Wavelet analysis of bender element signals

Accurate determination of shear wave arrival time using bender elements may be severely affected by a combination of near-field effects and reflected waves. These may mask the first arrival of the shear wave, making its detection difficult in the time domain. This paper describes an approach for measuring the shear wave arrival time through analysis of the output signal in the time-scale domain using a multi-scale wavelet transform. The local maxima lines of the wavelet transform modulus are observed at different scales, and all singularities are mathematically characterised, allowing subsequent detection of the singularity relating to the first arrival. Examples of the use of this approach on typical synthetic and experimental bender element signals are also supplied, and these results are compared with those from other time and frequency domain approaches. The wavelet approach is not affected by near-field effects, but instead is characterised by a relatively consistent singularity related to the shear wave arrival time, across a range of frequencies and noise levels.

RMA with quantile normalization mixes biological signals between different sample groups in microarray data analysis

Quantile normalization (QN) is a technique for microarray data processing and is the default normalization method in the Robust Multi-array Average (RMA) procedure, which was primarily designed for analysing gene expression data from Affymetrix arrays. Given the abundance of Affymetrix microarrays and the popularity of the RMA method, it is crucially important that the normalization procedure is applied appropriately. In this study we carried out simulation experiments and also analysed real microarray data to investigate the suitability of RMA when it is applied to dataset with different groups of biological samples. From our experiments, we showed that RMA with QN does not preserve the biological signal included in each group, but rather it would mix the signals between the groups. We also showed that the Median Polish method in the summarization step of RMA has similar mixing effect. RMA is one of the most widely used methods in microarray data processing and has been applied to a vast volume of data in biomedical research. The problematic behaviour of this method suggests that previous studies employing RMA could have been misadvised or adversely affected. Therefore we think it is crucially important that the research community recognizes the issue and starts to address it. The two core elements of the RMA method, quantile normalization and Median Polish, both have the undesirable effects of mixing biological signals between different sample groups, which can be detrimental to drawing valid biological conclusions and to any subsequent analyses. Based on the evidence presented here and that in the literature, we recommend exercising caution when using RMA as a method of processing microarray gene expression data, particularly in situations where there are likely to be unknown subgroups of samples.

Wavelets for the Analysis and Compression of Power System Disturbances

Wavelets introduce new classes of basis functions for time-frequency signal analysis and have properties particularly suited to the transient components and discontinuities evident in power system disturbances. Wavelet analysis involves representing signals in terms of simpler, fixed building blocks at different scales and positions. This paper examines the analysis and subsequent compression properties of the discrete wavelet and wavelet packet transforms and evaluates both transforms using an actual power system disturbance from a digital fault recorder. The paper presents comparative compression results using the wavelet and discrete cosine transforms and examines the application of wavelet compression in power monitoring to mitigate against data communications overheads.

Analysis of multiple aspects of a repeated signal: power and rate of rapping during shell fights in hermit crabs

Repeated activities used by animals during contests are assumed to act as signals advertising the quality of the sender. However, their exact functions are not well understood and observations fit only a limited set of the predictions made by models of signaling systems. Experimental studies of contest behavior tend to focus on analysis of the rate of signaling, but individual performances may also vary in magnitude. Both of these features can vary between outcomes and within contests. We examined changes in the rate and power of shell rapping during shell fights in hermit crabs. We show that both rate and power decline during the course of the encounter and that the duration of pauses between bouts of shell rapping increases with an index of the total effort put into each bout. This supports the idea that the vigor of shell rapping is regulated by fatigue and could therefore act as a signal of stamina. By examining different interacting components of this complex activity, we gain greater insight into its function than would be achieved by investigating a single aspect in isolation.

Ca(2+) signals coordinate zygotic polarization and cell cycle progression in the brown alga Fucus serratus

Zygotes of the fucoid brown algae provide excellent models for addressing fundamental questions about zygotic symmetry breaking. Although the acquisition of polarity is tightly coordinated with the timing and orientation of the first asymmetric division-with zygotes having to pass through a G1/S-phase checkpoint before the polarization axis can be fixed -the mechanisms behind the interdependence of polarization and cell cycle progression remain unclear. In this study, we combine in vivo Ca(2+) imaging, single cell monitoring of S-phase progression and multivariate analysis of high-throughput intracellular Ca(2+) buffer loading to demonstrate that Ca(2+) signals coordinate polarization and cell cycle progression in the Fucus serratus zygote. Consistent with earlier studies on this organism, and in contrast to animal models, we observe no fast Ca(2+) wave following fertilization. Rather, we show distinct slow localized Ca(2+) elevations associated with both fertilization and S-phase progression, and we show that both S-phase and zygotic polarization are dependent on pre-S-phase Ca(2+) increases. Surprisingly, this Ca(2+) requirement cannot be explained by co-dependence on a single G1/ S-phase checkpoint, as S phase and zygotic polarization are differentially sensitive to pre-S-phase Ca(2+) elevations and can be uncoupled. Furthermore, subsequent cell cycle progression through M phase is independent of localized actin polymerization and zygotic polarization. This absence of a morphogenesis checkpoint, together with the observed Ca(2+)dependences of S phase and polarization, show that the regulation of zygotic division in the brown algae differs from that in other eukaryotic model systems, such as yeast and Drosophila.

The chronic fatigue syndrome: A comparative pathway analysis

In this paper, we introduce a method to detect pathological pathways of a disease. We aim to identify biological processes rather than single genes affected by the chronic fatigue syndrome (CFS). So far, CFS has neither diagnostic clinical signals nor abnormalities that could be diagnosed by laboratory examinations. It is also unclear if the CFS represents one disease or can be subdivided in different categories. We use information from clinical trials, the gene ontology (GO) database as well as gene expression data to identify undirected dependency graphs (UDGs) representing biological processes according to the GO database. The structural comparison of UDGs of sick versus non-sick patients allows us to make predictions about the modification of pathways due to pathogenesis.

Effect of signal intensity normalization on the multivariate analysis of spectral data in complex 'real-world' datasets

Spectral signal intensities, especially in 'real-world' applications with nonstandardized sample presentation due to uncontrolled variables/factors, commonly require additional spectral processing to normalize signal intensity in an effective way. In this study, we have demonstrated the complexity of choosing a normalization routine in the presence of multiple spectrally distinct constituents by probing a dataset of Raman spectra. Variation in absolute signal intensity (90.1% of total variance) of the Raman spectra of these complex biological samples swamps the variation in useful signals (9.4% of total variance), degrading its diagnostic and evaluative potential.

Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease

We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by genotyping of top association signals in 56,682 additional individuals. This analysis identified 13 loci newly associated with CAD at P < 5 x 10(-8) and confirmed the association of 10 of 12 previously reported CAD loci. The 13 new loci showed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6% to 17% increase in the risk of CAD per allele. Notably, only three of the new loci showed significant association with traditional CAD risk factors and the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the new CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.

Analysis of information leakage from encrypted Skype conversations

Voice over IP (VoIP) has experienced a tremendous growth over the last few years and is now widely used among the population and for business purposes. The security of such VoIP systems is often assumed, creating a false sense of privacy. This paper investigates in detail the leakage of information from Skype, a widely used and protected VoIP application. Experiments have shown that isolated phonemes can be classified and given sentences identified. By using the dynamic time warping (DTW) algorithm, frequently used in speech processing, an accuracy of 60% can be reached. The results can be further improved by choosing specific training data and reach an accuracy of 83% under specific conditions. The initial results being speaker dependent, an approach involving the Kalman filter is proposed to extract the kernel of all training signals.

Spectrum efficient cooperative relaying based on outage-multiplexing tradeoff analysis.

Spectrum efficient multiple relay selection strategy for two-hop cooperative decode-and-forward relay networks is proposed for the case when the sum power among all relay nodes is limited. Based on the outage-multiplexing tradeoff (OMT), the number of active relay nodes is maximized so that the resulting sum-relay capacity is maximized while each relay outage capacity remains greater than or equal to a certain target level. Using asymptotic analysis, it is shown that for the proposed OMT relaying strategy the associated multiplexing and cooperative system diversity gains improve proportionally with the number of active relay nodes. It is also shown analytically that the proposed OMT relaying outperforms the conventional opportunistic single relaying in terms of the sum-relay capacity.