In silico analysis of candidate genes involved in light sensing and signal transduction pathways in soybean

Several aspects of photoperception and light signal transduction have been elucidated by studies with model plants. However, the information available for economically important crops, such as Fabaceae species, is scarce. In order to incorporate the existing genomic tools into a strategy to advance soybean research, we have investigated publicly available expressed sequence tag ( EST) sequence databases in order to identify Glycine max sequences related to genes involved in light-regulated developmental control in model plants. Approximately 38,000 sequences from open-access databases were investigated, and all bona fide and putative photoreceptor gene families were found in soybean sequence databases. We have identified G. max orthologs for several families of transcriptional regulators and cytoplasmic proteins mediating photoreceptor-induced responses, although some important Arabidopsis phytochrome-signaling components are absent. Moreover, soybean and Arabidopsis gene-family homologs appear to have undergone a distinct expansion process in some cases. We propose a working model of light perception, signal transduction and response-eliciting in G. max, based on the identified key components from Arabidopsis. These results demonstrate the power of comparative genomics between model systems and crop species to elucidate several aspects of plant physiology and metabolism.

A matching pursuit-based signal complexity measure for the analysis of newborn EEG

This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity, which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed relative structural complexity measure is used in the analysis of newborn EEG. To do this, firstly, a time-frequency (TF) decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure).

Benefits of amplification for speech recognition in background noise

The purpose of the present study was to examine the benefits of providing audible speech to listeners with sensorineural hearing loss when the speech is presented in a background noise. Previous studies have shown that when listeners have a severe hearing loss in the higher frequencies, providing audible speech (in a quiet background) to these higher frequencies usually results in no improvement in speech recognition. In the present experiments, speech was presented in a background of multitalker babble to listeners with various severities of hearing loss. The signal was low-pass filtered at numerous cutoff frequencies and speech recognition was measured as additional high-frequency speech information was provided to the hearing-impaired listeners. It was found in all cases, regardless of hearing loss or frequency range, that providing audible speech resulted in an increase in recognition score. The change in recognition as the cutoff frequency was increased, along with the amount of audible speech information in each condition (articulation index), was used to calculate the "efficiency" of providing audible speech. Efficiencies were positive for all degrees of hearing loss. However, the gains in recognition were small, and the maximum score obtained by an listener was low, due to the noise background. An analysis of error patterns showed that due to the limited speech audibility in a noise background, even severely impaired listeners used additional speech audibility in the high frequencies to improve their perception of the "easier" features of speech including voicing

Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

Analysis of small signal stability margins using genetic optimization

Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.

Quantum analysis of the nondegenerate optical parametric oscillator with injected signal

In this paper we study the nondegenerate optical parametric oscillator with injected signal, both analytically and numerically. We develop a perturbation approach which allows us to find approximate analytical solutions, starting from the full equations of motion in the positive-P representation. We demonstrate the regimes of validity of our approximations via comparison with the full stochastic results. We find that, with reasonably low levels of injected signal, the system allows for demonstrations of quantum entanglement and the Einstein-Podolsky-Rosen paradox. In contrast to the normal optical parametric oscillator operating below threshold, these features are demonstrated with relatively intense fields.

Absence of pathological scarring in the donor site of the scalp in burns: An analysis of 295 cases

Aim: This study aims to describe the incidence of complications on scalp from which a thin split-skin graft was harvested (0.005-0.007 in.) of the donor site in children and adult burn victims. Methods: We reviewed the medical records of 295 burn patients admitted in the Burn Unit of the Clinical Hospital of the Faculty of Medicine of Ribeirao Preto, from January 1998 to December 2007, whose scalps were used as donor site for grafts. Skin-graft thickness varied from 0.005 in. to 0.007 in. The occurrence of pathological healing was evaluated clinically and the time of epithelisation by the main surgeon and a plastic surgeon or a staff nurse. Results: Of the 295 patients whose scalps were used as donor site, 274 were followed from 6 months to 10 years after the procedure (median 18.2 months). Twenty-one patients were lost to follow-up in the first 6 months. No hypertrophic scarring or keloids on the donor site was observed. Five patients (1.82%) presented with folliculitis and two of them were evaluated with small areas of alopecia (0.7%), treated with resection of these areas and primary suture. The average time of epithelisation of the donor site was 7 days. Conclusion: The harvest of thinner split graft from the scalp is a safe procedure. (C) 2009 Elsevier Ltd and ISBI. All rights reserved.

Mutational analysis of branching in pea. Evidence that Rms1 and Rms5 regulate the same novel signal

The fifth increased branching ramosus (rms) mutant, rms5, from pea (Pisum sativum), is described here for phenotype and grafting responses with four other rms mutants. Xylem sap zeatin riboside concentration and shoot auxin levels in rms5 plants have also been compared with rms1 and wild type (WT). Rms1 and Rms5 appear to act closely at the biochemical or cellular level to control branching, because branching was inhibited in reciprocal epicotyl grafts between rms5 or rms1 and WT plants, but not inhibited in reciprocal grafts between rms5 and rmsl seedlings. The weakly transgressive or slightly additive phenotype of the rmsl rms5 double mutant provides further evidence for this interaction. Like rms1, rms5 rootstocks have reduced xylem sap cytokinin concentrations, and rms5 shoots do not appear deficient in indole-3-acetic acid or 4-chloroindole-3-acetic acid. Rms1 and Rms5 are similar in their interaction with other Rms genes. Reciprocal grafting studies with rmsl, rms2, and rms5, together with the fact that root xylem sap cytokinin concentrations are reduced in rms1 and rms5 and elevated in rms2 plants, indicates that Rms1 and Rms5 may control a different pathway than that controlled by Rms2. Our studies indicate that Rms1 and Rms5 may regulate a novel graft-transmissible signal involved in the control of branching.

Lateralization of speech production using verbal/manual dual tasks: meta-analysis of sex differences and practice effects

The present paper reviews the findings of 30 years of verbal/manual dual task studies, the method most commonly used to assess lateralization of speech production in non-clinical samples. Meta-analysis of 64 results revealed that both the type of manual task used and the nature of practice that is given influence the size of the laterality effect. A meta-analysis of 36 results examining the effect size of sex differences in estimate,, of lateralization of speech production indicated that males appear to show, slightly larger laterality effects than females. (C) 2002 Elsevier Science Ltd. All rights reserved.

Analysis of tongue shape and motion in speech production using statistical modeling

The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

Atrial activation during sinus rhythm in patients with rheumatic and non-rheumatic paroxysmal atrial fibrillation. Frequency-domain analysis using signal-averaged electrocardiography

OBJECTIVE: Using P-wave signal-averaged electrocardiography, we assessed the patterns of atrial electrical activation in patients with idiopathic atrial fibrillation as compared with patterns in patients with atrial fibrillation associated with structural heart disease. METHODS: Eighty patients with recurrent paroxysmal atrial fibrillation were divided into 3 groups as follows: group I - 40 patients with atrial fibrillation associated with non-rheumatic heart disease; group II - 25 patients with rheumatic atrial fibrillation; and group III - 15 patients with idiopathic atrial fibrillation. All patients underwent P-wave signal-averaged electrocardiography for frequency-domain analysis using spectrotemporal mapping and statistical techniques for detecting and quantifying intraatrial conduction disturbances. RESULTS: We observed an important fragmentation in atrial electrical conduction in 27% of the patients in group I, 64% of the patients in group II, and 67% of the patients in group III (p=0.003). CONCLUSION: Idiopathic atrial fibrillation has important intraatrial conduction disturbances. These alterations are similar to those observed in individuals with rheumatic atrial fibrillation, suggesting the existence of some degree of structural involvement of the atrial myocardium that cannot be detected with conventional electrocardiography and echocardiography.

Modular analysis of signal transduction networks

Modularity, signaling networks, sytems biology