In this paper, multi-disciplinary optimization techniques are applied to sail design. Two different mathematical models, providing the solution of the fluid-dynamic and the structural problems governing the behaviour of a complete sailplan, are coupled in a fluid-structure interaction (FSI) scheme, in order to determine the real flying shape of the sails and the forces acting on them. A numerical optimization algorithm is then applied, optimizing the structural pattern of the sailplan in order to maximize the driving force or other significant quantities.

Experimental studies on vehicular traffic provide data on quantities like density, flux, and mean speed of the vehicles. However, the diagrams relating these variables (the fundamental and \emph{speed} diagrams) show some peculiarities not yet fully reproduced nor explained by mathematical models. In this paper, resting on the methods of kinetic theory, we introduce a new traffic model which takes into account the heterogeneous nature of the flow of vehicles along a road. In more detail, the model considers traffic as a mixture of two or more populations of vehicles (e.g., cars and trucks) with different microscopic characteristics, in particular different lengths and/or maximum speeds. With this approach we gain some insights into the scattering of the data in the regime of congested traffic clearly shown by actual measurements.

The paper presents a novel method for color quantization (CQ) of dermoscopic images. The proposed method consists of an iterative procedure that selects image regions in a hierarchical way, according to the visual importance of their colors. Each region provides a color for the palette which is used for quantization. The method is automatic, image dependent and computationally not demanding. Preliminary results show that the mean square error of quantized dermoscopic images is competitive with existing CQ approaches.

In the last two decades, PSO (Particle Swarm Optimization) gained a lot of attention among the different derivative-free algorithms for global optimization. The simplicity of the implementation, compact memory usage and parallel structure represent some key features, largely appreciated. On the other hand, the absence of local information about the objective function slow down the algorithm when one or more constraints are violated, even if a penalty approach is applied. This situation becomes critical when the feasible set reduces to a small portion of the space in which the objective function needs to be investigated, and then the probability to find a feasible point by uniform sampling is small. In the present paper, a modification of the original PSO algorithm is proposed that both avoids the evaluation of the objective function outside the feasible set and preserves the parallel structure of the algorithm. Particular attention is dedicated to the parallel structure of the algorithm, in the view of its implementation on parallel architectures.

Long-range NMR data, namely residual dipolar couplings (RDCs) from external alignment and paramagnetic data, are becoming increasingly popular for the characterization of conformational heterogeneity of multidomain biomacromolecules and protein complexes. The question addressed here is how much information is contained in these averaged data. We have analyzed and compared the information content of conformationally averaged RDCs caused by steric alignment and of both RDCs and pseudocontact shifts caused by paramagnetic alignment, and found that, despite the substantial differences, they contain a similar amount of information. Furthermore, using several synthetic tests we find that both sets of data are equally good towards recovering the major state(s) in conformational distributions.

Tropospheric ozone is a key species for tropospheric chemistry and air quality. Its monitoring is essential to quantify sources, transport, chemical transformation and sinks of atmospheric pollution. Accurate data are required for understanding and predicting chemical weather. Space-borne observations are very promising for these concerns, especially those from IASI/MetOp. However, their sensitivity near the surface remains limited and advanced retrieval methods are needed to access to the information from the lowest troposphere. Ill-conditioning is a well-known issue of the retrieval of vertical atmospheric profiles. It produces oscillations in the retrieved profiles beyond the error margins defined by the mapping of the measurement noise onto the solution. Tikhonov regularization is often used to improve the conditioning of the inversion. As for any regularization scheme, a crucial step is the choice of the strength of the applied constraint. This choice depends on the measurement errors and on the sensitivity of the measurements to the target parameters at the different altitudes. For this reason a self-adapting and altitude-dependent regularization scheme is likely preferable over a fixed strength determined apriori, on the basis of sensitivity tests. Such a scheme was already introduced in 2009 and applied to atmospheric profiles retrieved from MIPAS/ENVISAT. The implementation of this method on nadir IASI retrievals required the appropriated definition of the target function used to optimize the constraint for lower tropospheric retrievals. The challenge for this new retrieval algorithm is to limit the use of a priori constraints to the minimal amount needed to perform the inversion. Since the sensitivity of the observations to the ozone amount in the lowest layers depends on the atmospheric and surface conditions, it is crucial for the inversion algorithm to tune accordingly the contribution of the a priori information. We apply the method first on simulated observations of tropospheric ozone for August 20th, 2009 over Europe. A first evaluation of the method is discussed in the paper. Significant improvements in terms of degrees of freedom (DOF) for the solution are achieved with a 15% increase on average. The error estimate during the retrieval is in better agreement with the true error, calculated as the difference between the retrieved ozone and the true ozone. The spatial distribution and the dispersion of the error are better described. Finally, a first attempt to apply the method to actual IASI measurements is presented.

One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases.

In this work a Discrete Boltzmann Model for the solution of transcritical 2D shallow water flows is presented and validated. In order to provide the model with transcritical capabilities, a particular multispeed velocity set has been employed for the discretization of the Boltzmann equation. It is shown that this particular set naturally yields a simple and closed procedure to determine higher order equilibrium distribution functions needed to simulate transcritical flow. The model is validated through several classical benchmarks and is proven to correctly and accurately simulate both 1D and 2D transitions between the two flow regimes.

Motivated by the observation that electrons in graphene, in the hydrodynamic regime of transport, can be treated as a two-dimensional ultrarelativistic gas with very low shear viscosity, we examine the existence of the Rayleigh-Bénard instability in a massless electron-hole plasma. First, we perform a linear stability analysis, derive the leading contributions to the relativistic Rayleigh number, and calculate the critical value above which the instability develops. By replacing typical values for graphene, such as thermal conductivity, shear viscosity, temperature, and sample sizes, we find that the instability might be experimentally observed in the near future. Additionally, we have performed simulations for vanishing reduced chemical potential and compare the measured critical Rayleigh number with the theoretical prediction, finding good agreement.

Plastic rearrangements play a crucial role in the characterization of soft-glassy materials, such as emulsions and foams. Based on numerical simulations of soft-glassy systems, we study the dynamics of plastic rearrangements at the hydrodynamic scales where thermal fluctuations can be neglected. Plastic rearrangements require an energy input, which can be either provided by external sources, or made available through time evolution in the coarsening dynamics, in which the total interfacial area decreases as a consequence of the slow evolution of the dispersed phase from smaller to large droplets/bubbles. We first demonstrate that our hydrodynamic model can quantitatively reproduce such coarsening dynamics. Then, considering periodically oscillating strains, we characterize the number of plastic rearrangements as a function of the external energy-supply, and show that they can be regarded as activated processes induced by a suitable "noise" effect. Here we use the word noise in a broad sense, referring to the internal non-equilibrium dynamics triggered by spatial random heterogeneities and coarsening. Finally, by exploring the interplay between the internal characteristic time-scale of the coarsening dynamics and the external time-scale associated with the imposed oscillating strain, we show that the system exhibits the phenomenon of stochastic resonance, thereby providing further credit to the mechanical activation scenario.

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The goal of this article is to study numerically the mixed convection in a differentially heated lid-driven cavity with non-uniform heating of the bottom wall. The velocity field is solved by a hybrid scheme with multiple relaxation time Lattice Boltzmann (MRT-LBM) model, while the temperature field is obtained by resolution of the energy balance equation using the finite difference method (FDM). First, the model is checked and validated using data from the literature. Validation of the present results with those available in the literature shows a good agreement. A good efficiency in time simulation is confirmed. Thereafter, the model has been applied to mixed convection in a driven cavity with non-uniform heating wall at the fixed Grashof number Gr = 10(6). It is found that, the heat transfer is weakened as the Richardson number is augmented. For Gr = 10(6), we note the appearance of secondary vortices at different positions of the cavity corners.

Numerical simulations of vesicle suspensions are performed in two dimensions to study their dynamical and rheological properties. An hybrid method is adopted, which combines a mesoscopic approach for the solvent with a curvature-elasticity model for the membrane. Shear flow is induced by two counter-sliding parallel walls, which generate a linear flow profile. The flow behavior is studied for various vesicle concentrations and viscosity ratios between the internal and the external fluid. Both the intrinsic viscosity and the thickness of depletion layers near the walls are found to increase with increasing viscosity ratio.

The rheology and dynamics of suspensions of fluid vesicles is investigated by a combination of molecular dynamics and mesoscale hydrodynamics simulations in two dimensions. The vesicle suspension is confined between two no-slip shearing walls. The flow behavior is studied as a function of the shear rate, the volume fraction of vesicles, and the viscosity ratio between inside and outside fluids. Results are obtained for the interactions of two vesicles, the intrinsic viscosity of the suspension, and the cell-free layer near the walls.

Cavitation in a liquid moving past a constraint is numerically investigated by means of a free-energy lattice Boltzmann simulation based on the van der Waals equation of state. The fluid is streamed past an obstacle and, depending on the pressure drop between inlet and outlet, vapor formation underneath the corner of the sack-wall is observed. The circumstances of cavitation formation are investigated and it is found that the local bulk pressure and mean stress are insufficient to explain the phenomenon. Results obtained in this study strongly suggest that the viscous stress, interfacial contributions to the local pressure, and the Laplace pressure are relevant to the opening of a vapor cavity. This can be described by a generalization of Joseph's criterion that includes these contributions. A macroscopic investigation, closer in spirit to engineering practice, measuring mass flow rate behavior and discharge coefficient was also performed. Simulations were carried out by fixing the total upstream pressure and varying the static downstream pressure for different kinematic viscosities. As theoretically predicted, mass flow rate increases linearly with the square root of the pressure drop. However, when cavitation occurs the mass flow growth rate is reduced and eventually it collapses into a choked flow state. Reduction of the mass flow growth rate coincides with a smaller discharge coefficient. Therefore, in the cavitating regime, as theoretically predicted and experimentally verified, the discharge coefficient grows with the Nurick cavitation number. On the other hand, in the non-cavitating regime the discharge coefficient grows with the Reynolds number due to the reduction of the boundary layer thickness.

The bubble cavitation problem in quiescent and sheared liquids is investigated using a third-order isothermal lattice Boltzmann (LB) model that describes a two-dimensional ($2D$) fluid obeying the van der Waals equation of state. The LB model has 16 off-lattice velocities and is based on the Gauss-Hermite quadrature method. The evolution equations for the distribution functions in this model are solved using the corner transport upwind numerical scheme on large square lattices (up to $4096 \times 4096$ nodes). In a quiescent liquid, the computer simulation results are in good agreement to the $2D$ Rayleigh-Plesset equation. In a sheared liquid, we investigated the evolution of the total bubble area, the bubble deformation and the bubble tilt angle, for various values of the shear rate. A linear relation between the dimensionless deformation coefficient $D$ and the capillary number $Ca$ is found at small $Ca$ but with a different factor than in equilibrium liquids. A non-linear regime is observed for $Ca \gtrsim 0.3$.

Broader comprehension of gene expression regulatory mechanisms can be gained from a global analysis of how transcription and degradation are coordinated to orchestrate complex cell responses. The role of messenger RNA (mRNA) turnover modulation in gene expression levels has become increasingly recognized. From such perspective, in this review we briefly illustrate how a simple but effective mathematical model of mRNA turnover and some experimental findings, may together shed light on the molecular mechanisms underpinning the major role of mRNA decay rates in shaping the kinetics of gene activation and repression

Background: Direct-acting antiviral drugs (DAA) regimen improve the SVR rate. However, adverse effects often lead to therapy interruption. This underlines the importance to find some predictive parameters of response in order to consider the possibility of a shorter time of antiviral treatment in the appearance of adverse effects without affecting the success of the therapy. Objectives: We aimed to examine the HCVAg kinetics in the early phase of treatment and its predictive value of SVR in patients undergoing TPV/Peg-IFN/RBV treatment. Study design: Twenty-three patients infected by HCV genotype 1 (1a n = 11; 1b n = 12) were included in this prospective study. Results: At baseline the median Log of HCVAg concentration in RVR and EVR patients were 3.15 fmol/L and 3.45 fmol/L, respectively with no significant differences. The baseline median HCV-RNA to HCVAg ratio was 233.77, this ratio was significantly lower when measured on day 1 (27.52) and on day 6 (24.84) (p < 0.001). The two-tailed Fisher's exact test indicated that the SVR response is statistically significantly different in patients with detected HCVAg at week1 compared to patients with no detectable HCVAg (p = 0.05). The sensitivity, specificity, and negative and positive predictive values (NPV, PPV) were 53.8, 87.5, 53.8 and 87.5%, respectively. The area under the ROC curve was 0.71 at day T6, the best cut-off of 3 fmol/L when evaluated with the HCVAg plasma concentration at dayT6. Conclusion: Undetectable HCVAg in the early phase of TPV/Peg-IFN/RBV treatment could represent an important parameter for predicting SVR.

Understanding the conditions ensuring the persistence of a population is an issue of primary importance in population biology. The first theoretical approach to the problem dates back to the 1950s with the Kierstead, Slobodkin, and Skellam (KiSS) model, namely a continuous reaction-diffusion equation for a population growing on a patch of finite size L surrounded by a deadly environment with infinite mortality, i.e., an oasis in a desert. The main outcome of the model is that only patches above a critical size allow for population persistence. Here we introduce an individual-based analog of the KiSS model to investigate the effects of discreteness and demographic stochasticity. In particular, we study the average time to extinction both above and below the critical patch size of the continuous model and investigate the quasistationary distribution of the number of individuals for patch sizes above the critical threshold.

We consider Volterra integral equations on time scales and present our study about the long time behavior of their solutions. We provide sufficient conditions for the stability and investigate the convergence properties when the kernel of the equations vanishes at infinity.