Abstract In this paper the Bi-Objective k-Length-Bounded Critical Disruption Path (BO-kLB-CDP) optimization problem is proposed, aimed at maximizing the interdiction effects provided on a network by removing a simple path connecting a given source and destination whose length does not exceed a certain threshold. The BO-kLB-CDP problem extends the Critical Disruption Path (CDP) problem introduced by Granata et al. in [Granata, D. and Steeger, G.

Primary biliary cholangitis (PBC) is a chronic, cholestatic, immune-mediated, and progressive liver disorder. Treatment to preventing the disease from advancing into later and irreversible stages is still an unmet clinical need. Accordingly, we set up a drug repurposing framework to find potential therapeutic agents targeting relevant pathways derived from an expanded pool of genes involved in different stages of PBC.

We have investigated systematically and statistically methanol-concentration effects on methane-hydrate nucleation using both experiment and restrained molecular-dynamics simulation, employing simple observables to achieve an initially homogeneous methane-supersaturated solution particularly favorable for nucleation realization in reasonable simulation times.

In this perspective we take stock of the current state of the art of computational models for droplets microfluidics and we suggest some strategies which may open the way to the full-scale simulation of microfluidic phenomena with interfaces, from near-contact interactions to the device operational lengths.

Objective: Customization of the rate of drug delivered based on individual patient requirements is of paramount importance in the design of drug delivery devices. Advances in manufacturing may enable multilayer drug delivery devices with different initial drug distributions in each layer. However, a robust mathematical understanding of how to optimize such capabilities is critically needed. The objective of this work is to determine the initial drug distribution needed in a spherical drug delivery device such as a capsule in order to obtain a desired drug release profile.

In this paper, the modal analysis model, made up by a linear combination of complex exponential functions, is considered. Padè approximants to the Z-transform of a noisy sample are then considered, and the asymptotic locus of their poles is studied. It turns out that this locus is strongly related to the complex exponentials of the model. By exploiting these properties, powerful methods for estimating the model parameters can be devised, which have both denoising and super-resolution capabilities.

Background: In a systems biology perspective, protein-protein interactions (PPI) are encoded in machine-readable formats to avoid issues encountered in their retrieval for the reconstruction of comprehensive interaction maps and biological pathways. However, the information stored in electronic formats currently used doesn't allow a valid automatic reconstruction of biological pathways.Results: We propose a logical model of PPI that takes into account the "state" of proteins before and after the interaction.

We develop a lumped parameter model to describe and predict the mass release of (absorption from) an arbitrary shaped body of any dimension in a large environment. Through the one-to-one analogy between diffusion-dominated mass transfer systems and electrical circuits we provide exact solutions in terms of averaged concentrations and mass released. An estimate of the equivalent resistance and of the release time is also given, and shown to be inversely proportional to the diffusivity.

A suspension of nanoparticles with very low volume fraction is found to assemble into a macroscopic cellular phase that is composed of particle-rich walls and particle-free voids under the collective influence of AC and DC voltages. Systematic study of this phase transition shows that it was the result of electrophoretic assembly into a two-dimensional configuration followed by spinodal decomposition into particle-rich walls and particle-poor cells mediated principally by electrohydrodynamic flow.

This paper presents an innovative approach to maximally disconnect a given network. More specifically, this work introduces the concept of a Critical Disruption Path, a path between a source and a destination vertex whose deletion minimizes the cardinality of the largest remaining connected component. Network interdiction models seek to optimally disrupt network operations. Existing interdiction models disrupt network operations by removing vertices or edges. We introduce the first problem and formulation that optimally fragments a network via interdicting a path.