We study spreading dynamics of a reaction diffusion process in a special class of heterogeneous graphs with Poissonian degree distribution and composed of both local and long range links. The behavior of the spreading dynamics on such networks are investigated by relating them to the topological features of graphs.

[object Object]Metals, extensively used in technology applications as well as in art metal works, have a chemical affinity for oxygen, water, sulphur and are particularly susceptible to electrochemical processes due to the environment. For this reason the monitoring of the effect of environmental conditions (temperature, humidity, pollutant concentration) on their mechanical and physical properties are considered a primary necessity for metal conservation and preservation.

We propose a model of a density-dependent compressible-incompressible fluid, which is intended as a simplified version of models based on mixture theory as, for instance, those arising in the study of biofilms, tumor growth and vasculogenesis. Though our model is, in some sense, close to the density-dependent incompressible Euler equations, it presents some differences that require a different approach from an analytical point of view. In this paper, we establish a result of local existence and uniqueness of solutions in Sobolev spaces to our model, using the Leray projector.

A comprehensive approach to Sobolev-type embeddings, involving arbitrary rearrangement-invariant norms on the entire Euclidean space R^n, is offered. In particular, the optimal target space in any such embedding is exhibited. Crucial in our analysis is a new reduction principle for the relevant embeddings, showing their equivalence to a couple of considerably simpler one-dimensional inequalities.

Effectively dealing with invasive species is a pervasive problem in environmental management. The damages, and associated costs, that stem from invasive species are well known, as is the benefit from their removal. We investigate problems where optimal control theory has been implemented, and we show that these problems can easily become hypersensitive, making their numerical solutions unstable. We show that transforming these problems from state-adjoint systems to state-control systems can provide useful insights into the system dynamics and simplify the numerics.

Under the current deluge of omics, module networks distinctively emerge as methods capable of not only identifying inherently coherent groups (modules), thus reducing dimensionality, but also hypothesizing cause-effect relationships between modules and their regulators. Module networks were first designed in the transcriptomic era and further exploited in the multi-omic context to assess (for example) miRNA regulation of gene expression.

Motivation: Cells derived by cellular engineering, i.e. differentiation of induced pluripotent stem cells and direct lineage reprogramming, carry a tremendous potential for medical applications and in particular for regenerative therapies. These approaches consist in the definition of lineage-specific experimental protocols that, by manipulation of a limited number of biological cues-niche mimicking factors, (in) activation of transcription factors, to name a few-enforce the final expression of cell-specific (marker) molecules.

Despite a long record of intense effort, the basic mechanisms by which dissipation emerges from the microscopic dynamics of a relativistic fluid still elude complete understanding. In particular, several details must still be finalized in the pathway from kinetic theory to hydrodynamics mainly in the derivation of the values of the transport coefficients. In this paper, we approach the problem by matching data from lattice-kinetic simulations with analytical predictions.