A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Comportamento dinamico fuori del piano di pareti murarie: influenza della deformabilità degli impalcati

The aim of this study was to investigate the influence of the diaphragm flexibility on the behavior of out-of-plane walls in masonry buildings. Simplified models have been developed to perform kinematic and dynamic analyses in order to compare the response of walls with different restraint conditions. Kinematic non linear analyses of assemblages of rigid blocks have been performed to obtain the acceleration-displacement curves for walls with different restraint conditions at the top. A simplified 2DOF model has been developed to analyse the dynamic response of the wall with an elastic spring at the top, following the Housner rigid behaviour hypothesis. The dissipation of energy is concentrated at every impact at the base of the wall and is modelled through the introduction of the coefficient of restitution. The sets of equations of the possible configurations of the wall, depending on the different positions of the centre of rotation at the base and at the intermediate hinge have been obtained. An algorithm for the numerical integration of the sets of the equations of motion in the time domain has been developed. Dynamic analyses of a set of walls with Gaussian impulses and recorded accelerograms inputs have been performed in order to compare the response of the simply supported wall with the one of the wall with elastic spring at the top. The influence of diaphragm stiffness Kd has been investigated determining the variation of maximum displacement demand with the value of Kd. A more regular trend has been obtained for the Gaussian input than for the recorded accelerograms.

A simple voltage/mass index increases the suspicion of amyloidotic cardiomyopathy: an electrocardiographic and echocardiographic study of 767 patients with increased left ventricular wall thickness due to different causes

Background-Amyloidotic cardiomyopathy (AC) can mimic true left ventricular hypertrophy (LVH), including hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD). We assessed the diagnostic value of combined electrocardiographic/echocardiographic indexes to identify AC among patients with increased echocardiographic LV wall thickness due to either different etiologies of amyloidosis or HCM or HHD. Method-First, we studied 469 consecutive patients: 262 with biopsy/genetically proven AC (with either AL or transthyretin (TTR)-related amyloidosis); 106 with HCM; 101 with HHD. We compared the diagnostic performance of: low QRS voltage, symmetric LVH, low QRS voltage plus interventricular septal thickness >1.98 cm, Sokolow index divided by the cross-sectional area of LV wall, Sokolow index divided by body surface area indexed LV mass (LVMI), Sokolow index divided by LV wall thickness, Sokolow index divided by (LV wall/height^2.7); peripheral QRS score divided by LVMI, Peripheral QRS score divided by LV wall thickness, Peripheral QRS score divided by LV wall thickness indexed to height^2.7, total QRS score divided by LVMI, total QRS score divided by LV wall thickness; total QRS score divided by (LV wall/height^2.7). We tested each criterion, separately in males and females, in the following settings: AC vs. HCM+HHD; AC vs. HCM; AL vs. HCM+HHD; AL vs. HCM; TTR vs. HCM+HHD; TTR vs. HCM. Results-Low QRS voltage showed high specificity but low sensitivity for the identification of AC. All the combined indexes had a higher diagnostic accuracy, being total QRS score divided by LV wall thickness or by LVMI associated with the best performances and the largest areas under the ROC curve. These results were validated in 298 consecutive patients with AC, HCM or HHD. Conclusions-In patients with increased LV wall thickness, a combined ECG/ echocardiogram analysis provides accurate indexes to non-invasively identify AC. Total QRS score divided by LVMI or LV wall thickness offers the best diagnostic performance.

Development of numerical methodologies to predict the liquid fuel sprays - wall interaction to optimize the mixing process of direct injection spark ignition engines

Nowadays the development of new Internal Combustion Engines is mainly driven by the need to reduce tailpipe emissions of pollutants, Green-House Gases and avoid the fossil fuels wasting. The design of dimension and shape of the combustion chamber together with the implementation of different injection strategies e.g., injection timing, spray targeting, higher injection pressure, play a key role in the accomplishment of the aforementioned targets. As far as the match between the fuel injection and evaporation and the combustion chamber shape is concerned, the assessment of the interaction between the liquid fuel spray and the engine walls in gasoline direct injection engines is crucial. The use of numerical simulations is an acknowledged technique to support the study of new technological solutions such as the design of new gasoline blends and of tailored injection strategies to pursue the target mixture formation. The current simulation framework lacks a well-defined best practice for the liquid fuel spray interaction simulation, which is a complex multi-physics problem. This thesis deals with the development of robust methodologies to approach the numerical simulation of the liquid fuel spray interaction with walls and lubricants. The accomplishment of this task was divided into three tasks: i) setup and validation of spray-wall impingement three-dimensional CFD spray simulations; ii) development of a one-dimensional model describing the liquid fuel – lubricant oil interaction; iii) development of a machine learning based algorithm aimed to define which mixture of known pure components mimics the physical behaviour of the real gasoline for the simulation of the liquid fuel spray interaction.

Advanced imaging study in cerebrovascular pathology for the personalization of therapy: from the capillary microcirculation to the vessel wall

Objectives: To investigate the use of intravascular optical coherence tomography (IVOCT) for carotid artery stenting (CAS) procedures in patients with atherosclerotic stenosis. Examine possible markers that might identify the onset of new cerebral ischemic lesions on MRI. Specifically, attention was drawn to the morphological features of the used dual layer stent, which could be underestimated during traditional CAS procedures. Secondary goals are to compare the safety and efficacy of different CAS techniques and the accuracy of the vessel analysis software’s on pre-operative CTA examination used to quantify ICA stenosis with the gold standard IVOCT. Material and Methods: Ten patients underwent CAS procedure with flow-arrest technique and IVOCT evaluations prior to and following stent deployment, while five matched patients underwent CAS procedure with distal embolic protection device (EPD) technique. All patients underwent 24-hours 3T MRI examination to check for ischemic lesions; all patients were treated with the same dual-layer stent. Results: Patients with new ischemic lesions demonstrated peculiar stent configuration in the distal end, and a strong Spearman’s rank order correlation was found among the volume of new DWI lesions and the stent configuration in its distal end (Rs: 0.81; p <0.001). No statistically significant differences were observed in the total burden of new ischemic lesions for each technique. The vessel analysis software's on CTA comparison demonstrated a higher diagnostic accuracy in the degree of ICA stenosis compared to the gold standard of IVOCT of the specialized software (ROC curve = 0.63; p = 0.06) compared to the general software (ROC curve = 0.57, p = 0.31). Conclusions: Study’s results support the use of IVOCT to allow recognition of potential features that can predict the onset of new cerebral ischemic lesions. Additionally, IVOCT made it possible to evaluate specialized software's increased accuracy in the pre-operative evaluation of ICA atherosclerotic stenosis.