Computational analysis of epigenetic information in human DNA sequences

Over the last few years, investigations of human epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies across defined regions within the human genome, and to identify new patterns between epigenetic mechanisms and DNA content. Signal processing methods, including Fourier and Wavelet Transformations, are employed and principal results are reported.

Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm

In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed rolling element bearing failures. The scheme consists of fault feature calculation, discriminative fault feature analysis, and fault classification. The proposed approach first computes wavelet-based fault features, including the respective relative wavelet packet node energy and entropy, by applying a wavelet packet transform to an incoming acoustic emission signal. The most discriminative fault features are then filtered from the originally produced feature vector by using discriminative fault feature analysis based on a binary bat algorithm (BBA). Finally, the proposed approach employs one-against-all multiclass support vector machines to identify multiple low-speed rolling element bearing defects. This study compares the proposed BBA-based dimensionality reduction scheme with four other dimensionality reduction methodologies in terms of classification performance. Experimental results show that the proposed methodology is superior to other dimensionality reduction approaches, yielding an average classification accuracy of 94.9%, 95.8%, and 98.4% under bearing rotational speeds at 20 revolutions-per-minute (RPM), 80 RPM, and 140 RPM, respectively.

Combined NIR/MIR analysis: A novel method for the classification of complex substances such as Illicium verum Hook. F. and its adulterants

A novel combined near- and mid-infrared (NIR and MIR) spectroscopic method has been researched and developed for the analysis of complex substances such as the Traditional Chinese Medicine (TCM), Illicium verum Hook. F. (IVHF), and its noxious adulterant, Iuicium lanceolatum A.C. Smith (ILACS). Three types of spectral matrix were submitted for classification with the use of the linear discriminant analysis (LDA) method. The data were pretreated with either the successive projections algorithm (SPA) or the discrete wavelet transform (DWT) method. The SPA method performed somewhat better, principally because it required less spectral features for its pretreatment model. Thus, NIR or MIR matrix as well as the combined NIR/MIR one, were pretreated by the SPA method, and then analysed by LDA. This approach enabled the prediction and classification of the IVHF, ILACS and mixed samples. The MIR spectral data produced somewhat better classification rates than the NIR data. However, the best results were obtained from the combined NIR/MIR data matrix with 95–100% correct classifications for calibration, validation and prediction. Principal component analysis (PCA) of the three types of spectral data supported the results obtained with the LDA classification method.

Evolution of Grain-Boundary Microstructure and Texture in Interstitial-Free Steel Processed by Equal-Channel Angular Extrusion

The equal-channel angular extrusion (ECAE) of Ti-bearing interstitial-free (IF) steel was performed following two different routes, up to four passes, at a temperature of 300 degrees C. The ECAE led to a grain refinement to submicron size. After the second pass, the grain size attained saturation thereafter. The microstructural analysis indicated the presence of coincident-site lattice (CSL) boundaries in significant fraction, in addition to a high volume fraction of high-angle random boundaries and some low-angle boundaries after the deformation. Among the special boundaries, Sigma 3 and Sigma 13 were the most prominent ones and their fraction depended on the processing route followed. A deviation in the misorientation angle distribution from the Mackenzie distribution was noticed. The crystallographic texture after the first pass resembled that of simple shear, with the {112}, {110}, and {123} aligned to the macroscopic shear plane.

3D shape extraction of human face in presence of facial hair: A profilometric approach

The increasing use of 3D modeling of Human Face in Face Recognition systems, User Interfaces, Graphics, Gaming and the like has made it an area of active study. Majority of the 3D sensors rely on color coded light projection for 3D estimation. Such systems fail to generate any response in regions covered by Facial Hair (like beard, mustache), and hence generate holes in the model which have to be filled manually later on. We propose the use of wavelet transform based analysis to extract the 3D model of Human Faces from a sinusoidal white light fringe projected image. Our method requires only a single image as input. The method is robust to texture variations on the face due to space-frequency localization property of the wavelet transform. It can generate models to pixel level refinement as the phase is estimated for each pixel by a continuous wavelet transform. In cases of sparse Facial Hair, the shape distortions due to hairs can be filtered out, yielding an estimate for the underlying face. We use a low-pass filtering approach to estimate the face texture from the same image. We demonstrate the method on several Human Faces both with and without Facial Hairs. Unseen views of the face are generated by texture mapping on different rotations of the obtained 3D structure. To the best of our knowledge, this is the first attempt to estimate 3D for Human Faces in presence of Facial hair structures like beard and mustache without generating holes in those areas.

Impact of water drops onto the junction of a hydrophobic texture and a hydrophilic smooth surface

Wettability gradient surfaces play a significant role in control and manipulation of liquid drops. The present work deals with the analysis of water drops impacting onto the junction line between hydrophobic texture and hydrophilic smooth portions of a dual-textured substrate made using stainless steel material. The hydrophobic textured portion of the substrate comprised of unidirectional parallel groove-like and pillar-like structures of uniform dimensions. A high-speed video camera recorded the spreading and receding dynamics of impacting drops. The drop impact dynamics during the early inertia driven impact regime remains unaffected by the dual-texture feature of the substrate. A larger retraction speed of drop liquid observed on the hydrophobic portion of the substrate during the impact of low velocity drops makes the drop liquid on the higher wettability portion to advance further (secondary drop spreading). The net horizontal drop velocity towards the hydrophilic portion of the dual-textured substrate decreases with increasing drop impact velocity. The available experimental results suggest that the movement of bulk drop liquid away from the impact point during drop impact on the dual-textured substrate is larger for the impact of low inertia drops. (C) 2010 Elsevier B.V. All rights reserved.

Homomorphic Analysis and Modeling of ECG Signals

Homomorphic analysis and pole-zero modeling of electrocardiogram (ECG) signals are presented in this paper. Four typical ECG signals are considered and deconvolved into their minimum and maximum phase components through cepstral filtering, with a view to study the possibility of more efficient feature selection from the component signals for diagnostic purposes. The complex cepstra of the signals are linearly filtered to extract the basic wavelet and the excitation function. The ECG signals are, in general, mixed phase and hence, exponential weighting is done to aid deconvolution of the signals. The basic wavelet for normal ECG approximates the action potential of the muscle fiber of the heart and the excitation function corresponds to the excitation pattern of the heart muscles during a cardiac cycle. The ECG signals and their components are pole-zero modeled and the pole-zero pattern of the models can give a clue to classify the normal and abnormal signals. Besides, storing only the parameters of the model can result in a data reduction of more than 3:1 for normal signals sampled at a moderate 128 samples/s

Local texture and microstructure in cube-oriented nickel single crystal deformed by equal channel angular extrusion

Local texture and microstructure was investigated to study the deformation mechanisms during equal channel angular extrusion of a high purity nickel single crystal of initial cube orientation. A detailed texture and microstructure analysis by various diffraction techniques revealed the complexity of the deformation patterns in different locations of the billet. A modeling approach, taking into account slip system activity, was used to interpret the development of this heterogeneous deformation.

Wavelet based spectral finite element modelling and detection of de-lamination in composite beams

In this paper, a model for composite beam with embedded de-lamination is developed using the wavelet based spectral finite element (WSFE) method particularly for damage detection using wave propagation analysis. The simulated responses are used as surrogate experimental results for the inverse problem of detection of damage using wavelet filtering. The WSFE technique is very similar to the fast fourier transform (FFT) based spectral finite element (FSFE) except that it uses compactly supported Daubechies scaling function approximation in time. Unlike FSFE formulation with periodicity assumption, the wavelet-based method allows imposition of initial values and thus is free from wrap around problems. This helps in analysis of finite length undamped structures, where the FSFE method fails to simulate accurate response. First, numerical experiments are performed to study the effect of de-lamination on the wave propagation characteristics. The responses are simulated for different de-lamination configurations for both broad-band and narrow-band excitations. Next, simulated responses are used for damage detection using wavelet analysis.

Microstructure and texture evolution during accumulative roll bonding of aluminium alloys AA2219/AA5086 composite laminates

Accumulative roll bonding of two aluminium alloys, AA2219 and AA5086 was carried out up to 8 passes. During the course of ARB, the deformation inhomogeneity between the two alloy layers results in interfacial instability after the 4th pass, necking of the AA5086 layers after the 6th pass and fracture along the necked regions after the 7th and 8th pass. The EBSD analysis shows deformation bands along the interfaces after 8 passes of ARB. The ARB-processed materials predominantly show characteristic deformation texture components. The weak texture after the 2nd pass results from the combination of a weakly-textured starting AA2219 layer and a strongly-textured starting AA5086 layer. A strong deformation texture forms due to the high imposed strain after a higher number of ARB passes. Subgrain formation and related shear banding induces copper/S components in the case of the small elongated grains, while planar slip leads to the formation of brass component in the large elongated grains.

Texture and microstructure evolution during cold rolling of Cu-Fe laminates prepared by accumulative roll bonding

Multi-layered materials have been made from Cu-Fe with approximately equal volume fractions using the Accumulated Roll Bonding (ARB) technique with less than 1 μm thickness of the individual layers. The so-obtained multi-layers have been subjected to deformation by cold rolling to 25, 50, 75, 87 and 93% reduction in thickness. A detailed characterization has been carried out using X-ray diffraction (line profile analysis and texture measurement) and electron (scanning and transmission) microscopy. It has been found that Fe layers are disintegrated whereas Cu retains its continuity within a layer. Microstructural Characterization from X-Ray Line profile Analysis (XRDLPA) through Variance Method reveals that large amount of strain is initially carried by Cu layers during deformation. In the Cu-Fe layer, the texture is comparatively weaker in Cu layer and strong in Fe layers. Brass Component increases up to 75% reduction and then decreases, while the ratio of Cu/S and Bs/S remains almost constant through out the deformation. After 50% reduction, dynamic recovery is predominant as indicated by the increase in the amount of low angle grain boundaries and decrease in dislocation density. The presence of R component indicates continuous dynamic recovery and recrystallization (CDRR) at the advanced stage of deformation.

Evolution of texture and microstructure during hot torsion of a magnesium alloy

A systematic study of the evolution of the microstructure and crystallographic texture during free end torsion of a single phase magnesium alloy Mg-3Al-0.3Mn (AM30) was carried out. The torsion tests were done at a temperature of 250 degrees C to different strain levels in order to examine the progressive evolution of the microstructure and texture. A detailed microstructural analysis was performed using the electron back-scattered diffraction technique. The observed microstructural features indicated the occurrence of continuous dynamic recovery and recrystallization, starting with the formation of subgrains and ending with recrystallized grains with high angle boundaries. Texture and microstructure evolution were analysed by decoupling the effects of imposed shear and of dynamic recrystallization. Microstructure was partitioned to separate the deformed grains from the recovered/recrystallized grains. The texture of the deformed part could be reproduced by viscoplastic self-consistent polycrystal simulations. Recovered/recrystallized grains were formed as a result of rotation of these grains so as to reach a low plastic energy state. (C) 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Signal Detection in Generalized Gaussian Noise by Nonlinear Wavelet Denoising

In this paper, a nonlinear suboptimal detector whose performance in heavy-tailed noise is significantly better than that of the matched filter is proposed. The detector consists of a nonlinear wavelet denoising filter to enhance the signal-to-noise ratio, followed by a replica correlator. Performance of the detector is investigated through an asymptotic theoretical analysis as well as Monte Carlo simulations. The proposed detector offers the following advantages over the optimal (in the Neyman-Pearson sense) detector: it is easier to implement, and it is more robust with respect to error in modeling the probability distribution of noise.

Auditory-motivated Gammatone wavelet transform

The ability of the continuous wavelet transform (CWT) to provide good time and frequency localization has made it a popular tool in time-frequency analysis of signals. Wavelets exhibit constant-Q property, which is also possessed by the basilar membrane filters in the peripheral auditory system. The basilar membrane filters or auditory filters are often modeled by a Gammatone function, which provides a good approximation to experimentally determined responses. The filterbank derived from these filters is referred to as a Gammatone filterbank. In general, wavelet analysis can be likened to a filterbank analysis and hence the interesting link between standard wavelet analysis and Gammatone filterbank. However, the Gammatone function does not exactly qualify as a wavelet because its time average is not zero. We show how bona fide wavelets can be constructed out of Gammatone functions. We analyze properties such as admissibility, time-bandwidth product, vanishing moments, which are particularly relevant in the context of wavelets. We also show how the proposed auditory wavelets are produced as the impulse response of a linear, shift-invariant system governed by a linear differential equation with constant coefficients. We propose analog circuit implementations of the proposed CWT. We also show how the Gammatone-derived wavelets can be used for singularity detection and time-frequency analysis of transient signals. (C) 2013 Elsevier B.V. All rights reserved.

Using heat treatment effects and EBSD analysis to tailor microstructure of hybrid Mg nanocomposite for enhanced overall mechanical response

In this study, a detailed investigation on the effect of heat treatment on the microstructural characteristics, texture evolution and mechanical properties of Mg-(5.6Ti+2.5B(4)C)(BM) hybrid nanocomposite is presented. Optimised heat treatment parameters, namely, heat treatment temperature and heat treatment time, were first identified through grain size and microhardness measurements. Initially, heat treatment of composites was conducted at temperature range between 100 and 300 degrees C for 1 h. Based on optical microscopic analysis and microhardness measurements, it was evident that significant grain growth and reduction in microhardness occurred for temperatures > 200 degrees C. The cutoff temperature that caused significant grain growth/matrix softening was thus identified. Second, at constant temperature (200 degrees C), the effect of variation of heat treatment time was carried out (ranging between 1 and 5 h) so as to identify the range wherein increase in average grain size and reduction in microhardness occurred. Furthering the study, the effect of optimised heat treatment parameters (200 degrees C, 5 h) on the microstructural texture evolution and hence, on the tensile and compressive properties of the Mg-(5.6Ti+2.5B(4)C)(BM) hybrid nanocomposite was carried out. From electron backscattered diffraction (EBSD) analysis, it was identified that the optimised heat treatment resulted in recrystallisation and residual stress relaxation, as evident from the presence of similar to 87% strain free grains, when compared to that observed in the non-heat treated/as extruded condition (i.e. 2.2 times greater than in the as extruded condition). For the heat treated composite, under both tensile and compressive loads, a significant improvement in fracture strain values (similar to 60% increase) was observed when compared to that of the non-heat treated counterpart, with similar to 20% reduction in yield strength. Based on structure-property correlation, the change in mechanical characteristics is identified to be due to: (1) the presence of less stressed matrix/reinforcement interface due to the relief of residual stresses and (2) texture weakening due to matrix recrystallisation effects, both arising due to heat treatment.