53 resultados para Sinusoids
Resumo:
There are many methods for decomposing signals into a sum of amplitude and frequency modulated sinusoids. In this paper we take a new estimation based approach. Identifying the problem as ill-posed, we show how to regularize the solution by imposing soft constraints on the amplitude and phase variables of the sinusoids. Estimation proceeds using a version of Kalman smoothing. We evaluate the method on synthetic and natural, clean and noisy signals, showing that it outperforms previous decompositions, but at a higher computational cost. © 2012 IEEE.
Resumo:
The merozoite stage of the malaria parasite that infects erythrocytes and causes the symptoms of the disease is initially formed inside host hepatocytes. However, the mechanism by which hepatic merozoites reach blood vessels (sinusoids) in the liver and escape the host immune system before invading erythrocytes remains unknown. Here, we show that parasites induce the death and the detachment of their host hepatocytes, followed by the budding of parasite-filled vesicles (merosomes) into the sinusoid lumen. Parasites simultaneously inhibit the exposure of phosphatidylserine on the outer leaflet of host plasma membranes, which act as "eat me" signals to phagocytes. Thus, the hepatocyte-derived merosomes appear to ensure both the migration of parasites into the bloodstream and their protection from host immunity.
Resumo:
World economies increasingly demand reliable and economical power supply and distribution. To achieve this aim the majority of power systems are becoming interconnected, with several power utilities supplying the one large network. One problem that occurs in a large interconnected power system is the regular occurrence of system disturbances which can result in the creation of intra-area oscillating modes. These modes can be regarded as the transient responses of the power system to excitation, which are generally characterised as decaying sinusoids. For a power system operating ideally these transient responses would ideally would have a “ring-down” time of 10-15 seconds. Sometimes equipment failures disturb the ideal operation of power systems and oscillating modes with ring-down times greater than 15 seconds arise. The larger settling times associated with such “poorly damped” modes cause substantial power flows between generation nodes, resulting in significant physical stresses on the power distribution system. If these modes are not just poorly damped but “negatively damped”, catastrophic failures of the system can occur. To ensure system stability and security of large power systems, the potentially dangerous oscillating modes generated from disturbances (such as equipment failure) must be quickly identified. The power utility must then apply appropriate damping control strategies. In power system monitoring there exist two facets of critical interest. The first is the estimation of modal parameters for a power system in normal, stable, operation. The second is the rapid detection of any substantial changes to this normal, stable operation (because of equipment breakdown for example). Most work to date has concentrated on the first of these two facets, i.e. on modal parameter estimation. Numerous modal parameter estimation techniques have been proposed and implemented, but all have limitations [1-13]. One of the key limitations of all existing parameter estimation methods is the fact that they require very long data records to provide accurate parameter estimates. This is a particularly significant problem after a sudden detrimental change in damping. One simply cannot afford to wait long enough to collect the large amounts of data required for existing parameter estimators. Motivated by this gap in the current body of knowledge and practice, the research reported in this thesis focuses heavily on rapid detection of changes (i.e. on the second facet mentioned above). This thesis reports on a number of new algorithms which can rapidly flag whether or not there has been a detrimental change to a stable operating system. It will be seen that the new algorithms enable sudden modal changes to be detected within quite short time frames (typically about 1 minute), using data from power systems in normal operation. The new methods reported in this thesis are summarised below. The Energy Based Detector (EBD): The rationale for this method is that the modal disturbance energy is greater for lightly damped modes than it is for heavily damped modes (because the latter decay more rapidly). Sudden changes in modal energy, then, imply sudden changes in modal damping. Because the method relies on data from power systems in normal operation, the modal disturbances are random. Accordingly, the disturbance energy is modelled as a random process (with the parameters of the model being determined from the power system under consideration). A threshold is then set based on the statistical model. The energy method is very simple to implement and is computationally efficient. It is, however, only able to determine whether or not a sudden modal deterioration has occurred; it cannot identify which mode has deteriorated. For this reason the method is particularly well suited to smaller interconnected power systems that involve only a single mode. Optimal Individual Mode Detector (OIMD): As discussed in the previous paragraph, the energy detector can only determine whether or not a change has occurred; it cannot flag which mode is responsible for the deterioration. The OIMD seeks to address this shortcoming. It uses optimal detection theory to test for sudden changes in individual modes. In practice, one can have an OIMD operating for all modes within a system, so that changes in any of the modes can be detected. Like the energy detector, the OIMD is based on a statistical model and a subsequently derived threshold test. The Kalman Innovation Detector (KID): This detector is an alternative to the OIMD. Unlike the OIMD, however, it does not explicitly monitor individual modes. Rather it relies on a key property of a Kalman filter, namely that the Kalman innovation (the difference between the estimated and observed outputs) is white as long as the Kalman filter model is valid. A Kalman filter model is set to represent a particular power system. If some event in the power system (such as equipment failure) causes a sudden change to the power system, the Kalman model will no longer be valid and the innovation will no longer be white. Furthermore, if there is a detrimental system change, the innovation spectrum will display strong peaks in the spectrum at frequency locations associated with changes. Hence the innovation spectrum can be monitored to both set-off an “alarm” when a change occurs and to identify which modal frequency has given rise to the change. The threshold for alarming is based on the simple Chi-Squared PDF for a normalised white noise spectrum [14, 15]. While the method can identify the mode which has deteriorated, it does not necessarily indicate whether there has been a frequency or damping change. The PPM discussed next can monitor frequency changes and so can provide some discrimination in this regard. The Polynomial Phase Method (PPM): In [16] the cubic phase (CP) function was introduced as a tool for revealing frequency related spectral changes. This thesis extends the cubic phase function to a generalised class of polynomial phase functions which can reveal frequency related spectral changes in power systems. A statistical analysis of the technique is performed. When applied to power system analysis, the PPM can provide knowledge of sudden shifts in frequency through both the new frequency estimate and the polynomial phase coefficient information. This knowledge can be then cross-referenced with other detection methods to provide improved detection benchmarks.
Resumo:
This paper considers the applicability of the least mean fourth (LM F) power gradient adaptation criteria with 'advantage' for signals associated with gaussian noise, the associated noise power estimate not being known. The proposed method, as an adaptive spectral estimator, is found to provide superior performance than the least mean square (LMS) adaptation for the same (or even lower) speed of convergence for signals having sufficiently high signal-to-gaussian noise ratio. The results include comparison of the performance of the LMS-tapped delay line, LMF-tapped delay line, LMS-lattice and LMF-lattice algorithms, with the Burg's block data method as reference. The signals, like sinusoids with noise and stochastic signals like EEG, are considered in this study.
Resumo:
A dense population of Pimelea trichostachya plants (Family Thymelaeaceae) in pasture poisoned a horse herd in southern inland Queensland in October-November 2005. Plant density was 2 to 45 g wet weight/m2 (mean 16 g/m2) from 5 to 69 plants/m2 (mean 38 plants/m2) representing 3 to 20% (mean 9%) of the volume of pasture on offer. Ten of 35 mares, fillies and geldings were affected. Clinical signs were loss of body weight, profound lethargy, serous nasal discharge, severe watery diarrhoea and subcutaneous oedema of the intermandibular space, chest and ventral midline. Pathological findings were anaemia, leucocytopenia, hypoproteinaemia, dilatation of the right ventricle of the heart, dilated hepatic portal veins and periportal hepatic sinusoids (peliosis hepatis), alimentary mucosal hyperaemia and oedema of mesenteric lymph nodes. Cattle grazing the same pasture were affected by Pimelea poisoning simultaneously. Removal of the horses to Pimelea-free pasture initiated recovery. The one other incident of this syndrome, previously only recognised in cattle in Australia, occurred in horses, in South Australia in 2002, with access to a dense Pimelea simplex population.
Resumo:
Cavernomas are rare neurovascular lesions, encountered in up to 10% of patients harboring vascular abnormalities of the CNS. Cavernomas consist of dilated thin-walled sinusoids or caverns covered by a single layer of endothelium. Due to advancements in neuroradiology, the number of cavernoma patients coming to be evaluated in neurosurgical practice is increasing. In the present work, we summarized our results on the treatment of cavernomas. Particular attention was paid to uncommon locations or insufficiently investigated cavernomas, including 1. Intraventricular cavernomas; 2. Multiple cavernomas; 3. Spinal cavernomas; and 4. Temporal lobe cavernomas. After analyzing the patient series with these lesions, we concluded that: 1. IVCs are characterized by a high tendency to cause repetitive hemorrhages in a short period of time after the first event. In most patients, hemorrhages were not life-threatening. Surgery is indicated when re-bleedings are frequent and the mass-effect causes progressive neurological deterioration. Modern microsurgical techniques allow safe removal of the IVC, but surgery on fourth ventricle cavernomas carries increased risk of postoperative cranial nerve deficits. 2. In MC cases, when the cavernoma bleeds or generates drug-resistant epilepsy, microsurgical removal of the symptomatic lesion is beneficial to patients. In our series, surgical removal of the most active cavernoma usually the biggest lesion with signs of recent hemorrhage - was safe and prevented further bleedings. Epilepsy outcome showed the effectiveness of active treatment of MCs. However, due to the remaining cavernomas, epileptogenic activity can persist postoperatively, frequently necessitating long-term use of antiepileptic drugs. 3. Spinal cavernomas can cause severe neurological deterioration due to low tolerance of the spinal cord to mass-effect with progressive myelopathy. When aggravated by extralesional massive hemorrhage, neurological decline is usually acute and requires immediate treatment. Microsurgical removal of a cavernoma is effective and safe, improving neurological deficits. Sensorimotor deficits and pain improved postoperatively at a high rate, whereas bladder dysfunction remained essentially unchanged, causing social discomfort to patients. 4. Microsurgical removal of temporal lobe cavernomas is beneficial for patents suffering from drug-resistant epilepsy. In our series, 69% of patients with this condition became seizure-free postoperatively. Duration of epilepsy did not correlate with seizure prognosis. The most frequent disabling symptom at follow-up was memory disorder, considered to be the result of a complex interplay between chronic epilepsy and possible damage to the temporal lobe during surgery.
Resumo:
We address the problem of high-resolution reconstruction in frequency-domain optical-coherence tomography (FDOCT). The traditional method employed uses the inverse discrete Fourier transform, which is limited in resolution due to the Heisenberg uncertainty principle. We propose a reconstruction technique based on zero-crossing (ZC) interval analysis. The motivation for our approach lies in the observation that, for a multilayered specimen, the backscattered signal may be expressed as a sum of sinusoids, and each sinusoid manifests as a peak in the FDOCT reconstruction. The successive ZC intervals of a sinusoid exhibit high consistency, with the intervals being inversely related to the frequency of the sinusoid. The statistics of the ZC intervals are used for detecting the frequencies present in the input signal. The noise robustness of the proposed technique is improved by using a cosine-modulated filter bank for separating the input into different frequency bands, and the ZC analysis is carried out on each band separately. The design of the filter bank requires the design of a prototype, which we accomplish using a Kaiser window approach. We show that the proposed method gives good results on synthesized and experimental data. The resolution is enhanced, and noise robustness is higher compared with the standard Fourier reconstruction. (c) 2012 Optical Society of America
Resumo:
Neural activity across the brain shows both spatial and temporal correlations at multiple scales, and understanding these correlations is a key step toward understanding cortical processing. Correlation in the local field potential (LFP) recorded from two brain areas is often characterized by computing the coherence, which is generally taken to reflect the degree of phase consistency across trials between two sites. Coherence, however, depends on two factors-phase consistency as well as amplitude covariation across trials-but the spatial structure of amplitude correlations across sites and its contribution to coherence are not well characterized. We recorded LFP from an array of microelectrodes chronically implanted in the primary visual cortex of monkeys and studied correlations in amplitude across electrodes as a function of interelectrode distance. We found that amplitude correlations showed a similar trend as coherence as a function of frequency and interelectrode distance. Importantly, even when phases were completely randomized between two electrodes, amplitude correlations introduced significant coherence. To quantify the contributions of phase consistency and amplitude correlations to coherence, we simulated pairs of sinusoids with varying phase consistency and amplitude correlations. These simulations confirmed that amplitude correlations can significantly bias coherence measurements, resulting in either over-or underestimation of true phase coherence. Our results highlight the importance of accounting for the correlations in amplitude while using coherence to study phase relationships across sites and frequencies.
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We consider the problem of parameter estimation from real-valued multi-tone signals. Such problems arise frequently in spectral estimation. More recently, they have gained new importance in finite-rate-of-innovation signal sampling and reconstruction. The annihilating filter is a key tool for parameter estimation in these problems. The standard annihilating filter design has to be modified to result in accurate estimation when dealing with real sinusoids, particularly because the real-valued nature of the sinusoids must be factored into the annihilating filter design. We show that the constraint on the annihilating filter can be relaxed by making use of the Hilbert transform. We refer to this approach as the Hilbert annihilating filter approach. We show that accurate parameter estimation is possible by this approach. In the single-tone case, the mean-square error performance increases by 6 dB for signal-to-noise ratio (SNR) greater than 0 dB. We also present experimental results in the multi-tone case, which show that a significant improvement (about 6 dB) is obtained when the parameters are close to 0 or pi. In the mid-frequency range, the improvement is about 2 to 3 dB.
Resumo:
We present an analysis of the rate of sign changes in the discrete Fourier spectrum of a sequence. The sign changes of either the real or imaginary parts of the spectrum are considered, and the rate of sign changes is termed as the spectral zero-crossing rate (SZCR). We show that SZCR carries information pertaining to the locations of transients within the temporal observation window. We show duality with temporal zero-crossing rate analysis by expressing the spectrum of a signal as a sum of sinusoids with random phases. This extension leads to spectral-domain iterative filtering approaches to stabilize the spectral zero-crossing rate and to improve upon the location estimates. The localization properties are compared with group-delay-based localization metrics in a stylized signal setting well-known in speech processing literature. We show applications to epoch estimation in voiced speech signals using the SZCR on the integrated linear prediction residue. The performance of the SZCR-based epoch localization technique is competitive with the state-of-the-art epoch estimation techniques that are based on average pitch period.
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We establish zero-crossing rate (ZCR) relations between the input and the subbands of a maximally decimated M-channel power complementary analysis filterbank when the input is a stationary Gaussian process. The ZCR at lag is defined as the number of sign changes between the samples of a sequence and its 1-sample shifted version, normalized by the sequence length. We derive the relationship between the ZCR of the Gaussian process at lags that are integer multiples of Al and the subband ZCRs. Based on this result, we propose a robust iterative autocorrelation estimator for a signal consisting of a sum of sinusoids of fixed amplitudes and uniformly distributed random phases. Simulation results show that the performance of the proposed estimator is better than the sample autocorrelation over the SNR range of -6 to 15 dB. Validation on a segment of a trumpet signal showed similar performance gains.
Resumo:
A study of human eye movements was made in order to elucidate the nature of the control mechanism in the binocular oculomotor system.
We first examined spontaneous eye movements during monocular and binocular fixation in order to determine the corrective roles of flicks and drifts. It was found that both types of motion correct fixational errors, although flicks are somewhat more active in this respect. Vergence error is a stimulus for correction by drifts but not by flicks, while binocular vertical discrepancy of the visual axes does not trigger corrective movements.
Second, we investigated the non-linearities of the oculomotor system by examining the eye movement responses to point targets moving in two dimensions in a subjectively unpredictable manner. Such motions consisted of hand-limited Gaussian random motion and also of the sum of several non-integrally related sinusoids. We found that there is no direct relationship between the phase and the gain of the oculomotor system. Delay of eye movements relative to target motion is determined by the necessity of generating a minimum afferent (input) signal at the retina in order to trigger corrective eye movements. The amplitude of the response is a function of the biological constraints of the efferent (output) portion of the system: for target motions of narrow bandwidth, the system responds preferentially to the highest frequency; for large bandwidth motions, the system distributes the available energy equally over all frequencies. Third, the power spectra of spontaneous eye movements were compared with the spectra of tracking eye movements for Gaussian random target motions of varying bandwidths. It was found that there is essentially no difference among the various curves. The oculomotor system tracks a target, not by increasing the mean rate of impulses along the motoneurons of the extra-ocular muscles, but rather by coordinating those spontaneous impulses which propagate along the motoneurons during stationary fixation. Thus, the system operates at full output at all times.
Fourth, we examined the relative magnitude and phase of motions of the left and the right visual axes during monocular and binocular viewing. We found that the two visual axes move vertically in perfect synchronization at all frequencies for any viewing condition. This is not true for horizontal motions: the amount of vergence noise is highest for stationary fixation and diminishes for tracking tasks as the bandwidth of the target motion increases. Furthermore, movements of the occluded eye are larger than those of the seeing eye in monocular viewing. This effect is more pronounced for horizontal motions, for stationary fixation, and for lower frequencies.
Finally, we have related our findings to previously known facts about the pertinent nerve pathways in order to postulate a model for the neurological binocular control of the visual axes.
Resumo:
In the first section of this thesis, two-dimensional properties of the human eye movement control system were studied. The vertical - horizontal interaction was investigated by using a two-dimensional target motion consisting of a sinusoid in one of the directions vertical or horizontal, and low-pass filtered Gaussian random motion of variable bandwidth (and hence information content) in the orthogonal direction. It was found that the random motion reduced the efficiency of the sinusoidal tracking. However, the sinusoidal tracking was only slightly dependent on the bandwidth of the random motion. Thus the system should be thought of as consisting of two independent channels with a small amount of mutual cross-talk.
These target motions were then rotated to discover whether or not the system is capable of recognizing the two-component nature of the target motion. That is, the sinusoid was presented along an oblique line (neither vertical nor horizontal) with the random motion orthogonal to it. The system did not simply track the vertical and horizontal components of motion, but rotated its frame of reference so that its two tracking channels coincided with the directions of the two target motion components. This recognition occurred even when the two orthogonal motions were both random, but with different bandwidths.
In the second section, time delays, prediction and power spectra were examined. Time delays were calculated in response to various periodic signals, various bandwidths of narrow-band Gaussian random motions and sinusoids. It was demonstrated that prediction occurred only when the target motion was periodic, and only if the harmonic content was such that the signal was sufficiently narrow-band. It appears as if general periodic motions are split into predictive and non-predictive components.
For unpredictable motions, the relationship between the time delay and the average speed of the retinal image was linear. Based on this I proposed a model explaining the time delays for both random and periodic motions. My experiments did not prove that the system is sampled data, or that it is continuous. However, the model can be interpreted as representative of a sample data system whose sample interval is a function of the target motion.
It was shown that increasing the bandwidth of the low-pass filtered Gaussian random motion resulted in an increase of the eye movement bandwidth. Some properties of the eyeball-muscle dynamics and the extraocular muscle "active state tension" were derived.
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A medula óssea adulta possui duas populações de células-tronco importantes no tratamento de diversas doenças hepáticas: células-tronco hematopoiéticas (CTHs) e células-tronco mesenquimais. A regeneração do fígado após a hepatectomia é um processo complexo que requer a proliferação de todas as células hepáticas. Fatores de crescimento, citocinas e componentes da matriz extracelular são elementos-chave nesse processo. As lamininas são uma família de proteínas de matriz extracelular, com funções adesivas e quimiotáticas pelo recrutamento de integrinas e outros receptores de superfície celular. No fígado normal, a laminina é expressa nas veias porta e centrolobular. O objetivo desse estudo foi investigar a expressão de laminina durante a regeneração hepática induzida por hepatectomia parcial e após o transplante de células mononucleares de medula óssea. As células mononucleares de medula óssea foram obtidas dos fêmures e tíbias de ratos, isoladas, marcadas com DAPI e injetadas pela veia porta em ratos recém-hepatectomizados. Os fígados foram coletados 15 minutos, 1 dia e 3 dias após a hepatectomia e o transplante de células de medula óssea e congelados. Os cortes foram imunomarcados com anticorpos primários anti-CD34 e anti-laminina de rato e observados em microscópio confocal de varredura a laser. Os resultados mostraram que 15 minutos após a hepatectomia parcial, as células-tronco hematopoiéticas CD34+ transplantadas foram encontradas em contato com a laminina localizada nas veias porta e centrolobular, indicando que a laminina poderia participar na adesão inicial das células-tronco a esses vasos logo após o seu transplante. Além disso, 1 e 3 dias após a hepatectomia, as células mononucleares de medula óssea transplantadas foram observadas nos sinusóides hepáticos expressando laminina. Esses resultados sugerem que a laminina pode ser um componente da matriz extracelular importante para a adesão e enxerto de células de medula óssea no fígado após uma lesão. Nós também analisamos a expressão de osteopontina (OPN) em células de medula óssea e CTHs. Os resultados por microscopia confocal demonstraram que a maioria das células mononucleares de medula óssea recém-isoladas expressa quantidades variáveis de OPN. Além disso, algumas CTHs CD34+ também expressam OPN. Após 1 e 4 dias de cultura, observamos uma diminuição de células expressando CD34, e um aumento na expressão de OPN pelas células mononucleares de medula óssea.
Resumo:
Liza parsia were exposed to sublethal (0.02 ppm) concentration of DDT for 15 days. The gill responded initially with copious secretion of mucus, oedematous separation of epithelial cells from the basement membrane and fusion of secondary gill lamellae. Hyperplasia of the cells lining primary gill lamellae and lamellar telangiectases (or aneurysms) was frequently seen after day 10 of exposure. Kidney exhibited hypertrophy of the epithelial cells lining proximal convoluted tubules which was followed by shrinkage in glomerular tufts, increase in Bowman's space, appearance of amorphous eosinophilic materials in the lumina of the tubules and focal necrosis on day 10 of the treatment. Hyaline droplets and casts were also encountered in the epithelial cells and lumina of the proximal tubules. Liver revealed an initial dilation of canaliculi and increased secretion of bile. Thereafter, the displacement of nuclei towards periphery of the hepatocytes, disorganization of blood sinusoids, pyknotic changes in nuclei, cytolysis and vacuolation as well as focal necrosis were noticed after day 10 of the intoxication.