Behavioral and EEG effects of GABAergic manipulation of the nigro-tectal pathway in the Wistar audiogenic rat (WAR) strain II: An EEG wavelet analysis and retrograde neuronal tracer approach

The role of the substantia nigra pars reticulata (SNPr) and superior colliculus (SC) network in rat strains susceptible to audiogenic seizures still remain underexplored in epileptology. In a previous study from our laboratory, the GABAergic drugs bicuculline (BIC) and muscimol (MUS) were microinjected into the deep layers of either the anterior SC (aSC) or the posterior SC (pSC) in animals of the Wistar audiogenic rat (WAR) strain submitted to acoustic stimulation, in which simultaneous electroencephalographic (EEG) recording of the aSC, pSC, SNPr and striatum was performed. Only MUS microinjected into the pSC blocked audiogenic seizures. In the present study, we expanded upon these previous results using the retrograde tracer Fluorogold (FG) microinjected into the aSC and pSC in conjunction with quantitative EEG analysis (wavelet transform), in the search for mechanisms associated with the susceptibility of this inbred strain to acoustic stimulation. Our hypothesis was that the WAR strain would have different connectivity between specific subareas of the superior colliculus and the SNPr when compared with resistant Wistar animals and that these connections would lead to altered behavior of this network during audiogenic seizures. Wavelet analysis showed that the only treatment with an anticonvulsant effect was MUS microinjected into the pSC region, and this treatment induced a sustained oscillation in the theta band only in the SNPr and in the pSC. These data suggest that in WAR animals, there are at least two subcortical loops and that the one involved in audiogenic seizure susceptibility appears to be the pSC-SNPr circuit. We also found that WARs presented an increase in the number of FG + projections from the posterior SNPr to both the aSC and pSC (primarily to the pSC), with both acting as proconvulsant nuclei when compared with Wistar rats. We concluded that these two different subcortical loops within the basal ganglia are probably a consequence of the WAR genetic background. (C) 2012 Elsevier Inc. All rights reserved.

A novel method for power quality multiple disturbance decomposition based on Independent Component Analysis

In this paper, a novel method for power quality signal decomposition is proposed based on Independent Component Analysis (ICA). This method aims to decompose the power system signal (voltage or current) into components that can provide more specific information about the different disturbances which are occurring simultaneously during a multiple disturbance situation. The ICA is originally a multichannel technique. However, the method proposes its use to blindly separate out disturbances existing in a single measured signal (single channel). Therefore, a preprocessing step for the ICA is proposed using a filter bank. The proposed method was applied to synthetic data, simulated data, as well as actual power system signals, showing a very good performance. A comparison with the decomposition provided by the Discrete Wavelet Transform shows that the proposed method presented better decoupling for the analyzed data. (C) 2012 Elsevier Ltd. All rights reserved.

Automatic lumen segmentation in IVOCT images using binary morphological reconstruction

Abstract Background Atherosclerosis causes millions of deaths, annually yielding billions in expenses round the world. Intravascular Optical Coherence Tomography (IVOCT) is a medical imaging modality, which displays high resolution images of coronary cross-section. Nonetheless, quantitative information can only be obtained with segmentation; consequently, more adequate diagnostics, therapies and interventions can be provided. Since it is a relatively new modality, many different segmentation methods, available in the literature for other modalities, could be successfully applied to IVOCT images, improving accuracies and uses. Method An automatic lumen segmentation approach, based on Wavelet Transform and Mathematical Morphology, is presented. The methodology is divided into three main parts. First, the preprocessing stage attenuates and enhances undesirable and important information, respectively. Second, in the feature extraction block, wavelet is associated with an adapted version of Otsu threshold; hence, tissue information is discriminated and binarized. Finally, binary morphological reconstruction improves the binary information and constructs the binary lumen object. Results The evaluation was carried out by segmenting 290 challenging images from human and pig coronaries, and rabbit iliac arteries; the outcomes were compared with the gold standards made by experts. The resultant accuracy was obtained: True Positive (%) = 99.29 ± 2.96, False Positive (%) = 3.69 ± 2.88, False Negative (%) = 0.71 ± 2.96, Max False Positive Distance (mm) = 0.1 ± 0.07, Max False Negative Distance (mm) = 0.06 ± 0.1. Conclusions In conclusion, by segmenting a number of IVOCT images with various features, the proposed technique showed to be robust and more accurate than published studies; in addition, the method is completely automatic, providing a new tool for IVOCT segmentation.

Analysis Methodology for Vortex-Induced Motion (VIM) of a Monocolumn Platform Applying the Hilbert-Huang Transform Method

Vortex-induced motion (VIM) is a highly nonlinear dynamic phenomenon. Usual spectral analysis methods, using the Fourier transform, rely on the hypotheses of linear and stationary dynamics. A method to treat nonstationary signals that emerge from nonlinear systems is denoted Hilbert-Huang transform (HHT) method. The development of an analysis methodology to study the VIM of a monocolumn production, storage, and offloading system using HHT is presented. The purposes of the present methodology are to improve the statistics analysis of VIM. The results showed to be comparable to results obtained from a traditional analysis (mean of the 10% highest peaks) particularly for the motions in the transverse direction, although the difference between the results from the traditional analysis for the motions in the in-line direction showed a difference of around 25%. The results from the HHT analysis are more reliable than the traditional ones, owing to the larger number of points to calculate the statistics characteristics. These results may be used to design risers and mooring lines, as well as to obtain VIM parameters to calibrate numerical predictions. [DOI: 10.1115/1.4003493]

Analysis of noise in aircraft cabins through the VHF channel

Purpose - The purpose of this paper is to present a method to analyze the noise in aircraft cabins through the VHF Aeronautical Communication Channel, aimed at examining an environment that has the possibility of communication problems between the aircraft crew and the professionals responsible for the controls on land. Design/methodology/approach - This analysis includes equipment normally used for identification and comparison of electromagnetic noise, the cabin and the environment that are present in an airport, as well as equipment for frequency analysis and intensity of those signals. The analysis is done in a reverse way, eliminating situations that are not common in the examined environment, until the identification of the situation with the irregularity. Findings - According to the results, the implementation of the Fourier transform for noise analysis in the cabin was efficient. These results demonstrate that through this transformation, the noise sources can be identified in the environments in cases where there is much spectrum pollution. Research limitations/implications - This kind of noise analysis is important, considering the importance of having good accuracy in airport environment analysis. Originality/value - The paper presents the main trends in the future of aviation communications, and describes the new applications that aim to minimize problems with the current VHF channel.

Fractal descriptors based on Fourier spectrum applied to texture analysis

This work proposes the development and study of a novel technique lot the generation of fractal descriptors used in texture analysis. The novel descriptors are obtained from a multiscale transform applied to the Fourier technique of fractal dimension calculus. The power spectrum of the Fourier transform of the image is plotted against the frequency in a log-log scale and a multiscale transform is applied to this curve. The obtained values are taken as the fractal descriptors of the image. The validation of the proposal is performed by the use of the descriptors for the classification of a dataset of texture images whose real classes are previously known. The classification precision is compared to other fractal descriptors known in the literature. The results confirm the efficiency of the proposed method. (C) 2012 Elsevier B.V. All rights reserved.

Shape analysis using fractal dimension: A curvature based approach

The present work shows a novel fractal dimension method for shape analysis. The proposed technique extracts descriptors from a shape by applying a multi-scale approach to the calculus of the fractal dimension. The fractal dimension is estimated by applying the curvature scale-space technique to the original shape. By applying a multi-scale transform to the calculus, we obtain a set of descriptors which is capable of describing the shape under investigation with high precision. We validate the computed descriptors in a classification process. The results demonstrate that the novel technique provides highly reliable descriptors, confirming the efficiency of the proposed method. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4757226]

Functional Magnetic Resonance Imaging Data Analysis by Autoregressive Estimator

The autoregressive (AR) estimator, a non-parametric method, is used to analyze functional magnetic resonance imaging (fMRI) data. The same method has been used, with success, in several other time series data analysis. It uses exclusively the available experimental data points to estimate the most plausible power spectra compatible with the experimental data and there is no need to make any assumption about non-measured points. The time series, obtained from fMRI block paradigm data, is analyzed by the AR method to determine the brain active regions involved in the processing of a given stimulus. This method is considerably more reliable than the fast Fourier transform or the parametric methods. The time series corresponding to each image pixel is analyzed using the AR estimator and the corresponding poles are obtained. The pole distribution gives the shape of power spectra, and the pixels with poles at the stimulation frequency are considered as the active regions. The method was applied in simulated and real data, its superiority is shown by the receiver operating characteristic curves which were obtained using the simulated data.

FTIR and SEM analysis of CO2 laser irradiated human enamel

Objectives: Considering the enamel chemical structure, especially carbonate band, which has a major role in the caries prevention, the objective of the present study was to assess the chemical alterations on the enamel irradiated with CO2 laser by means of FTIR spectroscopy and SEM analysis. Design: The enamel surfaces were analysed on a spectrometer for acquisition of the absorption spectrum relative to the chemical composition of the control sample. The irradiation was conducted with a 10.6-mu m CO2 laser (0.55 W, 660 W/cm(2)). The carbonate absorption band at 1600-1291 cm(-1) as well as the water absorption band at 3793-2652 cm(-1) was measured in each sample after the irradiation. The water band was measured again 24-h after the irradiation. The band area of each chemical compound was delimited, the background was subtracted, and the area under each band was integrated. Each area was normalized by the phosphate band (1190-702 cm(-1)). Results: There was a statistically significant decrease (p < 0.05) in the water content after irradiation (control: 0.184 +/- 0.04; irradiated: 0.078 +/- 0.026), which increased again after rehydration (0.145 +/- 0.038). The carbonate/phosphate ratio was measured initially (0.112 +/- 0.029) and its reduction after irradiation indicated the carbonate loss (0.088 +/- 0.014) (p < 0.05). Conclusion: The 10.6-mu m CO2 laser irradiation diminishes the carbonate and water contents in the enamel after irradiation. (C) 2012 Elsevier Ltd. All rights reserved.

Effect of dental tissue conditioners and matrix metalloproteinase inhibitors on type I collagen microstructure analyzed by Fourier transform infrared spectroscopy

This study aimed to evaluate the chemical interaction of collagen with some substances usually applied in dental treatments to increase the durability of adhesive restorations to dentin. Initially, the similarity between human dentin collagen and type I collagen obtained from commercial bovine membranes of Achilles deep tendon was compared by the Attenuated Total Reflectance technique of Fourier Transform Infrared (ATR-FTIR) spectroscopy. Finally, the effects of application of 35% phosphoric acid, 0.1M ethylenediaminetetraacetic acid (EDTA), 2% chlorhexidine, and 6.5% proanthocyanidin solution on microstructure of collagen and in the integrity of its triple helix were also evaluated by ATR-FTIR. It was observed that the commercial type I collagen can be used as an efficient substitute for demineralized human dentin in studies that use spectroscopy analysis. The 35% phosphoric acid significantly altered the organic content of amides, proline and hydroxyproline of type I collagen. The surface treatment with 0.1M EDTA, 2% chlorhexidine, or 6.5% proanthocyanidin did not promote deleterious structural changes to the collagen triple helix. The application of 6.5% proanthocyanidin on collagen promoted hydrogen bond formation. (c) 2012 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 2012.

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.