A spectroscopic comparison of selected Chinese kaolinite, coal bearing kaolinite and halloysite : a mid-infrared and near-infrared study

Mid-infrared (MIR) and near-infrared (NIR) spectroscopy have been compared and evaluated for differentiating kaolinite, coal bearing kaolinite and halloysite. Kaolinite, coal bearing kaolinite and halloysite are the three relative abundant mineral of the kaolin group, especially in China. In the MIR spectra, the differences are shown in the 3000-3600 cm-1 between kaolinite and halloysite. It can not be obviously differentiated the kaolinite and halloysite, let alone kaolinite and coal bearing kaolinite. However, NIR, together with MIR, give us the sufficient evidence to differentiate the kaolinite and halloysite, especially kaolinite and coal bearing kaolinite. There are obvious differences between kaolinite and halloysite in the all range of their spectra, and it also show some difference between kaolinite and coal bearing kaolinite. Therefore, the reproducibility of measurement, signal to noise ratio and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for mineral analysis.

The use of phase in complex spectrum subtraction for robust speech recognition

In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

Improving the performance of model-order selection criteria by partial-model selection search

The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.

Speckle reduction in optical coherence tomography imaging by affine-motion image registration

Signal-degrading speckle is one factor that can reduce the quality of optical coherence tomography images. We demonstrate the use of a hierarchical model-based motion estimation processing scheme based on an affine-motion model to reduce speckle in optical coherence tomography imaging, by image registration and the averaging of multiple B-scans. The proposed technique is evaluated against other methods available in the literature. The results from a set of retinal images show the benefit of the proposed technique, which provides an improvement in signal-to-noise ratio of the square root of the number of averaged images, leading to clearer visual information in the averaged image. The benefits of the proposed technique are also explored in the case of ocular anterior segment imaging.

Infrared and Raman spectroscopic studies of archaeological materials

The use of vibrational spectroscopic techniques to characterise historical artefacts and art works continues to grow and to provide the archaeologist and art historian with significant information with which to understand the nature and activities of previous peoples and civilizations. In addition, conservators can gain knowledge of the composition of artworks or historical objects and so are better equipped to ensure their preservation. Both infrared and Raman have been widely used. Microspectroscopy is the preferred sampling technique as it requires only a very small sample, which often can be recovered. The use of synchrotron radiation in conjunction with IR microspectroscopy is increasing because of the substantial benefits in terms of improved spatial resolution and signal-to-noise ratio. The key trend for the future is the growth in the use of portable instruments, both IR and Raman, which are becoming important because they allow non-destructive measurements to be made in situ, for example at an archaeological site or at a museum.

Acoustic emission for diesel engine monitoring: A review and preliminary

Vibration analysis has been a prime tool in condition monitoring of rotating machines, however, its application to internal combustion engines remains a challenge because engine vibration signatures are highly non-stationary that are not suitable for popular spectrum-based analysis. Signal-to-noise ratio is a main concern in engine signature analysis due to severe background noise being generated by consecutive mechanical events, such as combustion, valve opening and closing, especially in multi-cylinder engines. Acoustic Emission (AE) has been found to give excellent signal-to-noise ratio allowing discrimination of fine detail of normal or abnormal events during a given cycle. AE has been used to detect faults, such as exhaust valve leakage, fuel injection behaviour, and aspects of the combustion process. This paper presents a review of AE application to diesel engine monitoring and preliminary investigation of AE signature measured on an 18-cylinder diesel engine. AE is compared with vibration acceleration for varying operating conditions: load and speed. Frequency characteristics of AE from those events are analysed in time-frequency domain via short time Fourier trasform. The result shows a great potential of AE analysis for detection of various defects in diesel engines.

Deep Raman spectroscopy for the non-invasive standoff detection of concealed chemical threat agents

Deep Raman spectroscopy has been utilized for the standoff detection of concealed chemical threat agents from a distance of 15 meters under real life background illumination conditions. By using combined time and space resolved measurements, various explosive precursors hidden in opaque plastic containers were identified non-invasively. Our results confirm that combined time and space resolved Raman spectroscopy leads to higher selectivity towards the sub-layer over the surface layer as well as enhanced rejection of fluorescence from the container surface when compared to standoff spatially offset Raman spectroscopy. Raman spectra that have minimal interference from the packaging material and good signal-to-noise ratio were acquired within 5 seconds of measurement time. A new combined time and space resolved Raman spectrometer has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than picosecond-based laboratory systems.

3D reconstruction of long bones utilising magnetic resonance imaging (MRI)

The design of pre-contoured fracture fixation implants (plates and nails) that correctly fit the anatomy of a patient utilises 3D models of long bones with accurate geometric representation. 3D data is usually available from computed tomography (CT) scans of human cadavers that generally represent the above 60 year old age group. Thus, despite the fact that half of the seriously injured population comes from the 30 year age group and below, virtually no data exists from these younger age groups to inform the design of implants that optimally fit patients from these groups. Hence, relevant bone data from these age groups is required. The current gold standard for acquiring such data–CT–involves ionising radiation and cannot be used to scan healthy human volunteers. Magnetic resonance imaging (MRI) has been shown to be a potential alternative in the previous studies conducted using small bones (tarsal bones) and parts of the long bones. However, in order to use MRI effectively for 3D reconstruction of human long bones, further validations using long bones and appropriate reference standards are required. Accurate reconstruction of 3D models from CT or MRI data sets requires an accurate image segmentation method. Currently available sophisticated segmentation methods involve complex programming and mathematics that researchers are not trained to perform. Therefore, an accurate but relatively simple segmentation method is required for segmentation of CT and MRI data. Furthermore, some of the limitations of 1.5T MRI such as very long scanning times and poor contrast in articular regions can potentially be reduced by using higher field 3T MRI imaging. However, a quantification of the signal to noise ratio (SNR) gain at the bone - soft tissue interface should be performed; this is not reported in the literature. As MRI scanning of long bones has very long scanning times, the acquired images are more prone to motion artefacts due to random movements of the subject‟s limbs. One of the artefacts observed is the step artefact that is believed to occur from the random movements of the volunteer during a scan. This needs to be corrected before the models can be used for implant design. As the first aim, this study investigated two segmentation methods: intensity thresholding and Canny edge detection as accurate but simple segmentation methods for segmentation of MRI and CT data. The second aim was to investigate the usability of MRI as a radiation free imaging alternative to CT for reconstruction of 3D models of long bones. The third aim was to use 3T MRI to improve the poor contrast in articular regions and long scanning times of current MRI. The fourth and final aim was to minimise the step artefact using 3D modelling techniques. The segmentation methods were investigated using CT scans of five ovine femora. The single level thresholding was performed using a visually selected threshold level to segment the complete femur. For multilevel thresholding, multiple threshold levels calculated from the threshold selection method were used for the proximal, diaphyseal and distal regions of the femur. Canny edge detection was used by delineating the outer and inner contour of 2D images and then combining them to generate the 3D model. Models generated from these methods were compared to the reference standard generated using the mechanical contact scans of the denuded bone. The second aim was achieved using CT and MRI scans of five ovine femora and segmenting them using the multilevel threshold method. A surface geometric comparison was conducted between CT based, MRI based and reference models. To quantitatively compare the 1.5T images to the 3T MRI images, the right lower limbs of five healthy volunteers were scanned using scanners from the same manufacturer. The images obtained using the identical protocols were compared by means of SNR and contrast to noise ratio (CNR) of muscle, bone marrow and bone. In order to correct the step artefact in the final 3D models, the step was simulated in five ovine femora scanned with a 3T MRI scanner. The step was corrected using the iterative closest point (ICP) algorithm based aligning method. The present study demonstrated that the multi-threshold approach in combination with the threshold selection method can generate 3D models from long bones with an average deviation of 0.18 mm. The same was 0.24 mm of the single threshold method. There was a significant statistical difference between the accuracy of models generated by the two methods. In comparison, the Canny edge detection method generated average deviation of 0.20 mm. MRI based models exhibited 0.23 mm average deviation in comparison to the 0.18 mm average deviation of CT based models. The differences were not statistically significant. 3T MRI improved the contrast in the bone–muscle interfaces of most anatomical regions of femora and tibiae, potentially improving the inaccuracies conferred by poor contrast of the articular regions. Using the robust ICP algorithm to align the 3D surfaces, the step artefact that occurred by the volunteer moving the leg was corrected, generating errors of 0.32 ± 0.02 mm when compared with the reference standard. The study concludes that magnetic resonance imaging, together with simple multilevel thresholding segmentation, is able to produce 3D models of long bones with accurate geometric representations. The method is, therefore, a potential alternative to the current gold standard CT imaging.

Factors affecting 39K NMR detectability in rat tissue

In this study we have found that NMR detectability of 39K in rat thigh muscle may be substantially higher (up to 100% oftotal tissue potassium) than values previously reported of around 40%. The signal was found to consist of two superimposed components, one broad and one narrow, of approximately equal area. Investigations involving improvements in spectral parameters such as signal-to-noise ratio and baseline roll, together with computer simulations of spectra, show that the quality of the spectra has a major effect on the amount of signal detected, which is largely due to the loss of detectability of the broad signal component. In particular, lower-field spectrometers using conventional probes and detection methods generally have poorer signal-to-noise and worse baseline roll artifacts, which make detection of a broad component of the muscle signal difficult.

Effects of simulated cataracts on speech intelligibility

Limited research is available on how well visual cues integrate with auditory cues to improve speech intelligibility in persons with visual impairments, such as cataracts. We investigated whether simulated cataracts interfered with participants’ ability to use visual cues to help disambiguate a spoken message in the presence of spoken background noise. We tested 21 young adults with normal visual acuity and hearing sensitivity. Speech intelligibility was tested under three conditions: auditory only with no visual input, auditory-visual with normal viewing, and auditory-visual with simulated cataracts. Central Institute for the Deaf (CID) Everyday Speech Sentences were spoken by a live talker, mimicking a pre-recorded audio track, in the presence of pre-recorded four-person background babble at a signal-to-noise ratio (SNR) of -13 dB. The talker was masked to the experimental conditions to control for experimenter bias. Relative to the normal vision condition, speech intelligibility was significantly poorer, [t (20) = 4.17, p < .01, Cohen’s d =1.0], in the simulated cataract condition. These results suggest that cataracts can interfere with speech perception, which may occur through a reduction in visual cues, less effective integration or a combination of the two effects. These novel findings contribute to our understanding of the association between two common sensory problems in adults: reduced contrast sensitivity associated with cataracts and reduced face-to-face communication in noise.

Pedigree-free animal models : the relatedness matrix reloaded

Animal models typically require a known genetic pedigree to estimate quantitative genetic parameters. Here we test whether animal models can alternatively be based on estimates of relatedness derived entirely from molecular marker data. Our case study is the morphology of a wild bird population, for which we report estimates of the genetic variance-covariance matrices (G) of six morphological traits using three methods: the traditional animal model; a molecular marker-based approach to estimate heritability based on Ritland's pairwise regression method; and a new approach using a molecular genealogy arranged in a relatedness matrix (R) to replace the pedigree in an animal model. Using the traditional animal model, we found significant genetic variance for all six traits and positive genetic covariance among traits. The pairwise regression method did not return reliable estimates of quantitative genetic parameters in this population, with estimates of genetic variance and covariance typically being very small or negative. In contrast, we found mixed evidence for the use of the pedigree-free animal model. Similar to the pairwise regression method, the pedigree-free approach performed poorly when the full-rank R matrix based on the molecular genealogy was employed. However, performance improved substantially when we reduced the dimensionality of the R matrix in order to maximize the signal to noise ratio. Using reduced-rank R matrices generated estimates of genetic variance that were much closer to those from the traditional model. Nevertheless, this method was less reliable at estimating covariances, which were often estimated to be negative. Taken together, these results suggest that pedigree-free animal models can recover quantitative genetic information, although the signal remains relatively weak. It remains to be determined whether this problem can be overcome by the use of a more powerful battery of molecular markers and improved methods for reconstructing genealogies.

Automatic particle picking of biological molecules imaged by electron microscopy

One of the next great challenges of cell biology is the determination of the enormous number of protein structures encoded in genomes. In recent years, advances in electron cryo-microscopy and high-resolution single particle analysis have developed to the point where they now provide a methodology for high resolution structure determination. Using this approach, images of randomly oriented single particles are aligned computationally to reconstruct 3-D structures of proteins and even whole viruses. One of the limiting factors in obtaining high-resolution reconstructions is obtaining a large enough representative dataset ($>100,000$ particles). Traditionally particles have been manually picked which is an extremely labour intensive process. The problem is made especially difficult by the low signal-to-noise ratio of the images. This paper describes the development of automatic particle picking software, which has been tested with both negatively stained and cryo-electron micrographs. This algorithm has been shown to be capable of selecting most of the particles, with few false positives. Further work will involve extending the software to detect differently shaped and oriented particles.

Anatomical MR imaging of long bones : comparative performance of MRI at 1.5 T and 3 T

The current gold standard for the design of orthopaedic implants is 3D models of long bones obtained using computed tomography (CT). However, high-resolution CT imaging involves high radiation exposure, which limits its use in healthy human volunteers. Magnetic resonance imaging (MRI) is an attractive alternative for the scanning of healthy human volunteers for research purposes. Current limitations of MRI include difficulties of tissue segmentation within joints and long scanning times. In this work, we explore the possibility of overcoming these limitations through the use of MRI scanners operating at a higher field strength. We quantitatively compare the quality of anatomical MR images of long bones obtained at 1.5 T and 3 T and optimise the scanning protocol of 3 T MRI. FLASH images of the right leg of five human volunteers acquired at 1.5 T and 3 T were compared in terms of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The comparison showed a relatively high CNR and SNR at 3 T for most regions of the femur and tibia, with the exception of the distal diaphyseal region of the femur and the mid diaphyseal region of the tibia. This was accompanied by an ~65% increase in the longitudinal spin relaxation time (T1) of the muscle at 3 T compared to 1.5 T. The results suggest that MRI at 3 T may be able to enhance the segmentability and potentially improve the accuracy of 3D anatomical models of long bones, compared to 1.5 T. We discuss how the total imaging times at 3 T can be kept short while maximising the CNR and SNR of the images obtained.

Deep Raman Spectroscopy in the analytical forensic investigation of concealed substances

Deep Raman Spectroscopy is a domain within Raman spectroscopy consisting of techniques that facilitate the depth profiling of diffusely scattering media. Such variants include Time-Resolved Raman Spectroscopy (TRRS) and Spatially-Offset Raman Spectroscopy (SORS). A recent study has also demonstrated the integration of TRRS and SORS in the development of Time-Resolved Spatially-Offset Raman Spectroscopy (TR-SORS). This research demonstrates the application of specific deep Raman spectroscopic techniques to concealed samples commonly encountered in forensic and homeland security at various working distances. Additionally, the concepts behind these techniques are discussed at depth and prospective improvements to the individual techniques are investigated. Qualitative and quantitative analysis of samples based on spectral data acquired from SORS is performed with the aid of multivariate statistical techniques. By the end of this study, an objective comparison is made among the techniques within Deep Raman Spectroscopy based on their capabilities. The efficiency and quality of these techniques are determined based on the results procured which facilitates the understanding of the degree of selectivity for the deeper layer exhibited by the individual techniques relative to each other. TR-SORS was shown to exhibit an enhanced selectivity for the deeper layer relative to TRRS and SORS whilst providing spectral results with good signal-to-noise ratio. Conclusive results indicate that TR-SORS is a prospective deep Raman technique that offers higher selectivity towards deep layers and therefore enhances the non-invasive analysis of concealed substances from close range as well as standoff distances.

Investigation of megavoltage beams and detectors for electronic portal imaging

Accuracy of dose delivery in external beam radiotherapy is usually verified with electronic portal imaging (EPI) in which the treatment beam is used to check the positioning of the patient. However the resulting megavoltage x-ray images suffer from poor quality. The image quality can be improved by developing a special operating mode in the linear accelerator. The existing treatment beam is modified such that it produces enough low-energy photons for imaging. In this work the problem of optimizing the beam/detector combination to achieve optimal electronic portal image quality is addressed. The linac used for this study was modified to produce two experimental photon beams. These beams, named Al6 and Al10, were non-flat and were produced by 4MeV electrons hitting aluminum targets, 6 and 10mm thick respectively. The images produced by a conventional EPI system (6MV treatment beam and camera-based EPID with a Cu plate & Gd2O2S screen ) were compared with the images produced by the experimental beams and various screens with the same camera). The contrast of 0.8cm bone equivalent material in 5 cm water increased from 1.5% for the conventional system to 11% for the combination of Al6 beam with a 200mg/cm2 Gd2O2S screen. The signal-to-noise ratio calculated for 1cGy flood field images increased by about a factor of two for the same EPI systems. The spatial resolution of the two imaging systems was comparable. This work demonstrates that significant improvements in portal image contrast can be obtained by simultaneous optimization of the linac spectrum and EPI detector.