Politecnico di Torino

Artificial Intelligence for MRI-Based Identification of Autism Spectrum Disorder: A Systematic Review of Methods, Performance, and Clinical Translation

Background Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by impairments in social communication and restricted or repetitive behaviours. Early diagnosis is important for timely intervention, motivating increasing interest in computer-aided diagnos...

A cloud-edge collaborative dual-modal fault detection block for battery packs: Enabling intelligent safety management in electric vehicle battery systems

Intelligent diagnosis of battery pack faults using real-world data has become a key research focus in the era of vehicle-cloud integration. While cloud-based deep learning diagnostics have shown strong capability, edge-based fault diagnosis is increasingly preferred for its real-...

How can prospective life cycle assessment support the eco-design of an innovative battery-grade lithium carbonate production process?

The transition to low-carbon energy systems drives increasing lithium demand, making alternative recovery technologies essential for long-term supply resilience. This study shows how eco-design principles guide the identification of the most environmentally-friendly configuration...

Microfibrillated cellulose-reinforced bio-based epoxy composites for liquid deposition modeling

Abstract Sustainable alternatives to fossil-derived resins for additive manufacturing are increasingly in demand. This study investigates the use of microfibrillated cellulose (MFC) as a renewable reinforcing and rheology-modifying component in bio-based epoxy systems for Liquid...

Additive manufacturing of PHBH and PBAT biopolymers via fused filament fabrication: a comparison between thermal and thermo-mechanical properties

Abstract This study aims to investigate the thermal and thermo-mechanical properties of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBH) and poly (butylene adipate-co-terephthalate) (PBAT) as sustainable alternatives for fused filament fabrication (FFF). Starting from commerc...

Molecular modelling of high-entropy alloys: from quantum to atomistic, and machine learning

Abstract High-entropy alloys (HEAs), characterized by complex multielement compositions, offer broad opportunities to tune mechanical, corrosion, thermal, wetting, and functional properties, while their vast configurational space makes molecular modelling essential. This review e...

The impact of multi-injection events on a compression-ignition engine using ducted fuel injection: A numerical and experimental study

Ducted fuel injection (DFI) is a technology to curtail soot formation from diesel combustion while mitigating its typical trade-off with nitrogen oxides (NOx). Previous studies have demonstrated its potential in both vessel and compression-ignition (CI) engine applications relyin...

Monoaural and Binaural Classroom Acoustics for the Assessment of Speech Comprehension in Primary-School Children

The paper presents the results of monoaural and binaural acoustic measurements and speech-intelligibility tests conducted in two classrooms representative of typical school buildings in Italy. The sample of two classrooms was selected based on a statistical analysis of reverberat...

Semantic-aware decoding of covert inner speech: A multimodal EEG–EMG–audio framework

Non-invasive brain–computer interfaces (BCIs) aim to restore communication by decoding intended messages directly from neural activity, even without audible speech. However, evidence remains limited that non-invasive signals can support subject-held-out decoding of predefined sem...

Leveraging genetic programming to analyze heat transfer and pressure drop characteristics in open-cell metal foams

A numerical analysis of pressure drops and heat transfer characteristics in open-cell metal foams is presented, and predictive correlations relating thermo-fluid-dynamic performance to foam topology and flow conditions are proposed. The new possibilities offered by additive manuf...

Extruded Tunnel Lining Regeneration Project (ETLR): experimental campaign on real scale SFRC tunnel mock-ups

Background Automation in the construction industry is gaining increasing relevance, driven by the need to enhance productivity, foster innovation, and meet evolving societal demands. Slip-forming with extrudable steel fibre-reinforced concrete (SFRC) offers an innovative framewor...

Construction and characterisation of the DarkSide-20k veto silicon photo-multiplier tiles

Abstract Silicon photo-multipliers (SiPMs) are state-of-the-art sensors capable of detecting a single photoelectron under cryogenic conditions, with potentially lower radioactivity than widely used photomultiplier tubes. The DarkSide-20k experiment, designed to perform direct dar...

Backward-Euler Matrix Lyapunov Equation Solver - Theory and User Manual

A research MATLAB package for time-domain covariance analysis of linear time-invariant and time-varying structural systems subjected to non-stationary stochastic excitation, including systems written in augmented state space with input-generating filters. Response second-moment s...

Backward-Euler Matrix Lyapunov Equation Solver - Theory and User Manual

A research MATLAB package for time-domain covariance analysis of linear time-invariant and time-varying structural systems subjected to non-stationary stochastic excitation, including systems written in augmented state space with input-generating filters. Response second-moment s...

Building bridges across borders to co-develop flood early warning in the Sahel

Flood risk in the Sahel has increased markedly over recent decades, driven by the intensification of hydro-climatic hazards and the rapid growth of exposure in urban and peri-urban areas. In this context, FEWSs (FEWSs) are increasingly recognized as a key component of climate ser...

Simulation-guided predictive machine learning framework for optimizing directed energy deposition of Fe-Mn alloys

This study proposes a hybrid Finite Element Modeling (FEM) and Machine Learning (ML) framework for predicting melt pool geometry in the Directed Energy Deposition (DED) of Fe-Mn alloys. A thermal FEM model based on the Goldak double-ellipsoidal heat source was developed and valid...

Automated lung tumor segmentation using enhanced U-Net architectures: a multi-backbone comparative study for clinical applications

Lung cancer remains a leading cause of cancer-related mortality worldwide, and manual delineation of tumors on computed tomography (CT) is time-consuming and prone to inter-observer variability. This study systematically evaluates nine deep learning configurations for automated l...

Predictable and Scalable Analog Matrix–Vector Multiplication in Memristor Crossbars via Closed‐Form Wire‐Resistance Compensation

ABSTRACT Wire resistance in memristor crossbars introduces geometry‐dependent voltage attenuation that degrades analog matrix–vector multiplication (MVM), while parasitic sneak paths further distort output currents as array dimensions scale. Here, we develop a closed‐form distrib...

Photo-guided azopolymer hydrogel actuators

Amorphous azopolymers are fascinating materials that can be deformed in arbitrary directions by light. However, they are so far used mostly for microfabrication, to anisotropically reshape dry polymer structures - essentially as a post-processing fabrication step. This is because...

Interaction of walking activity and long-term air pollution on exacerbation rate in COPD

Background Regular walking activity can improve the prognosis in people with chronic obstructive pulmonary disease (COPD). However, its benefit may be reduced when living in highly polluted areas. Aim To assess the combined effects of walking activity and air pollution on the rat...