144 resultados para Signal de transduction
Resumo:
The importance of inter-and intracellular signal transduction in all forms of life cannot be underestimated. A large number of genes dedicated to cellular signalling are found in almost all sequenced genomes, and Mycobacteria are no exception. What appears to be interesting in Mycobacteria is that well characterized signalling mechanisms used by bacteria, such as the histidine-aspartate phosphorelay seen in two-component systems, are found alongside signalling components that closely mimic those seen in higher eukaryotes. This review will describe the important contribution made by researchers in India towards the identification and characterization of proteins involved in two-component signalling, protein phosphorylation and cyclic nucleotide metabolism. (C) 2011 Elsevier Ltd. All rights reserved.
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In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly sparse signals from noisy measurements can be viewed as a problem of recovery of approximately sparse signals from noiseless measurements, making the approach applicable to strictly sparse signal recovery from noisy measurements. The support recovery embedded in the approach makes it suitable for recovery of signals with same sparsity profiles, as in the problem of multiple measurement vectors (MMV). Simulation results show that the proposed algorithm, termed as JSSR-MP (joint support and signal recovery via message passing) algorithm, achieves performance comparable to that of sparse Bayesian learning (M-SBL) algorithm in the literature, at one order less complexity compared to the M-SBL algorithm.
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This paper presents a method of designing a programmable signal processor based on a bit parallel matrix vector matrix multiplier (linear transformer). The salient feature of this design is that the efficiency of the direct vector matrix multiplier is improved and VLSI design is made much simpler by trading off the more expensive arithematic operation (multiplication) for 'cheaper' manipulation (addition/subtraction) of the data.
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The problem of on-line recognition and retrieval of relatively weak industrial signals such as partial discharges (PD), buried in excessive noise, has been addressed in this paper. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) due to the overlapping broad band frequency spectrum of PI and PD pulses. Therefore, on-line, onsite, PD measurement is hardly possible in conventional frequency based DSP techniques. The observed PD signal is modeled as a linear combination of systematic and random components employing probabilistic principal component analysis (PPCA) and the pdf of the underlying stochastic process is obtained. The PD/PI pulses are assumed as the mean of the process and modeled instituting non-parametric methods, based on smooth FIR filters, and a maximum aposteriori probability (MAP) procedure employed therein, to estimate the filter coefficients. The classification of the pulses is undertaken using a simple PCA classifier. The methods proposed by the authors were found to be effective in automatic retrieval of PD pulses completely rejecting PI.
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The diversity order and coding gain are crucial for the performance of a multiple antenna communication system. It is known that space-time trellis codes (STTC) can be used to achieve these objectives. In particular, we can use STTCs to obtain large coding gains. Many attempts have been made to construct STTCs which achieve full-diversity and good coding gains, though a general method of construction does not exist. Delay diversity code (rate-1) is known to achieve full-diversity, for any number of transmit antennas and any signal set, but does not give a good coding gain. A product distance code based delay diversity scheme (Tarokh, V. et al., IEEE Trans. Inform. Theory, vol.44, p.744-65, 1998) enables one to improve the coding gain and construct STTCs for any given number of states using coding in conjunction with delay diversity; it was stated as an open problem. We achieve such a construction. We assume a shift register based model to construct an STTC for any state complexity. We derive a sufficient condition for this STTC to achieve full-diversity, based on the delay diversity scheme. This condition provides a framework to do coding in conjunction with delay diversity for any signal constellation. Using this condition, we provide a formal rate-1 STTC construction scheme for PSK signal sets, for any number of transmit antennas and any given number of states, which achieves full-diversity and gives a good coding gain.
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An extension to a formal verification approach of hybrid systems is proposed to verify analog and mixed signal (AMS) designs. AMS designs can be formally modeled as hybrid systems and therefore lend themselves to the formal analysis and verification techniques applied to hybrid systems. The proposed approach employs simulation traces obtained from an actual design implementation of AMS circuit blocks (for example, in the form of SPICE netlists) to carry out formal analysis and verification. This enables the same platform used for formally validating an abstract model of an AMS design, to be also used for validating its different refinements and design implementation; thereby, providing a simple route to formal verification at different levels of implementation. The feasibility of the proposed approach is demonstrated with a case study based on a tunnel diode oscillator. Since the device characteristic of a tunnel diode is highly non-linear with a negative resistance region, dynamic behavior of circuits in which it is employed as an element is difficult to model, analyze and verify within a general hybrid system formal verification tool. In the case study presented the formal model and the proposed computational techniques have been incorporated into CheckMate, a formal verification tool based on MATLAB and Simulink-Stateflow Framework from MathWorks.
Resumo:
We address the problem of recognition and retrieval of relatively weak industrial signal such as Partial Discharges (PD) buried in excessive noise. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) which has similar time-frequency characteristics as PD pulse. Therefore conventional frequency based DSP techniques are not useful in retrieving PD pulses. We employ statistical signal modeling based on combination of long-memory process and probabilistic principal component analysis (PPCA). An parametric analysis of the signal is exercised for extracting the features of desired pules. We incorporate a wavelet based bootstrap method for obtaining the noise training vectors from observed data. The procedure adopted in this work is completely different from the research work reported in the literature, which is generally based on deserved signal frequency and noise frequency.
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The coding gain in subband coding, a popular technique for achieving signal compression, depends on how the input signal spectrum is decomposed into subbands. The optimality of such decomposition is conventionally addressed by designing appropriate filter banks. The issue of optimal decomposition of the input spectrum is addressed by choosing the set of band that, for a given number of bands, will achieve maximum coding gain. A set of necessary conditions for such optimality is derived, and an algorithm to determine the optimal band edges is then proposed. These band edges along with ideal filters, achieve the upper bound of coding gain for a given number of bands. It is shown that with ideal filters, as well as with realizable filters for some given effective length, such a decomposition system performs better than the conventional nonuniform binary tree-structured decomposition in some cases for AR sources as well as images
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This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distributed (i.i.d) noise added to the input of each quantizer. The standard deviation sigma of quantizer noise is chosen to maximize the detection probability for a given false alarm probability. In the case of a weak signal, the optimum sigma also minimizes the mean-square difference between the output of the quantizer array and the output of the nonlinear transformation of the locally optimum detector. The optimum sigma depends only on the probability density functions (pdfs) of input noise and quantizer noise for weak signals, and also on the signal amplitude and the false alarm probability for non-weak signals. Improvement in detector performance stems primarily from quantization and to a lesser extent from the optimization of quantizer noise. For most input noise pdfs, the performance of the SSR detector is very close to that of the optimum detector. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Queens of many social insect species are known to maintain reproductive monopoly by pheromonal signalling of fecundity. Queens of the primitively eusocial wasp Ropalidia marginata appear to do so using secretions from their Dufour's glands, whose hydrocarbon composition is correlated with fertility. Solitary nest foundresses of R. marginata are without nestmates; hence expressing a queen signal can be redundant, since there is no one to receive the signal. But if queen pheromone is an honest signal inextricably linked with fertility, it should correlate with fertility and be expressed irrespective of the presence or absence of receivers of the signal, by virtue of being a byproduct of the state of fertility. Hence we compared the Dufour's gland hydrocarbons and ovaries of solitary foundresses with queens and workers of post-emergence nests. Our results suggest that queen pheromone composition in R. marginata is a byproduct of fertility and hence can honestly signal fertility. This provides important new evidence for the honest signalling hypothesis.
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Hydrogenperoxide (H2O2) is generated in mitochondria in aerobic cells as a minor product of electron transport, is inhibited selectively by phenolic acids (in animals) or salicylhydroxamate (in plants) and is regulated by hormones and environmental conditions. Failure to detect this activity is due to presence of H2O2-consuming reactions or inhibitors present in the reaction mixture. H2O2 has a role in metabolic regulation and signal transduction reactions. A number of enzymes and cellular activities are modified, mostly by oxidizing the protein-thiol groups, on adding H2O2 in mM concentrations. On complexing with vanadate, also occurring in traces, H2O2 forms diperoxovanadate (DPV), stable at physiological pH and resistant to degradation by catalase. DPV was found to substitute for H2O2 at concentrations orders of magnitude lower, and in presence of catalase, as a substrate for user reaction, horseradish peroxidase (HRP), and in inactivating glyceraldehyde-3-phosphate dehydrogenase. superoxide dismutase (SOD)-sensitive oxidation of NADH was found to operate as peroxovanadate cycle using traces of DPV and decameric vanadate (V-10) and reduces O-2 to peroxide (DPV in presence of free vanadate). This offers a model for respiratory burst. Diperoxovanadate reproduces several actions of H2O2 at low concentrations: enhances protein tyrosine phosphorylation, activates phospholipase D, produces smooth muscle contraction, and accelerates stress induced premature senescence (SIPS) and rounding in fibroblasts. Peroxovanadates can be useful tools in the studies on H2O2 in cellular activities and regulation.
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Carbon nanotubes dispersed in polymer matrix have been aligned in the form of fibers and interconnects and cured electrically and by UV light. Conductivity and effective semiconductor tunneling against reverse to forward bias field have been designed to have differentiable current-voltage response of each of the fiber/channel. The current-voltage response is a function of the strain applied to the fibers along axial direction. Biaxial and shear strains are correlated by differentiating signals from the aligned fibers/channels. Using a small doping of magnetic nanoparticles in these composite fibers, magneto-resistance properties are realized which are strong enough to use the resulting magnetostriction as a state variable for signal processing and computing. Various basic analog signal processing tasks such as addition, convolution and filtering etc. can be performed. These preliminary study shows promising application of the concept in combined analog-digital computation in carbon nanotube based fibers. Various dynamic effects such as relaxation, electric field dependent nonlinearities and hysteresis on the output signals are studied using experimental data and analytical model.