In this paper we propose a new modeling tech- nique for vehicular traffic flow, designed for capturing at a macroscopic level some effects, due to the microscopic granularity of the flow of cars, which would be lost with a purely continuous approach. The starting point is a multiscale method for pedestrian modeling, recently introduced in [1], in which measure-theoretic tools are used to manage the microscopic and the macroscopic scales under a unique framework. In the resulting coupled model the two scales coexist and share information, in the sense that the same system is simultaneously described from both a discrete (microscopic) and a continuous (macroscopic) perspective. This way it is possible to perform numerical simulations in which the single trajectories and the average density of the moving agents affect each other. Such a method is here revisited in order to deal with multi-population traffic flow on networks. For illustrative purposes, we focus on the simple case of the intersection of two roads. By exploiting one of the main features of the multiscale method, namely its dimension-independence, we treat one-dimensional roads and two-dimensional junctions in a natural way, without referring to classical network theory. Furthermore, thanks to the coupling between the microscopic and the macroscopic scales, we model the continuous flow of cars without losing the right amount of granularity, which characterizes the real physical system and triggers self-organization effects, such as, for example, the oscillatory patterns visible at jammed uncontrolled crossroads.

organizzazione di un minisimposio nell'ambito del convegno Seventh European Conference on Elliptic and Parabolic Problems, Gaeta (Italy), 20 - 25 Maggio 2012.

The turning circle maneuver of a self-propelled tanker like ship model is numerically simulated through the integration of the unsteady Reynolds averaged Navier-Stokes (uRaNS) equations coupled with the equations of the motion of a rigid body. The solution is achieved by means of the unsteady RANS solver Xnavis developed at CNR-INSEAN. The focus here is on the analysis of the maneuvering behavior of the ship with two different stern appendages configurations; namely, a twin screw with a single rudder and a twin screw, twin rudder with a central skeg. Each propeller is taken into account by a model based on the actuator disk concept; anyhow, in order to correctly capture the turning maneuvering behavior of the model, a suitable model which takes into account for oblique flow effects has to be considered. Results from a preliminary verification assessment are discussed; validation of the predicted trajectory and the kinematical parameters is provided by comparison with experimental data from free running tests. Maneuvering abilities of the two configurations are discussed; in order to better understand the different behavior of the two configurations, an in depth analysis of the force and moments on the hull and on the individual appendages is provided.

A mathematical model describing the bioventing technique for the decontamination of pol- luted subsoil will be presented. Bioventing is a biological technique: bacteria remove the contaminant transforming it and oxygen is consumed in the reaction. The numerical model is based on the fluid flow theory in porous media and bacteria population dynamics and it describes: pollutant degradation, oxygen and bacteria concentration. The mathematical model will be numerically solved and the results of some experiments will be presented.

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The dissociation energies of the intermetallic molecules AuSr and AuBa were for the first time determined by the Knudsen effusion mass spectrometry method. The two species were produced in the vapor phase equilibrated with apt mixtures of the constituent elements, and the dissociation equilibria were monitored mass-spectrometrically in the temperature range 1406-1971 K (AuSr) and 1505-1971 K (AuBa). The third-law analysis of the equilibrium data gives the following dissociation energies (D-0 degrees, in kJ/mol): 244.4 +/- 4.8 (AuSr) and 273.3 +/- 6.3 (AuBa), so completing the series of D-0 degrees s for the AuAE (AE = group 2 element) diatomics. The AuAE species were also studied computationally at the coupled cluster including single, double and perturbative triple excitation [CCSD(T)] level with basis sets of increasing zeta quality, and various complete basis set limit extrapolations were performed to calculate the dissociation energies. Furthermore, the entire series of the heteronuclear diatomic species formed from one group 11 (Cu, Ag) and one group 2 (Be, Mg, Ca, Sr, Ba) metal was studied by DFT with the hybrid meta-GGA TPSSh functional and the def2-QZVPP basis set, selected after screening a number of functional-basis set combinations using the AuAE species as benchmark. Dissociation energies, internuclear distances, vibrational frequencies, and anharmonic constants were determined for the CuAE and AgAE species and their thermal functions evaluated therefrom. On this basis, a thermodynamic evaluation of the formation of these species was carried out under various conditions. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4711085]

The parallel implementation of MUPHY, a concurrent multiscale code for large-scale hemodynamic simulations in anatomically realistic geometries, for multi-GPU platforms is presented. Performance tests show excellent results, with a nearly linear parallel speed-up on up to 32GPUs and a more than tenfold GPU/CPU acceleration, all across the range of GPUs. The basic MUPHY scheme combines a hydrokinetic (Lattice Boltzmann) representation of the blood plasma, with a Particle Dynamics treatment of suspended biological bodies, such as red blood cells. To the best of our knowledge, this represents the first effort in the direction of laying down general design principles for multiscale/physics parallel Particle Dynamics applications in non-ideal geometries. This configures the present multi-GPU version of MUPHY as one of the first examples of a high-performance parallel code for multiscale/physics biofluidic applications in realistically complex geometries. © 2012 Global-Science Press.

This paper deals with the elastic energy induced by systems of straight edge dislocations in the framework of linearized plane elasticity. The dislocations are introduced as point topological defects of the displacement-gradient fields. Following the core radius approach, we introduce a parameter ? > 0 representing the lattice spacing of the crystal, we remove a disc of radius ? around each dislocation and compute the elastic energy stored outside the union of such discs, namely outside the core region. Then, we analyze the asymptotic behaviour of the elastic energy as ? -> 0, in terms of ?-convergence. We focus on the self energy regime of order log 1/?; we show that configurations with logarithmic diverging energy converge, up to a subsequence, to a finite number of multiple dislocations and we compute the corresponding ?-limit. © 2012 Springer-Verlag.

Advances in experimental biology, coupled with advances in computational power, bring new challenges to the interdisciplinary field of computational biology. One such broad challenge lies in the reverse engineering of gene networks, and goes from determining the structure of static networks, to reconstructing the dynamics of interactions from time series data. Here, we focus our attention on the latter area, and in particular, on parameterizing a dynamic network of oriented interactions between genes. By basing the parameterizing approach on a known power-law relationship model between connected genes (S-system), we are able to account for non-linearity in the network, without compromising the ability to analyze network characteristics. In this article, we introduce the S-System Parameter Estimation Method (SPEM). SPEM, a freely available R software package (http://www.picb.ac.cn/ClinicalGenomicNTW/temp3.html), takes gene expression data in time series and returns the network of interactions as a set of differential equations. The methods, which are presented and tested here, are shown to provide accurate results not only on synthetic data, but more importantly on real and therefore noisy by nature, biological data. In summary, SPEM shows high sensitivity and positive predicted values, as well as free availability and expansibility (because based on open source software). We expect these characteristics to make it a useful and broadly applicable software in the challenging reconstruction of dynamic gene networks.

Translational and evidence based medicine can take advantage of biotechnology advances that offer a fast growing variety of high-throughput data for screening molecular activities of genomic, transcriptional, post-transcriptional and translational observations. The clinical information hidden in these data can be clarified with clinical bioinformatics approaches. We have recently proposed a method to analyze different layers of high-throughput (omic) data to preserve the emergent properties that appear in the cellular system when all molecular levels are interacting. We show here that this method applied to brain cancer data can uncover properties (i.e. molecules related to protective versus risky features in different types of brain cancers) that have been independently validated as survival markers, with potential important application in clinical practice. © 2012 Fronza et al.; licensee BioMed Central Ltd.

We address the complexity class of several problems related to finding a path in a properly colored directed graph. A properly colored graph is defined as a graph G whose vertex set is partitioned into X(G) stable subsets, where X(G) denotes the chromatic number of G. We show that to find a simple path that meets all the colors in a properly colored directed graph is NP-complete, and so are the problems of finding a shortest and longest of such paths between two specific nodes. © Springer Science+Business Media, LLC 2011.

Blue phases are liquid crystals made up by networks of defects, or disclination lines. While existing phase diagrams show a striking variety of competing metastable topologies for these networks, very little is known as to how to kinetically reach a target structure, or how to switch from one to the other, which is of paramount importance for devices. We theoretically identify two confined blue phase I systems in which by applying an appropriate series of electric field it is possible to select one of two bistable defect patterns. Our results may be used to realize new generation and fast switching energy-saving bistable devices in ultrathin surface treated blue phase I wafers.

Blue phases are networks of disclination lines, which occur in cholesteric liquid crystals near the transition to the isotropic phase. They have recently been used for the new generation of fast switching liquid crystal displays. Here we study numerically the steady states and switching hydrodynamics of blue phase I (BPI) and blue phase II (BPII) cells subjected to an electric field. When the field is on, there are three regimes: for very weak fields (and strong anchoring at the boundaries) the blue phases are almost unaffected, for intermediate fields the disclinations twist (for BPI) and unzip (for BPII), whereas for very large voltages the network dissolves in the bulk of the cell. Interestingly, we find that a BPII cell can recover its original structure when the field is switched off, whereas a BPI cell is found to be trapped more easily into metastable configurations. The kinetic pathways followed during switching on and off entails dramatic reorganisation of the discli nation networks. We also discuss the effect of changing the director field anchoring at the boundary planes and of varying the direction of the applied field.

Wireless sensor networks involve a large area of real-world contexts, such as national security, military and environmental control applications, traffic monitoring, among others. These applications generally consider the use of a large number of low-cost sensing devices to monitor the activities occurring in a certain set of target locations. One of the most important issue that is considered in this context is maximizing network lifetime, that is the amount of time in which this monitoring activity can be performed by opportunely switching the sensors from active to sleep mode. Indeed, the lifetime of the network can be maximized by individuating subset of sensors (i.e., covers) and switching among them. Two important aspects need to be taken into account among others: (i) coverage: each determined cover has to cover the entire set of targets, and (ii) connectivity: each cover should provide satisfactory network connectivity so that sensors can communicate for data gathering or data fusion (connected covers). In this paper we consider the problem of determining the maximum network lifetime to monitor all the targets by means of connected covers. We analyze the problem and propose an exact approach based on column generation and two heuristic approaches, namely a greedy algorithm and a GRASP algorithm, to solve it. We analyze the performance of the heuristic approaches by comparing the obtained solutions with those provided by the exact approach when available. Our preliminary experimental results show the proposed solution algorithms to be promising in terms of tradeoff between quality of solutions and computational effort. © 2011 Springer-Verlag.