Elmar Wolfgang Lang

A Geometric Algorithm for Overcomplete Linear ICA

Abstract Geometric algorithms for linear square independent component analysis (ICA) have recently received some attention due to their pictorial description and their relative ease of implementation. The geometric approach to ICA was proposed first by Puntonet and Prieto (Neural Process. Lett. 2 (1995), Signal Processing 46 (1995) 267) in order to separate linear mixtures. We generalize these algorithms to overcomplete cases with more sources than sensors. With geometric ICA we get an efficient method for the matrix-recovery step in the framework of a two-step approach to the source separation problem. The second step—source-recovery—uses a maximum-likelihood approach. There we prove that the shortest-path algorithm as proposed by Bofill and Zibulevsky (in: P. Pajunen, J. Karhunen (Eds.), Independent Component Analysis and Blind Signal Separation (Proceedings of ICA’2000), 2000, pp. 87–92) indeed solves the maximum-likelihood conditions.

Intronic microRNAs support their host genes by mediating synergistic and antagonistic regulatory effects

BackgroundMicroRNA-mediated control of gene expression via translational inhibition has substantial impact on cellular regulatory mechanisms. About 37% of mammalian microRNAs appear to be located within introns of protein coding genes, linking their expression to the promoter-driven regulation of the host gene. In our study we investigate this linkage towards a relationship beyond transcriptional co-regulation.ResultsUsing measures based on both annotation and experimental data, we show that intronic microRNAs tend to support their host genes by regulation of target gene expression with significantly correlated expression patterns. We used expression data of three differentiating cell types and compared gene expression profiles of host and target genes. Many microRNA target genes show expression patterns significantly correlated with the expressions of the microRNA host genes. By calculating functional similarities between host and predicted microRNA target genes based on GO annotations, we confirm that many microRNAs link host and target gene activity in an either synergistic or antagonistic manner.ConclusionsThese two regulatory effects may result from fine tuning of target gene expression functionally related to the host or knock-down of remaining opponent target gene expression. This finding allows to extend the common practice of mapping large scale gene expression data to protein associated genes with functionality of co-expressed intronic microRNAs.

Diffusion in simple fluids

Computed self diffusion coefficients for the Lennard-Jones and hard sphere fluids are related by where σB=σLJ(2/[1+ⅈ(1+2k B T/e)])1/6, the effective hard sphere diameter, is the (average) distance of closest approach in collisions between molecules which interact with the positive part of the LJ potential, and the Arrhenius term reflects the influence of the negative part. σLJ and ϵ are the size and well depth parameters. Measured diffusion coefficients of the halomethane liquids are reproduced by the equation over wide ranges of temperature and density and do not reveal any influence of the inelastic effects associated with molecular anisotropy.

Pressure and temperature dependence of the longitudinal proton relaxation times in supercooled water to -87°C and 2500 bar

The longitudinal proton relaxation times T1 of the water protons have been determined at 100.1 MHz in the temperature range from +20 to −87 °C and up to pressures of 2500 bar. At temperatures below +10 °C, the T1 isotherms exhibit a maximum at pressures between 1.5 and 2 kbar. While at +10 and 0 °C, T1 rises by ∼10% from its atmospheric pressure value, this maximum becomes much more pronounced between −20 and −45 °C. In this region application of pressure increases T1 by ∼100%. The isobars at 2 kbar and above run through a minimum at −76 °C, indicating that at this temperature ωτϑ?1 and that the proton relaxation rate cannot be described by the extreme narrowing condition below ∼−40 °C. The experimental T1 data and the τϑ values derived at 2 kbar could be treated by a sum of two exponentials. While the smaller activation energies derived from this fit of 3.44±0.17 kcal mole−1 is independent of pressure, the higher activation energy decreases from 13±0.65 kcal mole−1 at atmospheric pressure to 9.3±0.5 kcal...

Linear geometric ICA: fundamentals and algorithms

Geometric algorithms for linear independent component analysis (ICA) have recently received some attention due to their pictorial description and their relative ease of implementation. The geometric approach to ICA was proposed first by Puntonet and Prieto (1995). We will reconsider geometric ICA in a theoretic framework showing that fixed points of geometric ICA fulfill a geometric convergence condition (GCC), which the mixed images of the unit vectors satisfy too. This leads to a conjecture claiming that in the nongaussian unimodal symmetric case, there is only one stable fixed point, implying the uniqueness of geometric ICA after convergence. Guided by the principles of ordinary geometric ICA, we then present a new approach to linear geometric ICA based on histograms observing a considerable improvement in separation quality of different distributions and a sizable reduction in computational cost, by a factor of 100, compared to the ordinary geometric approach. Furthermore, we explore the accuracy of the algorithm depending on the number of samples and the choice of the mixing matrix, and compare geometric algorithms with classical ICA algorithms, namely, Extended Infomax and FastICA. Finally, we discuss the problem of high-dimensional data sets within the realm of geometrical ICA algorithms.

A Novel LMS Algorithm Applied to Adaptive Noise Cancellation

In this letter, we propose a novel least-mean-square (LMS) algorithm for filtering speech sounds in the adaptive noise cancellation (ANC) problem. It is based on the minimization of the squared Euclidean norm of the difference weight vector under a stability constraint defined over the a posteriori estimation error. To this purpose, the Lagrangian methodology has been used in order to propose a nonlinear adaptation rule defined in terms of the product of differential inputs and errors which means a generalization of the normalized (N)LMS algorithm. The proposed method yields better tracking ability in this context as shown in the experiments which are carried out on the AURORA 2 and 3 speech databases. They provide an extensive performance evaluation along with an exhaustive comparison to standard LMS algorithms with almost the same computational load, including the NLMS and other recently reported LMS algorithms such as the modified (M)-NLMS, the error nonlinearity (EN)-LMS, or the normalized data nonlinearity (NDN)-LMS adaptation.

Brain connectivity analysis: a short survey

This short survey the reviews recent literature on brain connectivity studies. It encompasses all forms of static and dynamic connectivity whether anatomical, functional, or effective. The last decade has seen an ever increasing number of studies devoted to deduce functional or effective connectivity, mostly from functional neuroimaging experiments. Resting state conditions have become a dominant experimental paradigm, and a number of resting state networks, among them the prominent default mode network, have been identified. Graphical models represent a convenient vehicle to formalize experimental findings and to closely and quantitatively characterize the various networks identified. Underlying these abstract concepts are anatomical networks, the so-called connectome, which can be investigated by functional imaging techniques as well. Future studies have to bridge the gap between anatomical neuronal connections and related functional or effective connectivities.

Nuclear magnetic relaxation rate dispersion in supercooled heavy water under high pressure

Spin‐lattice (T1) and spin–spin (T2) relaxation times of the deuterons in supercooled D2O at 225 MPa, measured at two frequencies: 55.54 and 39.14 MHz down to 188 K are reported. The results show that T1 and T2 become frequency dependent in supercooled liquid water under high hydrostatic pressure at temperatures below ∼220 K. Theoretical expressions for the relaxation rates are deduced under the assumption that the orientational fluctuations of the water molecules are composed of fast librational oscillations and slower diffusional motions. The effect of the librations is to reduce the size of the deuterium quadrupole coupling constant. The diffusional motions are nearly isotropic and dominate the T dependence of the relaxation times. The autocorrelation function of the slow orientational fluctuations was assumed to be exponential at long times with a single time constant, the orientational correlation time τ2. The T dependence of the latter is well described by the VTF equation. The parameters obtained b...

Correlations Between Light Penetration into Skin and the Therapeutic Outcome Following Laser Therapy of Port-wine Stains

For several years the flashlamp-pumped pulsed dye laser (FPDL) has been the favoured method for the treatment of port-wine stains (PWS). The therapeutic outcome of FPDL laser therapy depends on the anatomical location of the PWS and is mainly attributed to morphological parameters such as size and depth of the PWS blood vessels. The aim of this study was to show a correlation between the therapeutic outcome following FPDL therapy and the optical properties of the skin overlying the PWS vessels. For this purpose the therapeutic outcome following FPDL treatment (585 nm; 0.45 ms) of 884 PWS situated on different body sites was evaluated by judging the grade of fading of PWS colour. On the other hand the light penetration into 123 skin samples (thickness 0.10–1.35 mm) was determined between 450 nm and 1030 nm and compared with the PWS laser therapy outcome for equal locations by statistical analysis. PWS on the neck, trunk, arms or legs yielded a higher mean grade of fading as compared to PWS on the head. Within the face, a wide range of fading was evident. The light penetration into skin increased linearly with increasing wavelength and location-dependent differences were found. The attenuation coefficient was 22.8±5.3 mm−1 at 585 nm. No significant or strong correlation was observed between the therapeutic outcome of PWS laser therapy and the light penetration into skin. However, a correlation was obvious by plotting the respective profile plots. Therefore, among other effects, in particular morphological parameters of PWS vessels, the optical properties of the skin contribute to a small extent to the clinical outcome of PWS laser therapy.

Automatic computer aided diagnosis tool using component-based SVM

Alzheimer type dementia (ATD) is a progressive neurodegenerative disorder first affecting memory functions and then gradually affecting all cognitive functions with behavioral impairments and eventually causing death. Functional brain imaging including single-photon emission computed tomography (SPECT) is commonly used to guide the clinician’s diagnosis. However, conventional evaluation of these scans often relies on manual reorientation, visual reading and semiquantitative analysis of certain regions of the brain. These steps are time consuming, subjective and prone to error. This paper shows a fully automatic computer-aided diagnosis (CAD) system for improving the accuracy in the early diagnosis of the Alzheimer’s disease. The proposed approach is based on a first automatic feature selection, and secondly a combination of component-based support vector machine (SVM) classification and a pasting votes technique of ensemble SVM classifiers.