Proton magnetic resonance study of the structure of two tutton's salts

Proton magnetic resonance spectra of single crystals of two Tutton's salts, K2Zn (SO4)2.6H22O and K2Mg (SO4)2.6H2O, have been studied and the orientations of the water molecules in the structure have been determined. Using the heavy-atom structure of (NH4) 2Mgt(SO4)2.6H2O as determined by x-ray diffraction, a system of hydrogen bonds between the water and sulfate oxygens in Tutton's salts has been proposed. It appears that the x-ray structure needs considerable refinement.

Studies in sesquiterpenes-XVIII. The proton magnetic resonance spectra of some sesquiterpenes and the structure of humulene

The nuclear magnetic resonance spectra of longifolene, zerumbone, humulene, and their hydroderivatives have been studied in order to gauge the potentialities of this new tool in the field of sesquiterpenes. On the basis of present study, it has been possible to unequivocally fix the positions of the ethylene linkages in humulene and thus provide a straightforward solution of this hitherto unsolved problem.

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.

Hysteresis in model spin systems

The authors study the hysteretic response of model spin systems to periodic time-varying fields H(t) as a function of the amplitude H0 and the frequency Omega . At fixed H0, they find conventional, squarish hysteresis loops at low Omega , and rounded, roughly elliptical loops at high Omega , in agreement with experiment. For the O(N to infinity ), d=3, ( Phi 2)2 model with Langevin dynamics, they find a novel scaling behaviour for the area A of the hysteresis loop, of the form (valid for low fields) A approximately=H0066 Omega 0.33.

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.

On-board correction of systematic error of Earth sensors

Infrared Earth sensors are used in spacecraft for attitude sensing. Their accuracy is limited by systematic and random errors. Dominant sources of systematic errors are analyzed for a typical scanning infrared Earth sensor used in a remote-sensing satellite in a 900-km sun-synchronous orbit. The errors considered arise from 1) seasonable variation of infrared radiation, 2) oblate shape of the Earth, 3) ambient temperature of sensors, 4) changes in spin/scan period, and 5) misalignment of the axis of the sensors. Simple relations are derived using least-squares curve fitting for onboard correction of these errors. With these, it is possible to improve the accuracy of attitude determination by eight fold and achieve performance comparable to ground-based post-facto attitude computation.