Computer-aided optical characterization and sensing applications: from minerals to waste

Optical based characterization techniques and related analytical methodologies, originally utilized in the mineral sector, can be profitably applied to solid waste streams products as resulting from different recycling processes. This approach, when supported by digital tools allows to perform a full characterization of compositional and textural attributes of the different particulate solids constituting the waste flow streams. To reach this goal specific physical-chemical attributes must be collected, analyzed and processed in order to define, according to market requirements, specific classes of quality to assume as reference to define optimal processing strategies. Computer-assisted optical characterization, coupled with hyperspectral sensing devices and embedding recognition/classification logics, can contribute to reach these goals, dramatically reducing analytical time and costs. In this work an example of this “transfer approach”, from minerals to waste, is presented, analyzed and discussed, with reference to a porphyry copper ore sample and a WEEE product

NIR spectral signatures of flexor and extensor muscles of the upper and lower limb in humans at varying lengths

NIR spectroscopy provides the spectral signatures (i.e. “fingerprints”) of living human muscles, which represent specific, accurate, and reproducible measures of their overall biological status. We showed that chemometric analysis applied to NIR spectra acquired from the upper limb distinguishes the biceps from the triceps. We acquired muscles reflectance spectra in the Vis-SWIR regions (350-2500 nm), utilizing 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. Optical spectroscopy proves effective for studying human muscles in vivo and contribute to non-invasive more thorough evaluation of the muscular system

Il riciclo meccanico dei rifiuti di apparecchiature elettriche ed elettroniche. Una sfida tecnologica

Due to the technological progress, electronics became more and more part of our lifestyle. Alongside the continuous progress, the volume of electric and electronic waste (WEEE) steady arising. The WEEE, because of a large number of hazardous substances in various equipment, such as lead in printed circuit boards and cadmium in semiconductor chips, could cause serious environmental problems if not properly handled at the end of their life cycle (i.e. recycling and/or disposed-off). However, a significant amount of valuable materials is contained in WEEE, such as metals, high-quality plastic and other materials/elements that can be profitably recovered. WEEE recycling is considered a real opportunity for contrasting an inbound threat for the Industry and for the Environment. For these reasons it is thus essential to improve the WEEE recycling process, both from an economic and an environmental point of view. These two goals can be reached adopting new, and up-to-date, processing/recycling strategies based on innovative technologies allowing to implement more environmentally friendly and economically sustainable processing

Near InfraRed-based hyperspectral imaging approach for secondary raw materials processing in solid waste sector

In secondary raw materials and industrial recycling sectors there is the need of solving quality control issues. The development and deployment of an effective, fast and robust sensing architecture able to detect, characterize and sort solid waste products is of primary importance. Near InfraRed (NIR) based HyperSpectral Imaging (HSI) techniques to detect materials to recycle and/or solid waste products to process represents an interesting solution to address quality control issues in these sectors. In this paper, are presented two different case studies on the utilization of NIR-HSI to detect contaminants in household plastic packaging waste and recognize materials occurring in processed monitors and flat screen waste. The proposed approach consists of a cascade detection based on Partial Least Squares – Discriminant Analysis (PLS-DA) classifiers applied on hyprspectral images acquired in NIR range (1000-1700 nm)

Hyperspectral imaging logics: efficient strategies for agri-food products quality control

The increasingly normative severity and market competitiveness have led the agriculture sector and the food industry to constantly look for logic improvements that can be applied in processes monitoring systems. In a context where fast, non-destructive and reliable techniques are required, image analysis-based methods have gained interest, thanks to their ability to spatially characterize heterogeneous samples. In such a scenario, HyperSpectral Imaging (HSI) is an emerging technique that provides not only spatial information of imaging systems, but even spectral information of spectroscopy. The utilization of the HSI approach opens new interesting scenario to quality control logics in agricultural and food processing/manufacturing sectors. Three different case studies are presented in this paper. In particular, the utilization of an HSI system, working in SWIR range, was applied for: i) detecting contaminants in dried fruits to be packaged, ii) identifying olive fruits attacked by olive fruit flies and iii) recognizing flour type. In particular, the proposed approach is based on the application of Partial Least Squares – Discriminant Analysis (PLS-DA) classification method to HyperSpectral images in Short Wave InfraRed (SWIR) range (1000-2500 nm). The proposed case studies demonstrate that this logic can be successfully utilized as a quality control system on agri-food products coming from different manufacturing stages, but it can even be seen as an analytical core for sorting engines

Hyperspectral imaging applied to WEEE plastic recycling. A methodological approach

In this study, the possibility of applying the hyperspectral imaging (HSI) technique in the Short-Wave InfraRed (SWIR) spectral range to characterize polymeric parts coming from Waste from Electric and Electronic Equipment (WEEE) is explored. Different case studies are presented referring to the identification of (i) plastic flakes inside a mixed waste stream coming from a recycling plant of monitors and flat screens, (ii) different polymers inside a mixed plastic waste stream coming from End-Of-Life (EOL) electronic device housings and trims, (iii) contaminants (i.e., metals) in a mix of shredded plastic particles coming from a recycling line of electrical cables, and (iv) brominated plastics in mixed streams constituted by small appliances (i.e., cathode-ray tube televisions and monitors). The application of chemometric techniques to hyperspectral data demonstrated the potentiality of this approach for systematic utilization for material characterization, quality control and sorting purposes. The experimental findings highlight the feasibility of employing this method due to its user-friendly nature and quick detection response. To increase and optimize WEEE valorization avoiding disposal in landfills or incineration, recycling-oriented characterization and/or quality control of the processed products are fundamental to identify and quantify substances to be recovered

A dataset of Visible – Short Wave InfraRed reflectance spectra collected in–vivo on the dorsal and ventral aspect of arms

Advancement of technology and device miniaturization have made near infrared spectroscopy (NIRS) techniques cost–effective, small–sized, simple, and ready to use. We applied NIRS to analyze healthy human muscles in vivo, and we found that this technique produces reliable and reproducible spectral “fingerprints” of individual muscles, that can be successfully discriminated by chemometric predictive models. The dataset presented in this descriptor contains the reflectance spectra acquired in vivo from the ventral and dorsal aspects of the arm using an ASD FieldSpec® 4 Standard–Res field portable spectroradiometer (350–2500 nm), the values of the anthropometric variables measured in each subject, and the codes to assist access to the spectral data. The dataset can be used as a reference set of spectral signatures of “biceps” and “triceps” and for the development of automated methods of muscle detection

Near-Infrared Transflectance Spectroscopy Discriminates Solutions Containing Two Commercial Formulations of Botulinum Toxin Type A Diluted at Recommended Volumes for Clinical Reconstitution

: Botulinum neurotoxin type A (BoNT-A) is the active substance in pharmaceutical preparations widely used worldwide for the highly effective treatment of various disorders. Among the three commercial formulations of BoNT-A currently available in Italy for neurological indications, abobotulinum A toxin (Dysport\uae, Ipsen SpA, Milano, Italy) and incobotulinum A toxin (Xeomin\uae, Merz Pharma Italia srl, Milano, Italy) differ in the content of neurotoxin, non-toxic protein, and excipients. Clinical applications of BoNT-A adopt extremely diluted solutions (10-6 mg/mL) for injection in the target body district. Near-infrared spectroscopy (NIRS) and chemometrics allow rapid, non-invasive, and non-destructive methods for qualitative and quantitative analysis. No data are available to date on the chemometric analysis of the spectral fingerprints acquired from the diluted commercial formulations of BoNT-A. In this proof-of-concept study, we tested whether NIRS can categorize solutions of incobotulinum A toxin (lacking non-toxic proteins) and abobotulinum A toxin (containing non-toxic proteins). Distinct excipients in the two formulations were also analyzed. We acquired transmittance spectra in the visible and short-wave infrared regions (350-2500 nm) by an ASD FieldSpec 4\u2122 Standard-Res Spectrophotoradiometer, using a submerged dip probe designed to read spectra in transflectance mode from liquid samples. After preliminary spectra pre-processing, principal component analysis was applied to characterize the spectral features of the two BoNT-A solutions and those of the various excipients diluted according to clinical standards. Partial least squares-discriminant analysis was used to implement a classification model able to discriminate the BoNT-A solutions and excipients. NIRS distinguished solutions containing distinct BoNT-A commercial formulations (abobotulinum A toxin vs. incobotulinum A toxin) diluted at recommended volumes for clinical reconstitution, distinct proteins (HSA vs. incobotulinum A toxin), very diluted solutions of simple sugars (lactose vs. sucrose), and saline or water. Predictive models of botulinum toxin formulations were also performed with the highest precision and accuracy

The Ventricular System Enlarges Abnormally in the Seventies, Earlier in Men, and First in the Frontal Horn: A Study Based on More Than 3,000 Scans

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

PLS_optimizer

This script can help choosing the right combination of pre-processing algorithms for multivariate regression (i.e. Partial Least Squares regressions) problems and an appropriate number of latent variables