Asymtotic solution of the Frieman and Book equation for the pair-correlation function

Using Thomé's procedure, the asymptotic solutions of the Frieman and Book equation for the two-particle correlation in a plasma have been obtained in a complete form. The solution is interpreted in terms of the Lorentz distance. The exact expressions for the internal energy and pressure are evaluated and they are found to be a generalization of the result obtained earlier by others.

Investigations of superconducting bismuth cuprates of the general formula Bi2-xPbx(Ca,Sr,Y)n 1 Cun O2n 4 δ

In the (Bi,Pb)-Sr-Cu-O system we have examined many compositions which are either metallic or semiconducting. In the Bi2-xPbx(Ca, Sr)n+1 Cun O2n+4+δ system, we have established the superconducting properties of the n = 1 to 4 members. The Tc increases from n = 1 to 3 and does not increase further when n = 4. In Bi2Ca1-x,YxSr2Cu2Oy, the Tc decreases with increase in x.

Design of a FIR filter for image restoration using principal component neural networks

The neural network finds its application in many image denoising applications because of its inherent characteristics such as nonlinear mapping and self-adaptiveness. The design of filters largely depends on the a-priori knowledge about the type of noise. Due to this, standard filters are application and image specific. Widely used filtering algorithms reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design a finite impulse response filter based on principal component neural network (PCNN) is proposed in this study for image filtering, optimized in the sense of visual inspection and error metric. This algorithm exploits the inter-pixel correlation by iteratively updating the filter coefficients using PCNN. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions. Further, the number of unknown parameters is very few and most of these parameters are adaptively obtained from the processed image.

Thermal correlation functions of twisted quantum fields

We derive the thermal correlators for twisted quantum fields on noncommutative spacetime. We show that the thermal expectation value of the number operator is same as in commutative spacetime, but that higher correlators are sensitive to the noncommutativity parameters phi(mu nu).

The Shannon Cipher System with a Guessing Wiretapper: General Sources

The Shannon cipher system is studied in the context of general sources using a notion of computational secrecy introduced by Merhav & Arikan. Bounds are derived on limiting exponents of guessing moments for general sources. The bounds are shown to be tight for iid, Markov, and unifilar sources, thus recovering some known results. A close relationship between error exponents and correct decoding exponents formfixed rate source compression on the one hand and exponents for guessing moments on the other hand is established.

A general thermodynamic framework for understanding the behaviour of absorption chillers

In this article, a general definition of the process average temperature has been developed, and the impact of the various dissipative mechanisms on 1/COP of the chiller evaluated. The present component-by-component black box analysis removes the assumptions regarding the generator outlet temperature(s) and the component effective thermal conductances. Mass transfer resistance is also incorporated into the absorber analysis to arrive at a more realistic upper limit to the cooling capacity. Finally, the theoretical foundation for the absorption chiller T-s diagram is derived. This diagrammatic approach only requires the inlet and outlet conditions of the chiller components and can be employed as a practical tool for system analysis and comparison. (C) 2000 Elsevier Science Ltd and IIR. All rights reserved.

A general procedure for generation of curved DNA molecules.

A general method for generation of base-pairs in a curved DNA structure, for any prescribed values of helical parameters--unit rise (h), unit twist (theta), wedge roll (theta R) and wedge tilt (theta T), propeller twist (theta p) and displacement (D) is described. Its application for generation of uniform as well curved structures is also illustrated with some representative examples. An interesting relationship is observed between helical twist (theta), base-pair parameters theta x, theta y and the wedge parameters theta R, theta T, which has important consequences for the description and estimation of DNA curvature.

Correlation between stick-slip frictional sliding and charge transfer

A decade ago, Budakian and Putterman [Phys. Rev. Lett. 85, 1000 (2000)] ascribed friction to the formation of bonds arising from contact charging when a gold tip of a surface force apparatus was dragged on polymethylmethacrylate surface. We propose a stick-slip model that captures the observed correlation between stick-slip events and charge transfer, and the lack of dependence of the scale factor connecting the force jumps and charge transfer on normal load. Here, stick-slip dynamics arises as a competition between the viscoelastic and plastic deformation time scales and that due to the pull speed with contact charging playing a minor role. Our model provides an alternate basis for explaining most experimental results without ascribing friction to contact charging.

Distributed nonlinear optimization algorithms for general network problems

There are a number of large networks which occur in many problems dealing with the flow of power, communication signals, water, gas, transportable goods, etc. Both design and planning of these networks involve optimization problems. The first part of this paper introduces the common characteristics of a nonlinear network (the network may be linear, the objective function may be non linear, or both may be nonlinear). The second part develops a mathematical model trying to put together some important constraints based on the abstraction for a general network. The third part deals with solution procedures; it converts the network to a matrix based system of equations, gives the characteristics of the matrix and suggests two solution procedures, one of them being a new one. The fourth part handles spatially distributed networks and evolves a number of decomposition techniques so that we can solve the problem with the help of a distributed computer system. Algorithms for parallel processors and spatially distributed systems have been described.There are a number of common features that pertain to networks. A network consists of a set of nodes and arcs. In addition at every node, there is a possibility of an input (like power, water, message, goods etc) or an output or none. Normally, the network equations describe the flows amoungst nodes through the arcs. These network equations couple variables associated with nodes. Invariably, variables pertaining to arcs are constants; the result required will be flows through the arcs. To solve the normal base problem, we are given input flows at nodes, output flows at nodes and certain physical constraints on other variables at nodes and we should find out the flows through the network (variables at nodes will be referred to as across variables).The optimization problem involves in selecting inputs at nodes so as to optimise an objective function; the objective may be a cost function based on the inputs to be minimised or a loss function or an efficiency function. The above mathematical model can be solved using Lagrange Multiplier technique since the equalities are strong compared to inequalities. The Lagrange multiplier technique divides the solution procedure into two stages per iteration. Stage one calculates the problem variables % and stage two the multipliers lambda. It is shown that the Jacobian matrix used in stage one (for solving a nonlinear system of necessary conditions) occurs in the stage two also.A second solution procedure has also been imbedded into the first one. This is called total residue approach. It changes the equality constraints so that we can get faster convergence of the iterations.Both solution procedures are found to coverge in 3 to 7 iterations for a sample network.The availability of distributed computer systems — both LAN and WAN — suggest the need for algorithms to solve the optimization problems. Two types of algorithms have been proposed — one based on the physics of the network and the other on the property of the Jacobian matrix. Three algorithms have been deviced, one of them for the local area case. These algorithms are called as regional distributed algorithm, hierarchical regional distributed algorithm (both using the physics properties of the network), and locally distributed algorithm (a multiprocessor based approach with a local area network configuration). The approach used was to define an algorithm that is faster and uses minimum communications. These algorithms are found to converge at the same rate as the non distributed (unitary) case.

Enantiodiscrimination and extraction of short and long range homo- and hetero-nuclear residual dipolar couplings by a spin selective correlation experiment

A two dimensional correlation experiment for the measurement of short and long range homo- and hetero- nuclear residual dipolar couplings (RDCs) from the broad and featureless proton NMR spectra including C-13 satellites is proposed. The method employs a single natural abundant C-13 spin as a spy nucleus to probe all the coupled protons and permits the determination of RDCs of negligible strengths. The technique has been demonstrated for the study of organic chiral molecules aligned in chiral liquid crystal, where additional challenge is to unravel the overlapped spectrum of enantiomers. The significant advantage of the method is demonstrated in better chiral discrimination using homonuclear RDCs as additional parameters. (C) 2010 Elsevier B.V. All rights reserved.

Correlation of acoustic and thermal anomalies in ferroelectric crystals

The Pippard-Janovec relations are derived for correlating the anomalous elastic coefficient and the anomalous specific heat near the phase transitions of ferroelectric crystals. These relations are verified in the case of ferroelectric triglycine selenate crystal.

Mooij correlation in disordered metals

We point out that the Mooij correlation follows naturally from a dynamically disordered tight-binding Hamiltonian with random modulations of both the diagonal and the off-diagonal matrix elements which are known to act in opposition. The dynamic disorder is treated exactly while the static disorder is incorporated approximately as an effective additional time-dependent disorder affecting the diffusive electron. Such a time translation of static disorder is known to manifest itself in certain limits as a renormalization of the diffusion coefficient. The calculated conductivity exhibits the Mooij correlation at high temperatures, where quantum coherence associated with the static disorder can be ignored.

Optimal infinite-horizon feedback laws for a general class of constrained discrete-time systems: stability and moving-horizon approximations

Stability results are given for a class of feedback systems arising from the regulation of time-varying discrete-time systems using optimal infinite-horizon and moving-horizon feedback laws. The class is characterized by joint constraints on the state and the control, a general nonlinear cost function and nonlinear equations of motion possessing two special properties. It is shown that weak conditions on the cost function and the constraints are sufficient to guarantee uniform asymptotic stability of both the optimal infinite-horizon and movinghorizon feedback systems. The infinite-horizon cost associated with the moving-horizon feedback law approaches the optimal infinite-horizon cost as the moving horizon is extended.