Recently, an algorithm for coupling a Finite Volume (FV) method, that discretize the Navier-Stokes equations on block structured Eulerian grids, with the weakly-compressible SPH was presented. The algorithm takes advantage of the SPH method to discretize flow regions close to free-surfaces and of Finite Volume method to resolve the bulk flow and the wall regions. The continuity between the two solution is guaranteed by overlapping zones.

Interleukin-6 (IL-6) has been recently shown to play a central role in glucose homeostasis, since it stimulates the production and secretion of Glucagon-like Peptide-1 (GLP-1) from intestinal L-cells and pancreas, leading to an enhanced insulin response. In resting conditions, IL-6 is mainly produced by the adipose tissue whereas, during exercise, skeletal muscle contractions stimulate a marked IL-6 secretion as well. Available mathematical models describing the effects of exercise on glucose homeostasis, however, do not account for this IL-6 contribution.

Motivation: A computational model equipped with the main immunological features of the sea bass (Dicentrarchus labrax L.) immune system was used to predict more effective vaccination in fish. The performance of the model was evaluated by using the results of two in vivo vaccinations trials against L. anguillarum and P. damselae.

This paper focuses on an entropy based formalism to speed up the evaluation of the Structural SIMilarity (SSIM) index in images affected by a global distortion. Looking at images as information sources, a visual distortion typical set can be defined for SSIM. This typical set consists of just a subset of information belonging to the original image and the corresponding one in the distorted version. As side effect, some general theoretical criteria for the computation of any full reference quality assessment measure can be given in order to maximize its computational efficiency.

The paper presents a method for color quantization (CQ) which uses visual contrast for determining an image-dependent color palette. The proposed method selects image regions in a hierarchical way, according to the visual importance of their colors with respect to the whole image. The method is automatic, image dependent and requires a moderate computational effort. Preliminary results show that the quality of quantized images, measured in terms of Mean Square Error, Color Loss and SSIM, is competitive with some existing CQ approaches.

The large amount of work on community detection and its applications leaves unaddressed one important question: the statistical validation of the results. A methodology is presented that is able to clearly detect if the community structure found by some algorithms is statistically significant or is a result of chance, merely due to edge positions in the network. Given a community detection method and a network of interest, the proposal examines the stability of the partition recovered against random perturbations of the original graph structure.

This paper aims at increasing the visual quality of a blurred image according to the contrast sensitivity of a human observer. The main idea is to enhance those image details which can be perceived by a human observer without introducing annoying visible artifacts. To this aim, an adaptive wavelet decomposition is applied to the original blurry image. This decomposition splits the frequency axis into subbands whose central frequency and amplitude width are built according to the contrast sensitivity.

We provide a Clark-Ocone formula for square-integrable functionals of a general temporal point process satisfying only a mild moment condition, generalizing known results on the Poisson space. Some classical applications are given, namely a deviation bound and the construction of a hedging portfolio in a pure-jump market model. As a more modern application, we provide a bound on the total variation distance between two temporal point processes, improving in some sense a recent result in this direction.

We give general bounds in the Gaussian and Poisson approximations of innovations (or Skorohod integrals) defined on the space of point processes with Papangelou conditional intensity. We apply the general results to Gibbs point processes with pair potential and determinantal point processes. In particular, we provide explicit error bounds and quantitative limit theorems for stationary, inhibitory and finite range Gibbs point processes with pair potential and beta-Ginibre point processes.