In this talk, first, we review the concept of gene-environmental interaction on the light of emerging results and the use of modern high-throughput technologies; we illustrate its impact on the understanding of complex human diseases. Then, we provide an overview of the methods available to process NGS data with particular emphasis to the detection of genomic variants, the analysis of epigenomic and transcriptional data produced by modern sequencers. Finally, we discuss how multiomic data can be used to improve our way of studying complex diseases and can provide novel research perspectives.

Background: The DNA base composition is well known to be highly variable among organisms. Bio-physic studies on the effect of the GC increments on the DNA structure have shown that GC-richer DNA sequences are more bendable. The result was the keystone of the hypothesis proposing the metabolic rate as the major force driving the GC content variability, since an increased resistance to the torsion stress is mainly required during the transcription process to avoid DNA breakage.

Numerical optimisation of a ship hull requires, like every shape design optimisation problem, the definition of a parametric expression of the object to be deformed. In this phase, some decisions are taken regarding the shape variability and the portion of the hull to be modified: the parameterisation of the hull is problem-dependent, with implications from the performances to be optimised (objective functions), and the right choice is not easy.

On the occasion of the 140th anniversary of the birth of the famous Italian mathematician Beppo Levi (1875-1961), we publish an interview with his daughter Emilia. We also recall his brother Eugenio Elia Levi, a well-known and brilliant mathematician whose life was cut short at the front during World War I. A brief outline of Beppo Levi's life is followed by an introduction to a letter that he wrote to the periodical Israel in 1919, in part regarding the foundation of the state of Israel. Finally, we publish an English translation of the letter in its entirety.

We consider finite difference schemes which approximate one-dimensional dissipative hyperbolic systems. Using precise analytical time-decay estimates of the local truncation error, we show that it is possible to introduce some suitable modification in standard upwinding schemes to design schemes which are increasingly accurate for large times when approximating small perturbations of stable asymptotic states, respectively, around stationary solutions and in the diffusion (Chapman-Enskog) limit.

We study a nonlinear boundary value problem involving a nonlocal (integral) operator in the coefficients of the unknown function. Provided sufficient conditions for the existence and uniqueness of the solution, for its approximation, we propose a numerical method consisting of a classical discretization of the problem and an algorithm to solve the resulting nonlocal and nonlinear algebraic system by means of some iterative procedures. The second order of convergence is assured by different sufficient conditions, which can be alternatively used in dependence on the given data.

For the effective operation of sonar systems mounted inside the bulb of fast ships, it is important to reduce all the possible noise and vibration sources that radiate noise and interfere with sonar sensor response. In particular, pressure fluctuations induced by turbulent boundary layers on the sonar dome surface represent the major source of self-noise for on-board sensors. Reliable calculations of structural vibrations and noise radiated inside the dome require valid statistical descriptions of wall pressure fluctuations beneath the turbulent boundary layer.

An algorithm for computing the antitriangular factorization of symmetric matrices, relying only on orthogonal transformations, was recently proposed. The computed antitriangular form straightforwardly reveals the inertia of the matrix. A block version of the latter algorithm was described in a different paper, where it was noticed that the algorithm sometimes fails to compute the correct inertia of the matrix.In this paper we analyze a possible cause of the failure of detecting the inertia and propose a procedure to recover it.

International initiatives such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) are collecting multiple datasets at different genome-scales with the aim of identifying novel cancer biomarkers and predicting survival of patients. To analyze such data, several statistical methods have been applied, among them Cox regression models. Although these models provide a good statistical framework to analyze omic data, there is still a lack of studies that illustrate advantages and drawbacks in integrating biological information and selecting groups of biomarkers.