Integral estimates for weak solutions to a class of Dirichlet problems for nonlinear, fully anisotropic, elliptic equations with a zero order term are obtained by symmetrization techniques. The anisotropy of the principal part of the operator is governed by a general n-dimensional Young function of the gradient which is not necessarily of polynomial type and need not satisfy the $\Delta_2$-condition.

Purpose: We studied microRNAs as potential biomarkers for Pompe disease. Methods: We analyzed microRNA expression by small RNA-seq in tissues from the disease murine model at two different ages (3 and 9 months), and in plasma from Pompe patients. Results: In the mouse model we found 211 microRNAs that were differentially expressed in gastrocnemii and 66 in heart, with a different pattern of expression at different ages. In a preliminary analysis in plasma from six patients 55 microRNAs were differentially expressed.

E-commerce is a sector in continual growth in all countries and, in particular, the increase in B2C (Business to Consumer) e-commerce market has important effects on last-mile deliveries in city areas. The delivery of a parcel to a consumer's address involves not only high costs for both couriers (extended car routes) and consumers (high prices) and also greater environmental pollution. The growing demand for deliveries in urban areas involves increases in traffic and congestion problems and, consequently, environmental issues.

In this work a two level heuristic algorithm is described for a nearly real-time multi-vehicle many-to-many Dial-A-Ride Problem (DARP). This algorithm is ready to support a Demand Responsive Transportation System in which we face the problem of quickly evaluate a good-quality schedule for the vehicles and provide fast response to the users. The insertion heuristic is double dynamic nearly real-time and the objective function is to minimize the variance between the requested and scheduled time of pickup and delivery.

During the seismic cycle, in nature and as well as in lab samples, the crack density of rocks varies substantially, as stressed rocks approach a critical state and eventually fail (Vasseur et al, 2017; Nur, 1972; Gupta, 1973) . At Earth scales, small periodical stress variations such as seasonal loading/unloading and tides (Johnson_etal_2017) are constantly being superimposed on the tectonic loading stress of crustal rocks, inducing periodic changes in crack porosity, pore-fluid pressure, and saturation, that should leave a signature on crustal attenuation.

The distribution of the magnitudes of seismic events is generally assumed to be independent on past seismicity. However, by considering events in causal relation, for example, mother-daughter, it seems natural to assume that the magnitude of a daughter event is conditionally dependent on one of the corresponding mother events. In order to find experimental evidence supporting this hypothesis, we analyze different catalogs, both real and simulated, in two different ways. From each catalog, we obtain the law of the magnitude of the triggered events by kernel density.

We propose a version of the pure temporal epidemic type aftershock sequences (ETAS) model: the ETAS model with correlated magnitudes. As for the standard case, we assume the Gutenberg-Richter law to be the probability density for the magnitudes of the background events. Instead, the magnitude of the triggered shocks is assumed to be probabilistically dependent on that of the relative mother events. This probabilistic dependence is motivated by some recent works in the literature and by the results of a statistical analysis made on some seismic catalogs [Spassiani and Sebastiani, J. Geophys.

The problem of classifying multispectral image data is studied here. We propose a new Bayesian method for this. The method uses "a priori" spatial information modeled by means of a suitable Markov random field. The image data for each class are assumed to be i.i.d. following a multivariate Gaussian model with unknown mean and unknown diagonal covariance matrix. When the prior information is not used and the variances of the Gaussian model are equal, the method reduces to the standard K-means algorithm. All the parameters appearing in the posterior model are estimated simultaneously.

Recent studies have demonstrated the potential of dynamic contrast-enhanced magnetic resonance imaging (MRI) describing pulmonary perfusion. However, breathing motion, susceptibility artifacts, and a low signal-to-noise ratio (SNR) make automatic pixel-by-pixel analysis difficult. In the present work, we propose a novel method to compensate for breathing motion. In order to test the feasibility of this method, we enrolled 53 patients with pulmonary embolism (N = 24), chronic obstructive pulmonary disease (COPD) (N = 14), and acute pneumonia (N = 15).