Zobrazeno 1 - 10
of 5 048
pro vyhledávání: '"A. Rizzello"'
Shape Memory Alloys (SMAs) are a class of smart materials that exhibit a macroscopic contraction of up to 5% when heated via an electric current. This effect can be exploited for the development of novel unconventional actuators. Despite having many
Externí odkaz:
http://arxiv.org/abs/2305.13928
This work aims to predict channels in wireless communication systems based on noisy observations, utilizing sequence-to-sequence models with attention (Seq2Seq-attn) and transformer models. Both models are adapted from natural language processing to
Externí odkaz:
http://arxiv.org/abs/2302.00341
Autor:
Hoffmann, Matthias K., Heib, Lennart, Rizzello, Gianluca, Moretti, Giacomo, Flaßkamp, Kathrin
This contribution deals with multi-objective model-predictive control (MPC) of a wave energy converter (WEC) device concept, which can harvest energy from sea waves using a dielectric elastomer generator (DEG) power take-off system. We aim to maximis
Externí odkaz:
http://arxiv.org/abs/2212.03511
Autor:
Laura Melotti, Matteo Rinaldi, Marco Salice, Nikolas K. Dussias, Nicholas Vanigli, Carlo Calabrese, Eleonora Scaioli, Liliana Gabrielli, Tiziana Lazzarotto, Francesca Rosini, Pierluigi Viale, Paolo Gionchetti, Maddalena Giannella, Fernando Rizzello
Publikováno v:
Microbiology Spectrum, Vol 12, Iss 11 (2024)
ABSTRACT Cytomegalovirus (CMV) colitis is a serious concern worsening the prognosis of patients with ulcerative colitis (UC). We aimed to assess risk factors and prognostic impact of CMV colitis in patients with moderate-to-severe UC flare. We conduc
Externí odkaz:
https://doaj.org/article/31faf22bf0824a8b9e108927eeac0f7f
One way to improve the estimation of time varying channels is to incorporate knowledge of previous observations. In this context, Dynamical VAEs (DVAEs) build a promising deep learning (DL) framework which is well suited to learn the distribution of
Externí odkaz:
http://arxiv.org/abs/2210.17177
Autor:
Junyang Chen, Yifan Yu, Siyou Wang, Yu Shen, Yupeng Tian, Loris Rizzello, Kui Luo, Xiaohe Tian, Tinghua Wang, Liulin Xiong
Publikováno v:
Journal of Nanobiotechnology, Vol 22, Iss 1, Pp 1-12 (2024)
Abstract Understanding the intricate nanoscale architecture of neuronal myelin during central nervous system development is of utmost importance. However, current visualization methods heavily rely on electron microscopy or indirect fluorescent metho
Externí odkaz:
https://doaj.org/article/83a10e16c4af4c879e8d7a3dc2d21b87
In this work, we propose an efficient method for channel state information (CSI) adaptive quantization and feedback in frequency division duplexing (FDD) systems. Existing works mainly focus on the implementation of autoencoder (AE) neural networks (
Externí odkaz:
http://arxiv.org/abs/2207.06924
Autor:
Chiara Demarinis, Michela Verni, Prabin Koirala, Silvia Cera, Carlo Giuseppe Rizzello, Rossana Coda
Publikováno v:
Future Foods, Vol 9, Iss , Pp 100289- (2024)
Carob pulp powder and chickpea flour were used as ingredients in the formulation of a plant-based fermented beverage (gurt). Three different exopolysaccharide-producing strains (Levilactobacillus brevis AM7, Weissella confusa CK15, and Pediococcus cl
Externí odkaz:
https://doaj.org/article/8ce0510da5114d878646b09e4dcea5f9
To fully unlock the benefits of multiple-input multiple-output (MIMO) networks, downlink channel state information (CSI) is required at the base station (BS). In frequency division duplex (FDD) systems, the CSI is acquired through a feedback signal f
Externí odkaz:
http://arxiv.org/abs/2204.04723
Autor:
Degiacomi, Giulia, Chiarelli, Laurent R., Riabova, Olga, Loré, Nicola Ivan, Muñoz-Muñoz, Lara, Recchia, Deborah, Stelitano, Giovanni, Postiglione, Umberto, Saliu, Fabio, Griego, Anna, Scoffone, Viola Camilla, Kazakova, Elena, Scarpa, Edoardo, Ezquerra-Aznárez, José Manuel, Stamilla, Alessandro, Buroni, Silvia, Tortoli, Enrico, Rizzello, Loris, Sassera, Davide, Ramón-García, Santiago, Cirillo, Daniela Maria, Makarov, Vadim, Pasca, Maria Rosalia
Publikováno v:
In International Journal of Antimicrobial Agents October 2024 64(4)