Theory of the non-Fermi-liquid transition point in the two-impurity Kondo model

We present an explicit solution of the problem of two coupled spin-1/2 impurities, interacting with a band of conduction electrons. We obtain an exact effective bosonized Hamiltonian, which is then treated by two different methods (low-energy theory and mean-field approach). Scale invariance is explicitly shown at the quantum critical point. The staggered susceptibility behaves like ln(T(K)/T) at low T, whereas the magnetic susceptibility and [S1.S2] are well behaved at the transition. The divergence of C(T)/T when approaching the transition point is also studied. The non-Fermi-liquid (actually marginal-Fermi-liquid) critical point is shown to arise because of the existence of anomalous correlations, which lead to degeneracies between bosonic and fermionic states of the system. The methods developed in this paper are of interest for studying more physically relevant models, for instance, for high-T(c) cuprates.

Fracture Properties of Concrete-Concrete Interfaces Using Digital Image Correlation

The mode I and mode II fracture toughness and the critical strain energy release rate for different concrete-concrete jointed interfaces are experimentally determined using the Digital Image Correlation technique. Concrete beams having different compressive strength materials on either side of a centrally placed vertical interface are prepared and tested under three-point bending in a closed loop servo-controlled testing machine under crack mouth opening displacement control. Digital images are captured before loading (undeformed state) and at different instances of loading. These images are analyzed using correlation techniques to compute the surface displacements, strain components, crack opening and sliding displacements, load-point displacement, crack length and crack tip location. It is seen that the CMOD and vertical load-point displacement computed using DIC analysis matches well with those measured experimentally.

An examination of the BEBO model with the results of ab initio calculations of a reaction series

The BEBO (bond energy-bond order) model of Johnston and Parr is examined with the results of ab initio MO calculations on a series of metathetic reactions which involve hydrogen transfer. Energies are calculated at the 6-31G**/PMP2 = full//6-31G** level while the bond orders are estimated using the 6-31G** basis set with the geometry optimisation at the single configuration unrestricted Hartree-Fock frame. Our analysis reveals that the bond-order exponent in the BEBO theory is greater than unity for the reaction series and the entropy term becomes implicitly present in the BEBO model.

Combined Cryo and Room-Temperature Ball Milling to Produce Ultrafine Halide Crystallites

The combined milling at cryogenic temperature as well as room temperature (RT) has been carried out to prepare ultrafine NaCl crystallites. The milling has been done in evacuated tungsten carbide vials backfilled with high-purity Ar. The results indicate the effect duration of cryomilling prior to RT milling has a strong effect on the final crystallite size. The deformation aided sintering of NaCl crystallites during RT milling and leads to the formation of bimodal distribution of crystallites. The cuboidal-shaped NaCl crystallite undergoes a roughening transition due to plastic deformation. The experimental results are explained using the temperature-dependent mechanical properties of NaCl single crystals and plastic-deformation-induced roughening.

A Sub-Nyquist Sampling Method For Computing The Level-crossing-times Of An Analog Signal: Theory And Applications

We address the problem of computing the level-crossings of an analog signal from samples measured on a uniform grid. Such a problem is important, for example, in multilevel analog-to-digital (A/D) converters. The first operation in such sampling modalities is a comparator, which gives rise to a bilevel waveform. Since bilevel signals are not bandlimited, measuring the level-crossing times exactly becomes impractical within the conventional framework of Shannon sampling. In this paper, we propose a novel sub-Nyquist sampling technique for making measurements on a uniform grid and thereby for exactly computing the level-crossing times from those samples. The computational complexity of the technique is low and comprises simple arithmetic operations. We also present a finite-rate-of-innovation sampling perspective of the proposed approach and also show how exponential splines fit in naturally into the proposed sampling framework. We also discuss some concrete practical applications of the sampling technique.

Cooperative Spectrum Sensing Algorithms For OFDM Systems with Frequency Selective Channels

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user employs Orthogonal Frequency Division Multiplexing (OFDM). We specifically consider the scenario when the channel between the primary and a secondary user is frequency selective. We develop cooperative sequential detection algorithms based on energy detectors. We modify the detectors to mitigate the effects of some common model uncertainties such as timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. The performance of the proposed algorithms are studied via simulations. We show that the performance of the energy detector is not affected by the frequency selective channel. We also provide a theoretical analysis for some of our algorithms.

Bayesian Decentralized Spectrum Sensing in Cognitive Radio Networks

This paper considers the problem of spectrum sensing, i.e., the detection of whether or not a primary user is transmitting data by a cognitive radio. The Bayesian framework is adopted, with the performance measure being the probability of detection error. A decentralized setup, where N sensors use M observations each to arrive at individual decisions that are combined at a fusion center to form the overall decision is considered. The unknown fading channel between the primary sensor and the cognitive radios makes the individual decision rule computationally complex, hence, a generalized likelihood ratio test (GLRT)-based approach is adopted. Analysis of the probabilities of false alarm and miss detection of the proposed method reveals that the error exponent with respect to M is zero. Also, the fusion of N individual decisions offers a diversity advantage, similar to diversity reception in communication systems, and a tight bound on the error exponent is presented. Through an analysis in the low power regime, the number of observations needed as a function of received power, to achieve a given probability of error is determined. Monte-Carlo simulations confirm the accuracy of the analysis.

Robust Semi-Blind Estimation for Beamforming Based MIMO Wireless Communication

In this paper, we present robust semi-blind (SB) algorithms for the estimation of beamforming vectors for multiple-input multiple-output wireless communication. The transmitted symbol block is assumed to comprise of a known sequence of training (pilot) symbols followed by information bearing blind (unknown) data symbols. Analytical expressions are derived for the robust SB estimators of the MIMO receive and transmit beamforming vectors. These robust SB estimators employ a preliminary estimate obtained from the pilot symbol sequence and leverage the second-order statistical information from the blind data symbols. We employ the theory of Lagrangian duality to derive the robust estimate of the receive beamforming vector by maximizing an inner product, while constraining the channel estimate to lie in a confidence sphere centered at the initial pilot estimate. Two different schemes are then proposed for computing the robust estimate of the MIMO transmit beamforming vector. Simulation results presented in the end illustrate the superior performance of the robust SB estimators.

Bayesian Learning for Joint Sparse OFDM Channel Estimation and Data Detection

The impulse response of a typical wireless multipath channel can be modeled as a tapped delay line filter whose non-zero components are sparse relative to the channel delay spread. In this paper, a novel method of estimating such sparse multipath fading channels for OFDM systems is explored. In particular, Sparse Bayesian Learning (SBL) techniques are applied to jointly estimate the sparse channel and its second order statistics, and a new Bayesian Cramer-Rao bound is derived for the SBL algorithm. Further, in the context of OFDM channel estimation, an enhancement to the SBL algorithm is proposed, which uses an Expectation Maximization (EM) framework to jointly estimate the sparse channel, unknown data symbols and the second order statistics of the channel. The EM-SBL algorithm is able to recover the support as well as the channel taps more efficiently, and/or using fewer pilot symbols, than the SBL algorithm. To further improve the performance of the EM-SBL, a threshold-based pruning of the estimated second order statistics that are input to the algorithm is proposed, and its mean square error and symbol error rate performance is illustrated through Monte-Carlo simulations. Thus, the algorithms proposed in this paper are capable of obtaining efficient sparse channel estimates even in the presence of a small number of pilots.

Proposed role of w chromosome inactivation and the absence of dosage compensation in avian sex determination

Three features of avian sex chromosomes - female heterogamety (ZZ male, ZW female), the apparently inactive state of the W chromosome, and dose-dependent expression of Z-linked genes - are examined in regard to their possible relation to sex determination. It is proposed that the W chromosome is facultatively heterochromatic and that the Z and W chromosomes carry one or more homologous sex-determination genes. The absence of dosage compensation in ZZ embryos, and W inactivation in ZW embryos, would then bring about a 2n(ZZ)-n(ZW) inequality in the effective copy number of such genes. The absence of dosage compensation of Z-linked genes in ZZ embryos is viewed as a means by which two copies of Z-W homologous sex determination genes are kept active to meet the requirements of testis determination. W inactivation may promote ovarian development by reducing the effective copy number of these genes from 2n to n. If there is a W-specific gene for femaleness, spread of heterochromatization to this gene in cells forming the right gonadal primordium may explain the latter's normally undifferentiated state; reversal of heterochromatization may similarly explain the development of the right gonad into a testis following left ovariectomy.

Fatigue crack propagation model and size effect in concrete using dimensional analysis

It is well known that fatigue in concrete causes excessive deformations and cracking leading to structural failures. Due to quasi-brittle nature of concrete and formation of a fracture process zone, the rate of fatigue crack growth depends on a number of parameters, such as, the tensile strength, fracture toughness, loading ratio and most importantly the structural size. In this work, an analytical model is proposed for estimating the fatigue crack growth in concrete by using the concepts of dimensional analysis and including the above parameters. Knowing the governed and the governing parameters of the physical problem and by using the concepts of self-similarity, a relationship is obtained between different parameters involved. It is shown that the proposed fatigue law is able to capture the size effect in plain concrete and agrees well with different experimental results. Through a sensitivity analysis, it is shown that the structural size plays a dominant role followed by loading ratio and the initial crack length in fatigue crack propagation. (C) 2010 Elsevier Ltd. All rights reserved.

Fracture Analysis of Concrete Structural Components Accounting for Tension Softening Effect

This paper presents methodologies for fracture analysis of concrete structural components with and without considering tension softening effect. Stress intensity factor (SIF) is computed by using analytical approach and finite element analysis. In the analytical approach, SW accounting for tension softening effect has been obtained as the difference of SIP obtained using linear elastic fracture mechanics (LEFM) principles and SIP due to closing pressure. Superposition principle has been used by accounting for non-linearity in incremental form. SW due to crack closing force applied on the effective crack face inside the process zone has been computed using Green's function approach. In finite element analysis, the domain integral method has been used for computation of SIR The domain integral method is used to calculate the strain energy release rate and SIF when a crack grows. Numerical studies have been conducted on notched 3-point bending concrete specimen with and without considering the cohesive stresses. It is observed from the studies that SW obtained from the finite element analysis with and without considering the cohesive stresses is in good agreement with the corresponding analytical value. The effect of cohesive stress on SW decreases with increase of crack length. Further, studies have been conducted on geometrically similar structures and observed that (i) the effect of cohesive stress on SW is significant with increase of load for a particular crack length and (iii) SW values decreases with increase of tensile strength for a particular crack length and load.

On the improvement of diversity-multiplexing gain tradeoff in a training based TDD-simo system

This paper investigates the diversity-multiplexing gain tradeoff (DMT) of a time-division duplex (TDD) single-input multiple-output (SIMO) system with perfect channel state information (CSI) at the receiver (CSIR) and partial CSI at the transmitter (CSIT). The partial CSIT is acquired through a training sequence from the receiver to the transmitter. The training sequence is chosen in an intelligent manner based on the CSIR, to reduce the training length by a factor of r, the number of receive antennas. We show that, for the proposed training scheme and a given channel coherence time, the diversity order increases linearly with r for nonzero multiplexing gain. This is a significant improvement over conventional orthogonal training schemes.

Receiver-Only Optimized Vector Quantization for Noisy Channels

This paper considers the design and analysis of a filter at the receiver of a source coding system to mitigate the excess Mean-Squared Error (MSE) distortion caused due to channel errors. It is assumed that the source encoder is channel-agnostic, i.e., that a Vector Quantization (VQ) based compression designed for a noiseless channel is employed. The index output by the source encoder is sent over a noisy memoryless discrete symmetric channel, and the possibly incorrect received index is decoded by the corresponding VQ decoder. The output of the VQ decoder is processed by a receive filter to obtain an estimate of the source instantiation. In the sequel, the optimum linear receive filter structure to minimize the overall MSE is derived, and shown to have a minimum-mean squared error receiver type structure. Further, expressions are derived for the resulting high-rate MSE performance. The performance is compared with the MSE obtained using conventional VQ as well as the channel optimized VQ. The accuracy of the expressions is demonstrated through Monte Carlo simulations.

Power Management and Data Rate Maximization in Wireless Energy Harvesting Sensors

This paper considers the problem of power management and throughput maximization for energy neutral operation when using Energy Harvesting Sensors (EHS) to send data over wireless links. It is assumed that the EHS are designed to transmit data at a constant rate (using a fixed modulation and coding scheme) but are power-controlled. A framework under which the system designer can optimize the performance of EHS when the channel is Rayleigh fading is developed. For example, the highest average data rate that can be supported over a Rayleigh fading channel given the energy harvesting capability, the battery power storage efficiency and the maximum allowed transmit energy per slot is derived. Furthermore, the optimum transmission scheme that guarantees a particular data throughput is derived. The usefulness of the framework developed is illustrated through simulation results for specific examples.