Accumulating evidence suggests that pregnancy does not protect women from mental illness. The aim of this study was to assess the prevalence, sociodemographic correlates, and the risks factors for perinatal depression and anxiety. Five hundred ninety women between 28th and the 32nd gestational weeks were recruited and submitted to a sociodemographic, obstetric, and psychological interview. The Edinburgh Postnatal Depression Scale (EPDS) and the state-trait anxiety inventory (STAI-Y) were also administered in antenatal period and 3 months postnatally. The Structured Clinical Interview for DSM-IV (SCID-I) was used to diagnose mood and anxiety disorders. Three months after delivery, EPDS was administered by telephone interview. Women with an EPDS score ≥10 were 129 in antenatal period (21.9%) and 78 in postnatal period (13.2%). During pregnancy 121 women (20.5%) were positive for STAI-Y state and 149 women (25.3%) for STAI-Y trait. The most important risk factors for antenatal depression are: foreign nationality, conflictual relationship with family and partner, and lifetime psychiatric disorders. The principal risk factors for postnatal depression are: psychiatric disorders during pregnancy and artificial reproductive techniques. Psychiatric disorders, during and preceding pregnancy, are the strongest risk factors for antenatal state and trait anxiety. Antenatal depressive and anxiety symptoms appear to be as common as postnatal symptoms. These results provide clinical direction suggesting that early identification and treatment of perinatal affective disorders is particularly relevant to avoid more serious consequences for mothers and child.

a b s t r a c tThe modelling and the reduction of wear due to wheel-rail interaction is a fundamental aspect in the railway field, mainly correlated to running stability and safety, maintenance interventions and costs. In this work the authors present two innovative wheel profiles, specifically designed with the aim of improving the wear and stability behaviour of the standard ORE S1002 wheel profile matched with the UIC60 rail profile canted at 1/20 rad, which represents the wheel-rail combination adopted in Italian railway line.The two wheel profiles, conventionally named CD1 and DR2, have been developed by the authors in collaboration with Trenitalia S.p.A. The CD1 wheel profile has been designed with the purpose of spreading the contact points in the flange zone on a larger area in order to reduce wear phenomena and having a constant equivalent conicity for small lateral displacements of the wheelset with respect to the centred position in the track. The DR2 wheel profile is instead designed in order to guarantee the same kinematic characteristics of the matching formed by ORE S1002 wheel profile and UIC60 rail profile with laying angle a p equal to 1/40 rad, widely common in European railways and characterized by good performances in both wear and kinematic behaviour.Wheel profiles evolution has been calculated through a wear model developed and validated by the authors in previous works with experimental data relative to the Italian Aosta-Pre Saint Didier railway line. This model comprises two mutually interactive units: a vehicle model for the dynamic simulations and a model for the wear assessment. The whole model is based on a discrete process: each discrete step consists in one dynamic simulation and one profile update by means of the wear model while, within the discrete step, the profiles are supposed to be constant. The choice of an appropriate step is crucial in terms of precision and computational effort: the particular strategy adopted in the current work has been chosen for its capacity in representing the non-linear wear evolution and for the low computational time required.In the present research the investigated trainset is the passenger vehicle ALSTOM ALn 501 ''Minuetto'', which is usually equipped with the standard ORE S1002 wheel profile and UIC60 rail profile canted at 1/20 rad in Italian railways. The entire model has been simulated on a virtual track specifically developed to represent a statistical description of the whole Italian line. The data necessary to build the virtual track and the vehicle model were provided by Trenitalia S.p.A. and Rete Ferroviaria Italiana (RFI). Both the innovative wheel profiles developed in this research activity for the UIC60 rail with cant 1/20 rad have proven to work fine in terms of resistance to wear if compared with the old ORE S1002 wheel profile.

a b s t r a c tIn railway applications, the estimation of wear at the wheel-rail interface is an important field of study, mainly correlated to the planning of maintenance interventions, vehicle stability and the possibility of carrying out specific strategies for the wheel profile optimization. In this work the authors present a model for the evaluation of wheel and rail profile evolution due to wear specifically developed for complex railway networks. The model layout is made up of two mutually interactive but separate units: a vehicle model (composed of the multibody model and the global contact model) for the dynamical analysis and a model for the wear evaluation (composed of the local contact model, the wear evaluation procedure and the profile update strategy).The authors propose a statistical approach for the railway track description to study complex railway lines in order to achieve general significant accuracy results in a reasonable time: in fact the exhaustive simulation of the vehicle dynamics and of wear evolution on all the railway network turn out to be too expensive in terms of computational effort for each practical purpose.The wear model has been validated in collaboration with Trenitalia S.P.A and RFI, which have provided the technical documentation and the experimental data relating to some tests performed on a scenario that exhibits serious problems in terms of wear: the vehicle ALn 501 "Minuetto" circulating on the Aosta-Pre Saint Didier Italian line.

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The prediction of wheel and rail wear is a fundamental issue in the railway field, both in terms of vehicle stability and in terms of economic costs (planning of maintenance interventions). In particular the need of an accurate wear model arises from the interest of Trenitalia S.p.A. and Rete Ferroviara Italiana in designing new wheel and rail profiles and new bogie architectures optimized from the wear viewpoint with the aim of improving the wear and stability behavior of the standard ORE S1002 wheel profile matched with the UIC60 rail profile canted at 1/20 rad (which represents the wheel-rail combination adopted by the Italian railway line). In this work the authors present a wear model specifically developed for the evaluation of the wheel and rail profile evolution, the layout of which is made up of two mutually interactive but separate units: a vehicle model for the dynamical analysis and a model for the wear evaluation. Subsequently the new model has been compared with the wear evaluation procedure implemented in Simpack, a widely tested and validated multibody software for the analysis of the railway vehicle dynamics; the comparison aims both to evaluate the model performance (in terms of accuracy and efficiency) and to further validate the wear model (just tested, as regards the wheel wear prediction, in previous works related to the critical Aosta-Pre Saint Didier line).The comparison has been carried out considering a benchmark train composed by a locomotive (E.464) and a passenger vehicle (Vivalto) provided by Trenitalia while the simulations have been performed on a mean Italian railway line (obtained by means of a sta-