A Study of Long-range Correlations in Schizophrenia EEG using Detrended Fluctuation Analysis

In this paper, we have studied electroencephalogram (EEG) activity of schizophrenia patients, in resting eyes closed condition, with detrended fluctuation analysis (DFA). The DFA gives information about scaling and long-range correlations in time series. We computed DFA exponents from 30 scalp locations of 18 male neuroleptic-naIve, recent-onset schizophrenia (NRS) subjects and 15 healthy male control subjects. Our results have shown two scaling regions in all the scalp locations in all the subjects, with different slopes, corresponding to two scaling exponents. No significant differences between the groups were found with first scaling exponent (short-range). However, the second scaling exponent (long-range) were significantly lower in control subjects at all scalp locations (p<0.05, Kruskal-Wallis test). These findings suggest that the long-range scaling behavior of EEG is sensitive to schizophrenia, and this may provide an additional insight into the brain dysfunction in schizophrenia.

Supersolid Phase in One-Dimensional Bose-Hubbard Model With Extended Range Interactions: DMRG And Field Theoretic Study at Different Densities

We use the Density Matrix Renormalization Group and the Abelian bosonization method to study the effect of density on quantum phases of one-dimensional extended Bose-Hubbard model. We predict the existence of supersolid phase and also other quantum phases for this system. We have analyzed the role of extended range interaction parameters on solitonic phase near half-filling. We discuss the effects of dimerization in nearest neighbor hopping and interaction as well as next nearest neighbor interaction on the plateau phase at half-filling.

A novel neural network design for long range prediction of rainfall pattern

The importance of long-range prediction of rainfall pattern for devising and planning agricultural strategies cannot be overemphasized. However, the prediction of rainfall pattern remains a difficult problem and the desired level of accuracy has not been reached. The conventional methods for prediction of rainfall use either dynamical or statistical modelling. In this article we report the results of a new modelling technique using artificial neural networks. Artificial neural networks are especially useful where the dynamical processes and their interrelations for a given phenomenon are not known with sufficient accuracy. Since conventional neural networks were found to be unsuitable for simulating and predicting rainfall patterns, a generalized structure of a neural network was then explored and found to provide consistent prediction (hindcast) of all-India annual mean rainfall with good accuracy. Performance and consistency of this network are evaluated and compared with those of other (conventional) neural networks. It is shown that the generalized network can make consistently good prediction of annual mean rainfall. Immediate application and potential of such a prediction system are discussed.

Covariant differentials lead to the design of a novel self-tuning power system stabilizer

Application of differential geometry to study the dynamics of electrical machines by Gabriel Kron evoked only theoretical interest among the power system engineers and was considered hardly suitable for any practical use. Extension of Kron's work led to a physical understanding of the processes governing the small oscillation instability in power system. This in turn has made it possible to design a self-tuning Power System Stabilizer to contain the oscillatory instability over arm extended range of system and operating conditions. This paper briefly recounts the history of this development and touches upon the essential design features of the stabilizer. It presents some results from simulation studies, laboratory experiments and recently conducted field trials at actual plants-all of which help to establish the efficacy of the proposed stabilizer and corroborate the theoretical findings.

Probabilistic extension to realistic abductive reasoning model

In this paper, we give a method for probabilistic assignment to the Realistic Abductive Reasoning Model, The knowledge is assumed to be represented in the form of causal chaining, namely, hyper-bipartite network. Hyper-bipartite network is the most generalized form of knowledge representation for which, so far, there has been no way of assigning probability to the explanations, First, the inference mechanism using realistic abductive reasoning model is briefly described and then probability is assigned to each of the explanations so as to pick up the explanations in the decreasing order of plausibility.

Spin-Selective Correlation Experiment for Measurement of Long-Range J Couplings and for Assignment of (R/S) Enantiomers from the Residual Dipolar Couplings and DFT

We report the C-HETSERF experiment for determination of long- and short-range homo- and heteronuclear scalar couplings ((n)J(HH) and (n)J(XH), n >= 1) of organic molecules with a low sensitivity dilute heteronucleus in natural abundance. The method finds significant advantage in measurement of relative signs of long-range heteronuclear total couplings in chiral organic liquid crystal. The advantage of the method is demonstrated for the measurement of residual dipolar couplings (RDCs) in enantiomers oriented in the chiral liquid crystal with a focus to unambiguously assign R/S designation in a 2D spectrum. The alignment tensor calculated from the experimental RDCs and with the computed structures of enantiomers obtained by DFT calculations provides the size of the back-calculated RDCs. Smaller root-mean-square deviations (rmsd) between experimental and calculated RDCs indicate better agreement with the input structure and its correct designation of the stereogenic center.

Long-Range Visible Fluorescence Tunability Using Component-Modulated Coupled Quantum Dots

A simple route for tailoring emissions in the visible wavelength region by chemically coupling quantum dots composed of ZnSe and CdS is reported. coupled quantum dots offer a novel route for tuning electronic transitions via band-offset engineering at the material interface. This novel class of asymmetric. coupled quantum structures may offer a basis for a diverse set of building blocks for optoelectronic devices, ultrahigh density memories, and quantum information processing.

Space vector pulsewidth modulation — A status review

The technique of space vector pulsewidth modulation (SVM) is reviewed. The basic principle of SVM is derived and is compared with sine-triangle PWM. Operation in the overmodulation range is explained. Extension of SVM to other inverter-motor combinations such as three level inverters and split phase motors are discussed.

Vector summed sine wave tailored waveforms for dipolar excitation of ions in Paul trap mass spectrometers

A simple method to generate time domain tailored waveforms for excitation of ion axial amplitude in Paul trap mass spectrometers is described. The method is based on vector summation of sine waves followed by time domain sampling to obtain the discrete time domain data. A smoothing technique based on the time domain Kaiser window is then applied to the data so as to minimize the frequency domain Gibb's oscillations. The dynamic range of the time domain signal is controlled by phase modulation and time extension of the time domain waveform. Copyright (C) 1999 John Wiley & Sons, Ltd.

Dodecagonal space vector diagram using cascaded H-Bridge inverters

This paper proposes the development of dodecagonal (12-sided) space vector diagrams from cascaded H-Bridge inverters. As already reported in literatures, dodecagonal space vector diagrams have many advantages over conventional hexagonal ones. Some of them include the absence of 6n±1, (n=odd) harmonics from the phase voltage, and the extension of the linear modulation range. In this paper, a new power circuit is proposed for generating multiple dodecagons in the space vector plane. It consists of two cascaded H-Bridge cells fed from asymmetric dc voltage sources. It is shown that, with proper PWM timing calculation and placement of active and zero vectors, a very high quality of sine-wave can be produced. At the same time, the switching frequency of individual cells can be reduced substantially. Detailed PWM analysis, one design example and an elaborate simulation study is presented to support the proposed idea.

The absolute orientation of a molecule in space: Extension of the 'CIP' system

A scheme for denoting the absolute spatial orientation of molecules and molecular fragments is presented; this is based on three angular deviations - one for each spatial dimension - with respect to a reference orientation, which is itself defined with the help of certain features of the Cahn-Ingold-Prelog stereochemical notation. The new scheme helps in reconstructing the three-dimensional characteristics of molecules from purely verbal descriptors, and may thus find application in various information storage and retrieval processes (e.,-. encrypting holograms, etc.).

Low-temperature polaronic relaxations with variable range hopping conductivity in FeTiMO(6) (M = Ta,Nb,Sb)

Low-temperature dielectric measurements on FeTiMO(6) (M = Ta,Nb,Sb) rutile-type oxides at frequencies from 0.1 Hz to 10 MHz revealed anomalous dielectric relaxations with frequency dispersion. Unlike the high-temperature relaxor response of these materials, the low-temperature relaxations are polaronic in nature. The relationship between frequency and temperature of dielectric loss peak follows T(-1/4) behavior. The frequency dependence of ac conductivity shows the well-known universal dielectric response, while the dc conductivity follows Mott variable range hopping (VRH) behavior, confirming the polaronic origin of the observed dielectric relaxations. The frequency domain analysis of the dielectric spectra shows evidence for two relaxations, with the high-frequency relaxations following Mott VRH behavior more closely. Significantly, the Cr- and Ga-based analogs, CrTiNbO(6) and GaTiMO(6) (M = Ta,Nb), that were also studied, did not show these anomalies.

Synergy between the N-terminal and C-terminal domains of Mycobacterium tuberculosis HupB is essential for high-affinity binding, DNA supercoiling and inhibition of RecA-promoted strand exchange

The occurrence of DNA architectural proteins containing two functional domains derived from two different architectural proteins is an interesting emerging research theme in the field of nucleoid structure and function. Mycobacterium tuberculosis HupB, unlike Escherichia coli HU, is a two-domain protein that, in the N-terminal region, shows broad sequence homology with bacterial HU. The long C-terminal extension, on the other hand, contains seven PAKK/KAAK motifs, which are characteristic of the histone H1/H5 family of proteins. In this article, we describe several aspects of HupB function, in comparison with its truncated derivatives lacking either the C-terminus or N-terminus. We found that HupB binds a variety of DNA repair and replication intermediates with K(d) values in the nanomolar range. By contrast, the N-terminal fragment of M. tuberculosis HupB (HupB(MtbN)) showed diminished DNA-binding activity, with K(d) values in the micromolar range, and the C-terminal domain was completely devoid of DNA-binding activity. Unlike HupB(MtbN), HupB was able to constrain DNA in negative supercoils and introduce negative superhelical turns into relaxed DNA. Similarly, HupB exerted a robust inhibitory effect on DNA strand exchange promoted by cognate and noncognate RecA proteins, whereas HupB(MtbN), even at a 50-fold molar excess, had no inhibitory effect. Considered together, these results suggest that synergy between the N-terminal and C-terminal domains of HupB is essential for its DNA-binding ability, and to modulate the topological features of DNA, which has implications for processes such as DNA compaction, gene regulation, homologous recombination, and DNA repair.