Enhancing signal-to-noise ratio and resolution in low-field NMR relaxation measurements using post-acquisition digital filters

The traditional way to enhance signal-to-noise ratio (SNR) of nuclear magnetic resonance (NMR) signals is to increase the number of scans. However, this procedure increases the measuring time that can be prohibitive for some applications. Therefore, we have tested the use of several post-acquisition digital filters to enhance SNR up to one order of magnitude in time domain NMR (TD-NMR) relaxation measurements. The procedures were studied using continuous wave free precession (CWFP-T₁) signals, acquired with very low flip angles that contain six times more noise than the Carr–Purcell–Meiboom–Gill (CPMG) signal of the same sample and experimental time. Linear (LI) and logarithmic (LO) data compression, low-pass infinity impulse response (LP), Savitzky–Golay (SG), and wavelet transform (WA) post-acquisition filters enhanced the SNR of the CWFP-T₁ signals by at least six times. The best filters were LO, SG, and WA that have high enhancement in SNR without significant distortions in the ILT relaxation distribution data. Therefore, it was demonstrated that these post-acquisition digital filters could be a useful way to denoise CWFP-T₁, as well as CPMG noisy signals, and consequently reducing the experimental time. It was also demonstrated that filtered CWFP-T₁ method has the potential to be a rapid and nondestructive method to measure fat content in beef and certainly in other meat samples.     

Heisenberg-limited Measurements and Sub-Planck Structures in Phase Space

It is shown how sub-Planck phase-space structures can be used to achieve Heisenberg-limited sensitivity in weak force measurements. Nonclassical states of harmonic oscillators, such as superpositions of coherent states, are shown to be useful for the measurement of weak forces that cause translations or rotations in phase space, which is done by entangling the quantum oscillator with a two-level system. This method is closely related to the Loschmidt echo techniques employed in nuclear magnetic resonance experiments. Implementations of this strategy in cavity QED and ion traps are described.     

Affine Arithmetic: Concepts and Applications

Affine arithmetic is a model for self-validated numerical computation that keeps track of first-order correlations between computed and input quantities. We explain the main concepts in affine arithmetic and how it handles the dependency problem in standard interval arithmetic. We also describe some of its applications.     

Fracture mechanism of liquid‐crystalline epoxy resin systems with different phase structures

A liquid‐crystalline epoxy resin was cured at two different temperatures. The phases of the cured systems clearly showed isotropic and nematic polydomain structures, which depended on the curing temperature. The fracture toughness of the systems was measured, and the fracture mechanism was investigated with polarized IR measurements. The nematic polydomain structure system showed considerably higher fracture toughness than the isotropic structure. Moreover, both systems exhibited a reorientation of the network chains near the fracture surface during the fracture process, and the region of the network reorientation in the nematic polydomain structure system was larger than that in the isotropic structure system. © 2004 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 42: 4044–4052, 2004     

A modular integer GCD algorithm

This paper describes the first algorithm to compute the greatest common divisor (GCD) of two n-bit integers using a modular representation for intermediate values U, V and also for the result. It is based on a reduction step, similar to one used in the accelerated algorithm [T. Jebelean, A generalization of the binary GCD algorithm, in: ISSAC '93: International Symposium on Symbolic and Algebraic Computation, Kiev, Ukraine, 1993, pp. 111–116; K. Weber, The accelerated integer GCD algorithm, ACM Trans. Math. Softw. 21 (1995) 111–122] when U and V are close to the same size, that replaces U by (U−bV)/p, where p is one of the prime moduli and b is the unique integer in the interval (−p/2,p/2) such that . When the algorithm is executed on a bit common CRCW PRAM with O(nlognlogloglogn) processors, it takes O(n) time in the worst case. A heuristic model of the average case yields O(n/logn) time on the same number of processors.     

Memory effects in gas chromatographic detection with a microwave-induced plasma

Capillary gas chromatography coupled to microwave-inducedplasma detection furnishes sensitivity adequate for trace analysis when the signal is monitored at a carbon emission line. Work performed with one of these systems at high electronic gain for the carbon signal has revealed solvent band widths in excess of four minutes; these impeded quantification of peaks eluting after the solvent. This report discusses two phenomena which could be related to the unexpected intensity of this solvent response: photomultiplier tube saturation and carbon deposits in the quartz plasma discharge tube.     

Primal-dual proximal point algorithm for linearly constrained convex programming problems

A primal-dual version of the proximal point algorithm is developed for linearly constrained convex programming problems. The algorithm is an iterative method to find a saddle point of the Lagrangian of the problem. At each iteration of the algorithm, we compute an approximate saddle point of the Lagrangian function augmented by quadratic proximal terms of both primal and dual variables. Specifically, we first minimize the function with respect to the primal variables and then approximately maximize the resulting function of the dual variables. The merit of this approach exists in the fact that the latter function is differentiable and the maximization of this function is subject to no constraints. We discuss convergence properties of the algorithm and report some numerical results for network flow problems with separable quadratic costs.     

Construction of self-assembled monolayer terminated with N-heterocyclic carbene-rhodium(I) complex moiety

Functionalization of self-assembled monolayer (SAM) of alkanethiolate with metal containing unit is one of the versatile methods to obtain functional surfaces such as heterogeneous catalysts. However, organic molecules that strongly bind to transition metals at SAM terminal are limited. Recently N-heterocyclic carbenes (NHCs) such as cyclic diaminocarbenes have emerged as strongly σ-donating ligands forming a robust bond with broad spectrum of transition metals. In the present study, for the purpose of establishment of a new robust basement for heterogeneous metal catalysts, a SAM of the alkanethiolate terminated with NHC-rhodium(I) complex moiety was prepared by utilizing a newly designed disulfide molecule bearing NHC-metal complex terminals. X-ray photoelectron spectroscopy (XPS) analysis and angle resolved XPS measurement revealed successful formation of the Rh-complex-terminated SAM on a gold substrate. Infrared reflection absorption spectroscopy (IRRAS) analysis suggested that the linker methylene chains connecting the rhodium complex moiety and the gold surface are in a loosely packed structure. This unique chemical species, NHC, would be a promising candidate as a basement for the construction of functional surface.