Artificial Intelligence in Evaluation of Permanent Impairment: New Operational Frontiers.

Artificial intelligence (AI) and machine learning (ML) span multiple disciplines, including the medico-legal sciences, also with reference to the concept of disease and disability. In this context, the International Classification of Diseases, Injuries, and Causes of Death (ICD) is a standard for the classification of diseases and related problems developed by the World Health Organization (WHO), and it represents a valid tool for statistical and epidemiological studies. Indeed, the International Classification of Functioning, Disability, and Health (ICF) is outlined as a classification that aims to describe the state of health of people in relation to their existential spheres (social, family, work).

Machine Learning Scoring Functions for Drug Discovery from Experimental and Computer-Generated Protein-Ligand Structures: Towards Per-Target Scoring Functions.

In recent years, machine learning has been proposed as a promising strategy to build accurate scoring functions for computational docking finalized to numerically empowered drug discovery. However, the latest studies have suggested that over-optimistic results had been reported due to the correlations present in the experimental databases used for training and testing. Here, we investigate the performance of an artificial neural network in binding affinity predictions, comparing results obtained using both experimental protein-ligand structures as well as larger sets of computer-generated structures created using commercial software.

Chester Supersolid of Spatially Indirect Excitons in Double-Layer Semiconductor Heterostructures.

A supersolid, a counterintuitive quantum state in which a rigid lattice of particles flows without resistance, has to date not been unambiguously realized. Here we reveal a supersolid ground state of excitons in a double-layer semiconductor heterostructure over a wide range of layer separations outside the focus of recent experiments. This supersolid conforms to the original Chester supersolid with one exciton per supersolid site, as distinct from the alternative version reported in cold-atom systems of a periodic density modulation or clustering of the superfluid.

Complex Phase-Fluctuation Effects Correlated with Granularity in Superconducting NbN Nanofilms.

Superconducting nanofilms are tunable systems that can host a 3D-2D dimensional crossover leading to the Berezinskii-Kosterlitz-Thouless (BKT) superconducting transition approaching the 2D regime. Reducing the dimensionality further, from 2D to quasi-1D superconducting nanostructures with disorder, can generate quantum and thermal phase slips (PS) of the order parameter. Both BKT and PS are complex phase-fluctuation phenomena of difficult experiments.

Causes and Consequences of Ordering and Dynamic Phases of Confined Vortex Rows in Superconducting Nanostripes.

Understanding the behaviour of vortices under nanoscale confinement in superconducting circuits is important for the development of superconducting electronics and quantum technologies. Using numerical simulations based on the Ginzburg-Landau theory for non-homogeneous superconductivity in the presence of magnetic fields, we detail how lateral confinement organises vortices in a long superconducting nanostripe, presenting a phase diagram of vortex configurations as a function of the stripe width and magnetic field. We discuss why the average vortex density is reduced and reveal that confinement influences vortex dynamics in the dissipative regime under sourced electrical current, mapping out transitions between asynchronous and synchronous vortex rows crossing the nanostripe as the current is varied.

Sars-Cov2 world pandemic recurrent waves controlled by variants evolution and vaccination campaign.

While understanding the time evolution of Covid-19 pandemic is needed to plan economics and tune sanitary policies, a quantitative information of the recurrent epidemic waves is elusive. This work describes a statistical physics study of the subsequent waves in the epidemic spreading of Covid-19 and disclose the frequency components of the epidemic waves pattern over two years in United States, United Kingdom and Japan. These countries have been taken as representative cases of different containment policies such as "Mitigation" (USA and UK) and "Zero Covid" (Japan) policies.

Electronic Transport Mechanisms Correlated to Structural Properties of a Reduced Graphene Oxide Sponge.

We report morpho-structural properties and charge conduction mechanisms of a foamy "graphene sponge", having a density as low as ≈0.07 kg/m3 and a carbon to oxygen ratio C:O ≃ 13:1. The spongy texture analysed by scanning electron microscopy is made of irregularly-shaped millimetres-sized small flakes, containing small crystallites with a typical size of ≃16.

Metastable states in plateaus and multi-wave epidemic dynamics of Covid-19 spreading in Italy.

The control of Covid 19 epidemics by public health policy in Italy during the first and the second epidemic waves has been driven by using reproductive number R(t) to identify the supercritical (percolative), the subcritical (arrested), separated by the critical regime. Here we show that to quantify the Covid-19 spreading rate with containment measures there is a need of a 3D expanded parameter space phase diagram built by the combination of R(t) and doubling time T(t). In this space we identify the Covid-19 dynamics in Italy and its administrative Regions.

Epidemic spreading in an expanded parameter space: the supercritical scaling laws and subcritical metastable phases.

While the mathematical laws of uncontrolled epidemic spreading are well known, the statistical physics of coronavirus epidemics with containment measures is currently lacking. The modelling of available data of the first wave of the Covid-19 pandemic in 2020 over 230 days, in different countries representative of different containment policies is relevant to quantify the efficiency of these policies to face the containment of any successive wave. At this aim we have built a 3D phase diagram tracking the simultaneous evolution and the interplay of the doubling time,, and the reproductive number,measured using the methodological definition used by the Robert Koch Institute.

Efficiency of COVID-19 mobile contact tracing containment by measuring time-dependent doubling time.

The COVID-19 epidemic of the novel coronavirus (severe acute respiratory syndrome SARS-CoV-2) has spread around the world. While different containment policies using non-pharmaceutical interventions have been applied, their efficiencies are not known quantitatively. We show that the doubling time T (t) with the success s factor, the characteristic time of the exponential growth of T (t) in the arrested regime, is a reliable tool for early predictions of epidemic spread time evolution and provides a quantitative measure of the success of different containment measures.

Fiber-Sample Distance, An Important Parameter To Be Considered in Headspace Solid-Phase Microextraction Applications.

To define and control the parameters which impact headspace solid-phase microextraction (HS-SPME), it is important to reach the highest level of reproducibility. The present study aims to assess, for the first time, the effect of fiber-sample distance during HS-SPME in pre-equilibrium conditions. Analyses were primarily performed on mixtures of standard volatiles compounds (alkanes, alcohols, organic acids) designed in our lab and then on various food matrices (wine, chicken, cheese, tea), repeating already published experiments.

Evidence from Quantum Monte Carlo Simulations of Large-Gap Superfluidity and BCS-BEC Crossover in Double Electron-Hole Layers.

We report quantum Monte Carlo evidence of the existence of large gap superfluidity in electron-hole double layers over wide density ranges. The superfluid parameters evolve from normal state to BEC with decreasing density, with the BCS state restricted to a tiny range of densities due to the strong screening of Coulomb interactions, which causes the gap to rapidly become large near the onset of superfluidity. The superfluid properties exhibit similarities to ultracold fermions and iron-based superconductors, suggesting an underlying universal behavior of BCS-BEC crossovers in pairing systems.

Dimensional crossover and incipient quantum size effects in superconducting niobium nanofilms.

Superconducting and normal state properties of Niobium nanofilms have been systematically investigated as a function of film thickness, on different substrates. The width of the superconducting-to-normal transition for all films is remarkably narrow, confirming their high quality. The superconducting critical current density exhibits a pronounced maximum for thickness around 25 nm, marking the 3D-to-2D crossover.