Zobrazeno 1 - 10
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pro vyhledávání: '"CANTINI A"'
Large Language Models (LLMs) have revolutionized artificial intelligence, demonstrating remarkable computational power and linguistic capabilities. However, these models are inherently prone to various biases stemming from their training data. These
Externí odkaz:
http://arxiv.org/abs/2407.08441
In the digital era, the prevalence of depressive symptoms expressed on social media has raised serious concerns, necessitating advanced methodologies for timely detection. This paper addresses the challenge of interpretable depression detection by pr
Externí odkaz:
http://arxiv.org/abs/2401.17477
Autor:
Cantini, Luigi, Zahra, Ali
We introduce a general method to determine the large scale non-equilibrium steady-state properties of one-dimensional multi-species driven diffusive systems with open boundaries, generalizing thus the max-min current principle known for systems with
Externí odkaz:
http://arxiv.org/abs/2309.06231
Autor:
Eva Barcelona-Estaje, Mariana A. G. Oliva, Finlay Cunniffe, Aleixandre Rodrigo-Navarro, Paul Genever, Matthew J. Dalby, Pere Roca-Cusachs, Marco Cantini, Manuel Salmeron-Sanchez
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Mesenchymal stem cells (MSCs) interact with their surroundings via integrins, which link to the actin cytoskeleton and translate physical cues into biochemical signals through mechanotransduction. N-cadherins enable cell-cell communication a
Externí odkaz:
https://doaj.org/article/a543dfe5735e4aea80fa0fbcd864f61a
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-20 (2024)
Abstract The abundance of unpaired multimodal single-cell data has motivated a growing body of research into the development of diagonal integration methods. However, the state-of-the-art suffers from the loss of biological information due to feature
Externí odkaz:
https://doaj.org/article/add759a490ef488a8374ce2d59b563ca
Autor:
Sans-Planell, Oriol, Cantini, Francesco, Costa, Marco, Grazzi, Francesco, Morgano, Manuel, Yamada, Masako
This communication presents the results obtained at an experimental campaign at PSI BOA beamline using the combination of the ANET Compact Neutron Collimator (CNC) with the actual BOA pin-hole system. Through extensive resolution campaigns, it has be
Externí odkaz:
http://arxiv.org/abs/2302.14651
Autor:
Diego Lisboa Rios, Ana Agustina Bengoa, Patrícia Costa Lima da Silva, César Silva Santana Moura, Graciela Liliana Garrote, Analía Graciela Abraham, Gabriel da Rocha Fernandes, Jacques Robert Nicoli, Elisabeth Neumann, Álvaro Cantini Nunes
Publikováno v:
Applied Microbiology, Vol 4, Iss 3, Pp 1150-1164 (2024)
Comparative metatranscriptomics of the bacterial and yeast communities of two milk kefir beverages (MKAA1 and MKAA2) was carried out. They were obtained by fermentation with two different frozen stocks of the kefir grain CIDCA AGK1, differing in rheo
Externí odkaz:
https://doaj.org/article/b7431d1fe53e4a0da3955bbb73eec442
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-17 (2024)
Abstract Large Language Models (LLMs) are characterized by their inherent memory inefficiency and compute-intensive nature, making them impractical to run on low-resource devices and hindering their applicability in edge AI contexts. To address this
Externí odkaz:
https://doaj.org/article/e0c389c6014e469fae6a3dc05f689b61
Autor:
Sans-Planell, Oriol, Cantini, Francesco, Costa, Marco, Durisi, Elisabetta, Grazzi, Francesco, Mafucci, Ettore, Monti, Valeria, Bedogni, Roberto, Li, Yueer, van Eijck, Lambert
The ANET project aims at developing 2D compact neutron collimators for neutron imaging applications. The results of the ANET collimator performances, presented in this communication, are based on data collected at the FISH beamline at TU-Delft. Two i
Externí odkaz:
http://arxiv.org/abs/2301.07749
Autor:
Cantini, Riccardo, Marozzo, Fabrizio, Orsino, Alessio, Talia, Domenico, Trunfio, Paolo, Badia, Rosa M., Ejarque, Jorge, Vazquez, Fernando
Publikováno v:
Journal of Big Data, vol. 11, n. 19, 2024
The extensive use of HPC infrastructures and frameworks for running dataintensive applications has led to a growing interest in data partitioning techniques and strategies. In fact, application performance can be heavily affected by how data are part
Externí odkaz:
http://arxiv.org/abs/2211.10819