Cyber insurance is a rapidly developing area which draws more and more attention of practitioners and researchers. Insurance, an alternative way to deal with residual risks, was only recently applied to the cyber world. The immature cyber insurance market faces a number of unique challenges on the way of its development.In this paper we summarise the basic knowledge about cyber insurance available so far from both market and scientific perspectives. We provide a common background explaining basic terms and formalisation of the area.

Significant improvements in the computational performance of the lattice-Boltzmann (LB) model, coded in FORTRAN90, were achieved through application of enhancement techniques. Applied techniques include optimization of array memory layouts, data structure simplification, random number generation outside the simulation thread(s), code parallelization via OpenMP, and intra- and inter-timestep task pipelining.

This paper reports, for the first time, the computational performance of SequenceL for mesoscale simulations of large numbers of particles in a microfluidic device via the lattice-Boltzmann method. The performance of SequenceL simulations was assessed against the optimized serial and parallelized (via OpenMP directives) FORTRAN90 simulations. At present, OpenMP directives were not included in interparticle and particle-wall repulsive (steric) interaction calculations due to difficulties that arose from inter-iteration dependencies between consecutive iterations of the do-loops.

We use highly resolved numerical simulations to study turbulent Rayleigh-Benard convection in a cell with sinusoidally rough upper and lower surfaces in two dimensions for Pr = 1 and Ra = [4 x 10(6), 3 x 10(9)]. By varying the wavelength. at a fixed amplitude, we find an optimal wavelength lambda(opt) for which the Nusselt-Rayleigh scaling relation is (Nu - 1 proportional to Ra-0.483), maximizing the heat flux. This is consistent with the upper bound of Goluskin and Doering [J. Fluid Mech.

Fluid dynamics in intrinsically curved geometries is encountered in many physical systems in nature, ranging from microscopic bio-membranes all the way up to general relativity at cosmological scales. Despite the diversity of applications, all of these systems share a common feature: the free motion of particles is affected by inertial forces originating from the curvature of the embedding space.

Growth in static and controlled environments such as a Petri dish can be used to study the spatial population dynamics of microorganisms. However, natural populations such as marine microbes experience fluid advection and often grow up in heterogeneous environments. We investigate a generalized Fisher-Kolmogorov-Petrovsky-Piscounov (FKPP) equation describing single species population subject to a constant flow field and quenched random spatially inhomogeneous growth rates with a fertile overall growth condition.

The understanding of water transport in graphene oxide (GO) membranes stands out as a major theoretical problem in graphene research. Notwithstanding the intense efforts devoted to the subject in the recent years, a consolidated picture of water transport in GO membranes is yet to emerge. By performing mesoscale simulations of water transport in ultrathin GO membranes, we show that even small amounts of oxygen functionalities can lead to a dramatic drop of the GO permeability, in line with experimental findings.

We focus on the extension of the MLD2P4 package of parallel Algebraic MultiGrid (AMG) preconditioners, with the objective of improving its robustness and efficiency when dealing with sparse linear systems arising from anisotropic PDE problems on general meshes. We present a parallel implemen- tation of a new coarsening algorithm for symmetric positive definite matrices, which is based on a weighted matching approach.

Overcomplete representations such as wavelets and windowed Fourier expansions have become mainstays of modern statistical data analysis. In the present work, in the context of general finite frames, we derive an oracle expression for the mean quadratic risk of a linear diagonal de-noising procedure which immediately yields the optimal linear diagonal estimator. Moreover, we obtain an expression for an unbiased estimator of the risk of any smooth shrinkage rule.