Recent advances in materials and fabrication techniques provided portable, performant, sensing optical spectrometers readily operated by user-friendly cabled or wireless systems. Such systems allow rapid, non-invasive, and not destructive quantitative analysis of human tissues. This proof-of-principle investigation tested whether infrared spectroscopy techniques, currently utilized in a variety of areas, could be applied in living humans to categorize muscles. Using an ASD FieldSpec® 4 Standard-Res Spectroradiometer with a spectral sampling capability of 1.4 nm at 350–1000 nm and 1.1 nm at 1001–2500 nm, we acquired reflectance spectra in visible short-wave infra-red regions (350–2500 nm) from the upper limb muscles (flexors and extensors) of 20 healthy subjects (age 25–89 years, 9 women). Spectra off-line analysis included preliminary preprocessing, Principal Component Analysis, and Partial Least-Squares Discriminant Analysis. Near-infrared (NIR) spectroscopy proved valuable for noninvasive assessment of tissue optical properties in vivo . In addition to the non-invasive detection of tissue oxygenation, NIR spectroscopy provided the spectral signatures (ie, “fingerprints”) of upper limb flexors and extensors, which represent specific, accurate, and reproducible measures of the overall biological status of these muscles. Thus, non-invasive NIR spectroscopy enables more thorough evaluation of the muscular system and optimal monitoring of the effectiveness of therapeutic or rehabilitative interventions.

Objectives: To detect on computed tomography (CT) brain scans the trajectories of normal and abnormal ventricular enlargement during aging.Methods: For each 1-year age cohort, we assessed in 3,193 axial CT scans the Evans’ index (EI) in the anterior frontal horns and the parieto-occipital (POR) and temporal ratio (TR) in the posterior and inferior horns. Cut-off values for abnormal enlargement were based on previous clinical studies.Results: The mean age associated with normal linear measures was 71 years. Values for all three measures increased with age, showing a linear relationship below—but not above—each cut-off value. The mean age of participants with abnormal enlargement on CT progressed from 79 years for EI to 83 years for POR to 87 years for TR. These results suggested that ventricular dilatation progresses in an age–location relationship. First comes enlargement of the frontal horns (13.8% of scans), followed by the parieto-occipital horns (15.1% of scans) and then temporal horn enlargement (6.8% of scans). Scans from men displayed abnormal values earlier than scans from women (on average 6 years). Risk increased 5.1% annually for abnormal EI, 9.0% for abnormal POR, and 11% for abnormal TR (all p < 0.001). The most frequent agreement between categories (normal–abnormal) for values of neuroimaging measures was identified for POR–TR.Conclusion: The results of this large radiological study suggest that the ventricular system enlarges progressively during aging, and in a subset of patients follows an abnormal consecutive geometric dilatation, influenced by age and sex.

The technological innovation and the relentless marketing of new electronic products with improved performance generate increasing quantities of Waste from Electrical and Electronic Equipment (WEEE). In this scenario, End-Of-Life (EOL) flat monitors and screens represent a category generating, as a consequence of the rapid change in technology, an important amount of waste. Considering future estimations, the implementation of an adequate recycling infrastructure is necessary. An efficient, reliable and low-cost analytical tool is thus needed to perform detection/control actions in order to assess: i) waste composition and ii) physical-chemical attributes of the resulting materials. The knowledge of these information is a requirement to set-up and to implement correct recycling actions.In this study, a cascade identification approach, based on Near InfraRed (NIR) – HyperSpectral Imaging (HSI), was carried out. More in detail, a four-steps classification was designed, implemented and set-up in order to recognize different materials occurring in a specific WEEE stream: EOL milled monitors and flat screens. Adopting the proposed approach, different material categories are correctly recognized and classified. Obtained results can be useful not only to set-up a quality control system, but also to improve sorting actions in this specific recycling sector.

Recycling of post-consumer packaging wastes involves a complex chain of activities, usually based on three main stages, that is: i) collection from households or recovery from Municipal solid waste (MSW), ii) sorting and, finally, iii) mechanical recycling. The systematic identification of impurities inside plastic packaging waste streams, and the assessment of the different occurring materials, can be considered as one of the key issues to certify and to classify waste materials fed to recycling plants and to perform a full control of the resulting processed fractions and byproducts, that have to comply with market demands. The utilization of a Near InfraRed (NIR) – HyperSpectral Imaging (HSI) based methods, along with chemometrics and machine learning techniques, can fulfill these goals. In this paper, the HSI-based sorting logics, to apply, to implement and to set up to perform an automatic separation of paper, cardboard, plastics and multilayer packaging are investigated.

Recent advances in materials and fabrication techniques provided portable, performant, sensing optical spectrometers readily operated by user-friendly cabled or wireless systems. such systems allow rapid, non-invasive, and not destructive quantitative analysis of human tissues. This proof-ofprinciple investigation tested whether infrared spectroscopy techniques, currently utilized in a variety of areas, could be applied in living humans to categorize muscles. Using an ASD FieldSpec® 4 Standard-Res Spectroradiometer with a spectral sampling capability of 1.4 nm at 350-1000 nm and 1.1 nm at 1001-2500 nm, we acquired reflectance spectra in visible shortwave infra-red regions (350-2500 nm) from the upper limb muscles (flexors and extensors) of 20 healthy subjects (age 25-89 years, 9 women). Spectra off-line analysis included preliminary preprocessing, Principal Component Analysis, and Partial Least-Squares Discriminant Analysis. Near-infrared (NIR) spectroscopy proved valuable for noninvasive assessment of tissue optical properties in vivo. In addition to the non-invasive detection of tissue oxygenation, NIR spectroscopy provided the spectral signatures (ie, "fingerprints") of upper limb flexors and extensors, which represent specific, accurate, and reproducible measures of the overall biological status of these muscles. Thus, non-invasive NIR spectroscopy enables more thorough evaluation of the muscular system and optimal monitoring of the effectiveness of therapeutic or rehabilitative interventions.