Quick re-introduction of selective scalar interactions in a pure-shift NMR spectrum

A new 1D NMR experiment cited as `Quick G-SERF', which re-introduces selective proton-proton scalar interactions in a pure shift spectrum during real time data acquisition, is reported. The method provides information on multiple proton-proton couplings from a single experiment, analogous to the 2D G-SERF technique, while significantly shortening the experimental time by 1-2 orders of magnitude due to reduced dimension and enhanced sensitivity.

Performance Analysis of Space-Shift Keying in Decode-and-Forward Multihop MIMO Networks

In this paper, space-shift keying (SSK) is considered for multihop multiple-input-multiple-output (MIMO) networks. In SSK, only one among n(s) = 2(m) available transmit antennas, chosen on the basis of m information bits, is activated during transmission. We consider two different systems of multihop co-operation, where each node has multiple antennas and employs SSK. In system I, a multihop diversity relaying scheme is considered. In system II, a multihop multibranch relaying scheme is considered. In both systems, we adopt decode-and-forward (DF) relaying, where each relay forwards the signal only when it correctly decodes. We analyze the end-to-end bit error rate (BER) and diversity order of both the systems with SSK. For binary SSK (n(s) = 2), our analytical BER expression is exact, and our numerical results show that the BERs evaluated through the analytical expression overlap with those obtained through Monte Carlo simulations. For nonbinary SSK (n(s) > 2), we derive an approximate BER expression, where the analytically evaluated BER results closely follow the simulated BER results. We show the comparison of the BERs of SSK and conventional phase-shift keying (PSK) and also show the instances where SSK outperforms PSK. We also present the diversity analyses for SSK in systems I and II, which predict the achievable diversity orders as a function of system parameters.

J-Edited Pure Shift NMR for the Facile Measurement of (n)J(HH) for Specific Protons

We report a novel 1D J-edited pure shift NMR experiment (J-PSHIFT) that was constructed from a pseudo 2D experiment for the direct measurement of proton-proton scalar couplings. The experiment gives homonuclear broad-band H-1-decoupled H-1 NMR spectra, which provide a single peak for chemically distinct protons, and only retain the homonuclear-scalar-coupled doublet pattern at the chemical-shift positions of the protons in the coupled network of a specific proton. This permits the direct and unambiguous measurement of the magnitudes of the couplings. The incorporation of a 1D selective correlation spectroscopy (COSY)/ total correlation spectroscopy (TOCSY) block in lieu of the initial selective pulse, results in the exclusive detection of the correlated spectrum of a specific proton.

Effects of hydrogen bonding on amide-proton chemical shift anisotropy in a proline-containing model peptide

Longitudinal relaxation due to cross-correlation between dipolar ((HN-1H alpha)-H-1) and amide-proton chemical shift anisotropy (H-1(N) CSA) has been measured in a model tripeptide Piv-(L)Pro-(L)Pro-(L)Phe-OMe. The peptide bond across diproline segment is known to undergo cis/trans isomerization and only in the cis form does the lone Phe amide-proton become involved in intramolecular hydrogen bonding. The strength of the cross correlated relaxation interference is found to be significantly different between cis and trans forms, and this difference is shown as an influence of intramolecular hydrogen bonding on the amide-proton CSA. (C) 2015 Elsevier B.V. All rights reserved.

Negative hyperconjugation and red-, blue- or zero-shift in X-Z center dot center dot center dot Y complexes

A generalized explanation is provided for the existence of the red-and blue-shifting nature of X-Z bonds (Z = H, halogens, chalcogens, pnicogens, etc.) in X-Z center dot center dot center dot Y complexes based on computational studies on a selected set of weakly bonded complexes and analysis of existing literature data. The additional electrons and orbitals available on Z in comparison to H make for dramatic differences between the H-bond and the rest of the Z-bonds. The nature of the X-group and its influence on the X-Z bond length in the parent X-Z molecule largely controls the change in the X-Z bond length on X-Z center dot center dot center dot Y bond formation; the Y-group usually influences only the magnitude of the effects controlled by X. The major factors which control the X-Z bond length change are: (a) negative hyperconjugative donation of electron density from X-group to X-Z sigma* antibonding molecular orbital (ABMO) in the parent X-Z, (b) induced negative hyperconjugation from the lone pair of electrons on Z to the antibonding orbitals of the X-group, and (c) charge transfer (CT) from the Y-group to the X-Z sigma* orbital. The exchange repulsion from the Y-group that shifts partial electron density at the X-Z sigma* ABMO back to X leads to blue-shifting and the CT from the Y-group to the sigma* ABMO of X-Z leads to red-shifting. The balance between these two opposing forces decides red-, zero- or blue-shifting. A continuum of behaviour of X-Z bond length variation is inevitable in X-Z center dot center dot center dot Y complexes.

Performance of New Dynamic Benefit-Weighted Scheduling Scheme in DiffServ Networks

In this paper, we design a new dynamic packet scheduling scheme suitable for differentiated service (DiffServ) network. Designed dynamic benefit weighted scheduling (DBWS) uses a dynamic weighted computation scheme loosely based on weighted round robin (WRR) policy. It predicts the weight required by expedited forwarding (EF) service for the current time slot (t) based on two criteria; (i) previous weight allocated to it at time (t-1), and (ii) the average increase in the queue length of EF buffer. This prediction provides smooth bandwidth allocation to all the services by avoiding overbooking of resources for EF service and still providing guaranteed services for it. The performance is analyzed for various scenarios at high, medium and low traffic conditions. The results show that packet loss is minimized, end to end delay is minimized and jitter is reduced and therefore meet quality of service (QoS) requirement of a network.

Exact Phase Retrieval in Principal Shift-Invariant Spaces

We address the problem of phase retrieval from Fourier transform magnitude spectrum for continuous-time signals that lie in a shift-invariant space spanned by integer shifts of a generator kernel. The phase retrieval problem for such signals is formulated as one of reconstructing the combining coefficients in the shift-invariant basis expansion. We develop sufficient conditions on the coefficients and the bases to guarantee exact phase retrieval, by which we mean reconstruction up to a global phase factor. We present a new class of discrete-domain signals that are not necessarily minimum-phase, but allow for exact phase retrieval from their Fourier magnitude spectra. We also establish Hilbert transform relations between log-magnitude and phase spectra for this class of discrete signals. It turns out that the corresponding continuous-domain counterparts need not satisfy a Hilbert transform relation; notwithstanding, the continuous-domain signals can be reconstructed from their Fourier magnitude spectra. We validate the reconstruction guarantees through simulations for some important classes of signals such as bandlimited signals and piecewise-smooth signals. We also present an application of the proposed phase retrieval technique for artifact-free signal reconstruction in frequency-domain optical-coherence tomography (FDOCT).

IMAGE DENOISING USING OPTIMALLY WEIGHTED BILATERAL FILTERS: A SURE AND FAST APPROACH

The bilateral filter is known to be quite effective in denoising images corrupted with small dosages of additive Gaussian noise. The denoising performance of the filter, however, is known to degrade quickly with the increase in noise level. Several adaptations of the filter have been proposed in the literature to address this shortcoming, but often at a substantial computational overhead. In this paper, we report a simple pre-processing step that can substantially improve the denoising performance of the bilateral filter, at almost no additional cost. The modified filter is designed to be robust at large noise levels, and often tends to perform poorly below a certain noise threshold. To get the best of the original and the modified filter, we propose to combine them in a weighted fashion, where the weights are chosen to minimize (a surrogate of) the oracle mean-squared-error (MSE). The optimally-weighted filter is thus guaranteed to perform better than either of the component filters in terms of the MSE, at all noise levels. We also provide a fast algorithm for the weighted filtering. Visual and quantitative denoising results on standard test images are reported which demonstrate that the improvement over the original filter is significant both visually and in terms of PSNR. Moreover, the denoising performance of the optimally-weighted bilateral filter is competitive with the computation-intensive non-local means filter.

The convection during NaClO3 crystal growth observed by the phase shift interferometer

An optical diagnostic system consisting of the Mach-Zehnder interferometer with the phase shift device and an image processor has been developed for the study of the kinetics of the crystal growing process. The dissolution and crystallization process of NaClO3 crystal has been investigated. The concentration distributions around a growing and dissolving crystal have been obtained by using phase-shift of four-steps theory for the interpretation of the interferograms. The convection (a plume flow) has been visualized and analyzed in the process of the crystal growth. The experiment demonstrates that the buoyancy convection dominates the growth rate of the crystal growing face on the ground-based experiment.

Language model combination and adaptation using weighted finite state transducers

In speech recognition systems language model (LMs) are often constructed by training and combining multiple n-gram models. They can be either used to represent different genres or tasks found in diverse text sources, or capture stochastic properties of different linguistic symbol sequences, for example, syllables and words. Unsupervised LM adaptation may also be used to further improve robustness to varying styles or tasks. When using these techniques, extensive software changes are often required. In this paper an alternative and more general approach based on weighted finite state transducers (WFSTs) is investigated for LM combination and adaptation. As it is entirely based on well-defined WFST operations, minimum change to decoding tools is needed. A wide range of LM combination configurations can be flexibly supported. An efficient on-the-fly WFST decoding algorithm is also proposed. Significant error rate gains of 7.3% relative were obtained on a state-of-the-art broadcast audio recognition task using a history dependently adapted multi-level LM modelling both syllable and word sequences. ©2010 IEEE.

Pattern Recognition With Weighted Complex Networks

In this paper we introduce a weighted complex networks model to investigate and recognize structures of patterns. The regular treating in pattern recognition models is to describe each pattern as a high-dimensional vector which however is insufficient to express the structural information. Thus, a number of methods are developed to extract the structural information, such as different feature extraction algorithms used in pre-processing steps, or the local receptive fields in convolutional networks. In our model, each pattern is attributed to a weighted complex network, whose topology represents the structure of that pattern. Based upon the training samples, we get several prototypal complex networks which could stand for the general structural characteristics of patterns in different categories. We use these prototypal networks to recognize the unknown patterns. It is an attempt to use complex networks in pattern recognition, and our result shows the potential for real-world pattern recognition. A spatial parameter is introduced to get the optimal recognition accuracy, and it remains constant insensitive to the amount of training samples. We have discussed the interesting properties of the prototypal networks. An approximate linear relation is found between the strength and color of vertexes, in which we could compare the structural difference between each category. We have visualized these prototypal networks to show that their topology indeed represents the common characteristics of patterns. We have also shown that the asymmetric strength distribution in these prototypal networks brings high robustness for recognition. Our study may cast a light on understanding the mechanism of the biologic neuronal systems in object recognition as well.