Background & Aims: Acute liver failure is a rapidly progressive deterioration of hepatic function resulting in high mortality and morbidity. Metabolic enzymes can translocate to the nucleus to regulate histone acetylation and gene expression. Methods: Levels and activities of pyruvate dehydrogenase complex (PDHC) and lactate dehydrogenase (LDH) were evaluated in nuclear fractions of livers of mice exposed to various hepatotoxins including CD95-antibody, ?-amanitin, and acetaminophen.

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.

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.

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.

This paper is concerned with improving the performance of certain Markov chain algorithms for Monte Carlo simulation. We propose a new algorithm for simulating from multivariate Gaussian densities. This algorithm combines ideas from coupled Markov chain methods and from an existing algorithm based only on over-relaxation. The rate of convergence of the proposed and existing algorithms can be measured in terms of the square of the spectral radius of certain matrices. We present examples in which the proposed algorithm converges faster than the existing algorithm and the Gibbs sampler.

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).

An inverse diffusion problem that appears in Magnetic Resonance dosimetry is studied. The problem is shown to be equivalent to a deconvolution problem with a known kernel. To cope with the singularity of the kernel, nonlinear regularization functionals are considered which can provide regular solutions, reproduce steep gradients and impose positivity constraints. A fast deterministic algorithm for solving the involved non-convex minimization problem is used.

During the last 20 years, three seismic sequences affected the Apenninic belt (central Italy): Colfiorito (1997-98), L'Aquila (2009) and Amatrice Visso-Norcia Campotosto (2016-17). They lasted for a long time, with a series of moderate-to-large earthquakes distributed over 40-60 km long Apenninic-trending segments. Their closeness in space and time suggested to study their aftershock sequences to highlight similarities and differences. Aftershock space migration and the distribution of aftershock inter-arrival time were studied.