A regional multirnodulus algorithm for blind equalization of QAM signals: Introduction and steady-state analysis

It is well known that constant-modulus-based algorithms present a large mean-square error for high-order quadrature amplitude modulation (QAM) signals, which may damage the switching to decision-directed-based algorithms. In this paper, we introduce a regional multimodulus algorithm for blind equalization of QAM signals that performs similar to the supervised normalized least-mean-squares (NLMS) algorithm, independently of the QAM order. We find a theoretical relation between the coefficient vector of the proposed algorithm and the Wiener solution and also provide theoretical models for the steady-state excess mean-square error in a nonstationary environment. The proposed algorithm in conjunction with strategies to speed up its convergence and to avoid divergence can bypass the switching mechanism between the blind mode and the decision-directed mode. (c) 2012 Elsevier B.V. All rights reserved.

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.

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]

Mixed colonies of two species of congeneric stingless bees (Hymenoptera: Apinae, Meliponini) display environmentally-acquired and endogenously-produced recognition signals

Nestmate recognition is fundamental for the maintenance of social organization in insect nests. It is becoming well recognized that cuticle hydrocarbons mediate the recognition process, although the origin of recognition cues in stingless bees remains poorly explored. The present study investigates the effects of endogenously-produced and environmentally-acquired components in cuticular hydrocarbons in stingless bees. The tests are conducted using colonies of Plebeia droryana Friese and Plebeia remota Holmberg. Recognition tests are performed with four different groups: conspecific nestmates, conspecific non-nestmates, heterospecifics and conspecific, genetically-related individuals that emerge in a heterospecific nest. This last group is produced by introducing brood cells of P. droryana into a P. remota colony, and the resulting adult bees are tested for acceptance 10 days after emergence. For all groups, 15 individuals are sampled for chemical analysis. The results show the acceptance of all conspecific nestmates, and the rejection of almost every conspecific non-nestmate and every heterospecific bee. Genetically-related individuals emerging from heterospecific nests present intermediate rejection (66.7% rejection). Chemical analysis shows that P. droryana individuals emerging in a P. remota nest have small amounts of alkene and diene isomers found in P. remota cuticle that are not found in workers from the natal nest. The data clearly show that the majority of the compounds present in P. droryana cuticle are endogenously produced, although a few unsaturated compounds are acquired from the environment, increasing the chemical differences and, consequently, the rejection percentages.

Effect of sample storage time on detection of hybridization signals in Checkerboard DNA-DNA hybridization

Long-term sample storage can affect the intensity of the hybridization signals provided by molecular diagnostic methods that use chemiluminescent detection. The aim of this study was to evaluate the effect of different storage times on the hybridization signals of 13 bacterial species detected by the Checkerboard DNA-DNA hybridization method using whole-genomic DNA probes. Ninety-six subgingival biofilm samples were collected from 36 healthy subjects, and the intensity of hybridization signals was evaluated at 4 different time periods: (1) immediately after collecting (n = 24) and (2) after storage at -20 degrees C for 6 months (n = 24), (3) for 12 months (n = 24), and (4) for 24 months (n = 24). The intensity of hybridization signals obtained from groups 1 and 2 were significantly higher than in the other groups (p < 0.001). No differences were found between groups 1 and 2 (p > 0.05). The Checkerboard DNA-DNA hybridization method was suitable to detect hybridization signals from all groups evaluated, and the intensity of signals decreased significantly after long periods of sample storage.

Comparative Genome Analysis of Trichophyton rubrum and Related Dermatophytes Reveals Candidate Genes Involved in Infection

The major cause of athlete's foot is Trichophyton rubrum, a dermatophyte or fungal pathogen of human skin. To facilitate molecular analyses of the dermatophytes, we sequenced T. rubrum and four related species, Trichophyton tonsurans, Trichophyton equinum, Microsporum canis, and Microsporum gypseum. These species differ in host range, mating, and disease progression. The dermatophyte genomes are highly colinear yet contain gene family expansions not found in other human-associated fungi. Dermatophyte genomes are enriched for gene families containing the LysM domain, which binds chitin and potentially related carbohydrates. These LysM domains differ in sequence from those in other species in regions of the peptide that could affect substrate binding. The dermatophytes also encode novel sets of fungus-specific kinases with unknown specificity, including nonfunctional pseudokinases, which may inhibit phosphorylation by competing for kinase sites within substrates, acting as allosteric effectors, or acting as scaffolds for signaling. The dermatophytes are also enriched for a large number of enzymes that synthesize secondary metabolites, including dermatophyte-specific genes that could synthesize novel compounds. Finally, dermatophytes are enriched in several classes of proteases that are necessary for fungal growth and nutrient acquisition on keratinized tissues. Despite differences in mating ability, genes involved in mating and meiosis are conserved across species, suggesting the possibility of cryptic mating in species where it has not been previously detected. These genome analyses identify gene families that are important to our understanding of how dermatophytes cause chronic infections, how they interact with epithelial cells, and how they respond to the host immune response. IMPORTANCE Athlete's foot, jock itch, ringworm, and nail infections are common fungal infections, all caused by fungi known as dermatophytes (fungi that infect skin). This report presents the genome sequences of Trichophyton rubrum, the most frequent cause of athlete's foot, as well as four other common dermatophytes. Dermatophyte genomes are enriched for four gene classes that may contribute to the ability of these fungi to cause disease. These include (i) proteases secreted to degrade skin; (ii) kinases, including pseudokinases, that are involved in signaling necessary for adapting to skin; (iii) secondary metabolites, compounds that act as toxins or signals in the interactions between fungus and host; and (iv) a class of proteins (LysM) that appear to bind and mask cell wall components and carbohydrates, thus avoiding the host's immune response to the fungi. These genome sequences provide a strong foundation for future work in understanding how dermatophytes cause disease.

Effect of pulse repetition rate and number of pulses in the analysis of polypropylene and high density polyethylene by nanosecond infrared laser induced breakdown spectroscopy

Pulse repetition rates and the number of laser pulses are among the most important parameters that do affect the analysis of solid materials by laser induced breakdown spectroscopy, and the knowledge of their effects is of fundamental importance for suggesting analytical strategies when dealing with laser ablation processes of polymers. In this contribution, the influence of these parameters in the ablated mass and in the features of craters was evaluated in polypropylene and high density polyethylene plates containing pigment-based PbCrO4. Surface characterization and craters profile were carried out by perfilometry and scanning electron microscopy. Area, volume and profile of craters were obtained using Taylor Map software. A laser induced breakdown spectroscopy system consisted of a Q-Switched Nd:YAG laser (1064 nm, 5 ns) and an Echelle spectrometer equipped with ICCD detector were used. The evaluated operating conditions consisted of 10, 25 and 50 laser pulses at 1, 5 and 10 Hz, 250 mJ/pulse (85 J cm(-2)), 2 mu s delay time and 6 mu s integration time gate. Differences in the topographical features among craters of both polymers were observed. The decrease in the repetition rate resulted in irregular craters and formation of edges, especially in polypropylene sample. The differences in the topographical features and ablated masses were attributed to the influence of the degree of crystallinity, crystalline melting temperature and glass transition temperature in the ablation process of the high density polyethylene and polypropylene. It was also observed that the intensities of chromium and lead emission signals obtained at 10 Hz were two times higher than at 5 Hz by keeping the number of laser pulses constant. (C) 2011 Elsevier B. V. All rights reserved.

Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis

Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiff(max)) for q not equal 1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiff(max) values were capable of distinguish HRV groups (p-values 5.10 x 10(-3); 1.11 x 10(-7), and 5.50 x 10(-7) for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4758815]

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.

Extensive cross-talk and global regulators identified from an analysis of the integrated transcriptional and signaling network in Escherichia coli

To understand the regulatory dynamics of transcription factors (TFs) and their interplay with other cellular components we have integrated transcriptional, protein-protein and the allosteric or equivalent interactions which mediate the physiological activity of TFs in Escherichia coli. To study this integrated network we computed a set of network measurements followed by principal component analysis (PCA), investigated the correlations between network structure and dynamics, and carried out a procedure for motif detection. In particular, we show that outliers identified in the integrated network based on their network properties correspond to previously characterized global transcriptional regulators. Furthermore, outliers are highly and widely expressed across conditions, thus supporting their global nature in controlling many genes in the cell. Motifs revealed that TFs not only interact physically with each other but also obtain feedback from signals delivered by signaling proteins supporting the extensive cross-talk between different types of networks. Our analysis can lead to the development of a general framework for detecting and understanding global regulatory factors in regulatory networks and reinforces the importance of integrating multiple types of interactions in underpinning the interrelationships between them.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

Effects of laser focusing and fluence on the analysis of pellets of plant materials by laser-induced breakdown spectroscopy

The effects of laser focusing and fluence on LIBS analysis of pellets of plant leaves was evaluated. A Q-switched Nd:YAG laser (5ns, 10Hz, 1064nm) was used and the emission signals were collected by lenses into an optical fiber coupled to a spectrometer with Echelle optics and ICCD. Data were acquired from the accumulation of 20 laser pulses at 2.0 mu s delay and 5.0 mu s integration time gate. The emission signal intensities increased with both laser fluence and spot size. Higher sensitivities for Ca, K, Mg, P, Al, B, Cu, Fe, Mn, and Zn determinations were observed for fluences in the range from 25 to 60Jcm(-2). Coefficients of variation of site-to-site measurements were generally lower than 10% (n=30 sites, 20 laser pulses/site) for a fluence of 50Jcm(-2) and 750 mu m spot size. For most elements, there is an indication that accuracy is improved with higher fluences. (C) 2012 Elsevier B.V. All rights reserved.