Stabilizing hadron resonance gas models

We examine the stability of hadron resonance gas models by extending them to include undiscovered resonances through the Hagedorn formula. We find that the influence of unknown resonances on thermodynamics is large but bounded. We model the decays of resonances and investigate the ratios of particle yields in heavy-ion collisions. We find that observables such as hydrodynamics and hadron yield ratios change little upon extending the model. As a result, heavy-ion collisions at the RHIC and LHC are insensitive to a possible exponential rise in the hadronic density of states, thus increasing the stability of the predictions of hadron resonance gas models in this context. Hadron resonance gases are internally consistent up to a temperature higher than the crossover temperature in QCD, but by examining quark number susceptibilities we find that their region of applicability ends below the QCD crossover.

Pressure dependence of chlorine nuclear quadrupole resonance in sodium chlorate

The pressure dependence of the chlorine NQR frequency in NaClo3 has been investigated up to 20 k bar hydrostatic pressure. A distinct break in slope in the pressure dependence of the resonance frequency is observed near 11 k bar. This is attributed to a phase transition reported earlier by Bridgman in this pressure region.

Performance analysis of a suprathreshold, stochastic resonance based nonlinear detector

In this paper we introduce a nonlinear detector based on the phenomenon of suprathreshold stochastic resonance (SSR). We first present a model (an array of 1-bit quantizers) that demonstrates the SSR phenomenon. We then use this as a pre-processor to the conventional matched filter. We employ the Neyman-Pearson(NP) detection strategy and compare the performances of the matched filter, the SSR-based detector and the optimal detector. Although the proposed detector is non-optimal, for non-Gaussian noises with heavy tails (leptokurtic) it shows better performance than the matched filter. In situations where the noise is known to be leptokurtic without the availability of the exact knowledge of its distribution, the proposed detector turns out to be a better choice than the matched filter.

A suprathreshold stochastic resonance based pre-processor for direction-of-arrival estimation

In this paper we propose a nonlinear preprocessor for enhancing the performance of processors used for direction-of-arrival (DOA) estimation in heavy-tailed non-Gaussian noise. The preprocessor based on the phenomenon of suprathreshold stochastic resonance (SSR), provides SNR gain. The preprocessed data is used for DOA estimation by the MUSIC algorithm. Simulation results are presented to show that the SSR preprocessor provides a significant improvement in the performance of MUSIC in heavy-tailed noise at low SNR.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

An electron paramagnetic resonance study of Pr0.6Ca0.4MnO3 across the charge-ordering transition

We report the first electron paramagnetic resonance studies of single crystals and powders of Pr0.6Ca0.4MnO3 in the 300-4.2 K range, covering the charge-ordering transition (Tco) at ~240 K and antiferromagnetic transition (TN) at ~170 K. The asymmetry parameter for the Dysonian single-crystal spectra shows an anomalous increase at Tco. Below Tco the g-value increases continuously, suggesting a gradual strengthening of the orbital ordering. The linewidth undergoes a sudden increase at Tco and continues to increase down to TN. The intensity increases as the temperature is decreased until Tco is reached, due to the renormalization of the magnetic susceptibility arising from the build-up of ferromagnetic correlations.

Chlorine-35 nuclear quadrupole resonance study of molecular torsional motion in some chloropyridine-N-oxides and chloroquinoline-N-oxides

Chlorine has been substituted at the 2- and 4-positions in the pyridine and quinoline rings of the corresponding N-oxides and 35Cl n.q.r. spectra have been studied in the temperature range 77–300 K. The change in the n.q.r. frequencies in N-oxides as compared to their parent compounds are interpreted in terms of the conjugative effect and the inductive effect of the N+—O– group. The negative temperature coefficients of the resonance frequencies in chloropyridine-N-oxides have been analysed using the Bayer, Kushida and Brown equations. The calculated torsional frequencies, which are in the range 52–78 cm–1, are found to be only slightly temperature dependent.

Contactless conductivity of nanoparticles from electron magnetic resonance lineshape analysis

A contactless method to determine the electrical conductivity of nanoparticles is presented. It is based on the lineshape analysis of electron magnetic resonance signals which are `Dysonian' for conducting samples of sizes larger than the skin depth. The method is validated bymeasurements on a bulk sample of La0.67Sr0.33MnO3 where it gives values close to those obtained from direct measurement of conductivity and is then used to determine the conductivity of nanoparticles of La0.67Sr0.33MnO3 dispersed in polyvinyl alcohol as a function of temperature. (C) 2010 Elsevier Ltd. All rights reserved.