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). This paper lays the foundations for proposing an operating model for the use of AI in the assessment of impairments with the aim of making the information system as homogeneous as possible, starting from the main coding systems of the reference pathologies and functional damages. Providing a scientific basis for the understanding and study of health, as well as establishing a common language for the assessment of disability in its various meanings through AI systems, will allow for the improvement and standardization of communication between the various expert users.

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. Interestingly, similar performances are obtained on both databases. We find a noticeable performance suppression when moving from random horizontal tests to vertical tests performed on target proteins not included in the training data. The possibility to train the network on relatively easily created computer-generated databases leads us to explore per-target scoring functions, trained and tested ad-hoc on complexes including only one target protein. Encouraging results are obtained, depending on the type of protein being addressed.

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. We provide the phase diagram augmented by the supersolid. This new phase appears at layer separations much smaller than the predicted exciton normal solid, and it persists up to a solid-solid transition where the quantum phase coherence collapses. The ranges of layer separations and exciton densities in our phase diagram are well within reach of the current experimental capabilities.

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. We characterized superconducting NbN nanofilms thinner than 15 nm, on different substrates, by temperature-dependent resistivity and current-voltage (I-V) characteristics. Our measurements evidence clear features related to the emergence of BKT transition and PS events. The contemporary observation in the same system of BKT transition and PS events, and their tunable evolution in temperature and thickness was explained as due to the nano-conducting paths forming in a granular NbN system. In one of the investigated samples, we were able to trace and characterize the continuous evolution in temperature from quantum to thermal PS. Our analysis established that the detected complex phase phenomena are strongly related to the interplay between the typical size of the nano-conductive paths and the superconducting coherence length.

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. Synchronous crossings are of particular interest, since they cause single-mode modulations in the voltage drop along the stripe in a high (typically GHz to THz) frequency range.

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. The supercritical phases in spreading have been identified by intervals with RIC-index > 0. We have used the wavelet transform of infection and fatality waves to get the spectral analysis showing a dominant component around 130 days. Data of the world dynamic clearly indicates also the crossover to a different phase due to the enforcement of vaccination campaign. In Japan and United Kingdom, we observed the emergence in the infection waves of a long period component (~ 170 days) during vaccination campaign. These results indicate slowing down of the epidemic spreading dynamics due to the vaccination campaign. Finally, we find an intrinsic difference between infection and fatality waves pointing to a non-trivial variation of the lethality due to different gene variants.

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 ≃16.3 nm. A defect density as high as ≃2.6 × 1011 cm-2 has been estimated by the Raman intensity of D and G peaks, dominating the spectrum from room temperature down to ≃153 K. Despite the high C:O ratio, the graphene sponge exhibits an insulating electrical behavior, with a raise of the resistance value at ≃6 K up to 5 orders of magnitude with respect to the room temperature value. A variable range hopping (VRH) conduction, with a strong 2D character, dominates the charge carriers transport, from 300 K down to 20 K. At T < 20 K, graphene sponge resistance tends to saturate, suggesting a temperature-independent quantum tunnelling. The 2D-VRH conduction originates from structural disorder and is consistent with hopping of charge carriers between sp2 defects in the plane, where sp3 clusters related to oxygen functional groups act as potential barriers.

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 Rt(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 Rt(t) and doubling time Td(t). In this space we identify the Covid-19 dynamics in Italy and its administrative Regions. The supercritical regime is mathematically characterized by (i) the power law of Td vs. [Rt(t) - 1] and (ii) the exponential behaviour of Td vs. time, either in the first and in the second wave. The novel 3D phase diagram shows clearly metastable states appearing before and after the second wave critical regime. for loosening quarantine and tracing of actives cases. The metastable states are precursors of the abrupt onset of a next nascent wave supercritical regime. This dynamic description allows epidemics predictions needed by policymakers interested to point to the target "zero infections" with the elimination of SARS-CoV-2, using the Finding mobile Tracing policy joint with vaccination-campaign, in order to avoid the emergence of recurrent new variants of SARS-CoV-2 virus, accompined by recurrent long lockdowns, with large economical losses, and large number of fatalities.

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,Td, and the reproductive number,Rtmeasured using the methodological definition used by the Robert Koch Institute. In this expanded parameter space three different main phases,supercritical,criticalandsubcriticalare identified. Moreover, we have found that in thesupercriticalregime withRt> 1 the doubling time is smaller than 40 days. In this phase we have established the power law relation betweenTdand (Rt- 1)-νwith the exponentνdepending on the definition of reproductive number. In thesubcriticalregime whereRt< 1 andTd> 100 days, we have identified arrested metastable phases whereTdis nearly constant.

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 d(t) with the success s factor, the characteristic time of the exponential growth of T d(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. The efficiency of the containment policy lockdown case finding mobile tracing (LFT) using mandatory mobile contact tracing is much higher than that of the lockdown stop and go policy proposed by the Imperial College team in London. A very low s factor was reached by the LFT policy, giving the shortest time width of the positive case curve and the lowest number of fatalities. The LFT policy was able to reduce the number of fatalities by a factor of 100 in the first 100 d of the COVID-19 epidemic, reduce the time width of the COVID-19 pandemic curve by a factor 2.5, and rapidly stop new outbreaks and thereby avoid a second wave to date.

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. Extractions were performed varying fiber penetration depths (10-60 mm) at different times (10-60 min) and temperatures of extraction (30-80 °C). The study revealed that variation of the distance between the fiber and the sample into the vial clearly impacts the results obtained during HS-SPME when conditions are such that no equilibrium is reached in HS. For example, in wine analysis, the percentage of octanoic acid at 80 °C was higher at 40 mm (7.5 ± 0.2%) than that at 20 mm (4.4 ± 0.3%). Moreover, regardless of the extraction temperature, the lower the time of extraction, the stronger the dependence on the fiber-sample distance. Indeed, at 60 °C, the obtained response factors for octadecane at 20 and 40 mm of fiber penetration were 21.8 and 44.5, respectively, after 10 min of extraction, 54.1 and 71.0 after 30 min, and 79.4 and 82.4 after 60 min of extraction. The analyses have been here corroborated by a theoretical model based on the diffusion equation. Therefore, to improve the method robustness during HS-SPME studies, we suggest specifying the fiber penetration depth or the fiber-sample distance with the other parameters of extraction.

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. The magnetic penetration depth shows a sizeable enhancement for the thinnest films. Additional amplification effects of the superconducting properties have been obtained with sapphire substrates or squeezing the lateral size of the nanofilms. For thickness close to 20 nm we measured a doubled perpendicular critical magnetic field compared to its large thickness value, indicating shortening of the correlation length and the formation of small Cooper pairs. Our data analysis indicates an exciting interplay between quantum-size and proximity effects together with strong-coupling effects and the importance of disorder in the thinnest films, placing these nanofilms close to the BCS-BEC crossover regime.