale leads to the formation of vertical coherent regions with high vorticity oriented along the rotation axis. By seeding the flowwithmillions ofinertialparticles,wequantify -- forthefirsttime -- theeffects ofthose coherent vertical structures on the preferential concentration of light and heavy particles. Furthermore, we quantitatively show that extreme fluctuations, leading to deviations from a normal-distributed statistics, result from the entangled interaction of the vertical structures with the turbulent background. Finally, we present the first-ever measurement of the relative importance between Stokes drag, Coriolis force, and centripetal force along the trajectories of inertial particles. We discover that vortical coherent structures lead to unexpected diffusion properties for heavy and light particles in the directions parallel and perpendicular to the rotation axis.

MIPAS on ENVISAT performed almost continuously measurements of the atmospheric composition for almost 10 years, from June 2002 to April 2012. These ten years cover a period when the first effect of the dismiss of the emission of the CFCs after the Montreal protocol ratification in 1987can be measured. Even if ten years constitute a short period to derive trends, it has been proven that useful information on time variation of atmospheric constituents can be derived from the analysis of these measurements. However, previous versions of MIPAS on ENVISAT dataset were characterized by an instrumental drift due to the fact that some detectors used by MIPAS were affected by non-linearities, which change with time due to the ageing of the detectors and this was cause of a non negligible systematic error in the trend estimation. The new full mission reprocessed dataset V7 that will be released very soon uses L1 files where the impact of the ageing of the detectors on non-linearities has been corrected. Furthermore, also the L2 processor has been upgraded with new functionalities improving the performances of the processor. We present the results of study of trends derived from the analysis of the new MIPAS V7 products on several MIPAS target species including ozone depleting species, like CFC-11, CFC-12, CCl4 and HCFC-22.

A new technique for color quantization is suggested. First, pre-quantization is accomplished by means of spatial resolution reduction; then, color aggregation is accomplished based on the distance between colors in the color space. Color aggregation is an iterated process where the number of iterations is given by the difference between the number of colors of the pre-quantized image, and the number of colors desired for the quantized image. Color mapping is finally accomplished. Performance evaluation is done in terms of generally adopted quality measures. Comparisons with other methods in the literature are also provided.

A new technique is presented for color image segmentation. Five processes are accomplished that are respectively dealing with color image quantization, noisy regions removal, removal of thin regions, color-based region merging, and area-based region merging. Some parameters involved in the method are automatically computed, others are fixed depending on the specific application. Thus, the method is characterized by some flexibility that makes it useful for different applications. The method has been checked on color images from publicly available repositories. The performance of the method has been evaluated in terms of Precision, Recall and F-measure. The obtained results are satisfactory from both a qualitative and a quantitative point of view.

Abstract In this paper the Bi-Objective k-Length-Bounded Critical Disruption Path (BO-kLB-CDP) optimization problem is proposed, aimed at maximizing the interdiction effects provided on a network by removing a simple path connecting a given source and destination whose length does not exceed a certain threshold. The BO-kLB-CDP problem extends the Critical Disruption Path (CDP) problem introduced by Granata et al. in [Granata, D. and Steeger, G. and Rebennack, S., Network interdiction via a Critical Disruption Path: Branch-and-Price algorithms, Computers & Operations Research, Volume 40, Issue 11, November 2013, Pages 2689-2702]. Several real applications of this class of optimization problems arise in the field of security, surveillance, transportation and evacuation operations. In order to overcome some limits of the original {CDP} problem and increase its suitability for practical purposes, first we consider a length limitation for Critical Disruption Paths. Second, we generalize the concept of network interdiction considered in the CDP: beside minimizing the cardinality of the maximal connected component after the removal of the CDP, now we are also interested in maximizing the number of connected components in the residual graph. A Mixed Integer Programming formulation for the BO-kLB-CDP problem is therefore proposed and discussed, presenting the results of a multiple objective analysis performed through a computational experience on a large set of instances.

Background: Macrophages cover a major role in the immune system, being the most plastic cell yielding several key immune functions. Methods: Here we derived a minimalistic gene regulatory network model for the differentiation of macrophages into the two phenotypes M1 (pro-) and M2 (anti-inflammatory).

A malicious alteration of system-provided timeline can negatively affect the reliability of computer forensics. Indeed, detecting such changes and possibly reconstructing the correct timeline of events is of paramount importance for court admissibility and logical coherence of collected evidence. However, reconstructing the correct timeline for a set of network nodes can be difficult since an adversary has a wealth of opportunities to disrupt the timeline and to generate a fake one. This aspect is exacerbated in cloud computing, where host and guest machine-time can be manipulated in various ways by an adversary. Therefore, it is important to guarantee the integrity of the timeline of events for cloud host and guest nodes, or at least to ensure that timeline alterations do not go undetected. This paper provides several contributions. First, we survey the issues related to cloud machine-time reliability. Then, we introduce a novel architecture (CURE) aimed at providing timeline resilience to cloud nodes. Further, we implement the proposed framework and extensively test it on both a simulated environment and on a real cloud. We evaluate and discuss collected results showing the effectiveness of our proposal. (C) 2016 Elsevier B.V. All rights reserved.

this chapter discussed advanced technologies that can help provide trust in the cloud

this chapter discusses secure management of virtualized resources in a Cloud

this Chapter discusses secure assessment and authorization for private Clouds

Connections between microscopic follow-the-leader and macroscopic fluid-dynamics traffic flow models are already well understood in the case of vehicles moving on a single road. Analogous connections in the case of road networks are instead lacking. This is probably due to the fact that macroscopic traffic models on networks are in general ill-posed, since the conservation of the mass is not sufficient alone to characterize a unique solution at junctions. This ambiguity makes more difficult to find the right limit of the microscopic model, which, in turn, can be defined in different ways near the junctions. In this paper we show that a natural extension of the first-order follow-the-leader model on networks corresponds, as the number of vehicles tends to infinity, to the LWR-based multi-path model introduced in [4, 5].

In this paper we are concerned with multiscale modeling, control, and simulation of self-organizing agents leaving an unknown area under limited visibility, with special emphasis on crowds. We first introduce a new microscopic model characterized by an exploration phase and an evacuation phase. The main ingredients of the model are an alignment term, accounting for the herding effect typical of uncertain behavior, and a random walk, accounting for the need to explore the environment under limited visibility. We consider both metrical and topological interactions. Moreover, a few special agents, the leaders, not recognized as such by the crowd, are "hidden" in the crowd with a special controlled dynamic. Next, relying on a Boltzmann approach, we derive a mesoscopic model for a continuum density of followers, coupled with a microscopic description for the leaders' dynamics. Finally, optimal control of the crowd is studied. It is assumed that leaders aim at steering the crowd towards the exits so to ease the evacuation and limit clogging effects, and locally optimal behavior of leaders is computed. Numerical simulations show the efficiency of the control techniques in both microscopic and mesoscopic settings. We also perform a real experiment with people to study the feasibility of such a bottom-up control technique.

Presentazione a convegno

The RapidCell (RC) model was originally developed to simulate flagellar bacterial chemotaxis in environments with spatiotemporally varying chemoattractant gradients. RC is best suited for motility simulations in unbounded nonfluid environments; this limits its use in biomedical applications hinging on bacteria-fluid dynamics in microchannels. In this study, we eliminated this constraint by coupling the RC model with the colloidal lattice Boltzmann (LB) model. RC-LB coupling was accomplished by tracking positions of chemoreceptors on particle surfaces that vary with particles' angular and translational velocities, and by including forces and torques due to particles' tumbling and running motions in particle force-and torque-balance equations. The coupled model successfully simulated trajectories of particles in initially stagnant fluids in bounded domains, involving a chemoattractant contained in a confined zone with a narrow inlet or concentric multiringed inline obstacles, mimicking tumor vasculature geometry. Chemotactically successful particles exhibited higher attractant concentrations near the receptor clusters, transient increases in the motor bias, and transient fluctuations in methylated proteins at the cell scale, while exhibiting more frequent higher particle translation velocities and smaller angular velocities than chemotactically unsuccessful particles at the particle scale. In these simulations, the chemotactic particles reached the chemoattractant with the success rates of 20-72 %, whereas nonchemotactic particles would be unsuccessful. The coupled RC-LB model is the first step toward development of a multiscale simulation tool that bridges cell-scale signal and adaptation dynamics with particle-scale fluid-particle dynamics to simulate chemotaxis-driven bacterial motility in microchannel networks, typically observed in tumor vasculatures, in the context of targeted drug delivery.

The main steps taking the Lattice Boltzmann (LB) method beyond the realm of continuum hydrodynamics are discussed along with an appraisal of future prospects for coupling LB with other computational kinetic methods, such as Bird's Direct Simulation Monte Carlo and/or Discrete Velocity Models.

We present a Lattice Boltzmann method for the simulation of a wide range of Knudsen regimes. The method is assessed in terms of normalised discharge for flow across parallel plates and three-dimensional flows in porous media. Available analytical solutions are well reproduced, supporting the the method as an appealing candidate to bridge the gap between the hydrodynamic regime and free molecular motion.