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Iterative Classification of Graph-Set-Based Designs (IC-GSBD) for the Down-Selection of Aircraft Thermal Management Systems

Autor: Sirico Jr., Anthony, Herber, Daniel R

In this paper, we present Iterative Classification of Graph-Set-Based Design (IC-GSBD), a framework utilizing graph-based techniques with geometric deep learning (GDL) integrated within a set-based design (SBD) approach for the classification and dow

Externí odkaz: http://arxiv.org/abs/2312.03270

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On the Use of Geometric Deep Learning for the Iterative Classification and Down-Selection of Analog Electric Circuits

Autor: Sirico Jr., Anthony, Herber, Daniel R.

Many complex engineering systems can be represented in a topological form, such as graphs. This paper utilizes a machine learning technique called Geometric Deep Learning (GDL) to aid designers with challenging, graph-centric design problems. The str

Externí odkaz: http://arxiv.org/abs/2303.09770

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Akademický článek

Multimodality imaging and functional assessment in patients with systemic right ventricle and biventricular physiology: a retrospective single-center study

Autor: Alice Pozza, Martina Avesani, Irene Cattapan, Elena Reffo, Annachiara Cavaliere, Jolanda Sabatino, Sofia Piana, Anna Molinaroli, Domenico Sirico, Biagio Castaldi, Alessia Cerutti, Roberta Biffanti, Giovanni di Salvo

Publikováno v: Monaldi Archives for Chest Disease (2024)

Systemic right ventricle (sRV) dysfunction is frequent in patients with congenitally corrected transposition of great arteries (cc-TGA) and those with dextro-transposition of great arteries (D-TGA) after Mustard/Senning operations. This condition sho

Externí odkaz: https://doaj.org/article/4eb14aedafd94ce78d3f06bf3117ed49

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Single-cell phase-contrast tomograms data encoded by 3D Zernike descriptors

Autor: Memmolo, Pasquale, Pirone, Daniele, Sirico, Daniele G., Miccio, Lisa, Bianco, Vittorio, Ayoub, Ahmed B., Psaltis, Demetri, Ferraro, Pietro

Phase-contrast tomographic flow cytometry combines quantitative 3D analysis of unstained single cells and high-throughput. A crucial issue of this method is the storage and management of the huge amount of 3D tomographic data. Here we show an effecti

Externí odkaz: http://arxiv.org/abs/2207.04854

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Akademický článek

Implications of hormonal carcinogenesis for transgender and gender-diverse people undergoing gender-affirming hormone therapy: an up-to-date review

Autor: Matteo Lambertini, Filippo Pietrantonio, Dario Trapani, Francesco Perrone, Rossana Berardi, Saverio Cinieri, Chiara Cassani, Amelia Barcellini, Filippo Ghelardi, Alberto Giovanni Leone, Stefania Bonadonna, Marianna Sirico, Barbara Tagliaferri, Stefano Maccarone, Davide Dalu, Lorenzo Ruggieri, Simone Nardin, Nicla La Verde

Publikováno v: BMJ Oncology, Vol 3, Iss 1 (2024)

Transgender and gender-diverse (TGD) individuals face an elevated risk of cancer in comparison with the general population. This increased risk is primarily attributed to an imbalanced exposure to modifiable risk factors and a limited adherence to ca

Externí odkaz: https://doaj.org/article/cd6d545d3744429793ab86b364cf13fe

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