Archivio della ricerca della Scuola Superiore Sant'Anna
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Enhancing upper limb motor recovery prediction after acute stroke using EEG and subacute data
No full textElectroencephalography (EEG) has shown promise in assessing and monitoring functional recovery in stroke survivors, but its utility in predicting upper limb motor recovery in a data-driven framework remains underexplored. This study presents a novel EEG-based machine-learning model, StrokeRecovNet, developed to predict motor recovery outcomes based on the upper extremity subscale of the Fugl-Meyer Assessment (FMAUE). StrokeRecovNet is a feed-forward neural network optimized for regression tasks, leveraging 221 candidate EEG biomarkers, spanning spectral and functional connectivity domains, along with baseline clinical information. These inputs are used to predict follow-up FMAUE scores in stroke survivors who underwent standard rehabilitative protocols. We validated our pipeline on two independent datasets of patients in the acute and subacute post-stroke phases. StrokeRecovNet consistently outperformed the proportional recovery rule (PRR), a standard benchmark based on initial impairment, in predicting FMAUE scores in the subacute stage (median absolute error, MAE: StrokeRecovNet = 5.85, PRR = 19.00). Incorporating support data from the subacute dataset led to improved predictive performance in the acute sample (MAE: StrokeRecovNet = 5.87, PRR = 8.80), whereas the model trained solely on the acute data did not (MAE: 13.74). Key features contributing to the model's success included brain symmetry indices and functional connectivity measures, evolving across recovery stages. These findings demonstrate the potential of EEG-based biomarkers to predict individual recovery trajectories. This work introduces a novel, data-driven approach to forecasting upper limb recovery using EEG and suggests that EEG data from the subacute stage, which is more readily available in clinical settings, can enhance early predictions, paving the way for personalized post-stroke rehabilitation strategies
Improved residual stress evaluation with Hole-Drilling and DIC through the L-curve tool and super-resolution along depth
No full textFull-field methods such as Electronic Speckle Pattern Interferometry (ESPI) and Digital Image Correlation (DIC)
emerge as promising alternatives to strain rosette in the hole-drilling method, each with its own advantages
and limitations. In particular, DIC stands out as a method requiring minimal (and cheap) specimen preparation;
however, its sensitivity is approximately one order of magnitude lower than that of conventional strain gauge
techniques.
We address two fundamental questions. First, how can the inverse problem of the hole-drilling method
be systematically approached outside the well-established framework of ASTM E837, which provides users
with comprehensive guidance, including automated regularization procedures? Second, thanks to full-field
measurement techniques, is it possible to retrieve stress distributions at a spatial resolution finer than the
drilling step?
We revisit the theoretical development of the inverse problem, aiming to directly identify the residual
stresses from raw images, without intermediate pre-processing of the displacement fields. We introduce the
L-curve method – well established in other scientific domains – as a rational tool for the choice of the
regularization parameter. Finally, we show that, in principle, it would be possible to identify the entire stress
distribution from a single drilling increment. We perform a deep rolling treatment on an aluminum specimen
and compare the residual stresses identified using both a strain gauge rosette and DIC.
We demonstrate that the proposed framework yields results comparable to those obtained using strain
gauge rosettes, while minimizing user-dependent arbitrariness. Furthermore, we show that depth superresolution
of at least a factor of two is already achievable with current technological capabilities
ATTIVITÀ DI FORMAZIONE E COMUNICAZIONE DI CUI ALLA MISURA “PNRR M6C2 1.3.1 B) PER L’ADOZIONE E L’UTILIZZO FSE DA PARTE DELLE REGIONI – RISORSE PER COMPETENZE DIGITALI” FORMAZIONE DEI FORMATORI
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Educazione interculturale e vulnerabilità: una chiave di lettura efficace per l’inclusione scolastica?
No full textIl saggio esamina il rapporto tra educazione interculturale e vulnerabilità, interrogandosi sulla possibilità di utilizzare quest’ultima come criterio interpretativoper indagare l’effettività della tutela dei diritti fondamentali ingioco inuna prospettiva di eguaglianza sostanziale e personalista. A partire da una ricostruzione teorica delle due nozioni, il contributo ne indaga potenzialità e limiti nel contesto dell’inclusione scolastica di diverse condizioni di vulnerabilità, qualiquelle delle persone con disabilità e con backgroundmigratorio. A tal fine, l’analisi tiene conto del ruolo propulsivo svolto dalla giurisprudenzadella Cortecostituzionaleitalianae della Corte europea dei diritti dell’uomo, nonché dei principali strumenti normativi, a livello siasovranazionale sia interno. L’articolo mette in luce come un impiego flessibile e intersezionale della vulnerabilità possa contribuire a orientare politiche più inclusive, in coerenza con l’orizzonte universalistico dell’educazione interculturale
Lateralized differences in ultrasonic courtship songs and their impact on reproductive strategies in Ostrinia furnacalis (Lepidoptera: Crambidae)
No full textBACKGROUND: Lateralized courtship behaviors in Ostrinia furnacalis (Guenée) play a pivotal role in reproductive success. However, the variation in ultrasonic courtship sounds produced by males during these lateralized displays, and their subsequent impact on mating success, remain unexplored. To address this gap, this study examined differences in the ultrasonic courtship song characteristics of left- and right-biased courtship displays and their influence on mating outcomes. Mating trials were conducted to record and analyze variations in ultrasonic courtship songs behaviours and associated acoustic parameters, including dominant frequencies, pulse durations, pulse intervals, and the number of pulses emitted during left- and right-biased displays, as defined by the male's turning direction during copulation attempts. RESULTS: Our findings revealed that left-biased ultrasonic songs featured shorter pulse durations, tighter inter-pulse intervals, and dominant frequencies between 55 and 65 kHz. These acoustic traits closely matched profiles observed in successful mating events, whereas right-biased emissions (65–80 kHz) were frequently associated with unsuccessful mating attempts. Left-biased songs of shorter duration (28–38 s) were positively correlated with greater mating success, whereas the longer durations observed in right-biased displays (40–60 s) were linked to lower mating success. Moreover, males exhibiting left-biased courtship behavior required fewer mating attempts to achieve successful copulation. CONCLUSIONS: This study provides the first clear evidence of lateralized ultrasonic courtship behavior in O. furnacalis, with left-biased displays conferring a reproductive advantage. The findings highlight the ecological and evolutionary importance of acoustic lateralization in moth communication. Future research should investigate how ecological factors such as predator-driven selection, habitat structure, and female sensory biases influence these lateralized courtship behaviors. Such understanding can directly support more effective, behaviorally informed pest control strategies. These results contribute to the development of targeted approaches, such as pheromone traps and acoustic interference. © 2025 Society of Chemical Industry
Using deep learning to assess the toxicological effects of sublethal exposure of a novel green pesticide in a stored‐product beetle
No full textBACKGROUND: Managing stored-grain pests requires new strategies to limit economic and health risks. This study analyses the sublethal effects of the natural compound carlina oxide on Prostephanus truncatus, providing new behavioural insights through a multidisciplinary approach. A fully automatic computer vision approach was developed to label two specific insect body parts, enabling the generation of an annotated dataset without manual intervention. This dataset was used to train a convolutional neural network (CNN) for pose estimation. A second dedicated CNN focused on the antennae to investigate neuroethological and sensory variations. RESULTS: CNN for body parts detection achieved an average precision of 0.78, recall of 0.90, and F1 score of 0.84 on the test dataset. An additional CNN tracked key points for antennal pose estimation. Motor analysis showed that the LC30 of carlina oxide reduced average speed and distance, induced altered exploratory behaviour, and affected thigmotaxis. Statistically significant features were evaluated using machine learning classifiers: random forest, support vector machine, and K-nearest neighbours. The analysis comparing control and treated groups distinguishes LC30 and LC10 from the control group, while SHapley Additive exPlanation (SHAP) analysis explained the features contribution to predictions. CONCLUSIONS: Metrics poorly distinguish individuals in the LC10 and LC30 classes, supporting the employment of lower sublethal concentration for the control of P. truncatus. However, our findings indicate possible neuroethological effects of green pesticides on sensory systems, highlighting the need for an accurate risk assessment to minimize ecosystem impacts and supporting integrated pest management within One-Health and Eco-Health frameworks. © 2026 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry
Succinate Modulation as a Biochemical Correlate of Metabolic and Neurobehavioral Changes Associated With Intermittent Fasting in Obesity
No full textAim: Obesity significantly impacts the central nervous system (CNS), increasing the risks of neuropsychiatric disorders and dementia. Intermittent fasting (IF) shows promise for improving peripheral and CNS health, but its mechanisms are unclear. Methods: Using a diet-induced obesity mouse model [10 weeks high fat diet (HFD), then 4 weeks intervention], we compared HFD, HFD-IF, ad libitum control chow (CC), and CC-IF groups. Results: Switching to CC or IF reduced body weight, fat mass, and improved glucose tolerance. Notably, CC-IF uniquely enhanced exploration and reduced anxiety-like behavior. Transcriptomics revealed HFD-induced hippocampal neuroinflammation, whereas metabolomics identified a specific succinate signature in CC-IF mice: plasma concentration decreased, whereas liver and brown adipose tissue (BAT) levels increased. Succinate supplementation mimicked CC-IF metabolic and behavioral benefits and reduced hippocampal inflammation. Conclusion: These findings suggest that regulating plasma succinate and its metabolism in liver and BAT may represent a novel biochemical correlate underlying the metabolic, neuroinflammatory, and behavioral improvements induced by IF