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The interest in Moon exploration has grown substantially in the last few years, appointing the Moon as the first step toward deep space exploration. However, the current state-of-the-art approach for lunar landing does not always reach the required performance levels. This contribution presents a potential implementation of a dedicated lunar communication and navigation service (LCNS) and the performance levels achievable by a representative lunar lander mission that uses the LCNS. The expected positioning precision during the final descent and at the landing site is demonstrated here with a variance-covariance analysis starting from reasonable assumptions about the capabilities of a potential dedicated LCNS system. The performance in positioning and navigation achievable during a generic moon-landing phase significantly outperforms existing ground-based baseline solutions, enabling the stringent requirements from the International Space Exploration Coordination Group (ISECG) to be met. [ABSTRACT FROM AUTHOR]

In the context of Deep Space Exploration as planned by the International Space Exploration Coordination Group (ISECG), the Moon represents a significant step to feed forward what could be done on Mars. Navigation is a key-technology to enable the cislunar and lunar volume discovery. The use of Earth Global Navigation Satellite System (GNSS) signals at Moon altitude has been extensively studied in the past, within and outside the European Space Agency (ESA). Namely, this interest has been reflected in "The Interoperable Global Navigation Satellite Systems Space Service Volume" booklet issued by the International Committee on GNSS (ICG) in 2018 (United Nations - Office for Outer Space Affairs, 2018). However, the main limitation on accurately performing this kind of analysis has always been the limited knowledge of the actual GNSS transmit antenna patterns outside the main lobe, i.e. side-lobes. ESA published the first patterns of GPS satellites using data collected in GIOVE-A (Unwin et al., 2013) and, more recently, the National Aeronautics and Space Administration (NASA) shared very detailed 3D patterns of all GPS Blocks (Donaldson et al., 2018). This allows both ESA and NASA to perform detailed analysis of the expected visibility of GNSS signals at moon altitude. In particular, NASA published visibility results using a GPS-only receiver in a Moon Transfer Orbit (MTO) demonstrating the potential of GPS-based navigation up to the Moon (considering signals above 22 dB-Hz with a 14dBi antenna) (Ashman, 2018). The present paper presents the results of numerical simulations for a Single-Frequency (SF) receiver in the Deep Space Gateway (DSG) orbit, which is an Earth-Moon L2 Halo orbit, using both Galileo and GPS, for which detailed 3D antenna patterns were used. It demonstrates the importance of considering the azimuthal asymmetry of the GNSS antenna patterns and the necessity of using an interoperable Galileo-GPS receiver at such altitudes. Additionally, a comparative analysis between the frequency bands E1/L1 and E5a/L5 is performed to select the one providing the best results. In conclusion, it shows that a high number of satellites is visible at Moon altitude using a receiver with a 14 dBi antenna and a 15 dB-Hz Carrier-to-Noise density ratio acquisition and tracking threshold. Finally, the second part of the paper provides ESA plans for In-Orbit Demonstration (IOD) of the use of GNSS at Moon altitude, covering both CubeSat missions and the DSG. [ABSTRACT FROM AUTHOR]

Background: The World Health Organization (WHO) reported in 2013 that approximately 360 million people have disabling hearing loss, of which 32 million are children. A major consequence of hearing loss is a disability in communication: development of spoken language is often delayed in children with hearing loss, or absent in total deafness. Such children can benefit from a range of interventions such as hearing aids, cochlear implants, and educational and social support. Hearing screening can prevent the most severe consequences of hearing loss, but it is preferable first to consider populations with a high probability of developing hearing impairment. The present study assessed the incidence of hearing impairment through ABR in infants at high risk at Casa Sollievo della Sofferenza Hospital in southern Italy. Material and methods: The paper reports the results of auditory brain stem response (ABR) testing over a period of 3 years on infants born with a history of infantile respiratory distress syndrome (IRDS), otoacoustic emission failure at hearing screening, low birth-weight (<1800 g), family history of deafness, hyperbiluribinemia, premature birth, congenital infection (cytomegalovirus), or craniofacial anomalies. Results: Of 549 infants tested, 469 (85.4%) showed normal hearing, 51 (9.3%) suffered mild hearing impairment, 6 (1.1%) had moderate hearing impairment, 8 (1.5%) had severe hearing loss, and 15 (2.7%) failed to show any response at maximum intensity levels in both ears. For the hearing loss categories, the most important risk factors were found to be (in order of importance): craniofacial malformation, CMV infection, and familial factors. Conclusions: ABR is an important clinical tool in the identification and quantification of hearing impairment. In neonatal screening it is preferable first to consider populations with a high probability of developing hearing losses. [ABSTRACT FROM AUTHOR]

With the renewed interest in the lunar surface exploration, the European Space Agency is supporting, as part of the Moonlight program, the development of a dedicated Lunar Communications and Navigation Service (LCNS) infrastructure. This should enable to achieve real time positioning and autonomous navigation in the cislunar space, including, among others, lunar landing and surface operations. One of the services proposed, as part of the LunaNet framework (NASA, 2022), is called the Lunar Augmented Navigation Service (LANS) and it is based on a GNSS-like concept. However, compared to Earth-based GNSS, the expected number of available satellites in lunar orbit will initially be limited, which triggers the interest of coupling these technologies at the receiver level with other navigation data sources. In the case of surface rovers, use of digital elevation model (DEM) data has shown to be a potential other source of information to support positioning. The purpose of this contribution is to look at the actual navigation performances achievable when using a simple (four satellites constellation) lunar radio navigation constellation combined with a DEM, through a state estimation filter, for different rover dynamic and different DEM accuracy levels. It is shown that a 5 meter real-time horizontal position accuracy can be achieved, for 99.7% of the time, using a precise enough DEM (5 m/pixel) and a 4 satellite-constellation under different rover's dynamic conditions (i.e. velocities). [ABSTRACT FROM AUTHOR]

Aim: Functional Management and Recovery is a standardized Psychoeducational Intervention, derived from "Integro", an effective salutogenic-psychoeducational intervention for people in recovery journey, designed to improve recovery and functioning of individuals with psychotic disorders in Psychiatric Residential Facilities (PRFs). The aim of this study is to evaluate the primary and secondary outcomes of this intervention elaborated specifically for PRFs where evidence based structured interventions seem rare and desirable. Methods: 66 individuals with psychotic disorders were recruited in 9 PRFs dislocated in the North, Center and South Italy and 63 underwent a multicenter follow-up study with a two time-point evaluation (t0, pre-treatment and t1, 6 months;). At each time point, social functioning was assessed as primary outcome by the Personal and Social Performance scale (PSP); furthermore, psychopathological status was assessed by Brief Psychiatric Rating Scale (BPRS), Recovery by Recovery Assessment Scale (RAS), Cognitive Functioning by Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Stress management by Stress-Scale, Cognitive Flexibility by Modified Five-Point Test (M-FPT), Emotional Intelligence by Emotional Intelligence Index (EI-I), the PRF Atmosphere and the Opinion of users about the PFR by an ad hoc questionnaire. The Abilities Knowledge, the Utility and Pleasantness of sessions were measured by an ad hoc list of items. Results: 63 individuals out of 66, 52 (82,5%) affected by schizophrenia and 11 (17,5%) by bipolar I disorder with psychotic symptoms according to DSM-5-TR completed the study. At the end of the study, 43 (68,3%) were male, 57 (90.5%) were single, 5 (7.9%) engaged, 1 (1.6%) married; 45 (71.4%) unemployed. The total scores of PSP, RAS, BPRS, BANS, Stress management, Abilities Knowledge, Utility and Pleasantness of sessions showed a statistically significant improvement at t1 vs. t0. Two sub-scales out of 5 of M-FPT showed a statistically significant improvement. The Emotional Intelligence, the Unit Atmosphere and the Opinion of Users about PFR improved without statistical significance. Six months after the end of the follow-up study 22 individuals of the sample were dismissed with a very high turnover. Conclusions: After a six-month follow-up (a short period of time), these results showed improvement in functioning, the primary outcome, as well as in the following secondary outcome variables: RAS, BPRS, BANS, Stress management, Abilities Knowledge, two sub-scales out of 5 of M-FPT, Utility and Pleasantness of sessions. Overall, a remarkable impact of psychoeducational structured intervention on the key Recovery variables is observed. Further studies are needed to address extent and duration of these improvements. [ABSTRACT FROM AUTHOR]

We present IT-SNOW, a serially complete and multi-year snow reanalysis for Italy (∼ 301 × 10 3 km2) – a transitional continental-to-Mediterranean region where snow plays an important but still poorly constrained societal and ecological role. IT-SNOW provides ∼ 500 m daily maps of snow water equivalent (SWE), snow depth, bulk snow density, and liquid water content for the initial period 1 September 2010–31 August 2021, with future updates envisaged on a regular basis. As the output of an operational chain employed in real-world civil protection applications (S3M Italy), IT-SNOW ingests input data from thousands of automatic weather stations, snow-covered-area maps from Sentinel-2, MODIS (Moderate Resolution Imaging Spectroradiometer), and H SAF products, as well as maps of snow depth from the spatialization of over 350 on-the-ground snow depth sensors. Validation using Sentinel-1-based maps of snow depth and a variety of independent, in situ snow data from three focus regions (Aosta Valley, Lombardy, and Molise) show little to no mean bias compared to the former, and root mean square errors are of the typical order of 30–60 cm and 90–300 mm for in situ, measured snow depth and snow water equivalent, respectively. Estimates of peak SWE by IT-SNOW are also well correlated with annual streamflow at the closure section of 102 basins across Italy (0.87), with ratios between peak water volume in snow and annual streamflow that are in line with expectations for this mixed rain–snow region (22 % on average and 12 % median). Examples of use allowed us to estimate 13.70 ± 4.9 Gm3 of water volume stored in snow across the Italian landscape at peak accumulation, which on average occurs on 4 March ± 10 d. Nearly 52 % of the mean seasonal SWE is accumulated across the Po river basin, followed by the Adige river (23 %), and central Apennines (5 %). IT-SNOW is freely available at 10.5281/zenodo.7034956 and can contribute to better constraining the role of snow for seasonal to annual water resources – a crucial endeavor in a warming and drier climate. [ABSTRACT FROM AUTHOR]

We present IT-SNOW, a serially complete and multi-year snow reanalysis for Italy (300k+ km²) covering a transitional continental-to-Mediterranean region where snow plays an important, but still poorly constrained societal and ecological role. IT-SNOW provides ∼500-m, daily maps of Snow Water Equivalent (SWE), snow depth, bulk-snow density, and liquid water content for the 5 period 01/09/2010 - 31/08/2021, with future updates envisaged on a regular basis. As the output of an operational chain employed in real-world civil-protection applications (S3M Italy), IT-SNOW ingests input data from thousands of automatic weather stations, snow-covered-area maps from Sentinel 2, MODIS, and H-SAF products, and maps of snow depth from the spazialization of 350+ on-the-ground snow-depth sensors. Validation using Sentinel-1-based maps of snow depth and a variety of independent, in-situ snow data from three focus regions (Aosta Valley, Lombardia, and Molise) shows little to none mean bias compared to the former, and Root Mean Square Errors on the order of 30 to 60 cm and 90 to 300 mm for in-situ, measured snow depth and Snow Water Equivalent, respectively. Estimates of peak SWE by IT-SNOW are also well correlated with annual streamflow at the closure section of 102 basins across Italy (0.87), with ratios between peak SWE and annual streamflow that are in line with expectations for this mixed rain-snow region (22% on average). Examples of use allowed us to estimate 13.70 ± 4.9 Gm3 of SWE across the Italian landscape at peak accumulation, which on average occurs on the 4th of March. Nearly 52% of mean seasonal SWE is accumulated across the Po river basin, followed by the Adige river (23%), and central Apennines (5%). IT-SNOW is freely available with the following DOI: https://doi.org/10.5281/zenodo.7034956 (Avanzi et al., 2022b) and can contribute to better constraining the role of snow for seasonal to annual water resources - a crucial endevor in a warming and drier climate. [ABSTRACT FROM AUTHOR]

With the renewed interest in lunar surface exploration, the European Space Agency envisions to stimulate the creation of lunar communications and navigation services (LCNS) to enable, among others, autonomous navigation capabilities for lunar rovers. As the number of satellites foreseen in such a service is much smaller compared to Earth-based global navigation satellite systems, different complementary technologies are pursued to improve the attainable navigation accuracy for lunar rovers. One way to improve the position accuracy provided by the LCNS satellites is to constrain their vertical position using a high resolution digital elevation model (DEM). This article presents the results of a variance covariance analysis of an extended Kalman filter implementation in which the LCNS ranging measurements are used together with the altitude provided by a DEM from the Lunar Orbiter Laser Altimeter instrument of the Lunar Reconnaissance Orbiter. Assuming a realistic orbit determination and time synchronization accuracy of the LCNS satellites, the usage of a navigation-grade inertial measurement unit and an oven-controlled crystal oscillator, a 3-sigma position accuracy of less than 10 m can be obtained. Furthermore, the availability is substantially improved as the DEM-aided solution enables a position solution in case of only 3 visible satellites. [ABSTRACT FROM AUTHOR]

Reducing errors in streamflow simulations is one of the main issues for a reliable forecast system aimed to manage floods and water resources. Data assimilation is a powerful tool to reduce model errors. Unfortunately, its use in operational chains with distributed and physically based models is a challenging issue since many methodologies require computational times that are hardly compatible with operational needs. The implemented methodology corrects modelled water level in channels and root-zone soil moisture using real-time water level gauge stations. Model's variables are corrected locally, then the updates are propagated upstream with a simple approach that accounts for sub-basins' contributions. The overfitting issue, which arises when updating a spatially distributed model with sparse streamflow data, is hence here addressed in the context of a large-scale operational implementation working in real time thanks to the simplicity of the strategy. To test the method, a hindcast of daily simulations covering 18 months was performed on the Italian Tevere basin, and the modelling results with and without assimilation were compared. The setup was that currently in place in the operational framework in both cases. The analysis evidences a clear overall benefit of applying the proposed method even out of the assimilation time window. [ABSTRACT FROM AUTHOR]

Radar-rainfall estimation is a complex process that involves several error sources, some of which are related to the environmental context. The presence of orographic obstacles heavily affects the quality of the retrieved radar products. In relatively flat terrain conditions, dual-polarization capability has been proven either to increase the data quality or to improve the rainfall estimate. The potential benefit of using polarimetric techniques for precipitation retrieval is evaluated here using data coming from two radar systems operating in Italy under complex-orography conditions. The analysis outlines encouraging results that might open new scenarios for operational applications. Indeed, the applied rainfall algorithm employing specific differential phase mostly outperformed the examined reflectivity-based retrieval techniques except for the analyzed winter storm. In the latter case, the likely contamination by frozen or melting snow tended to degrade the performance of the examined Kdp-based rainfall algorithms. [ABSTRACT FROM AUTHOR]

Hydrological monitoring systems relying on radar data and distributed hydrological models are now feasible at large-scale and represent effective early warning systems for flash floods. Here we describe a system that allows hydrological occurrences in terms of streamflow at a national scale to be monitored. We then evaluate its operational application in Italy, a country characterized by various climatic conditions and topographic features. The proposed system exploits a modified conditional merging (MCM) algorithm to generate rainfall estimates by blending data from national radar and rain-gauge networks. Then, we use the merged rainfall fields as input for the distributed and continuous hydrological model, Continuum, to obtain real-time streamflow predictions. We assess its performance in terms of rainfall estimates from MCM, using cross-validation and comparison with a conditional merging technique at an event-scale. We also assess its performance against rainfall fields from ground-based data at catchment-scale. We further evaluate the performance of the hydrological system in terms of streamflow against observed data (relative error on high flows less than 25% and Nash–Sutcliffe Efficiency greater than 0.5 for 72% and 46% of the calibrated study sections, respectively). These results, therefore, confirm the suitability of such an approach, even at national scale, over a wide range of catchment types, climates, and hydrometeorological regimes, and for operational purposes. [ABSTRACT FROM AUTHOR]