A robotic model to investigate human motor control

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1H-NMR-Based Metabolomics in Autism Spectrum Disorder and Pediatric Acute-Onset Neuropsychiatric Syndrome

We recently described a unique plasma metabolite profile in subjects with pediatric acute-onset neuropsychiatric syndrome (PANS), suggesting pathogenic models involving specific patterns of neurotransmission, neuroinflammation, and oxidative stress. Here, we extend the analysis to a group of patients with autism spectrum disorder (ASD), as a consensus has recently emerged around its immune-mediated pathophysiology with a widespread involvement of brain networks. This observational case-control study enrolled patients referred for PANS and ASD from June 2019 to May 2020, as well as neurotypical age and gender-matched control subjects. Thirty-four PANS outpatients, fifteen ASD outpatients, and twenty-five neurotypical subjects underwent physical and neuropsychiatric evaluations, alongside serum metabolomic analysis with 1H-NMR. In supervised models, the metabolomic profile of ASD was significantly different from controls (p = 0.0001), with skewed concentrations of asparagine, aspartate, betaine, glycine, lactate, glucose, and pyruvate. Metabolomic separation was also observed between PANS and ASD subjects (p = 0.02), with differences in the concentrations of arginine, aspartate, betaine, choline, creatine phosphate, glycine, pyruvate, and tryptophan. We confirmed a unique serum metabolomic profile of PANS compared with both ASD and neurotypical subjects, distinguishing PANS as a pathophysiological entity per se. Tryptophan and glycine appear as neuroinflammatory fingerprints of PANS and ASD, respectively. In particular, a reduction in glycine would primarily affect NMDA-R excitatory tone, overall impairing downstream glutamatergic, dopaminergic, and GABAergic transmissions. Nonetheless, we found metabolomic similarities between PANS and ASD that suggest a putative role of N-methyl-D-aspartate receptor (NMDA-R) dysfunction in both disorders. Metabolomics-based approaches could contribute to the identification of novel ASD and PANS biomarkers

Sistema per l’identificazione di difetti su una superficie di almeno una porzione di una scocca e relativo metodo

La presente invenzione riguarda un sistema e un metodo per l’identificazione, la classificazione e la successiva rimozione di difetti di fabbricazione presenti sui componenti di veicoli

UAVIMALS: Unmanned Aerial Vehicle Integrated with Micro Airborne Laser Scanner

Il progetto consiste in un piccolo drone, leggero e trasportabile, utile come strumento di rilievo della morfologia della superficie del terreno. La sua ingegnerizzazione è stata il frutto di un finanziamento National Geographic Society che ha consentito l’integrazione tra un mezzo personalizzato e un sensore laser a stato solido. Il sistema ha ottenuto ottimi risultati nel context test, la città medievale di Cencelle (VT), rivelando i profili di due grandi ambienti urbani, posti a ridosso delle mura urbiche, non ancora intercettati dalle indagini di scavo

A novel shared control algorithm for industrial robots

Human management of robots in many specific industrial activities has long been imperative, due to the elevated levels of complexity involved, which can only be overcome through long and wasteful preprogrammed activities. The shared control approach is one of the most emergent procedures that can compensate and optimally couple human smartness with the high precision and productivity characteristic to mechatronic systems. To explore and to exploit this approach in the industrial field, an innovative shared control algorithm was elaborated, designed and validated in a specific case study