A study on orthogonality sampling.

The goal of this paper is to study and further develop the orthogonality sampling or stationary waves algorithm for the detection of the location and shape of objects from the far field pattern of scattered waves in electromagnetics or acoustics. Orthogonality sampling can be seen as a special beam forming algorithm with some links to the point source method and to the linear sampling method. The basic idea of orthogonality sampling is to sample the space under consideration by calculating scalar products of the measured far field pattern , with a test function for all y in a subset Q of the space , m = 2, 3. The way in which this is carried out is important to extract the information which the scattered fields contain. The theoretical foundation of orthogonality sampling is only partly resolved, and the goal of this work is to initiate further research by numerical demonstration of the high potential of the approach. We implement the method for a two-dimensional setting for the Helmholtz equation, which represents electromagnetic scattering when the setup is independent of the third coordinate. We show reconstructions of the location and shape of objects from measurements of the scattered field for one or several directions of incidence and one or many frequencies or wave numbers, respectively. In particular, we visualize the indicator function both with the Dirichlet and Neumann boundary condition and for complicated inhomogeneous media.

Using idealized snow forcing to test teleconnections with the Indian summer monsoon in the Hadley Centre GCM

Anomalous heavy snow during winter or spring has long been regarded as a possible precursor of deficient Indian monsoon rainfall during the subsequent summer. However previous work in this field is inconclusive, in terms of the mechanism that communicates snow anomalies to the monsoon summer, and even the region from which snow has the most impact. In this study we explore these issues in coupled and atmosphere-only versions of the Hadley Centre model. A 1050-year control integration of the HadCM3 coupled model, which well represents the seasonal cycle of snow cover over the Eurasian continent, is analysed and shows evidence for weakened monsoons being preceded by strong snow forcing (in the absence of ENSO) over either the Himalaya/Tibetan Plateau or north/west Eurasia regions. However, empirical orthogonal function (EOF) analysis of springtime interannual variability in snow depth shows the leading mode to have opposite signs between these two regions, suggesting that competing mechanisms may be possible. To determine the dominant region, ensemble integrations are carried out using HadAM3, the atmospheric component of HadCM3, and a variety of anomalous snow forcing initial conditions obtained from the control integration of the coupled model. Forcings are applied during spring in separate experiments over the Himalaya/Tibetan Plateau and north/west Eurasia regions, in conjunction with climatological SSTs in order to avoid the direct effects of ENSO. With the aid of idealized forcing conditions in sensitivity tests, we demonstrate that forcing from the Himalaya region is dominant in this model via a Blanford-type mechanism involving reduced surface sensible heat and longwave fluxes, reduced heating of the troposphere over the Tibetan Plateau and consequently a reduced meridional tropospheric temperature gradient which weakens the monsoon during early summer. Snow albedo is shown to be key to the mechanism, explaining around 50% of the perturbation in sensible heating over the Tibetan Plateau, and accounting for the majority of cooling through the troposphere.

Prefrontal cortical-ventral striatal interactions involved in affective modulation of attentional performance: implications for corticostriatal circuit function

Anatomically segregated systems linking the frontal cortex and the striatum are involved in various aspects of cognitive, affective, and motor processing. In this study, we examined the effects of combined unilateral lesions of the medial prefrontal cortex (mPFC) and the core subregion of the nucleus accumbens (AcbC) in opposite hemispheres (disconnection) on a continuous performance, visual attention test [five-choice serial reaction-time task (5CSRTT)]. The disconnection lesion produced a set of specific changes in performance of the 5CSRTT, resembling changes that followed bilateral AcbC lesions while, in addition, comprising a subset of the behavioral changes after bilateral mPFC lesions previously reported using the same task. Specifically, both mPFC/AcbC disconnection and bilateral AcbC lesions markedly affected aspects of response control related to affective feedback, as indexed by perseverative responding in the 5CSRTT. These effects were comparable, although not identical, to those in animals with either bilateral AcbC or mPFC/AcbC disconnection lesions. The mPFC/AcbC disconnection resulted in a behavioral profile largely distinct from that produced by disconnection of a similar circuit described previously, between the mPFC and the dorsomedial striatum, which were shown to form a functional network underlying aspects of visual attention and attention to action. This distinction provides an insight into the functional specialization of corticostriatal circuits in similar behavioral contexts.

Unification of the probe and singular sources methods for the inverse boundary value problem by the no-response test

In this article, we use the no-response test idea, introduced in Luke and Potthast (2003) and Potthast (Preprint) and the inverse obstacle problem, to identify the interface of the discontinuity of the coefficient gamma of the equation del (.) gamma(x)del + c(x) with piecewise regular gamma and bounded function c(x). We use infinitely many Cauchy data as measurement and give a reconstructive method to localize the interface. We will base this multiwave version of the no-response test on two different proofs. The first one contains a pointwise estimate as used by the singular sources method. The second one is built on an energy (or an integral) estimate which is the basis of the probe method. As a conclusion of this, the probe and the singular sources methods are equivalent regarding their convergence and the no-response test can be seen as a unified framework for these methods. As a further contribution, we provide a formula to reconstruct the values of the jump of gamma(x), x is an element of partial derivative D at the boundary. A second consequence of this formula is that the blow-up rate of the indicator functions of the probe and singular sources methods at the interface is given by the order of the singularity of the fundamental solution.

The binding site distance test score: a robust method for the assessment of predicted protein binding sites

We propose a novel method for scoring the accuracy of protein binding site predictions – the Binding-site Distance Test (BDT) score. Recently, the Matthews Correlation Coefficient (MCC) has been used to evaluate binding site predictions, both by developers of new methods and by the assessors for the community wide prediction experiment – CASP8. Whilst being a rigorous scoring method, the MCC does not take into account the actual 3D location of the predicted residues from the observed binding site. Thus, an incorrectly predicted site that is nevertheless close to the observed binding site will obtain an identical score to the same number of nonbinding residues predicted at random. The MCC is somewhat affected by the subjectivity of determining observed binding residues and the ambiguity of choosing distance cutoffs. By contrast the BDT method produces continuous scores ranging between 0 and 1, relating to the distance between the predicted and observed residues. Residues predicted close to the binding site will score higher than those more distant, providing a better reflection of the true accuracy of predictions. The CASP8 function predictions were evaluated using both the MCC and BDT methods and the scores were compared. The BDT was found to strongly correlate with the MCC scores whilst also being less susceptible to the subjectivity of defining binding residues. We therefore suggest that this new simple score is a potentially more robust method for future evaluations of protein-ligand binding site predictions.

Effect of hyaluronidase on ocular motility and eyelid function in sub-Tenon's anaesthesia: randomised controlled trial

Purpose: To assess the effect of hyaluronidase on eye and eyelid movements when used as an adjunct in sub-Tenon's anaesthesia. Methods: A total of 60 patients who had sub-Tenon's anaesthesia prior to phacoemulsification surgery were divided into two equal groups in a double-masked randomised controlled fashion. Of these, Group A had 4 ml lignocaine 2%, while Group B had 4ml lignocaine 2% with the addition of sodium hyaluronidase 75 IU/ml. Ocular motility, levator, and orbicularis oculi function were measured in all patients at 5 and 8 min. Levator function was scored from 0 (no function) to 3 (complete function) while orbicularis function was scored from 0 to 2. The score for ocular motility was the sum in four positions of gaze, each position scoring from 0 to 2. Results were compared using a nonparametric test. Results Group B achieved significantly better ocular and lid akinesia than Group A both at 5 and 8 min with P < 0.01. The median scores for levator function at 5 and 8 min were 2 for Group A and 0 for Group B. For orbicularis function, the median scores at both time intervals were 2 for Group A and 1 for Group B. For ocular motility, the median score for Group A at 5 min was 3 and at 8 min was 2.5; for Group B at 5 min was 0.5 and at 8 min was 0. Conclusions: The addition of hyaluronidase in sub-Tenon's anaesthesia has a significant effect in improving ocular and lid (levator and orbicularis) akinesia.

A test of the master gene hypothesis for interspersed repetitive DNA sequences

Many families of interspersed repetitive DNA elements, including human Alu and LINE (Long Interspersed Element) elements, have been proposed to have accumulated through repeated copying from a single source locus: the "master gene." The extent to which a master gene model is applicable has implications for the origin, evolution, and function of such sequences. One repetitive element family for which a convincing case for a master gene has been made is the rodent ID (identifier) elements. Here we devise a new test of the master gene model and use it to show that mouse ID element sequences are not compatible with a strict master gene model. We suggest that a single master gene is rarely, if ever, likely to be responsible for the accumulation of any repeat family.

Calculation of converged rovibrational energies and partition function for methane using vibrational-rotational configuration interaction

The rovibration partition function of CH4 was calculated in the temperature range of 100-1000 K using well-converged energy levels that were calculated by vibrational-rotational configuration interaction using the Watson Hamiltonian for total angular momenta J=0-50 and the MULTIMODE computer program. The configuration state functions are products of ground-state occupied and virtual modals obtained using the vibrational self-consistent field method. The Gilbert and Jordan potential energy surface was used for the calculations. The resulting partition function was used to test the harmonic oscillator approximation and the separable-rotation approximation. The harmonic oscillator, rigid-rotator approximation is in error by a factor of 2.3 at 300 K, but we also propose a separable-rotation approximation that is accurate within 2% from 100 to 1000 K. (C) 2004 American Institute of Physics.

Modulation of the fecal microflora profile and immune function by a novel trans-galactooligosaccharide mixture (B-GOS) in healthy elderly volunteers

Background: Aging is associated with reduced numbers of beneficial colonic bifidobacteria and impaired immunity. Galactooligosaccharides (GOSs) stimulate the growth of bifidobacteria in younger adults, but little is known about their effects in the elderly and their immunomodulatory capacity. Objective: We assessed the effect of a prebiotic GOS mixture (B-GOS) on immune function and fecal microflora composition in healthy elderly subjects. Design: In a double-blind, placebo-controlled, crossover study, 44 elderly subjects were randomly assigned to receive either a placebo or the B-GOS treatment (5.5 g/d). Subjects consumed the treatments for 10 wk, and then went through a 4-wk washout period, before switching to the other treatment for the final 10 wk. Blood and fecal samples were collected at the beginning, middle (5 wk), and end of the test period. Predominant bacterial groups were quantified, and phagocytosis, natural killer (NK) cell activity, cytokine production, plasma cholesterol, and HDL cholesterol were measured. Results: B-GOS significantly increased the numbers of beneficial bacteria, especially bifidobacteria, at the expense of less beneficial groups compared with the baseline and placebo. Significant increases in phagocytosis, NK cell activity, and the production of antiinflammatory cytokine interleukin-10 (IL-10) and significant reduction in the production of proinflammatory cytokines (IL-6, IL-1 beta , and tumor necrosis factor-alpha) were also observed. B-GOS exerted no effects on total cholesterol or HDL-cholesterol production, however. Conclusions: B-GOS administration to healthy elderly persons resulted in positive effects on both the microflora composition and the immune response. Therefore, B-GOS may be a useful dietary candidate for the enhancement of gastrointestinal health and immune function in elderly persons. Am J Clin Nutr 2008; 88: 1438-46.

A preliminary investigation of the running digit span as a test of working memory

The objective of this study was to compare performance on different versions of the running span task, and to examine the relationship between task performance and tests of episodic memory and executive function. We found that the average capacity of the running span was approximately 4 digits, and at long sequence lengths, performance was no longer affected by varying the running span window. Both episodic and executive function measures correlated with short and long running spans. suggesting that a simple dissociation between immediate memory and executive processes in short and long running digit span tasks may not be warranted.

Dissociating mere exposure and repetition priming as a function of word type

The mere exposure effect is defined as enhanced attitude toward a stimulus that has been repeatedly exposed. Repetition priming is defined as facilitated processing of a previously exposed stimulus. We conducted a direct comparison between the two phenomena to test the assumption that the mere exposure effect represents an example of repetition priming. In two experiments, having studied a set of words or nonwords, participants were given a repetition priming task (perceptual identification) or one of two mere exposure (affective liking or preference judgment) tasks. Repetition printing was obtained for both words and nonwords, but only nonwords produced a mere exposure effect. This demonstrates a key boundary for observing the mere exposure effect, one not readily accommodated by a perceptual representation systems (Tulving & Schacter, 1990) account, which assumes that both phenomena should show some sensitivity to nonwords and words.

Probability density function estimation using orthogonal forward regression

Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression technique is adopted to construct sparse kernel density estimates. The proposed algorithm incrementally minimises a leave-one-out test error score to select a sparse kernel model, and a local regularisation method is incorporated into the density construction process to further enforce sparsity. The kernel weights are finally updated using the multiplicative nonnegative quadratic programming algorithm, which has the ability to reduce the model size further. Except for the kernel width, the proposed algorithm has no other parameters that need tuning, and the user is not required to specify any additional criterion to terminate the density construction procedure. Two examples are used to demonstrate the ability of this regression-based approach to effectively construct a sparse kernel density estimate with comparable accuracy to that of the full-sample optimised Parzen window density estimate.

Prediction of Parkinson’s Disease tremor onset using a radial basis function neural network based on particle swarm optimization

Deep Brain Stimulation (DBS) has been successfully used throughout the world for the treatment of Parkinson's disease symptoms. To control abnormal spontaneous electrical activity in target brain areas DBS utilizes a continuous stimulation signal. This continuous power draw means that its implanted battery power source needs to be replaced every 18–24 months. To prolong the life span of the battery, a technique to accurately recognize and predict the onset of the Parkinson's disease tremors in human subjects and thus implement an on-demand stimulator is discussed here. The approach is to use a radial basis function neural network (RBFNN) based on particle swarm optimization (PSO) and principal component analysis (PCA) with Local Field Potential (LFP) data recorded via the stimulation electrodes to predict activity related to tremor onset. To test this approach, LFPs from the subthalamic nucleus (STN) obtained through deep brain electrodes implanted in a Parkinson patient are used to train the network. To validate the network's performance, electromyographic (EMG) signals from the patient's forearm are recorded in parallel with the LFPs to accurately determine occurrences of tremor, and these are compared to the performance of the network. It has been found that detection accuracies of up to 89% are possible. Performance comparisons have also been made between a conventional RBFNN and an RBFNN based on PSO which show a marginal decrease in performance but with notable reduction in computational overhead.

Acute effects of elevated NEFA on vascular function: a comparison of SFA and MUFA

There is emerging evidence to show that high levels of NEFA contribute to endothelial dysfunction and impaired insulin sensitivity. However, the impact of NEFA composition remains unclear. A total of ten healthy men consumed test drinks containing 50 g of palm stearin (rich in SFA) or high-oleic sunflower oil (rich in MUFA) on separate occasions; a third day included no fat as a control. The fats were emulsified into chocolate drinks and given as a bolus (approximately 10 g fat) at baseline followed by smaller amounts (approximately 3 g fat) every 30 min throughout the 6 h study day. An intravenous heparin infusion was initiated 2 h after the bolus, which resulted in a three- to fourfold increase in circulating NEFA level from baseline. Mean arterial stiffness as measured by digital volume pulse was higher during the consumption of SFA (P,0·001) but not MUFA (P¼0·089) compared with the control. Overall insulin and gastric inhibitory peptide response was greater during the consumption of both fats compared with the control (P,0·001); there was a second insulin peak in response to MUFA unlike SFA. Consumption of SFA resulted in higher levels of soluble intercellular adhesion molecule-1 (sI-CAM) at 330 min than that of MUFA or control (P#0·048). There was no effect of the test drinks on glucose, total nitrite, plasminogen activator inhibitor-1 or endothelin-1 concentrations. The present study indicates a potential negative impact of elevated NEFA derived from the consumption of SFA on arterial stiffness and sI-CAM levels. More studies are needed to fully investigate the impact of NEFA composition on risk factors for CVD.

Dual-orthogonal radial basis function networks for nonlinear time series prediction

A new structure of Radial Basis Function (RBF) neural network called the Dual-orthogonal RBF Network (DRBF) is introduced for nonlinear time series prediction. The hidden nodes of a conventional RBF network compare the Euclidean distance between the network input vector and the centres, and the node responses are radially symmetrical. But in time series prediction where the system input vectors are lagged system outputs, which are usually highly correlated, the Euclidean distance measure may not be appropriate. The DRBF network modifies the distance metric by introducing a classification function which is based on the estimation data set. Training the DRBF networks consists of two stages. Learning the classification related basis functions and the important input nodes, followed by selecting the regressors and learning the weights of the hidden nodes. In both cases, a forward Orthogonal Least Squares (OLS) selection procedure is applied, initially to select the important input nodes and then to select the important centres. Simulation results of single-step and multi-step ahead predictions over a test data set are included to demonstrate the effectiveness of the new approach.