942 resultados para spatial correlation


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A construction for a family of sequences over the 8-ary AM-PSK constellation that has maximum nontrivial correlation magnitude bounded as theta(max) less than or similar to root N is presented here. The famfly is asymptotically optimal with respect to the Welch bound on maximum magnitude of correlation. The 8-ary AM-PSK constellation is a subset of the 16-QAM constellation. We also construct two families of sequences over 16-QAM with theta(max) less than or similar to root 2 root N. These families are constructed by interleaving sets of sequences. A construction for a famBy of low-correlation sequences over QAM alphabet of size 2(2m) is presented with maximum nontrivial normalized correlation parameter bounded above by less than or similar to a root N, where N is the period of the sequences in the family and where a ranges from 1.61 in the case of 16-QAM modulation to 2.76 for large m. When used in a CDMA setting, the family will permit each user to modulate the code sequence with 2m bits of data. Interestingly, the construction permits users on the reverse link of the CDMA channel to communicate using varying data rates by switching between sequence famflies; associated to different values of the parameter m. Other features of the sequence families are improved Euclidean distance between different data symbols in comparison with PSK signaling and compatibility of the QAM sequence families with sequences belonging to the large quaternary sequence families {S(p)}.

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Since the 1980 s, laminin-1 has been linked to regeneration of the central nervous system (CNS) and promotion of neuronal migration and axon guidance during CNS development. In this thesis, we clarify the role of γ1 laminin and its KDI tripeptide in development of human embryonic spinal cord, in regeneration of adult rat spinal cord injury (SCI), in kainic acid-induced neuronal death, and in the spinal cord tissue of amyotrophic lateral sclerosis (ALS). We demonstrated that γ1 laminin together with α1, β1, and β3 laminins localize at the floor plate region in human embryonic spinal cord. This localization of γ1 laminin is in spatial and temporal correlation with development of the spinal cord and indicates that γ1 laminin may participate in commissural axon guidance during the embryonic development of the human CNS. With in vitro studies using the Matrigel culture system, we demonstrated that the KDI tripeptide of γ1 laminin provides a chemotrophic guidance cue for neurites of the human embryonic dorsal spinal cord, verifying the functional ability of γ1 laminin to guide commissural axons. Results from our experimental SCI model demonstrate that the KDI tripeptide enhanced functional recovery and promoted neurite outgrowth across the mechanically injured area in the adult rat spinal cord. Furthermore, our findings indicate that the KDI tripeptide as a non-competitive inhibitor of the ionotropic glutamate receptors can provide when administered in adequate concentrations an effective method to protect neurons against glutamate-induced excitotoxic cell death. Human postmortem samples were used to study motor neuron disease, ALS (IV), and the study revealed that in human ALS spinal cord, γ1 laminin was selectively over-expressed by reactive astrocytes, and that this over-expression may correlate with disease severity. The multiple ways by which γ1 laminin and its KDI tripeptide provide neurotrophic protection and enhance neuronal viability suggest that the over-expression of γ1 laminin may be a glial attempt to provide protection for neurons against ALS pathology. The KDI tripeptide is effective therapeutically thus far in animal models only. However, because KDI containing γ1 laminin exists naturally in the human CNS, KDI therapies are unlikely to be toxic or allergenic. Results from our animal models are encouraging, with no toxic side-effects detected even at high concentrations, but the ultimate confirmation can be achieved only after clinical trials. More research is still needed until the KDI tripeptide is refined into a clinically applicable method to treat various neurological disorders.

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In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates the predicted error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. In quantization phase, we used a modified SPIHT algorithm to achieve efficiency in memory requirements. The memory constraint plays a vital role in wireless and bandwidth-limited applications. A single reusable list is used instead of three continuously growing linked lists as in case of SPIHT. This method is error resilient. The performance is measured in terms of PSNR and memory requirements. The algorithm shows good compression performance and significant savings in memory. (C) 2006 Elsevier B.V. All rights reserved.

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A test for time-varying correlation is developed within the framework of a dynamic conditional score (DCS) model for both Gaussian and Student t-distributions. The test may be interpreted as a Lagrange multiplier test and modified to allow for the estimation of models for time-varying volatility in the individual series. Unlike standard moment-based tests, the score-based test statistic includes information on the level of correlation under the null hypothesis and local power arguments indicate the benefits of doing so. A simulation study shows that the performance of the score-based test is strong relative to existing tests across a range of data generating processes. An application to the Hong Kong and South Korean equity markets shows that the new test reveals changes in correlation that are not detected by the standard moment-based test.

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The compositional, structural, microstructural, dc electrical conductivity and optical properties of undoped zinc oxide films prepared by the sol-gel process using a spin-coating technique were investigated. The ZnO films were obtained by 5 cycle spin-coated and dried zinc oxide films followed by annealing in air at 600 A degrees C. The films deposited on the platinum coated silicon substrate were crystallized in a hexagonal wurtzite form. The energy-dispersive X-ray (EDX) spectrometry shows Zn and O elements in the products with an approximate molar ratio. TEM image of ZnO thin film shows that a grain of about 60-80 nm in size is really an aggregate of many small crystallites of around 10-20 nm. Electron diffraction pattern shows that the ZnO films exhibited hexagonal structure. The SEM micrograph showed that the films consist in nanocrystalline grains randomly distributed with voids in different regions. The dc conductivity found in the range of 10(-5)-10(-6) (Omega cm)(-1). The optical study showed that the spectra for all samples give the transparency in the visible range.

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We study quench dynamics and defect production in the Kitaev and the extended Kitaev models. For the Kitaev model in one dimension, we show that in the limit of slow quench rate, the defect density n∼1/√τ, where 1/τ is the quench rate. We also compute the defect correlation function by providing an exact calculation of all independent nonzero spin correlation functions of the model. In two dimensions, where the quench dynamics takes the system across a critical line, we elaborate on the results of earlier work [K. Sengupta, D. Sen, and S. Mondal, Phys. Rev. Lett. 100, 077204 (2008)] to discuss the unconventional scaling of the defect density with the quench rate. In this context, we outline a general proof that for a d-dimensional quantum model, where the quench takes the system through a d−m dimensional gapless (critical) surface characterized by correlation length exponent ν and dynamical critical exponent z, the defect density n∼1/τmν/(zν+1). We also discuss the variation of the shape and spatial extent of the defect correlation function with both the rate of quench and the model parameters and compute the entropy generated during such a quenching process. Finally, we study the defect scaling law, entropy generation and defect correlation function of the two-dimensional extended Kitaev model.

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The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. Many of these approaches aim at only analyzing the chaotic nature and not its prediction. In the present study, an attempt is made to identify chaos using various techniques and prediction is also done by generating ensembles in order to quantify the uncertainty involved. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha, Mahanadi and All-India for the period 1955-2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series. Correlation dimension method is done on th phase randomized and first derivative of the data series to check whether the saturation of the dimension is due to the inherent linear correlation structure or due to low dimensional dynamics. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996-2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are done from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. (C) 2010 Elsevier Ltd. All rights reserved.

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Plasma membranes regulate the influx and efflux of molecules across themselves and are also responsible for primary signal transduction between cells or within the same cell. Presence of lateral heterogeneity and the ability of reorganization are essential requirements for effective functioning of biomembranes. Lipid rafts are small, heterogeneous, dynamic domains enriched in glycosphingolipids, sphingomyelin and cholesterol, and profoundly influence membrane organization. Glycosphingolipids are inclined towards formation of liquid-ordered phases in membranes, both with and without cholesterol; they are therefore prime players in domain formation. Here, we discuss the role of glycosphingolipids in microdomain formation and their spatial organization within these rafts.

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Residual viscosity is a unique function of density for pure Freon-12 and Freon-22 vapors. Also, a plot of residual viscosity against density for Freon-12 and Freon-22 vapors exhibits a regular trend. These phenomena form the basis for predicting the viscosity of mixtures of Freon-12 and Freon-22 vapors.

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A correlation for entropy and enthalpy based on the two-parameter law of corresponding states and the reference substance concept has been obtained. For 199 points tested, the over-all average absolute deviation and the maximum deviations in the calculated values of entropy with the available data are 0.74 and 7.20%. The corresponding deviations of enthalpy are 1.86 and 15.0%, respectively. A compressibility chart for chloromethanes has been made and shown to be superior to existing charts. For 102 points tested, the average absolute and maximum deviations in the compressibilities were 1.80 and 19.5%, respectively.

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Two algorithms are outlined, each of which has interesting features for modeling of spatial variability of rock depth. In this paper, reduced level of rock at Bangalore, India, is arrived from the 652 boreholes data in the area covering 220 sqa <.km. Support vector machine (SVM) and relevance vector machine (RVM) have been utilized to predict the reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth. The support vector machine (SVM) that is firmly based on the theory of statistical learning theory uses regression technique by introducing epsilon-insensitive loss function has been adopted. RVM is a probabilistic model similar to the widespread SVM, but where the training takes place in a Bayesian framework. Prediction results show the ability of learning machine to build accurate models for spatial variability of rock depth with strong predictive capabilities. The paper also highlights the capability ofRVM over the SVM model.

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Hydrothermal treatment of a slurry of badly crystalline (beta(bc)) nickel hydroxide at different temperatures (65-170 degrees C) results in the progressive ordering of the structure by the step-wise elimination of disorders. Interstratification is eliminated at 140 degrees C, while cation vacancies are eliminated at 170 degrees C. A small percentage of stacking faults continue to persist even in `crystalline' samples. Electrochemical investigations show that the crystalline nickel hydroxide has a very low (0.4 e/Ni) reversible charge storage capacity. An incidence of at least 15% stacking faults combined with cation vacancies is essential for nickel hydroxide to perform close to its theoretical (1 e/ Ni) discharge capacity. (c) 2005 The Electrochemical Society.

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A new equation for predicting the thermal conductivities of organic liquids using dimension-less analysis is given. The equation (Equation Presented) correlates 51 different liquids tested within 11% average error and 17% standard deviation. A comparison of the proposed equation with the available correlations and its application to some industrially important liquids show that this equation can be safely used to calculate the thermal conductivities at 20°C. and 1 atm. pressure for organic liquids of known molecular weight. Cp and ΔHv - the only two parameters for which experimental values must be known for making use of this equation - can be calculated using other well known correlations. The proposed equation is not applicable to inorganic liquids.

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The significant correlation coefficient between the terrestial heat flow and thermal conductivity computed from the continental heat flow data by Horai and Nur [1]2) may be explained as a natural consequence of terrestrial heat flow through a random medium. The theory predicts a value of 0.40 for the correlation coefficient. A simple statistical test shows that the majority of the computed coefficients belong to the statistical population whose mean is equal to the theoretical correlation coefficient. There are, however, a few observations of unsually high correlation coefficient which cannot be explained by the above hypothesis.

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