Monitoring the last Apennine glacier: recent in situ campaigns and modelling of Calderone glacial apparatus

The Calderone glacier is at present the most southern glacier in Europe (42° 28' 15’’ N). The little apparatus (about 20.000 m2 in surface area) has been giving an interesting response both to short- and long-term climatic variations which resulted in a considerable reduction in surface area and volume. The glacial apparatus is split into two ice bodies (glacierets) since 2000. The two glacierets are located in a deep northward valley below the top of the Corno Grande (2912 m asl) in the centre of the Gran Sasso d’Italia mountain range (Central Italy). Such glacial apparatus has been subjected to a strong reduction, with a loss of total surface area of about 50% and thickness of about 65%with respect to the hypothetical size (about 105.00 m2 and 55 m at the Little Ice Age). Since early 90s the Calderone glacier has been subjected to several multidisciplinary field campaigns to monitor and evaluate its role as an environmental indicator in the framework of global warming. Starting from historical series related to more than a century of records, the variability of the different glacier properties has been estimated by using classical geomorphologic methods as well as in situ and remote sensing techniques. In particular, the last field campaigns, in 2015, 2016 and 2019, have been carried out using Ground Penetrating Radar equipped with different antenna frequencies, drone-based survey, snow pit measurements and chemical-physical sampling. The measurement campaigns have been complemented by a regional climate analysis, spanning the last fifty years, and snowpack modelling initialized with microphysical snow data (e.g., snow density, crystal shape and size, hardness). The snowpack chemical analyses include the main and trace elements, soluble inorganic and organic ions, EC/OC and PAH, with different spatial resolution depending on the analytes. We present here the methodological approach used and some preliminary results

A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

Snow metamorphism and densification : comparison of measured, parametrised and modelled data

The study objective was to compare the specific surface area (SSA) decrease rates and densification rates calculated with a parametrisation (Schleef et al. 2014b) and the widely used snow cover model SNOWPACK (Bartelt and Lehning 2002; Lehning et al. 2002b,a) with the values measured for samples extracted from the continuous stratigraphy measurements during a recent snow campaign at Weissfluhjoch, Switzerland. The vertical profiles of penetration force and the structural element length measured with the Snow Micro Penetrometer (SMP) were used to infer the SSA and density profiles using a statistical relation, thus it was possible to calculate the SSA decrease rate and the densification rate for each chosen snow sample. Knowing the sample temperature it was also possible to use the parametrisation to calculate the SSA decrease rates and densification rates and to compare them to the measured rates. The SSA decrease rates and densification rates of the samples were also calculated from the optical-equivalent grain size simulated with SNOWPACK and then compared to the measured rates. It was demonstrated that the parametrisation reproduced better than the model the measured SSA decrease rates but in both cases the measured rates were underestimated, especially for samples subject to high overburden stress. A new fit of the SSA decrease rate parametrisation on the measured rates improved the correlation but did not change the parametrisation performances for samples subject to high load. This is consistent with the fact that the parametrization was derived for new snow. It was also shown that the parametrisation reproduced much better than the model the measured densification rates, even if they were slightly underestimated. A new fit of the densification rate parametrisation on the measured rates improved the correlation but it still did not provide a one-to-one relation between parametrised and measured rates. All the results show that order of magnitude agreement is readily achieved, while it is necessary to further discern methodological uncertainties from potentially missing physical processes in the parametrizations. Nevertheless the thesis demonstrates the new analysis opportunities for validating models and parametrizations from continuous SMP measurements.by Edoardo RaparelliUniversity of Innsbruck, Masterarbeit, 2018(VLID)288222

Forze di attrito in guarnizioni per cilindri pneumatici

In questo articolo viene presentato un metodo sperimentale per la misura della forza di attrito in attuatori pneumatici mediante l’utilizzo di un tribometro standard da laboratorio opportunamente attrezzato per riprodurre reali condizioni di montaggio e di lavoro delle guarnizioni

Snowpack modelling in central Italy: analysis and comparison of high-resolution WRF-driven Noah LSM and Alpine3D simulations

Italy is a territory characterized by complex orography. Its main mountain chains are the Alps, which identify the northern Italian border, and the Apennines, which cross the entire Italian peninsula ranging from north-west to south-east. The major Apennines peaks reach almost 3000 meters and are located in central Italy, in the Abruzzo region. The near Mediterranean sea is an important source of moisture, which permits to this region to experience a substantial snow cover during winter. Thanks to the orientation of the Apennines chain and the height of its peaks the Abruzzo region is characterized by different climate types. This affects the precipitation patterns and the snowpack evolution, resulting in high regional variability of the snow cover. The goal of this study is to investigate the snow cover evolution in the Abruzzo region, using and comparing different snowpack models. To this end we have used the Weather Research and Forecasting (WRF) model to drive the Noah Land Surface Model (LSM) and the sophisticated three-dimensional snow cover model Alpine3D to simulate the snow cover evolution at regional scale. Noah LSM is already on-line coupled with WRF, but this is not the case for Alpine3D. Thus we have modified and used the interfacing library MeteoIO to force Alpine3D with the meteorological data simulated with WRF, off-line coupling the two models. We have validated the WRF simulation using a dense network of automatic weather stations (AWS), obtaining good agreement between simulated and observed data. We have found that the snow depth simulated with Noah LSM presents a negative bias, caused by the inability of the model to reproduce correctly the snow densification rate. Instead, Alpine3D is capable to better reproduce the observed densification rate, thanks to its more detailed description of the snow metamorphism processes. However, the snow depth simulated with Alpine3D presents a negative bias, caused by an underestimation of the new snow depth, which has a negative impact on the entire simulation

Biological Response of Irisin Induced by Different Types of Exercise in Obese Subjects: A Non-Inferiority Controlled Randomized Study

Background: Weight loss through physical exercise is warranted among obese individuals. Recently, a greater benefit in cardiorespiratory fitness was achievable with high-intensity interval training (HIIT) as compared with moderate intensity continuous training. The beneficial effect of training on CV health might be related to a specific modulation of circulating irisin, an adypo-myokine implicated in the regulation of energy expenditure. Methods: The present study investigates the circulating plasma levels of irisin at baseline and in response to 12-week of training program either with HIIT or moderate-intensity continuous training (MICT) among young female and male obese subjects. Clinical, anthropometric, and training characteristics for each participant were available. A sex-disaggregated data for circulating plasma levels of irisin pre- and post-training are provided as well as an adjusted multivariate linear regression model to identify the determinants of post-training irisin levels. Results: Data from a total of 32 obese healthy individuals (47% female, mean age 38.7 years, mean BMI 35.6 kg/m2), randomized in a 1:1 manner to HIIT or MICT were analyzed. Circulating plasma levels of irisin similarly and significantly decreased in both MICT and HIIT interventional groups. Females had higher post-exercise irisin levels than males (6.32 [5.51–6.75] vs. 4.97 [4.57–5.72] μg/mL, p = 0.001). When stratified by an interventional group, a statistically significant difference was observed only for the MICT group (male, 4.76 [4.20–5.45] μg/mL vs. female 6.48 [4.88–6.84] μg/mL p = 0.03). The circulating post-training level of irisin was independently associated with post-training fat-free mass (β −0.34, 95% confidence interval, CI −0.062, −0.006, p = 0.019) in a model adjusted confounders. When female sex was added into the adjusted model, it was retained as the only factor independently associated with irisin levels (β 1.22, 95% CI, 0.50, 1.93, p = 0.002). Conclusions: In obese healthy subjects, circulating irisin levels were reduced in response to 12-weeks of exercise involving either HIIT or MICT. A sex-specific differences in circulating irisin levels at baseline and as biological response to chronic exercise was described. Sex-specific biological response of irisin to exercise should be further explored to tailor sex-specific training approaches for improving the cardiovascular health of obese healthy subjects

Concepts and Controversies in Haemostasis and Thrombosis Associated with Liver Disease: Proceedings of the 7th International Coagulation in Liver Disease Conference

Patients with acute and chronic liver disease frequently acquire unique changes in haemodynamic and haemostatic pathways that may result in life-threatening bleeding and thrombosis. Additionally, activation of haemostatic pathways may play a role in disease progression through parenchymal extinction, organ atrophy, recruitment of inflammatory cells and activation of stellate cells. In the setting of a previously entrenched set of clinical perceptions, the slowly evolving evidence-based paradigms of haemostasis in cirrhosis are now more carefully scrutinized. The 7th International Conference on Coagulation in Liver Disease (held biennially since 2005) met in October of 2017 in Rome, Italy, to discuss and debate important topics in this field. This document provides a statement-based thematic summary of the meeting presented here amid a framework of the most current evidence. The review of the literature, preparation of the document and presentation of each summary statement below are based on systematic approaches used in published guidance documents

Hemostatic balance in patients with liver cirrhosis: Report of a consensus conference

Patients with cirrhosis present with hemostatic alterations secondary to reduced availability of pro-coagulant and anti-coagulant factors. The net effect of these changes is a rebalanced hemostatic system. The Italian Association of the Study of the Liver (AISF) and the Italian Society of Internal Medicine (SIMI) promoted a consensus conference on the hemostatic balance in patients with cirrhosis. The consensus process started with the review of the literature by a scientific board of experts and ended with a formal consensus meeting in Rome in December 2014. The statements were graded according to quality of evidence and strength of recommendations, and approved by an independent jury. The statements presented here highlight strengths and weaknesses of current laboratory tests to assess bleeding and thrombotic risk in cirrhotic patients, the pathophysiology of hemostatic perturbations in this condition, and outline the optimal management of bleeding and thrombosis in patients with liver cirrhosis