Universal behaviour in erosive burning of solid propellants

This paper considers the extensive data and correlations on the erosive burning of solid propellants. A relatively simple nondimensional relationship between the ratio of the actual to nonerosive burn rate (eta) and a quantity g, which is the product of g(0)-the ratio of free stream mass flux to the mass flux from the surface for nonerosive condition-and Re-0(m), where Re-0 is the Reynolds number based on the nonerosive mass flux of the propellant and port diameter, is shown to correlate most data within the accuracies of the experiments with m = -0.125. This shows the above relationship to account for the effects of pressure, aluminum, even up to a proportion of 17%, burn rate catalysts, and motor size. It is concluded that the suggested correlation between eta and g may be adopted universally for most practical propellants. (C) 1997 by The Combustion Institute.

On approximately universal schemes for two-hop networks

Full-duplex and half-duplex two-hop networks are considered. Explicit coding schemes which are approximately universal over a class of fading distributions are identified, for the case when the network has either one or two relays.

Insights into the Regulatory Characteristics of the Mycobacterial Dephosphocoenzyme A Kinase: Implications for the Universal CoA Biosynthesis Pathway

Being vastly different from the human counterpart, we suggest that the last enzyme of the Mycobacterium tuberculosis Coenzyme A biosynthetic pathway, dephosphocoenzyme A kinase (CoaE) could be a good anti-tubercular target. Here we describe detailed investigations into the regulatory features of the enzyme, affected via two mechanisms. Enzymatic activity is regulated by CTP which strongly binds the enzyme at a site overlapping that of the leading substrate, dephosphocoenzyme A (DCoA), thereby obscuring the binding site and limiting catalysis. The organism has evolved a second layer of regulation by employing a dynamic equilibrium between the trimeric and monomeric forms of CoaE as a means of regulating the effective concentration of active enzyme. We show that the monomer is the active form of the enzyme and the interplay between the regulator, CTP and the substrate, DCoA, affects enzymatic activity. Detailed kinetic data have been corroborated by size exclusion chromatography, dynamic light scattering, glutaraldehyde crosslinking, limited proteolysis and fluorescence investigations on the enzyme all of which corroborate the effects of the ligands on the enzyme oligomeric status and activity. Cysteine mutagenesis and the effects of reducing agents on mycobacterial CoaE oligomerization further validate that the latter is not cysteine-mediated or reduction-sensitive. These studies thus shed light on the novel regulatory features employed to regulate metabolite flow through the last step of a critical biosynthetic pathway by keeping the latter catalytically dormant till the need arises, the transition to the active form affected by a delicate crosstalk between an essential cellular metabolite (CTP) and the precursor to the pathway end-product (DCoA).

Effect of two-level systems on the spectral density of universal conductance fluctuations in doped Si

We have studied the power spectral density [S(f) = gamma/f(alpha)] of universal conductance fluctuations (UCF's) in heavily doped single crystals of Si, when the scatterers themselves act as the primary source of dephasing. We observed that the scatterers, with internal dynamics like two-level-systems, produce a significant, temperature-dependent reduction in the spectral slope alpha when T less than or similar to 10 K, as compared to the bare 1/f (alphaapproximate to1) spectrum at higher temperatures. It is further shown that an upper cutoff frequency (f(m)) in the UCF spectrum is necessary in order to restrict the magnitude of conductance fluctuations, [(deltaG(phi))(2)], per phase coherent region (L-phi(3)) to [(deltaGphi)(2)](1/2) less than or similar to e(2)/h. We find that f(m) approximate to tau(D)(-1), where tau(D) = L-2/D, is the time scale of the diffusive motion of the electron along the active length (L) of the sample (D is the electron diffusivity).

Hydrogen-bond dynamics near a micellar surface: Origin of the universal slow relaxation at complex aqueous interfaces

The dynamics of hydrogen bonds among water molecules themselves and with the polar head groups (PHG) at a micellar surface have been investigated by long molecular dynamics simulations. The lifetime of the hydrogen bond between a PHG and a water molecule is found to be much longer than that between any two water molecules, and is likely to be a general feature of hydrophilic surfaces of organized assemblies. Analyses of individual water trajectories suggest that water molecules can remain bound to the micellar surface for more than 100 ps. The activation energy for such a transition from the bound to a free state for the water molecules is estimated to be about 3.5 kcal/mol.

Hybrid LCI/VSI Power Circuit-A Universal High-Power Converter Solution for Wound Field Synchronous Motor Drives

Load commutated inverter (LCI)-fed wound field synchronous motor drives are used for medium-voltage high-power drive applications. This drive suffers from drawbacks such as complex starting procedure, sixth harmonic torque pulsations, quasi square wave motor current, notches in the terminal voltages, etc. In this paper, a hybrid converter circuit, consisting of an LCI and a voltage source inverter (VSI), is proposed, which can be a universal high-power converter solution for wound field synchronous motor drives. The proposed circuit, with the addition of a current-controlled VSI, overcomes nearly all of the shortcomings present in the conventional LCI-based system besides providing many additional advantages. In the proposed drive, the motor voltage and current are always sinusoidal even with the LCI switching at the fundamental frequency. The performance of the drive is demonstrated with detailed experimental waveforms from a 15.8-hp salient pole wound field synchronous machine. Finally, a brief description of the control scheme used for the proposed circuit is given.

LZW Based Distance Measures for Spoken Language Identification

We present a new approach to spoken language modeling for language identification (LID) using the Lempel-Ziv-Welch (LZW) algorithm. The LZW technique is applicable to any kind of tokenization of the speech signal. Because of the efficiency of LZW algorithm to obtain variable length symbol strings in the training data, the LZW codebook captures the essentials of a language effectively. We develop two new deterministic measures for LID based on the LZW algorithm namely: (i) Compression ratio score (LZW-CR) and (ii) weighted discriminant score (LZW-WDS). To assess these measures, we consider error-free tokenization of speech as well as artificially induced noise in the tokenization. It is shown that for a 6 language LID task of OGI-TS database with clean tokenization, the new model (LZW-WDS) performs slightly better than the conventional bigram model. For noisy tokenization, which is the more realistic case, LZW-WDS significantly outperforms the bigram technique

Computational Biology and Language

Current scientific research is characterized by increasing specialization, accumulating knowledge at a high speed due to parallel advances in a multitude of sub-disciplines. Recent estimates suggest that human knowledge doubles every two to three years – and with the advances in information and communication technologies, this wide body of scientific knowledge is available to anyone, anywhere, anytime. This may also be referred to as ambient intelligence – an environment characterized by plentiful and available knowledge. The bottleneck in utilizing this knowledge for specific applications is not accessing but assimilating the information and transforming it to suit the needs for a specific application. The increasingly specialized areas of scientific research often have the common goal of converting data into insight allowing the identification of solutions to scientific problems. Due to this common goal, there are strong parallels between different areas of applications that can be exploited and used to cross-fertilize different disciplines. For example, the same fundamental statistical methods are used extensively in speech and language processing, in materials science applications, in visual processing and in biomedicine. Each sub-discipline has found its own specialized methodologies making these statistical methods successful to the given application. The unification of specialized areas is possible because many different problems can share strong analogies, making the theories developed for one problem applicable to other areas of research. It is the goal of this paper to demonstrate the utility of merging two disparate areas of applications to advance scientific research. The merging process requires cross-disciplinary collaboration to allow maximal exploitation of advances in one sub-discipline for that of another. We will demonstrate this general concept with the specific example of merging language technologies and computational biology.

Language identification using parallel sub-word recognition

Parallel sub-word recognition (PSWR) is a new model that has been proposed for language identification (LID) which does not need elaborate phonetic labeling of the speech data in a foreign language. The new approach performs a front-end tokenization in terms of sub-word units which are designed by automatic segmentation, segment clustering and segment HMM modeling. We develop PSWR based LID in a framework similar to the parallel phone recognition (PPR) approach in the literature. This includes a front-end tokenizer and a back-end language model, for each language to be identified. Considering various combinations of the statistical evaluation scores, it is found that PSWR can perform as well as PPR, even with broad acoustic sub-word tokenization, thus making it an efficient alternative to the PPR system.

Singlet-state creation and universal quantum computation in NMR using a genetic algorithm

The experimental implementation of a quantum algorithm requires the decomposition of unitary operators. Here we treat unitary-operator decomposition as an optimization problem, and use a genetic algorithm-a global-optimization method inspired by nature's evolutionary process-for operator decomposition. We apply this method to NMR quantum information processing, and find a probabilistic way of performing universal quantum computation using global hard pulses. We also demonstrate the efficient creation of the singlet state (a special type of Bell state) directly from thermal equilibrium, using an optimum sequence of pulses. © 2012 American Physical Society.

Singlet-state creation and universal quantum computation in NMR using a genetic algorithm

The experimental implementation of a quantum algorithm requires the decomposition of unitary operators. Here we treat unitary-operator decomposition as an optimization problem, and use a genetic algorithm-a global-optimization method inspired by nature's evolutionary process-for operator decomposition. We apply this method to NMR quantum information processing, and find a probabilistic way of performing universal quantum computation using global hard pulses. We also demonstrate the efficient creation of the singlet state (a special type of Bell state) directly from thermal equilibrium, using an optimum sequence of pulses.

Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences

Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.

Direct Observation of Valley Hybridization and Universal Symmetry of Graphene with Mesoscopic Conductance Fluctuations

In graphene, the valleys represent spinlike quantities and can act as a physical resource in valley-based electronics to produce novel quantum computation schemes. Here we demonstrate a direct route to tune and read the valley quantum states of disordered graphene by measuring the mesoscopic conductance fluctuations. We show that the conductance fluctuations in graphene at low temperatures are reduced by a factor of 4 when valley triplet states are gapped in the presence of short-range potential scatterers at high carrier densities. We also show that this implies a gate tunable universal symmetry class that outlines a fundamental feature arising from graphene's unique crystal structure.