Near infrared spectroscopy of marble from Chillagoe, Australia and in comparison with other selected natural carbonates

Marble from the Chillagoe deposits was extensively used in the construction of Australia’s parliament house. Near infrared (NIR) spectroscopy has been applied to study the quality of marble from the Chillagoe marble deposits and to distinguish between different types of marble in the Chillagoe deposits. A comparison of the NIR spectra of marble with dolomite and monohydrocalcite is made. The spectrum of the marble closely resembles that of monohydrocalcite and is different from that of dolomite. The infrared spectra of the minerals are characterised by OH and water stretching vibrations. Both the first and second fundamental overtones of these bands are observed in the NIR spectra. Marble is characterised by NIR bands at 4005, 4268 and 4340 cm–1, attributed to carbonate combination bands and overtones. Marble also shows NIR bands at 5005, 5106, 5234 and 5334 cm–1 assigned to water combination bands. Finally the NIR spectrum of the marble displays broad low-intensity features centred upon 6905 cm–1 attributed to the water first overtones. It appears feasible to identify marble through the use of NIR spectroscopy.

The molecular structure of chloritoid: A mid-infrared and near-infrared spectroscopic study

The mineral chloritoid collected from the argillite in the bottom of Yaopo Formation of Western Beijing was characterized by mid-infrared (MIR) and near-infrared (NIR) spectroscopy. The MIR spectra showed all fundamental vibrations including the hydroxyl units, basic aluminosilicate framework and the influence of iron on the chloritoid structure. The NIR spectrum of the chloritoid showed combination (ν + δ)OH bands with the fundamental stretching (ν) and bending (δ) vibrations. Based on the chemical component data and the analysis result from the MIR and NIR spectra, the crystal structure of chloritoid from western hills of Beijing, China, can be illustrated. Therefore, the application of the technique across the entire infrared region is expected to become more routine and extend its usefulness, and the reproducibility of measurement and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for the unit cell structural analysis.

Near infrared spectroscopy of selected natural magnesium carbonates: implications for geosequestration

The approach to remove greenhouse gases by pumping liquid CO2 several kilometres below the ground implies that many carbonate containing minerals will be formed. Among these minerals, the formation of hydromagnesite, dypingite and nesquehonite are possible, thus necessitating a study of such minerals. These minerals with a hydrotalcite-related formulae have been characterised by a combination of infrared and near infrared spectroscopy. Layered double hydroxides (also known as anionic clays or hydrotalcites) are a group of layered clay minerals described by the general formula: [M1–x2+Mx3+(OH)2]x+[An–]x/n∙mH2O. The infrared spectra of the minerals are characterised by OH and water stretching vibrations. Both the first and second fundamental overtones of these bands are observed in the NIR spectra in the 7030–7235 cm–1 and 10,490–10,570 cm–1 spectral ranges. Intense (CO3)2– symmetrical and anti-symmetrical stretching vibrations confirm the distortion of the carbonate anion. The position of the water bending vibration indicates water is strongly hydrogen-bonded to the carbonate anion in the mineral structure. NIR spectroscopy offers a method for quickly analysing such materials.

Information-theoretic analysis of brain white matter fiber orientation distribution functions

We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

Robust principal component analysis in water quality index development

Some statistical procedures already available in literature are employed in developing the water quality index, WQI. The nature of complexity and interdependency that occur in physical and chemical processes of water could be easier explained if statistical approaches were applied to water quality indexing. The most popular statistical method used in developing WQI is the principal component analysis (PCA). In literature, the WQI development based on the classical PCA mostly used water quality data that have been transformed and normalized. Outliers may be considered in or eliminated from the analysis. However, the classical mean and sample covariance matrix used in classical PCA methodology is not reliable if the outliers exist in the data. Since the presence of outliers may affect the computation of the principal component, robust principal component analysis, RPCA should be used. Focusing in Langat River, the RPCA-WQI was introduced for the first time in this study to re-calculate the DOE-WQI. Results show that the RPCA-WQI is capable to capture similar distribution in the existing DOE-WQI.

Combining HPLC-DAD and ICP-MS data for improved analysis of complex samples: Classification of the root samples from Cortex moutan

A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

FIA : an open foresic integration architecture for composing digital evidence

The analysis and value of digital evidence in an investigation has been the domain of discourse in the digital forensic community for several years. While many works have considered different approaches to model digital evidence, a comprehensive understanding of the process of merging different evidence items recovered during a forensic analysis is still a distant dream. With the advent of modern technologies, pro-active measures are integral to keeping abreast of all forms of cyber crimes and attacks. This paper motivates the need to formalize the process of analyzing digital evidence from multiple sources simultaneously. In this paper, we present the forensic integration architecture (FIA) which provides a framework for abstracting the evidence source and storage format information from digital evidence and explores the concept of integrating evidence information from multiple sources. The FIA architecture identifies evidence information from multiple sources that enables an investigator to build theories to reconstruct the past. FIA is hierarchically composed of multiple layers and adopts a technology independent approach. FIA is also open and extensible making it simple to adapt to technological changes. We present a case study using a hypothetical car theft case to demonstrate the concepts and illustrate the value it brings into the field.

Development of self-efficacy and expectancy measures for benzodiazepines

This study aimed to develop and assess the reliability and validity of a pair of self-report questionnaires to measure self-efficacy and expectancy associated with benzodiazepine use, the Benzodiazepine Refusal Self- Efficacy Questionnaire (BRSEQ) and the Benzodiazepine Expectancy Questionnaire (BEQ). Internal structure of the questionnaireswas established by principal component analysis (PCA) in a sample of 155 respondents, and verified by confirmatory factor analyses (CFA) in a second independent sample (n=139) using structural equation modeling. The PCA of the BRSEQ resulted in a 16-item, 4-factor scale, and the BEQ formed an 18-item, 2-factor scale. Both scales were internally reliable. CFA confirmed these internal structures and reduced the questionnaires to a 14-item self-efficacy scale and a 12-item expectancy scale. Lower self-efficacy and higher expectancy were moderately associated with higher scores on the SDS-B. The scales provide reliable measures for assessing benzodiazepine self-efficacy and expectancies. Future research will examine the utility of the scales in prospective prediction of benzodiazepine cessation.

EPR, UV-visible and near infrared spectroscopic characterization of dolomite

Dolomite mineral samples having white and light green colours of Indian origin have been characterized by EPR, optical and NIR spectroscopy. The optical spectrum exhibits a number of electronic bands due to presence of Fe(III) ions in the mineral. From EPR studies, the parameters of g for Fe(III) and g, A and D for Mn(II) are evaluated and the data confirm that the ions are in distorted octahedron. Optical absorption studies reveal that Fe(III) is in distorted octahedron. The bands in NIR spectra are due to the overtones and combinations of water molecules. Thus EPR and optical absorption spectral studies have proven useful for the study of the chemistry of dolomite.

Vibrational spectroscopic studies of laboratory scale polymer melt processing : application to a thermoplastic polyurethane nanocomposite

A laboratory scale twin screw extruder has been interfaced with a near infrared (NIR) spectrometer via a fibre optic link so that NIR spectra can be collected continuously during the small scale experimental melt state processing of polymeric materials. This system can be used to investigate melt state processes such as reactive extrusion, in real time, in order to explore the kinetics and mechanism of the reaction. A further advantage of the system is that it has the capability to measure apparent viscosity simultaneously which gives important additional information about molecular weight changes and polymer degradation during processing. The system was used to study the melt processing of a nanocomposite consisting of a thermoplastic polyurethane and an organically modified layered silicate.

Characterisation of soluble components and PAH in PM10 atmospheric particulate matter in Brisbane

Fours sets of PM10 samples were collected in three sites in SEQ from December 2002 to August 2004. Three of these sets of samples were collected by QLD EPA as a part of their regular air monitoring program at Woolloongabba, Rocklea and Eagle Farm. Half of the samples were used in this study for the analysis of water-soluble ions, which are Na+, K+, Mg2+, Ca2+, NH4 +, Cl-, NO3 -, SO4 2-, F-, Br-, NO2 -, PO4 -3 and the other half was retained by QLD EPA. The fourth set of samples was collected at Rocklea, specifically for this study. A quarter of the samples obtained from this set of samples were used to analyse water-soluble ions; a quarter of the sample was used to analyse Pb, Cu, Al, Fe, Mn and Zn; and the rests were used to analyse US EPA 16 priority PAHs. The water-soluble ions were extracted ultrasonically with water and the major watersoluble anions as well as NH4 + were analysed using IC. Na+, K+, Mg2+, Ca2+ Pb, Cu, Al, Fe, Mn and Zn were analysed using ICP-AES while PAHs were extracted by acetonitrile and analysed using HPLC. Of the analysed water-soluble ions, Cl-, NO3 -, SO4 2-, Na+, K+, Mg2+ and Ca2+ were high in concentration and determined in all the samples. F-, Br-, NO2 -, PO4 -3 and NH4 + ions were lower in concentration and determined only in some samples. Na+ and Cl- were high in all samples indicating the importance of a marine source. Principal Component Analysis (PCA) was used to examine the temporal variations of the water-soluble ions at the three sites. The results indicated that there was no major difference between the three sites. However, comparing the average concentrations of ions and Cl-/Na+ it was concluded that Woolloongabba had more marine influence than the other sites. Al, Fe and Zn were detected in all samples. Al and Fe were high in all samples indicating the significance of a source of crustal matter. Cu, Mn and Pb were in low concentrations and were determined only in some samples. The lower Pb concentrations observed in the study than in previous studies indicate that the phasing-out of leaded petrol had an appreciable impact on Pb levels in SEQ. This study reports for the first time, simultaneous data on the water-soluble, metal ion and PAH levels of PM10 aerosols in Brisbane, and provides information on the most likely sources of these chemical species. Such information can be used alongside those that already exist to formulate PM10 pollution reduction strategies for SEQ in order to protect the community from the adverse effects of PM pollution.

Microstructural characterization of electron beam evaporated tungsten oxide films for gas sensing applications

Tungsten trioxide is one of the potential semiconducting materials used for sensing NH3, CO, CH4 and acetaldehyde gases. The current research aims at development, microstructural characterization and gas sensing properties of thin films of Tungsten trioxide (WO3). In this paper, we intend to present the microstructural characterization of these films as a function of post annealing heat treatment. Microstructural and elemental analysis of electron beam evaporated WO3 thin films and iron doped WO3 films (WO3:Fe) have been carried out using analytical techniques such as Transmission electron microscopy, Rutherford Backscattered Spectroscopy and XPS analysis. TEM analysis revealed that annealing at 300oC for 1 hour improves cyrstallinity of WO3 film. Both WO3 and WO3:Fe films had uniform thickness and the values corresponded to those measured during deposition. RBS results show a fairly high concentration of oxygen at the film surface as well as in the bulk for both films, which might be due to adsorption of oxygen from atmosphere or lattice oxygen vacancy inherent in WO3 structure. XPS results indicate that tungsten exists in 4d electronic state on the surface but at a depth of 10 nm, both 4d and 4f electronic states were observed. Atomic force microscopy reveals nanosize particles and porous structure of the film. This study shows e-beam evaporation technique produces nanoaparticles and porous WO3 films suitable for gas sensing applications and doping with iron decreases the porosity and particle size which can help improve the gas selectivity.

The structure of selected magnesium carbonate minerals : a near infrared and mid-infrared spectroscopic study

The approach to remove green house gases by pumping liquid CO2 several kilometres below the ground implies that many carbonate containing minerals will be formed. Among these minerals the formation of dypingite and artinite are possible; thus necessitating a study of such minerals. Two carbonate bearing minerals dypingite and artinite with a hydrotalcite related formulae have been characterised by a combination of infrared and near-infrared spectroscopy. The infrared spectra of both minerals are characterised by OH and water stretching vibrations. Both the first and second fundamental overtones of these bands are observed in the NIR spectra in the 7030 to 7235 cm-1 and 10490 to 10570 cm-1. Intense (CO3)2- symmetric and antisymmetric stretching vibrations confirm the distortion of the carbonate anion. The position of the water bending vibration indicates water is strongly hydrogen bonded to the carbonate anion in the mineral structure. Split NIR bands at around 8675 and 11100 cm-1 indicates that some replacement of magnesium ions by ferrous ions in the mineral structure has occurred.

A model for computer profiling

This paper discusses the use of models in automatic computer forensic analysis, and proposes and elaborates on a novel model for use in computer profiling, the computer profiling object model. The computer profiling object model is an information model which models a computer as objects with various attributes and inter-relationships. These together provide the information necessary for a human investigator or an automated reasoning engine to make judgements as to the probable usage and evidentiary value of a computer system. The computer profiling object model can be implemented so as to support automated analysis to provide an investigator with the information needed to decide whether manual analysis is required.