Next Technology Tecnotessile (Italy)

A solvent-free approach to the direct polymerization of lactic acid is reported. IR irradiation ensures efficient heating, while acid catalysts promote dehydrative condensation under atmospheric pressure, enabling a green, zero-waste process.

Dementia affects millions of people worldwide, placing a significant burden on healthcare systems. Early and accurate diagnosis is crucial for managing the disease, with clinical tests like the Mini-Mental State Examination (MMSE) playing a key role. To alleviate pressure on healthcare resources and support telemedicine, remote administration of such tests through artificial agents must be explored. However, different administration modalities may evoke varying psychophysiological responses in patients. This study aims to evaluate the feasibility of administering the MMSE via a tablet and compare the psychophysiological responses elicited by tablet-based and psychologist-led administration. Contactless technologies, such as thermography, are used to measure these responses, providing valuable insight into stress and engagement. The Wilcoxon signed rank test delivered a lower engagement state (zval=-3.895, p=9.84·10-5) during the psychologist-administered MMSE when compare with the tablet-based administration. The study explores the potential for tablet-based MMSE administration, demonstrating its reliability and fostering the shifting to digital methods.

Cerebral palsy (CP) is a non-progressive neurologic condition that causes gait limitations, spasticity, and impaired balance and coordination. Robotic-assisted gait training (RAGT) has become a common rehabilitation tool employed to improve the gait pattern of people with neurological impairments. However, few studies have demonstrated the effectiveness of RAGT in children with CP and its neurological effects through portable neuroimaging techniques, such as functional near-infrared spectroscopy (fNIRS). The aim of the study is to evaluate the neurophysiological processes elicited by RAGT in children with CP through fNIRS, which was acquired during three sessions in one month. The repeated measure ANOVA was applied to the β-values delivered by the General Linear Model (GLM) analysis used for fNIRS data analysis, showing significant differences in the activation of both prefrontal cortex (F (1.652, 6.606) = 7.638; p = 0.022), and sensorimotor cortex (F (1.294, 5.175) = 11.92; p = 0.014) during the different RAGT sessions. In addition, a cross-validated Machine Learning (ML) framework was implemented to estimate the gross motor function measure (GMFM-88) from the GLM β-values, obtaining an estimation with a correlation coefficient r = 0.78. This approach can be used to tailor clinical treatment to each child, improving the effectiveness of rehabilitation for children with CP.

Driver’s drowsiness is one of the major causes of traffic accidents worldwide. An early detection of episodes of sleepiness becomes of fundamental importance for safety purposes. Several studies demonstrated that PERCLOS, that is the percentage of eyelid closure over the pupil across time, is one of the most accurate parameters for drowsiness state assessment. However, since PERCLOS is typically computed from the visible video of the subjects, its evaluation is strictly dependent on the lighting conditions and it is not accessible if the driver wears sunglasses. The objective of this study is to overcome these limitations, evaluating drowsy states using a low-cost and high-resolution thermal infrared technology. Ten sleep-deprived subjects were recruited for the experiment, consisting in one-hour driving task on a driving static simulator. During the experiment, facial skin temperature was recorded by means of the thermal camera Device Alab SmartIr640, together with facial visible videos of the subjects. Relevant thermal features were estimated from facial regions of interest (i.e., nose tip, glabella) whereas PERCLOS was performed on visible videos. Features were extracted over a time window of 30 seconds. A data-driven multivariate machine learning approach based on a three-level Support Vector Classification of the drowsy state (AWAKE class: PERCLOS<0.15, FATIGUE class: 0.15<PERCLOS<0.23, and SLEEPY class: PERCLOS>0.15) was employed. The average classification accuracy was 0.65±0.09 (mean ± standard deviation). Although preliminary, these results indicate the possibility to assess driver's drowsiness based on facial thermal features, overcoming the limitation related to lighting condition and eyes detection, typical of standard methods.

Pyomelanin mimics from homogentisic acid (HGA) and gentisic acid (GA) were biosynthesized by the oxidative enzyme T. versicolor laccase at physiological pH to obtain water soluble melanins. The pigments show brown-black color, broad band visible light absorption, a persistent paramagnetism and high antioxidant activity. The EPR approach shows that at least two different radical species are present in both cases, contributing to the paramagnetism of the samples. This achievement can also shed light on the composition of the ochronotic pigment in the Alkaptonuria disease. On the other hand, these soluble pyomelanin mimics, sharing physico-chemical properties with eumelanin, can represent a suitable alternative to replace the insoluble melanin pigment in biotechnological applications.