Zobrazeno 1 - 10
of 3 403
pro vyhledávání: '"P, Salvetti"'
An infinite game on the set of real numbers appeared in Matthew Baker's work [Math. Mag. 80 (2007), no. 5, pp. 377--380] in which he asks whether it can help characterize countable subsets of the reals. This question is in a similar spirit to how the
Externí odkaz:
http://arxiv.org/abs/2408.14624
Autor:
Fruzza, Filippo, Lamioni, Rachele, Mariotti, Alessandro, Salvetti, Maria Vittoria, Galletti, Chiara
Publikováno v:
Fuel 362 (2024) 130838
Hydrogen has emerged as a promising option for promoting decarbonization in various sectors by serving as a replacement for natural gas while retaining the combustion-based conversion system. However, its higher reactivity compared to natural gas int
Externí odkaz:
http://arxiv.org/abs/2311.18441
Autor:
Léa Chazot-Franguiadakis, Joelle Eid, Gwendoline Delecourt, Pauline J. Kolbeck, Saskia Brugère, Bastien Molcrette, Marius Socol, Marylène Mougel, Anna Salvetti, Vincent Démery, Jean-Christophe Lacroix, Véronique Bennevault, Philippe Guégan, Martin Castelnovo, Fabien Montel
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024)
Abstract Viruses have remarkable physical properties and complex interactions with their environment. However, their aggregation in confined spaces remains unexplored, although this phenomenon is of paramount importance for understanding viral infect
Externí odkaz:
https://doaj.org/article/a45134be978a44bcacdb795ed89ac8b9
Autor:
Moldovan, Gabriel, Mariotti, Alessandro, Cordier, Laurent, Lehnasch, Guillaume, Salvetti, Maria - Vittoria, Meldi, Marcello
The potential for data-driven applications to scale-resolving simulations of turbulent flows is assessed herein. Multigrid sequential data assimilation algorithms have been used to calibrate solvers for Large Eddy Simulation for the analysis of the h
Externí odkaz:
http://arxiv.org/abs/2212.13831
Autor:
Bruna Moreno Dias, Lúcia Marta Giunta da Silva, Marina de Góes Salvetti, Carmen Silvia Gabriel
Publikováno v:
Revista Brasileira de Enfermagem, Vol 77, Iss 4 (2024)
ABSTRACT Objective: to reflect on the perspectives of adopting the Progress Test in undergraduate nursing education. Methods: this is a reflective study, based on authors’ critical thinking and supported by national and international literature on
Externí odkaz:
https://doaj.org/article/8c13a70cb22145369ddb77b44641f43c
Autor:
Vitória Salvetti Valentini dos Santos, Simone Felitti, Sheila Cristina Lordelo Wludarski, Ana Luiza Carneiro Binotto, Mateus dos Santos Silva, Marina de Góes Salvetti
Publikováno v:
Revista Brasileira de Cancerologia, Vol 70, Iss 3 (2024)
Introdução: A neoplasia de esôfago é o sétimo câncer mais frequentemente diagnosticado e a sexta principal causa de morte relacionada ao câncer no mundo. No Brasil, ocupa a 13ª posição entre os tipos de câncer mais frequentes. Os sítios m
Externí odkaz:
https://doaj.org/article/3b1634274e4b4fa1865c2ca2410f1ce1
Autor:
Marchionna, Luca, Pugliese, Giulio, Martini, Mauro, Angarano, Simone, Salvetti, Francesco, Chiaberge, Marcello
Publikováno v:
Sensors. 2023; 23(2):752
The game of Jenga represents an inspiring benchmark for developing innovative manipulation solutions for complex tasks. Indeed, it encouraged the study of novel robotics methods to successfully extract blocks from the tower. A Jenga game round undoub
Externí odkaz:
http://arxiv.org/abs/2211.07977
Autor:
Angarano, Simone, Salvetti, Francesco, Mazzia, Vittorio, Fantin, Giovanni, Gandini, Dario, Chiaberge, Marcello
Publikováno v:
SAI: Computing Conference 2022 Proceedings - Springer
Precise and accurate localization in outdoor and indoor environments is a challenging problem that currently constitutes a significant limitation for several practical applications. Ultra-wideband (UWB) localization technology represents a valuable l
Externí odkaz:
http://arxiv.org/abs/2209.03021
Single-Image Super-Resolution can support robotic tasks in environments where a reliable visual stream is required to monitor the mission, handle teleoperation or study relevant visual details. In this work, we propose an efficient Generative Adversa
Externí odkaz:
http://arxiv.org/abs/2209.03355
Domain Generalization (DG) studies the capability of a deep learning model to generalize to out-of-training distributions. In the last decade, literature has been massively filled with training methodologies that claim to obtain more abstract and rob
Externí odkaz:
http://arxiv.org/abs/2209.01121