Zobrazeno 1 - 10
of 10 757
pro vyhledávání: '"Pozza, A. A. A."'
Autor:
Pozza, Marco
We extend the study of eikonal Hamilton-Jacobi equations posed on networks performed by Siconolfi and Sorrentino (Anal. PDE, 2018) to a more general setting. Their approach essentially exploits that such equations correspond to discrete problems on a
Externí odkaz:
http://arxiv.org/abs/2412.01625
We prove a homogenization result for a family of time-dependent Hamilton-Jacobi equations, rescaled by a parameter $\varepsilon$ tending to zero, posed on a periodic network, with a suitable notion of periodicity that will be defined. As $\varepsilon
Externí odkaz:
http://arxiv.org/abs/2411.03803
We examine the numerical approximation of time-dependent Hamilton-Jacobi equations on networks, providing a convergence error estimate for the semi-Lagrangian scheme introduced in (Carlini and Siconolfi, 2023), where convergence was proven without an
Externí odkaz:
http://arxiv.org/abs/2411.02356
Autor:
Pozza, Francesco, Zanella, Giacomo
We study multiproposal Markov chain Monte Carlo algorithms, such as Multiple-try or generalised Metropolis-Hastings schemes, which have recently received renewed attention due to their amenability to parallel computing. First, we prove that no multip
Externí odkaz:
http://arxiv.org/abs/2410.23174
Routinely-implemented deterministic approximations of posterior distributions from, e.g., Laplace method, variational Bayes and expectation-propagation, generally rely on symmetric approximating densities, often taken to be Gaussian. This choice faci
Externí odkaz:
http://arxiv.org/abs/2409.14167
Autor:
Pozza, Stefano
We present the first formulation of the optimal polynomial approximation of the solution of linear non-autonomous systems of ODEs in the framework of the so-called $\star$-product. This product is the basis of new approaches for the solution of such
Externí odkaz:
http://arxiv.org/abs/2404.19645
Autor:
Beatrice Salmaso, Melania Scarpa, Valerio Pellegrini, Astghik Stepanyan, Roberta Salmaso, Andromachi Kotsafti, Federico Scognamiglio, Dario Gregori, Giorgio Rivella, Ottavia De Simoni, Giulia Becherucci, Silvia Negro, Chiara Vignotto, Gaya Spolverato, Cesare Ruffolo, Imerio Angriman, Francesca Bergamo, Valentina Chiminazzo, Isacco Maretto, Maurizio Zizzo, Francesco Marchegiani, Luca Facci, Stefano Brignola, Gianluca Businello, Laurino Licia, Vincenza Guzzardo, Luca Dal Santo, Ceccon Carlotta, Marco Massani, Anna Pozza, Ivana Cataldo, Tommaso Stecca, Angelo Paolo Dei Tos, Vittorina Zagonel, Pierluigi Pilati, Boris Franzato, Antonio Scapinello, Giulia Pozza, Mario Godina, Giovanni Pirozzolo, Alfonso Recordare, Isabella Mondi, Corrado Da Lio, Roberto Merenda, Giovanni Bordignon, Daunia Verdi, Luca Saadeh, Silvio Guerriero, Alessandra Piccioli, Giulia Noaro, Roberto Cola, Giuseppe Portale, Chiara Cipollari, Matteo Zuin, Salvatore Candioli, Laura Gavagna, Fabio Ricagna, Monica Ortenzi, Mario Guerrieri, Giovanni Tagliente, Monica Tomassi, Umberto Tedeschi, Andrea Porzionato, Marco Agostini, Riccardo Quoc Bao, Francesco Cavallin, Gaia Tussardi, Barbara Di Camillo, Romeo Bardini, Ignazio Castagliuolo, Salvatore Pucciarelli, Matteo Fassan, Marco Scarpa
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Lynch syndrome is rarely associated with rectal cancer (RC) and thus, metachronous RC has been scarcely investigated. This study aimed to analyze the mucosal immune microenvironment in sporadic and metachronous RC. We analyzed the mucosal im
Externí odkaz:
https://doaj.org/article/cda4fa0daa04498d819fda0dd2dd459b
Autor:
Oh, Ki-Hwan, Borgioli, Leonardo, Mangano, Alberto, Valle, Valentina, Di Pangrazio, Marco, Toti, Francesco, Pozza, Gioia, Ambrosini, Luciano, Ducas, Alvaro, Zefran, Milos, Chen, Liaohai, Giulianotti, Pier Cristoforo
In recent years, the potential applications of machine learning to Minimally Invasive Surgery (MIS) have spurred interest in data sets that can be used to develop data-driven tools. This paper introduces a novel dataset recorded during ex vivo pseudo
Externí odkaz:
http://arxiv.org/abs/2312.01183
In quantum mechanics, the Rosen-Zener model represents a two-level quantum system. Its generalization to multiple degenerate sets of states leads to larger non-autonomous linear system of ordinary differential equations (ODEs). We propose a new metho
Externí odkaz:
http://arxiv.org/abs/2311.04144
Publikováno v:
Journal of Dairy Science, Vol 107, Iss 12, Pp 10352-10360 (2024)
ABSTRACT: Milk and whey are subjected to quick deterioration due to bacterial growth. Turning them into powder allows for extended shelf life, easier storage, and more effective transport. Monitoring mineral elements in dairy powders is crucial for b
Externí odkaz:
https://doaj.org/article/26695712225e45249d019d8194120af7