Penalized wavelet nonparametric univariate logistic regression for irregular spaced data

This paper concerns the study of a non-smooth logistic regression function. The focus is on a high-dimensional binary response case by penalizing the decomposition of the unknown logit regression function on a wavelet basis of functions evaluated on the sampling design. Sample sizes are arbitrary (not necessarily dyadic) and we consider general designs. We study separable wavelet estimators, exploiting sparsity of wavelet decompositions for signals belonging to homogeneous Besov spaces, and using efficient iterative proximal gradient descent algorithms.

A Fast Retrieval Model for Synergistic Inversion of Nadir / Zenith Spectral Radiance Measurements

Starting from 2019, the Italian Space Agency (ASI) is supporting dedicated projects for the development of new methods, tools and competences for the interpretation and the exploitation of the future measurements of the FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) experiment. FORUM will be the ninth Earth Explorer mission of the European Space Agency, scheduled for launch on a polar orbiting satellite in 2027.

Efficient GPU parallelization of adaptive mesh refinement technique for high-order compressible solver with immersed boundary

A new, highly parallelized, adaptive mesh refinement (AMR) library, equipped with an accurate immersed boundary (IB) method for solving the compressible Navier-Stokes system is presented. The library, named ADAM, is designed to efficiently exploit modern exascale GPU-accelerated supercomputers and it is implemented with a highly modular structure in order to make easy to leverage it for a wide range of CFD applications.

Controlling release from encapsulated drug-loaded devices: insights from modeling the dissolution front propagation

Dissolution of drug from its solid form to a dissolved form is an important consideration in the design and optimization of drug delivery devices, particularly owing to the abundance of emerging compounds that are extremely poorly soluble. When the solid dosage form is encapsulated, for example by the porous walls of an implant, the impact of the encapsulant drug transport properties is a further confounding issue. In such a case, dissolution and diffusion work in tandem to control the release of drug.

Numerical simulation of a compressible gas flow in porous media bioremendiation

In a subsoil bioremediation intervention air or oxygen is injected in the polluted region and then a model for unsaturated porous media it is required, based on the theory of the dynamics of multiphase fluids in porous media. In order to optmize the costs of the intervention it is useful to consider the gas as compressible and this fact introduces nonlinearity in the mathematical model. The physical problem is described by a system of equations and the unknowns are: pollutant; bacteria concentration; oxygen saturation and oxygen pressure.

The Malliavin Stein Method For Normal Random Walks with dependent increments

We derive bounds on the Kolmogorov distance between the dis- tribution of a random functional of a {0, 1}-valued random sequence and the normal distribution. Our approach, which relies on the general framework of stochastic analysis for discrete-time normal martingales, extends existing results obtained for independent Bernoulli (or Rademacher) sequences. In particular, we obtain Kolmogorov distance bounds for the sum of normalized random sequences without any independence assumption.

A network-constrain Weibull AFT model based on proximal gradient descent method

In this work, we propose and explore a novel network-constraint survival methodology considering the Weibull accelerated failure time (AFT) model combined with a penalized likelihood approach for variable selection and estimation [2]. Our estimator explicitly incorporates the correlation patterns among predictors using a double penalty that promotes both sparsity and the grouping effect. In or- der to solve the structured sparse regression problems we present an efficient iterative computational algorithm based on proximal gradient descent method [1].

Comparison of the IASI water deficit index and other vegetation indices: the case study of the intense 2022 drought over the Po Valley

Exploiting the Infrared Atmospheric Sounder Interferometer (IASI) profiling capability for surface parameters, atmospheric temperature, and water vapour we have designed a new Water Deficit Index (wdi) to monitor drought and heatwaves. Because of climate change at a global level, drought is becoming a strong emergency also in countries which never experienced it, such as the Mediterranean mid-latitude area and, in particular, Italy. The last two years strongly affected the northern part of Italy, i.e. the Po Valley, causing high vegetation and soil water stress.