Publications by authors named "S Silvestri"

Chondrosarcomas (CHS) constitute approximately 20% of all primary malignant bone tumors, characterized by a slow growth rate with initial manifestation of few signs and symptoms. These malignant cartilaginous neoplasms, particularly those with dedifferentiated histological subtypes, pose significant therapeutic challenges, as they exhibit high resistance to both radiation and chemotherapy. Ranging from relatively benign, low-grade tumors (grade I) to aggressive high-grade tumors with the potential for lung metastases and a grim prognosis, there is a critical need for innovative diagnostic and therapeutic approaches, particularly for patients with more aggressive forms.

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Article Synopsis
  • The study aims to evaluate the effectiveness of seismocardiogram (SCG) and gyrocardiogram (GCG) in differentiating aortic stenosis (AS) patients from healthy individuals, discovering the best sensor placement for accurate classification.
  • SCG and GCG data were collected from 15 participants and analyzed using both machine learning and deep learning techniques, yielding the highest accuracy from the Support Vector Machine (SVM) at specific heart locations.
  • By combining SCG and GCG signals, accuracy improved significantly, reaching up to 97.2% with a single sensor, demonstrating a reliable method for classifying AS patients.
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The assessment of unilateral spatial neglect (USN) primarily relies on paper-and-pencil tests, which do not fully represent daily life difficulties. To address this limitation, ecological tests, like the Baking Tray Test (BTT), have been developed. However, the original BTT identifies the presence of USN without providing information on its severity.

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This study focuses on the integration and validation of a filtering face piece 3 (FFP3) facemask module for monitoring breathing activity in industrial environments. The key objective is to ensure accurate, real-time respiratory rate (RR) monitoring while maintaining workers' comfort. RR monitoring is conducted through temperature variations detected using temperature sensors tested in two configurations: sensor t, integrated inside the exhalation valve and necessitating structural mask modifications, and sensor t, mounted externally in a 3D-printed structure, thus preserving its certification as a piece of personal protective equipment (PPE).

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This is the first record on literature to use biochar as support for CoFeO to applicate and evaluate it as photocatalyst for degradation of organic pollutants. The support was verified by XRD, FT-IR, SEM, EDS and band gap. Composites CFO1BQ3, CFO1BQ1, and CFO3BQ1 showed 100% degradation in 60 min.

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