Higher Institute on Territorial Systems for Innovation
PORTO@iris (Publications Open Repository TOrino - Politecnico di Torino)Not a member yet
146173 research outputs found
Sort by
Sustainable Plant-Derived Coatings for Titanium Implants: Dual Drug and Ion Release Capabilities
No full textIn this study, hybrid coatings for titanium implants were developed based on strontium titanate layers further functionalized with polyphenols derived from mint, nettle, and sage extracts. The coatings were additionally loaded with ciprofloxacin as an antibacterial agent through interactions with Mg2+ ions present in the polyphenolic part of the layer. The obtained materials were comprehensively characterized using SEM, AFM, FT-IR, zeta potential analysis, water contact angle measurements, corrosion resistance tests, and adhesion studies. The results demonstrated that the type of plant extract significantly influenced the composition and thickness of the polyphenolic layer, which in turn affected ciprofloxacin sorption and release profiles. All coatings enabled a rapid therapeutic release of the antibiotic within the first hour, followed by a sustained release lasting up to 8-10 h. Simultaneously, Mg2+ and Sr2+ ions were released in biologically relevant concentrations, supporting bone tissue regeneration. The hybrid layers markedly enhanced hydrophilicity, corrosion resistance, and adhesion to the Ti6Al4V substrate. These findings highlight the potential of the proposed strategy as a dual-function surface modification, providing both antibacterial protection and osteogenic stimulation, and thus represent a promising approach for next-generation titanium implants. Moreover, the use of plant-derived polyphenols obtained from renewable herbal sources introduces a sustainable and environmentally friendly alternative to synthetic coating agents. The proposed fabrication process relies on aqueous, low-temperature conditions and avoids toxic reagents, aligning with the principles of green chemistry
A Volume-Optimized Hybrid EMI Filter for Automotive Traction Inverters
No full textElectromagnetic interference (EMI) filters play a cru-
cial role in automotive inverters but can occupy a significant por-
tion of the overall system volume, particularly in wide-bandgap
(WBG) semiconductor-based designs, due to their higher power
density compared to Silicon-based ones. To address this issue, this
article proposes the use of active capacitors as a replacement for
passive ones, effectively reducing the required common-mode (CM)
inductance. A detailed analysis of the active capacitor operation
is presented, along with design equations to aid implementation.
Based on this approach, a hybrid EMI filter (HEF) is proposed.
Experimental prototypes have been developed and tested to vali-
date the concept. The results demonstrate that the HEF achieves
comparable filtering performance to conventional passive designs
while reducing the volume of magnetic components by 50%
Inverse consistency error for validating deformable image registration: an explorative study on computational phantoms
No full textBackground and Purpose: Validation of deformable image registration (DIR) remains predominantly contourbased; this study evaluated inverse consistency error (ICE) as an automated voxelwise metric for DIR accuracy.
Materials and Methods: Synthetic ground-truth DVFs were generated using geometric and head-and-neck (HN) digital phantoms undergoing controlled global and local deformations. DIR was performed with the ANACONDA algorithm in RayStation. ICE maps derived from clinical DVFs were compared with ground-truth registration error (GTRE), target registration error (TRE) from 20 anatomical landmarks, and mean distance to agreement (MDA) for 22 propagated ROIs.
Results: Ground-truth DVFs showed negligible ICE values, confirming mathematical invertibility. In HN phantoms, median ICE and GTRE were 0.8 +/- 0.2 mm and 1.6 +/- 0.4 mm, respectively. ICE correlated strongly with GTRE (R = 0.85, p 15 mm due to DIR regularisation. Across all datasets, ICE correctly identified high-uncertainty subregions that were not detected by contour-based metrics.
Conclusions: ICE enables automated voxel-wise quantification of DIR uncertainty directly from clinical DVFs. It complements traditional contour-based metrics and may support patient-specific QA and more reliable dose mapping in adaptive and re-irradiation radiotherapy workflows
STEM-CARES
No full textScience, Technology, Engineering, and Mathematics (STEM) education is at a critical juncture in the era of artificial intelligence (AI), where educators’ ability to integrate emerging technologies could significantly impact learning and innovation. However, many of them face multiple barriers, including limited access to practical resources, collaborative platforms, and AI-driven teaching strategies tailored to their needs. Additionally, gaps in AI literacy, disparities in technological infrastructure, resistance to change, and insufficient professional development hinder effective implementation, widening educational inequalities and limiting the adoption of innovative pedagogical approaches in STEM education. These challenges create a growing divide between technological advancements and their meaningful integration into higher education, restricting educators’ ability to prepare students for AI-driven careers. In response, STEM-CARES (STEM Community for AI Resources and Educational Strategies) emerges as a solution to bridge these gaps through a dynamic platform that provides curated AI-based teaching strategies, fosters real-time collaboration, and promotes the ethical integration of AI in education. This initiative seeks to empower educators by offering centralized access to AI-enhanced resources, facilitating a global knowledge-sharing community, and leveraging AI to address disparities in access to digital tools. The expected impact includes improved teaching quality, increased student engagement, professional growth for educators, and the development of scalable AI-driven strategies that provide actionable insights for educational policy and EdTech innovation. By combining interdisciplinary expertise, STEM-CARES aspires to become a leading model for global collaboration in STEM education, aligning with international efforts to build inclusive, high-quality, and future-ready learning environments where AI can be a catalyst for equality and innovation
Road Obstacle Video Segmentation
No full textWith the growing deployment of autonomous driving agents, the detection and segmentation of road obstacles have become critical to ensure safe autonomous navigation. However, existing road-obstacle segmentation methods are applied on individual frames, overlooking the temporal nature of the problem, leading to inconsistent prediction maps between consecutive frames. In this work, we demonstrate that the road-obstacle segmentation task is inherently temporal, since the segmentation maps for consecutive frames are strongly correlated. To address this, we curate and adapt four evaluation benchmarks for road-obstacle video segmentation and evaluate 11 state-of-the-art image- and video-based segmentation methods on these benchmarks. Moreover, we introduce two strong baseline methods based on vision foundation models. Our approach establishes a new state-of-the-art in road-obstacle video segmentation for long-range video sequences, providing valuable insights and direction for future research
Design and Fabrication of 2D Filler-Reinforced Nanostructured Composites for Advanced Hydrogen Energy Applications
No full textL'abstract è presente nell'allegato / the abstract is in the attachmen
Sparse Gabor representations of metaplectic operators: controlled exponential decay and Schrödinger confinement
Full text linkMotivated by the phase space analysis of Schrödinger evolution operators, in this paper we investigate how metaplectic operators are approximately diagonalized along the corresponding symplectic flows by exponentially localized Gabor wave packets. Quantitative bounds for the matrix coefficients arising in the Gabor wave packet decomposition of such operators are established, revealing precise exponential decay rates together with subtler dispersive and spreading phenomena. To this end, we present several novel results concerning the time-frequency analysis of functions with controlled Gelfand-Shilov regularity, which are of independent interest.
As a byproduct, we generalize Vemuri's Gaussian confinement results for the solutions of the quantum harmonic oscillator in two respects, namely by encompassing general exponential decay rates as well as arbitrary quadratic Schrödinger propagators. In particular, we extensively discuss some prominent models such as the harmonic oscillator, the free particle in a constant magnetic field and fractional Fourier transforms
Toward Robust, Responsible and Trustworthy Speech Foundation Models
Full text linkL'abstract è presente nell'allegato / the abstract is in the attachmen
Time-domain parametric models for floating structures: A Loewner-based approach
Full text linkDesign, control, and optimisation of offshore floating structures have undergone significant evolution in recent years, driven by cutting-edge technology, including novel marine renewable energy sources and autonomous underwater vehicles. A key cornerstone is the availability of mathematical models capable of providing an accurate (yet computationally tractable) prediction of their behaviour, under different ocean conditions. The most widely adopted approach for capturing fluid–structure interactions is based on linear potential flow theory, where the system’s hydrodynamic behaviour is described through a finite set of frequency-dependent linear coefficients. A well-known limitation of this frequency-domain approach is its inherently non-parametric nature: if not parameterised accordingly, effective time-domain simulation necessitates the numerical solution of a convolution operator, which describes memory effects due to the surrounding fluid, an approach inconvenient for both simulation (computational) and control design (representational compatibility). Not only is a closed-form expression fundamental, but any candidate parametric model also needs to comply with the physical properties characterising a floating structure, including input/output stability, minimum-phase behaviour, and passivity. This paper presents a novel approach to producing physically consistent parametric structures for time-domain modelling of floating systems, utilising a Loewner-based method. The models, capable of providing approximate interpolation of raw frequency-domain data computed with off-the-shelf hydrodynamic solvers, accurately capture the complex behaviour of multi-mode and multi-body offshore structures, while respecting the dynamical properties associated with the system’s physics. The technique is illustrated in detail, using four different offshore structures from various fields of ocean engineering, highlighting the benefits of the proposed time-domain modelling framework
The Dirichlet problem on lower dimensional boundaries: Schauder estimates via perforated domains
Full text linkIn this paper, we investigate the Dirichlet problem on lower dimensional manifolds for a
class of weighted elliptic equations with coefficients that are singular on such sets. Specifically, we study
the problem
(
− div(|y|
aA(x, y)∇u) = |y|
a
f + div(|y|
aF),
u = ψ, on Σ0,
where (x, y) ∈ R
d−n × R
n
, 2 ≤ n ≤ d, a + n ∈ (0, 2), and Σ0 = {|y| = 0} is the lower dimensional
manifold where the equation loses uniform ellipticity.
Our primary objective is to establish C
0,α and C
1,α regularity estimates up to Σ0, under suitable
assumptions on the coefficients and the data. Our approach combines perforated domain approximations,
Liouville-type theorems and a blow-up argument