Generation and reduction of the data for the Ulysses gravitational wave experiment

A procedure for the generation and reduction of the radiometric data known as REGRES is described. The software is implemented on a HP-1000F computer and was tested on REGRES data relative to the Voyager I spacecraft. The REGRES data are a current output of NASA's Orbit Determination Program. The software package was developed in view of the data analysis of the gravitational wave experiment planned for the European spacecraft Ulysses

Mineral Recognition and Liberation Degree Measurements in Industrial Ore Processing

This study aims at identifying calculation procedures and representation methods for identifying the mineral species present in a rock. The goal of the study is to identify: the characteristic spectrum for each mineral species identified in the ore; the main shape of the individual species; the preferential arrangement of the individual mineral species; the grain-size distribution of the individual mineral species and of the grains resulting from comminution processes; the degree of liberation for each mineral; and the degree of liberation of the comminution products obtained from the ores

Characterization of Oxidized Zinc (Calamine) Ores by Scanning Electron Microscopy and Electron Microprobe Analysis

Textural and structural features of Sardinian oxidized zinc (calamine) ores have been established by scanning electron microscopy and electron microprobe analysis, the elements analyzed being Zn, Pb, Ca and Fe. The surface composition of grains produced by comminution has also been determined, especially with reference to the presence of smithsonite and cerussite. The methodological approach adopted has revealed intimate intergrowth of the mineral species present and contamination of the main mineral by inclusions of other species, which explains why it is so difficult to obtain good recoveries and high-quality concentrates by beneficiation processes

Deceleration of the solar wind in the Earth foreshock region: ISEE 2 and IMP 8 observations

The deceleration of the solar wind in the region of the interplanetary space filled by ions backstreaming from the Earth bow shock was studied using a two spacecraft technique. This deceleration, which is correlated with the "diffuse" but not with the "reflected" ion population, depends on the solar wind bulk velocity: at low velocities (below 300 km/sec) the velocity decrease is about 5 km/sec, while at higher velocities (above 400 km/sec) the decrease may be as large as 30 km/sec. Along with this deceleration, the solar wind undergoes a deflection of about 1 deg away from the direction of the Earth bow shock. The energy balance shows that the kinetic energy loss far exceeds the thermal energy which is possibly gained by the solar wind, therefore, at least part of this energy must go into waves and/or into the backstreaming ions

Micro X-ray fluorescence imaging coupled with chemometrics to detect and classify asbestos fibers in demolition waste

Asbestos was largely used in the past by several countries all over the world. From 1900 to 1990 asbestos-containing materials (ACMs) were produced in large amounts and mainly utilized to produce insulation, flame retardant materials, as well as to improve the mechanical and the chemical characteristics of construction materials. Its extensive use has therefore led to the presence of fibers in existing buildings and within the construction and demolition waste. A fast, reliable and accurate recognition of ACMs represents an important target to be reached. In this paper the use of micro X-ray fluorescence (micro-XRF) technique coupled with a statistical multivariate approach was applied and discussed with reference to ACMs characterization. Different elemental maps of the ACMs were preliminary acquired in order to evaluate distribution and composition of asbestos fibers, then samples energy spectra where collected and processed using chemometric methods to perform an automatic classification of the different typologies of asbestos fibers. Spectral data were analyzed using PLS-Toolbox™ (Eigenvector Research, Inc.) running into Matlab® (The Mathworks, Inc.) environment. An automatic classification model was then built and applied. Results showed that asbestos fibers were correctly identified and classified according to their chemical composition. The proposed approach, based on micro-XRF analysis combined with an automatic classification of the elemental maps, is not only effective and non-destructive, it is fast, and it does not require the presence of a trained operator. The application of the developed methodology can help to correctly characterize and manage demolition waste where ACMs are present

Evaluation of elements distribution in printed circuit boards from mobile phones by micro x-ray fluorescence

A micro X-ray fluorescence-based approach for the chemical characterization of spent printed circuit boards (PCBSPCBSS) from mobile phones was applied. More in detail, twelve spent mobile phones were grouped into three clusters according to brands, models and year of release, and a study to evaluate the technological evolution of PCBSs over time was carried out. Precious metals and hazardous elements were investigated, revealing a few differences between samples from the different groups. For instance, the distribution of gold on PCBS layers was more widespread for the older analyzed samples, and smaller quantities of bromine and lead were detected in the more recent models in accordance with the Restriction of Hazardous Substances Directive 2002/95/EC. Analysis of PCBS composition should contribute towards correctly managing such a complex waste, maximizing the recovery of base, critical and precious metals and considering the possible presence of harmful elements requiring careful management. The experimental results showed how, using the proposed approach, distribution maps for chemical elements present in PCBSs could be obtained, thus allowing the definition of optimal strategies for further handling (i.e. classification) and processing (i.e. critical/precious metal recovery)

Hierarchical modelling for recycling-oriented classification of shredded spent flat monitor products based on hyperspectral imaging

The number of flat monitors from televisions, notebooks and tablets has increased dramatically in recent years, thus resulting in a corresponding rise in Waste from Electrical and Electronic Equipment (WEEE). This fact is linked to the production of new high-performance electronic devices. Taking into account a future volume growth trend of WEEE, the implementation of adequate recycling architectures embedding recognition/classification logics to handle the collected WEEE physical-chemical at-tributes, is thus necessary. These integrated hardware and software architectures should be efficient, reliable, low cost, and capable of performing detection/control actions to assess: i) WEEE composition and ii) physical-chemical attributes of the resulting recovered flow streams. This information is fundamental in setting up and implementing appropriate recycling actions. In this study, a hierarchical classification modelling approach, based on Near InfraRed (NIR)-Hyperspectral Imaging (HSI), was carried out. More in detail, a 3-step hierarchical modelling procedure was designed, implemented and set up in order to recognize different materials present in a specific WEEE stream: End-of-Life (EoL) shredded monitors and flat screens. By adopting the proposed approach, different categories are correctly recognized. The results obtained showed how the proposed approach not only allows the set up of a “one shot” quality control system, but also contributes towards improving the sorting process

Asbestos detection in construction and demolition waste by different classification methods applied to short-wave infrared hyperspectral images

In this study, different multivariate classification methods were applied to hyperspectral images acquired, in the short-wave infrared range (SWIR: 1000-2500 nm), to define and evaluate quality control actions applied to construction and demolition waste (C&DW) flow streams, with particular reference to the detection of hazardous material as asbestos. Three asbestos fibers classes (i.e., amosite, chrysotile and crocidolite) inside asbestos-containing materials (ACM) were investigated. Samples were divided into two groups: calibration and validation datasets. The acquired hyperspectral images were first explored by Principal Component Analysis (PCA). The following multivariate classification methods were selected in order to verify and compare their efficiency and robustness: Hierarchical Partial Least Squares-Discriminant Analysis (Hi-PLSDA), Principal Component Analysis k-Nearest Neighbors (PCA-kNN) and Error Correcting Output Coding with Support Vector Machines (ECOC-SVM). The classification results obtained for the three models were evaluated by prediction maps and the values of performance parameters (Sensitivity and Specificity). Micro-X-ray fluorescence (micro-XRF) maps confirmed the correctness of classification results. The results demonstrate how SWIR-HSI technology, coupled with multivariate analysis modelling, is a promising approach to develop both "off-line" and "online" fast, reliable and robust quality control strategies, finalized to perform a quick assessment of ACM presence

Direction-dependent secondary bonds and their stepwise melting in a uracil-based molecular crystal studied by infrared spectroscopy and theoretical modeling

Three types of supramolecular interactions are identified in the three crystallographic directions in crystals of 1,4-bis[(1-hexylurac-6-yl)ethynyl]benzene, a uracil-based molecule with a linear backbone. These three interactions, characterized by their strongest component, are: intermolecular double H-bonds along the molecular axis, London dispersion interaction of hexyl chains connecting these linear assemblies, and $\pi$--$\pi$ stacking of the aromatic rings perpendicular to the molecular planes. On heating, two transitions happen, disordering of hexyl chains at 473 K, followed by H-bond melting at 534 K. The nature of the bonds and transitions was established by matrix-isolation and temperature-dependent infrared spectroscopy and supported by theoretical computations

Chrysotile detection in soils with proximal hyperspectral sensing and chemometrics

In this work the authors present an innovative methodology, based on proximal hyperspectral sensing and chemometric techniques, aimed at detecting asbestos containing soils. Short Wave InfraRed (SWIR) reflectance spectra of reference samples containing known chrysotile fractions were collected in laboratory. Since the identification of asbestos containing soils depends on the contaminant mass percentage (weight/weight), two supervised multivariate data projection methods were evaluated for asbestos concentration prediction. The first results are reported here, together with advantages and limits of the analytical methods. Orthogonal Partial Least Squares (PLS) regression showed the lowest error in prediction and the highest coefficient of determination in prediction. This technique would support screening activities frequently conducted during environmental assessment and remediation projects