Quaderni MOX
Pubblicazioni
del Laboratorio di Modellistica e Calcolo Scientifico MOX. I lavori riguardano prevalentemente il campo dell'analisi numerica, della statistica e della modellistica matematica applicata a problemi di interesse ingegneristico. Il sito del Laboratorio MOX è raggiungibile
all'indirizzo mox.polimi.it
Trovati 1287 prodotti
-
48/2021 - 17/07/2021
Riccobelli, D.
Active elasticity drives the formation of periodic beading in damaged axons | Abstract | | In several pathological conditions, such as coronavirus infections, multiple sclerosis, Alzheimer's and Parkinson's diseases, the physiological shape of axons is altered and a periodic sequence of bulges appears. Experimental evidences suggest that such morphological changes are caused by the disruption of the microtubules composing the cytoskeleton of the axon. In this paper, we develop a mathematical model of damaged axons based on the theory of continuum mechanics and nonlinear elasticity. The axon is described as a cylinder composed of an inner passive part, called axoplasm, and an outer active cortex, composed mainly of F-actin and able to contract thanks to myosin-II motors. Through a linear stability analysis we show that, as the shear modulus of the axoplasm diminishes due to the disruption of the cytoskeleton, the active contraction of the cortex makes the cylindrical configuration unstable to axisymmetric perturbations, leading to a beading pattern. Finally, the non-linear evolution of the bifurcated branches is investigated through finite element simulations. |
-
47/2021 - 17/07/2021
Orlando, G; Della Rocca, A; Barbante, P. F.; Bonaventura, L.; Parolini, N.
An efficient and accurate implicit DG solver for the incompressible Navier-Stokes equations | Abstract | | We propose an efficient, accurate and robust implicit solver for the incompressible Navier-Stokes equations, based on a DG spatial discretization and on the TR-BDF2 method for time discretization. The effectiveness of the method is demonstrated in a number of classical benchmarks, which highlight its superior efficiency with respect to other widely used implicit approaches. The parallel implementation of the proposed method in the framework of the deal.II software package allows for accurate and efficient adaptive simulations in complex geometries, which makes the proposed solver attractive for large scale industrial applications. |
-
46/2021 - 02/07/2021
Diquigiovanni, J.; Fontana, M.; Vantini, F.
Conformal Prediction Bandsfor Multivariate Functional Data | Abstract | | Motivated by the pressing request of methods able to create prediction sets in ageneral regression framework for a multivariate functional response and pushed bynew methodological advancements in non-parametric prediction for functional data,we propose a set of conformal predictors that produce finite-sample either validor exact multivariate simultaneous prediction bands under the mild assumption ofexchangeable regression pairs. The fact that the prediction bands can be built aroundany regression estimator and that can be easily found in closed form yields a verywidely usable method, which is fairly straightforward to implement. In addition,we first introduce and then describe a specific conformal predictor that guaranteesan asymptotic result in terms of efficiency and inducing prediction bands able tomodulate their width based on the local behavior and magnitude of the functionaldata. The method is investigated and analyzed through a simulation study and areal-world application in the field of urban mobility. |
-
45/2021 - 02/07/2021
Diquigiovanni, J.; Fontana, M.; Vantini, S.
Distribution-Free Prediction Bands for Multivariate Functional Time Series: an Application to the Italian Gas Market | Abstract | | Uncertainty quantification in forecasting represents a topic of great importance in statistics, especially when dealing with complex data characterized by non-trivial dependence structure. Pushed by novel works concerning distribution-free prediction, we propose a scalable procedure that outputs closed-form simultaneous prediction bands for multivariate functional response variables in a time series setting, which is able to guarantee performance bounds in terms of unconditional coverage and asymptotic exactness, both under some conditions. After evaluating its performance on synthetic data, the method is used to build multivariate prediction bands for daily demand and offer curves in the Italian gas market. The prediction framework thus obtained allows traders to directly evaluate the impact of their own offers/bids on the market, providing an intriguing tool for the business practice. |
-
44/2021 - 01/07/2021
Gentili, G.G.; Khosronejad, M.; Bernasconi, G.; Perotto, S.; Micheletti, S.
Efficient Modeling of Multimode Guided Acoustic Wave Propagation in Deformed Pipelines by Hierarchical Model Reduction | Abstract | | The fi nite element based hierarchical model (HiMod) reduction technique is here
applied, for the fi rst time, to model guided acoustic wave propagation in deformed
pipelines in a linear regime. This method turns out to be extremely efficient to
discretize the linearized Helmholtz equation for acoustic waves. The selection of
a suitable modal transverse basis for the acoustic fi eld allows us to speed up the
computation by orders of magnitude with respect to a standard 3D finite element
discretization. |
-
43/2021 - 24/06/2021
Salvador, M.; Fedele, M.; Africa, P.C.; Sung, E.; Dede', L.; Prakosa, A.; Chrispin, J.; Trayanova, N.; Quarteroni, A.
Electromechanical modeling of human ventricles with ischemic cardiomyopathy: numerical simulations in sinus rhythm and under arrhythmia | Abstract | | We developed a novel patient-specific computational model for the numerical simulation of ventricular electromechanics in patients with ischemic cardiomyopathy (ICM). This model reproduces the activity both in sinus rhythm (SR) and in ventricular tachycardia (VT). The presence of scars, grey zones and non-remodeled regions of the myocardium is accounted for by the introduction of a spatially heterogeneous coefficient in the 3D electromechanics model. This 3D electromechanics model is firstly coupled with a 2-element Windkessel afterload model to fit the pressure-volume (PV) loop of a patient-specific left ventricle (LV) with ICM in SR. Then, we employ the coupling with a 0D closed-loop circulation model to analyze a VT circuit over multiple heartbeats on the same LV. We highlight similarities and differences on the solutions obtained by the electrophysiology model and those of the electromechanics model, while considering different scenarios for the circulatory system. We observe that very different parametrizations of the circulation model induce the same hemodynamical considerations for the patient at hand. Specifically, we classify this VT as unstable. We conclude by stressing the importance of combining electrophysiological, mechanical and hemodynamical models to provide relevant clinical indicators in how arrhythmias evolve and can potentially lead to sudden cardiac death. |
-
42/2021 - 23/06/2021
Calissano, A.; Fontana, M.; Zeni, G.; Vantini, S.
Conformal Prediction Sets for Populations of Graphs | Abstract | | In the latest years, scholars started focusing on how to develop statistical tool for the analysis of population of complex data, such as sets of labelled or unlabelled graphs graphs. The present works adds to this literature by focusing on a strangely overlooked area, namely the formulation of prediction sets.
By exploiting cutting edge techniques in the realm of machine learning, we propose a forecasting method for populations of both labelled and unlabelled graphs based on Conformal Prediction, able to identify prediction regions. Our method is model-free, achieves finite-sample validity, is computationally efficient and it identifies interpretable prediction sets, in the shape of a parallelotope. To explore the features of this novel forecasting technique, a simulation study and and a real-world example are presented. |
-
41/2021 - 21/06/2021
Costa, G., Cavinato, L., Maschi, C., Fiz, F., Sollini, M., Politi, L. S., Chiti, A., Balzarini, L., Aghemo, A., di Tommaso, L., Ieva, F., Torzilli, G., Viganò, L.
Virtual Biopsy for Diagnosis of Chemotherapy-Associated Liver Injuries and Steatohepatitis: A Combined Radiomic and Clinical Model in Patients with Colorectal Liver Metastases | Abstract | | Non-invasive diagnosis of chemotherapy-associated liver injuries (CALI) is still an unmet need. The present study aims to elucidate the contribution of radiomics to the diagnosis of sinusoidal dilatation (SinDil), nodular regenerative hyperplasia (NRH), and non-alcoholic steatohepatitis (NASH). Patients undergoing hepatectomy for colorectal metastases after chemotherapy (January 2018-February 2020) were retrospectively analyzed. Radiomic features were extracted from a standardized volume of non-tumoral liver parenchyma outlined in the portal phase of preoper- ative post-chemotherapy computed tomography. Seventy-eight patients were analyzed: 25 had grade 2–3 SinDil, 27 NRH, and 14 NASH. Three radiomic fingerprints independently predicted SinDil: GLRLM_f3 (OR = 12.25), NGLDM_f1 (OR = 7.77), and GLZLM_f2 (OR = 0.53). Combining clinical, laboratory, and radiomic data, the predictive model had accuracy = 82%, sensitivity = 64%, and specificity = 91% (AUC = 0.87 vs. AUC = 0.77 of the model without radiomics). Three radiomic parameters predicted NRH: conventional_HUQ2 (OR = 0.76), GLZLM_f2 (OR = 0.05), and GLZLM_f3 (OR = 7.97). The combined clinical/laboratory/radiomic model had accuracy = 85%, sensitivity = 81%, and specificity = 86% (AUC = 0.91 vs. AUC = 0.85 without radiomics). NASH was predicted by conventional_HUQ2 (OR = 0.79) with accuracy = 91%, sensitivity = 86%, and specificity = 92% (AUC = 0.93 vs. AUC = 0.83 without radiomics). In the validation set, accuracy was 72%, 71%, and 91% for SinDil, NRH, and NASH. Radiomic analysis of liver parenchyma may provide a signature that, in combination with clinical and laboratory data, improves the diagnosis of CALI. |
|
