900 resultados para Spectral peak track


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Spectral peak resolution was investigated in normal hearing (NH), hearing impaired (HI), and cochlear implant (CI) listeners. The task involved discriminating between two rippled noise stimuli in which the frequency positions of the log-spaced peaks and valleys were interchanged. The ripple spacing was varied adaptively from 0.13 to 11.31 ripples/octave, and the minimum ripple spacing at which a reversal in peak and trough positions could be detected was determined as the spectral peak resolution threshold for each listener. Spectral peak resolution was best, on average, in NH listeners, poorest in CI listeners, and intermediate for HI listeners. There was a significant relationship between spectral peak resolution and both vowel and consonant recognition in quiet across the three listener groups. The results indicate that the degree of spectral peak resolution required for accurate vowel and consonant recognition in quiet backgrounds is around 4 ripples/octave, and that spectral peak resolution poorer than around 1–2 ripples/octave may result in highly degraded speech recognition. These results suggest that efforts to improve spectral peak resolution for HI and CI users may lead to improved speech recognition

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Hydration forces are thought to result from the energetic cost of water rearrangement near macromolecular surfaces. Raman spectra, collected on the same collagen samples on which these forces were measured, reveal a continuous change in water hydrogen-bonding structure as a function of separation between collagen triple helices. The varying spectral parameters track the force-distance curve. The energetic cost of water “restructuring,” estimated from the spectra, is consistent with the measured energy of intermolecular interaction. These correlations support the idea that the change in water structure underlies the exponentially varying forces seen in this system at least over the 13–18-Å range of interaxial separations.

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Short-term spectral analysis was carried out on geochemical logging data from ODP Site 704. The FFT was used to compute the amplitude spectra of short-term overlapping segments to produce depth-period-amplitude spectrograms of the logging data. The spectrograms provided a means of evaluating the significance of the observed periodic components. The periodic components that were consistently present and prominent across a given record interval were considered to be significant. Changes in the spectrogram characteristics seem to reflect changes in either lithology, sedimentation rates, or hiatuses and may therefore provide useful information to aid in stratigraphic and paleoenvironmental studies. The dominant periodicity during the late Pleistocene and Brunhes Chron (0.97 to 0.47 Ma) was determined to be > 100,000 yr whereas the upper Matuyama Chron was dominated by the 41,000-yr periodicity. These periodicities suggest that the sedimentation patterns within the upper Matuyama Chron (0.98-1.78 Ma) were influenced by the Milankovitch obliquity cycle and those within the latest Matuyama-Brunhes Chron (<0.98 Ma) by the eccentricity cycle. The Brunhes/Matuyama boundary therefore represents a major discontinuity. Periodicities observed within the lower Matuyama and the upper Gauss Chron did not correlate with any of the periodicities within the Milankovitch frequency bands.

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PEGylation is a strategy that has been used to improve the biochemical properties of proteins and their physical and thermal stabilities. In this study, hen egg-white lysozyme (EC 3.2.1.17; LZ) was modified with methoxypolyethylene glycol-p-nitrophenyl carbonate (mPEG-pNP, MW 5000). This PEGylation of LZ produced conjugates that retained full enzyme activity with glycol chitosan, independent of degree of enzyme modification; its biological activity with the substrate Micrococcus lysodeikticus was altered according to its degree of modification. The conjugate obtained with a low degree of mPEG-pNP/NH(2) modification was studied by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF), demonstrating a spectral peak at m/z 19,988 Da with 77% of its original enzymatic activity. Spectroscopic studies of Fourier transform infrared (FIR) and circular dichroism (CD) did not show any relevant differences in protein structure between the native and conjugate LZ. Studies of the effects of pH and temperature on PEGylated LZ indicated that the conjugate was active over a broad pH range, stable at 50 degrees C, and demonstrated resistance to proteolytic degradation. (C) 2010 Elsevier B.V. All rights reserved.

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Wide-range spectral coverage of blazar-type active galactic nuclei is of paramount importance for understanding the particle acceleration mechanisms assumed to take place in their jets. The Major Atmospheric Gamma Imaging Cerenkov (MAGIC) telescope participated in three multiwavelength (MWL) campaigns, observing the blazar Markarian (Mkn) 421 during the nights of April 28 and 29, 2006, and June 14, 2006. Aims. We analyzed the corresponding MAGIC very-high energy observations during 9 nights from April 22 to 30, 2006 and on June 14, 2006. We inferred light curves with sub-day resolution and night-by-night energy spectra. Methods. MAGIC detects γ-rays by observing extended air showers in the atmosphere. The obtained air-shower images were analyzed using the standard MAGIC analysis chain. Results. A strong γ-ray signal was detected from Mkn 421 on all observation nights. The flux (E > 250 GeV) varied on night-by-night basis between (0.92±0.11) × 10-10 cm-2 s-1 (0.57 Crab units) and (3.21±0.15) × 10-10 cm-2 s-1 (2.0 Crab units) in April 2006. There is a clear indication for intra-night variability with a doubling time of 36± min on the night of April 29, 2006, establishing once more rapid flux variability for this object. For all individual nights γ-ray spectra could be inferred, with power-law indices ranging from 1.66 to 2.47. We did not find statistically significant correlations between the spectral index and the flux state for individual nights. During the June 2006 campaign, a flux substantially lower than the one measured by the Whipple 10-m telescope four days later was found. Using a log-parabolic power law fit we deduced for some data sets the location of the spectral peak in the very-high energy regime. Our results confirm the indications of rising peak energy with increasing flux, as expected in leptonic acceleration models.

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Time-series measurements from a moored data buoy located in the Bay of Bengal captured signals of inertial oscillation forced by the September 1997 cyclone. The progressive vector diagram showed mean northeastward current with well-defined clockwise circulation. Spectral analysis exhibited inertial peak at 0.67 cpd with blue shift and high rotary coefficient of –0.99, which signifies strong circular inertial oscillation. The wind and SST also exhibited spectral peak at inertial band (0.69 cpd) with higher blue shift. The inertial amplitude of 148.8 cm/s corresponding to a wind stress of 0.99 N/m2 and spectral peak near the local inertial frequency (0.653 cpd) indicate that the transfer of momentum was high.

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We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistence estimation. The timescale errors are modelled parametrically and included in the simulations for determining (1) the upper levels of the spectrum of the red-noise AR(1) alternative and (2) the uncertainty of the frequency of a spectral peak. Application of REDFITmc2 to ice core and stalagmite records of palaeoclimate allowed a more realistic evaluation of spectral peaks than when ignoring this source of uncertainty. The results support qualitatively the intuition that stronger effects on the spectrum estimate (decreased detectability and increased frequency uncertainty) occur for higher frequencies. The surplus information brought by algorithm REDFITmc2 is that those effects are quantified. Regarding timescale construction, not only the fixpoints, dating errors and the functional form of the age-depth model play a role. Also the joint distribution of all time points (serial correlation, stratigraphic order) determines spectrum estimation.

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The North Atlantic Ocean subpolar gyre (NA SPG) is an important region for initialising decadal climate forecasts. Climate model simulations and palaeo climate reconstructions have indicated that this region could also exhibit large, internally generated variability on decadal timescales. Understanding these modes of variability, their consistency across models, and the conditions in which they exist, is clearly important for improving the skill of decadal predictions — particularly when these predictions are made with the same underlying climate models. Here we describe and analyse a mode of internal variability in the NA SPG in a state-of-the-art, high resolution, coupled climate model. This mode has a period of 17 years and explains 15–30% of the annual variance in related ocean indices. It arises due to the advection of heat content anomalies around the NA SPG. Anomalous circulation drives the variability in the southern half of the NA SPG, whilst mean circulation and anomalous temperatures are important in the northern half. A negative feedback between Labrador Sea temperatures/densities and those in the North Atlantic Current is identified, which allows for the phase reversal. The atmosphere is found to act as a positive feedback on to this mode via the North Atlantic Oscillation which itself exhibits a spectral peak at 17 years. Decadal ocean density changes associated with this mode are driven by variations in temperature, rather than salinity — a point which models often disagree on and which we suggest may affect the veracity of the underlying assumptions of anomaly-assimilating decadal prediction methodologies.

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Pós-graduação em Estudos Linguísticos - IBILCE

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Objetivos Investigar o uso do EEG quantitativo (qEEG) em pacientes com encefalopatias agudas (EAs ) e anormalidades da atividade de base no EEG. Método s pacientes foram divididos em prognóstico favorável (grupo A, 43 pacientes) e desfavorável (grupo B, 5 pacientes). O programa EEGLAB foi utilizado para a análise do qEEG. Um gráfico da potência espectral de todos os canais foi gerado para cada participante. Os dois grupos foram comparados estatisticamente. Resultados No grupo A, a análise espectral revelou picos (frequências teta e alfa) em 84% (38/45) dos pacientes. No grupo B, um pico espectral na frequência delta foi detectado em um paciente. Os pacientes remanescentes dos dois grupos não apresentaram picos espectrais. A análise estatística mostrou menores frequências registradas nos eletrodos posteriores dos pacientes do grupo B. Conclusão O qEEG pode ser útil na avaliação de pacientes com EAs auxiliando na determinação do prognóstico.

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We investigated the color vision pattern in Cebus apella monkeys by means of electroretinogram measurements (ERG) and genetic analysis. Based on ERG we could discriminate among three types of dichromatic males. Among females, this classification is more complex and requires additional genetic analysis. We found five among 10 possible different phenotypes, two trichromats and three dichromats. We also found that Cebus present a new allele with spectral peak near 552 nm, with the amino acid combination SFT at positions 180, 277 and 285 of the opsin gene, in addition to the previously described SYT, AFT and AFA alleles. (C) 2009 Elsevier Ltd. All rights reserved.

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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.

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We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistence estimation. The timescale errors are modelled parametrically and included in the simulations for determining (1) the upper levels of the spectrum of the red-noise AR(1) alternative and (2) the uncertainty of the frequency of a spectral peak. Application of REDFITmc2 to ice core and stalagmite records of palaeoclimate allowed a more realistic evaluation of spectral peaks than when ignoring this source of uncertainty. The results support qualitatively the intuition that stronger effects on the spectrum estimate (decreased detectability and increased frequency uncertainty) occur for higher frequencies. The surplus information brought by algorithm REDFITmc2 is that those effects are quantified. Regarding timescale construction, not only the fixpoints, dating errors and the functional form of the age-depth model play a role. Also the joint distribution of all time points (serial correlation, stratigraphic order) determines spectrum estimation.