Exploring the transverse spin structure of the nucleon

We discuss our present understanding of the transverse spin structure of the nucleon and of related properties originating from parton transverse motion. Starting from the transversity distribution and the ways to access it, we then address the role played by spin and transverse momentum dependent (TMD) distributions in azimuthal and transverse single spin asymmetries. The latest extractions of the Sivers, Collins and transversity functions are also presented.Comment: 8 pages, 6 ps figures, uses aipproc.cls. Invited talk at "6th International Conference on Perspectives in Hadronic Physics (Hadron 08)", Trieste, Italy, 12-18 May 2008. Submitted to AIP Conf.Pro

A Measurement System for the Characterization of Wireless Charging Stations for Electric Vehicles

This paper describes a new traceable measurement system, designed for the characterization of inductive charging stations for electric vehicles. The measuring system is able to measure on-site the performance and efficiency of the charging station and converters. The basic relative uncertainty is 10-3, but actual measurement conditions could worsen this figure. The measurement system aims at accurately measure the power at the batteries and the power transferred from the ground to the on board resonant circuit and makes possible a benchmarking between station measuring systems. Finally, it allows the characterization of the magnetic emissions by correlating them with the electric current in the coils

A new tool for the evaluation of the rehabilitation outcomes in older persons. a machine learning model to predict functional status 1 year ahead

Purpose To date, the assessment of disability in older people is obtained utilizing a Comprehensive Geriatric Assessment (CGA). However, it is often difficult to understand which areas of CGA are most predictive of the disability. The aim of this study is to evaluate the possibility to early predict—1year ahead—the disability level of a patient using machine leaning models. Methods Community-dwelling older people were enrolled in this study. CGA was made at baseline and at 1year follow-up. After collecting input/independent variables (i.e., age, gender, schooling followed, body mass index, information on smoking, polypharmacy, functional status, cognitive performance, depression, nutritional status), we performed two distinct Support Vector Machine models (SVMs) able to predict functional status 1year ahead. To validate the choice of the model, the results achieved with the SVMs were compared with the output produced by simple linear regression models. Results 218 patients (mean age = 78.01; SD = 7.85; male = 39%) were recruited. The combination of the two SVMs is able to achieve a higher prediction accuracy (exceeding 80% instances correctly classified vs 67% instances correctly classified by the combination of the two linear regression models). Furthermore, SVMs are able to classify both the three categories, self sufficiently, disability risk and disability, while linear regression model separates the population only in two groups (self-sufficiency and disability) without identifying the intermediate category (disability risk) which turns out to be the most critical one. Conclusions The development of such a model can contribute to the early detection of patients at risk of self-sufficiency loss

The propagation of ULF waves from the Earth's foreshock region to ground: the case study of 15 February 2009

A long-duration upstream ultralow frequency (ULF) wave event was detected on 15 February 2009 by Cluster satellites, close to the bow shock nose. A clear wave activity was identified when the interplanetary magnetic field orientation was favorable to the local generation. We examined the wave properties in both the solar wind and the spacecraft frame during a selected time interval and found that foreshock waves were essentially Alfven waves propagating at a small angle with respect to the interplanetary magnetic field. A comparison of Cluster observations with those on the ground, in the polar cap and at low-latitude stations, confirms the results of previous studies, indicating that upstream waves can reach different ground regions along different paths

Assessment of heat transfer and Mach number effects on high-speed turbulent boundary layers

High-speed vehicles experience a highly challenging environment in which the free-stream Mach number and surface temperature greatly influence aerodynamic drag and heat transfer. The interplay of these two parameters strongly affects the near-wall dynamics of high-speed turbulent boundary layers in a non-trivial way, breaking similarity arguments on velocity and temperature fields, typically derived for adiabatic cases. In this work, we present direct numerical simulations of flat-plate zero-pressure-gradient turbulent boundary layers spanning three free-stream Mach numbers [2,4,6] and four wall temperature conditions (from adiabatic to very cold walls), emphasising the choice of the diabatic parameter $\mathit{\Theta}$ (Zhang, Bi, Hussain & She, J. Fluid Mech., vol. 739, pp. 392-420) to recover a similar flow organisation at different Mach numbers. We link qualitative observations on flow patterns to first- and second-order statistics to explain the strong decoupling of temperature-velocity fluctuations that occurs at reduced wall temperatures and high Mach numbers. For these cases, we find that the mean temperature gradient in the near-wall region can reach such a strong intensity that it promotes the formation of a secondary peak of thermal production in the viscous sublayer, which is in direct contrast with the monotonic behaviour of adiabatic profiles. We propose different physical mechanisms induced by wall-cooling and compressibility that result in apparently similar flow features, such as a higher peak in the streamwise velocity turbulence intensity, and distinct ones, such as the separation of turbulent scales

Fear and anxiety related to COVID-19 pandemic may predispose to perinatal depression in Italy

The COVID-19 pandemic situation significantly affected the mental health of the general and clinical population. However, few studies investigated which COVID-19-related psychopathological determinants may predispose to perinatal depression. We evaluated the impact of COVID-19 related anxiety and fear on perinatal depression in Italy. We retrospectively screened 184 perinatal outpatients afferent to Perinatal Mental Health outpatient service, during March 2020-March 2021, by administering the Edinburgh Postnatal Depression Scale (EPDS), the Fear of COVID-19 (FCV-19-S) and the Coronavirus Anxiety Scale (CAS). Among these, 85 patients agreed to be recruited in the present study. The mean EPDS score was 9.0, experiencing a clinically relevant perinatal depression in 45.7% of the sample. The mean FCV-19-S score was 15.0 and CAS was 1.7. Linear regression analyses demonstrated that FCV-19-S and CAS scores statistically significantly predicted EPDS total scores. A positive significant correlation was reported between FCV-19-S and EPDS and between CAS and EPDS. During the COVID-19 pandemic, women in their perinatal period, independently of previous psychiatric history, experienced increased levels of anxiety, fear and psychological distress, due to subsequent isolation, quarantine, lockdown and deprivation of their normal social support. Further preventive and screening strategies should be implemented in order to early identify at-risk pregnant and puerperal women during the COVID-19 pandemic

Aerosol Optical Depth of the Main Aerosol Species over Italian Cities Based on the NASA/MERRA-2 Model Reanalysis

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) provides data at 0.5° × 0.625° resolution covering a period from 1 January 1980 to the present. Natural and anthropogenic aerosols are simulated in MERRA-2, considering the Goddard chemistry, aerosol, radiation, and transport model. This model simulates the sources, sinks, and chemistry of mixed aerosol tracers: dust, sea salt, hydrophobic and hydrophilic black carbon and organic carbon, and sulfate. MERRA-2 aerosol reanalysis is a pioneering tool for investigating air quality issues, noteworthy for its global coverage and its distinction of aerosol speciation expressed in the form of aerosol optical depth (AOD). The aim of this work was to use the MERRA-2 reanalysis to study urban air pollution at a national scale by analyzing the AOD. AOD trends were evaluated for a 30-year period (1987–2017) over five Italian cities (Milan, Rome, Cagliari, Taranto, and Palermo) in order to investigate the impacts of urbanization, industrialization, air quality regulations, and regional transport on urban aerosol load. AOD evolution predicted by the MERRA-2 model in the period 2002–2017 showed a generalized decreasing trend over the selected cities. The anthropogenic signature on total AOD was between 50% and 80%, with the largest contribution deriving from sulfate

DEFINITION OF THE FLEXIBLE AIRCRAFT LONGITUDINAL MODEL FOR A PRELIMINARY CONTROL DESIGN

Developing control system of high aspect ratio aircraft can be challenging due to flexibility involved in the control loop design. A model based approach can be straightforward to tune the control system parameters and, to this aim, a reliable aircraft flexible model is necessary. This paper aims to present the approach followed to design the longitudinal control strategy considering the aircraft simulator in the loop. The elastic modes are calculated from the lumped mass geometrical model and an aerodynamic properties from a reference aircraft. The approach and the model validation have been done in partnership with Leonardo Aircraft, as a thesis topic. Beginning with verification of the trim conditions, the flexible dynamic modes are compared to the rigid ones in order to highlight the relevant changes in the aircraft modes. A preliminary design of the longitudinal control strategy is herein proposed to achieve the dynamic response objectives