The structures of bacteriorhodopsin with different retinal-Schiff base orientations--computer modeling and energy minimization studies

Bacteriorhodopsin has been the subject of intense study in order to understand its photochemical function. The recent atomic model proposed by Henderson and coworkers based on electron cryo-microscopic studies has helped in understanding many of the structural and functional aspects of bacteriorhodopsin. However, the accuracy of the positions of the side chains is not very high since the model is based on low-resolution data. In this study, we have minimized the energy of this structure of bacteriorhodopsin and analyzed various types of interactions such as - intrahelical and interhelical hydrogen bonds and retinal environment. In order to understand the photochemical action, it is necessary to obtain information on the structures adopted at the intermediate states. In this direction, we have generated some intermediate structures taking into account certain experimental data, by computer modeling studies. Various isomers of retinal with 13-cis and/or 15-cis conformations and all possible staggered orientations of Lys-216 side chain were generated. The resultant structures were examined for the distance between Lys-216-schiff base nitrogen and the carboxylate oxygen atoms of Asp-96 - a residue which is known to reprotonate the schiff base at later stages of photocycle. Some of the structures were selected on the basis of suitable retinal orientation and the stability of these structures were tested by energy minimization studies. Further, the minimized structures are analyzed for the hydrogen bond interactions and retinal environment and the results are compared with those of the minimized rest state structure. The importance of functional groups in stabilizing the structure of bacteriorhodopsin and in participating dynamically during the photocycle have been discussed.

Suboptimal Midcourse Guidance of Interceptors for High-Speed Targets with Alignment Angle Constraint

Using the recently developed computationally efficient model predictive static programming and a closely related model predictive spread control concept, two nonlinear suboptimal midcourse guidance laws are presented in this paper for interceptors engaging against incoming high-speed ballistic missiles. The guidance laws are primarily based on nonlinear optimal control theory, and hence imbed effective trajectory optimization concepts into the guidance laws. Apart from being energy efficient by minimizing the control usage throughout the trajectory (minimum control usage leads to minimum turning, and hence leads to minimum induced drag), both of these laws enforce desired alignment constraints in both elevation and azimuth in a hard-constraint sense. This good alignment during midcourse is expected to enhance the effectiveness of the terminal guidance substantially. Both point mass as well as six-degree-of-freedom simulation results (with a realistic inner-loop autopilot based on dynamic inversion) are presented in this paper, which clearly shows the effectiveness of the proposed guidance laws. It has also been observed that, even with different perturbations of missile parameters, the performance of guidance is satisfactory. A comparison study, with the vector explicit guidance scheme proposed earlier in the literature, also shows that the newly proposed model-predictive-static-programming-based and model-predictive-spread-control-based guidance schemes lead to lesser lateral acceleration demand and lesser velocity loss during engagement.

Analysis, Design, Modeling, and Implementation of an Active Clamp HF Link Converter

This paper deals with the system oriented analysis, design, modeling, and implementation of active clamp HF link three phase converter. The main advantage of the topology is reduced size, weight, and cost of the isolation transformer. However, violation of basic power conversion rules due to presence of the leakage inductance in the HF transformer causes over voltage stresses across the cycloconverter devices. It makes use of the snubber circuit necessary in such topologies. The conventional RCD snubbers are dissipative in nature and hence inefficient. The efficiency of the system is greatly improved by using regenerative snubber or active clamp circuit. It consists of an active switching device with an anti-parallel diode and one capacitor to absorb the energy stored in the leakage inductance of the isolation transformer and to regenerate the same without affecting circuit performance. The turn on instant and duration of the active device are selected such that it requires simple commutation requirements. The time domain expressions for circuit dynamics, design criteria of the snubber capacitor with two conflicting constrains (over voltage stress across the devices and the resonating current duration), the simulation results based on generalized circuit model and the experimental results based on laboratory prototype are presented.

Micromechanical modeling of granular materials: effect of confining pressure on mechanical behavior

This paper reports the effect of confining pressure on the mechanical behavior of granular materials from micromechanical considerations starting from the grain scale level, based on the results of numerically simulated tests on disc assemblages using discrete element modeling (DEM). The two macro parameters which are influenced by the increase in confining pressure are stiffness (increases) and volume change (decreases). The lateral strain coefficient (Poisson's ratio) at the beginning of the test is more or less constant. The angle of internal friction slightly decreases with increase in confining pressure. The numerical results of disc assemblages indicate very clearly a non-linear Mohr-Coulomb failure envelope with increase in confining pressure. The increase in average coordination number and accompanying decrease of fabric anisotropy reduce the shear strength at higher confining pressures. Micromechanical explanations of the macroscopic behavior are presented in terms of the force and fabric anisotropy coefficients. (C) 1999 Elsevier Science Ltd. AII rights reserved.

Stochastic dynamics modeling of the protein sequence length distribution in genomes: implications for microbial evolution

In this paper, we report an analysis of the protein sequence length distribution for 13 bacteria, four archaea and one eukaryote whose genomes have been completely sequenced, The frequency distribution of protein sequence length for all the 18 organisms are remarkably similar, independent of genome size and can be described in terms of a lognormal probability distribution function. A simple stochastic model based on multiplicative processes has been proposed to explain the sequence length distribution. The stochastic model supports the random-origin hypothesis of protein sequences in genomes. Distributions of large proteins deviate from the overall lognormal behavior. Their cumulative distribution follows a power-law analogous to Pareto's law used to describe the income distribution of the wealthy. The protein sequence length distribution in genomes of organisms has important implications for microbial evolution and applications. (C) 1999 Elsevier Science B.V. All rights reserved.

Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization

In this paper, power management algorithms for energy harvesting sensors (EHS) that operate purely based on energy harvested from the environment are proposed. To maintain energy neutrality, EHS nodes schedule their utilization of the harvested power so as to save/draw energy into/from an inefficient battery during peak/low energy harvesting periods, respectively. Under this constraint, one of the key system design goals is to transmit as much data as possible given the energy harvesting profile. For implementational simplicity, it is assumed that the EHS transmits at a constant data rate with power control, when the channel is sufficiently good. By converting the data rate maximization problem into a convex optimization problem, the optimal load scheduling (power management) algorithm that maximizes the average data rate subject to energy neutrality is derived. Also, the energy storage requirements on the battery for implementing the proposed algorithm are calculated. Further, robust schemes that account for the insufficiency of battery storage capacity, or errors in the prediction of the harvested power are proposed. The superior performance of the proposed algorithms over conventional scheduling schemes are demonstrated through computations using numerical data from solar energy harvesting databases.

Modeling of concrete cracking-A hybrid technique of using displacement discontinuity element method and direct boundary element method

This paper presents a new approach by making use of a hybrid method of using the displacement discontinuity element method and direct boundary element method to model concrete cracking by incorporating fictitious crack model. Fracture mechanics approach is followed using the Hillerborg's fictitious crack model. A boundary element based substructure method and a hybrid technique of using displacement discontinuity element method and direct boundary element method are compared in this paper. In order to represent the process zone ahead of the crack, closing forces are assumed to act in such a way that they obey a linear normal stress-crack opening displacement law. Plain concrete beams with and without initial crack under three-point loading were analyzed by both the methods. The numerical results obtained were shown to agree well with the results from existing finite element method. The model is capable of reproducing the whole range of load-deflection response including strain-softening and snap-back behavior as illustrated in the numerical examples. (C) 2011 Elsevier Ltd. All rights reserved.

Large eddy simulation of a premixed flame with approximate deconvolution modeling

Approximate deconvolution modeling is a very recent approach to large eddy simulation of turbulent flows. It has been applied to compressible flows with success. Here, a premixed flame which forms in the wake of a flameholder has been selected to examine the subgrid-scale modeling of reaction rate by this new method because a previous plane two-dimensional simulation of this wake flame, using a wrinkling function and artificial flame thickening, had revealed discrepancies when compared with experiment. The present simulation is of the temporal evolution of a round wakelike flow at two Reynolds numbers, Re = 2000 and 10,000, based on wake defect velocity and wake diameter. A Fourier-spectral code has been used. The reaction is single-step and irreversible, and the rate follows an Arrhenius law. The reference simulation at the lower Reynolds number is fully resolved. At Re = 10,000, subgrid-scale contributions are significant. It was found that subgrid-scale modeling in the present simulation agrees more closely with unresolved subgrid-scale effects observed in experiment. Specifically, the highest contributions appeared in thin folded regions created by vortex convection. The wrinkling function approach had not selected subgrid-scale effects in these regions.

Numerical modeling of heat and mass transfer in laser surface alloying: Non-equilibrium solidification effects

A transient macroscopic model is developed for studying heat and mass transfer in a single-pass laser surface alloying process, with particular emphasis on non-equilibrium solidification considerations. The solution for species concentration distribution requires suitable treatment of non-equilibrium mass transfer conditions. In this context, microscopic features pertaining to non-equilibrium effects on account of solutal undercooling are incorporated through the formulation of a modified partition-coefficient. The effective partition-coefficient is numerically modeled by Means of a number of macroscopically observable parameters related to the solidifying domain. The numerical model is so developed that the modifications on account of non-equilibrium solidification considerations can be conveniently implemented in existing numerical codes based on equilibrium solidification considerations.

Efficient statistical modeling for the compression of tree structured intermediate code

We propose a scheme for the compression of tree structured intermediate code consisting of a sequence of trees specified by a regular tree grammar. The scheme is based on arithmetic coding, and the model that works in conjunction with the coder is automatically generated from the syntactical specification of the tree language. Experiments on data sets consisting of intermediate code trees yield compression ratios ranging from 2.5 to 8, for file sizes ranging from 167 bytes to 1 megabyte.

Modeling of nonreacting and reacting turbulent spray jets using a fully stochastic separated flow approach

Numerical modeling of several turbulent nonreacting and reacting spray jets is carried out using a fully stochastic separated flow (FSSF) approach. As is widely used, the carrier-phase is considered in an Eulerian framework, while the dispersed phase is tracked in a Lagrangian framework following the stochastic separated flow (SSF) model. Various interactions between the two phases are taken into account by means of two-way coupling. Spray evaporation is described using a thermal model with an infinite conductivity in the liquid phase. The gas-phase turbulence terms are closed using the k-epsilon model. A novel mixture fraction based approach is used to stochastically model the fluctuating temperature and composition in the gas phase and these are then used to refine the estimates of the heat and mass transfer rates between the droplets and the surrounding gas-phase. In classical SSF (CSSF) methods, stochastic fluctuations of only the gas-phase velocity are modeled. Successful implementation of the FSSF approach to turbulent nonreacting and reacting spray jets is demonstrated. Results are compared against experimental measurements as well as with predictions using the CSSF approach for both nonreacting and reacting spray jets. The FSSF approach shows little difference from the CSSF predictions for nonreacting spray jets but differences are significant for reacting spray jets. In general, the FSSF approach gives good predictions of the flame length and structure but further improvements in modeling may be needed to improve the accuracy of some details of the Predictions. (C) 2011 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Subspace Based Speech Enhancement Using Gaussian Mixture Model

Traditional subspace based speech enhancement (SSE)methods use linear minimum mean square error (LMMSE) estimation that is optimal if the Karhunen Loeve transform (KLT) coefficients of speech and noise are Gaussian distributed. In this paper, we investigate the use of Gaussian mixture (GM) density for modeling the non-Gaussian statistics of the clean speech KLT coefficients. Using Gaussian mixture model (GMM), the optimum minimum mean square error (MMSE) estimator is found to be nonlinear and the traditional LMMSE estimator is shown to be a special case. Experimental results show that the proposed method provides better enhancement performance than the traditional subspace based methods.Index Terms: Subspace based speech enhancement, Gaussian mixture density, MMSE estimation.

Comparison of AM-FM Based Features For Robust Speech Recognition

Effective feature extraction for robust speech recognition is a widely addressed topic and currently there is much effort to invoke non-stationary signal models instead of quasi-stationary signal models leading to standard features such as LPC or MFCC. Joint amplitude modulation and frequency modulation (AM-FM) is a classical non-parametric approach to non-stationary signal modeling and recently new feature sets for automatic speech recognition (ASR) have been derived based on a multi-band AM-FM representation of the signal. We consider several of these representations and compare their performances for robust speech recognition in noise, using the AURORA-2 database. We show that FEPSTRUM representation proposed is more effective than others. We also propose an improvement to FEPSTRUM based on the Teager energy operator (TEO) and show that it can selectively outperform even FEPSTRUM

Voltage and Temperature Scalable Standard Cell Leakage Models Based on Stacks for Statistical Leakage Characterization

With extensive use of dynamic voltage scaling (DVS) there is increasing need for voltage scalable models. Similarly, leakage being very sensitive to temperature motivates the need for a temperature scalable model as well. We characterize standard cell libraries for statistical leakage analysis based on models for transistor stacks. Modeling stacks has the advantage of using a single model across many gates there by reducing the number of models that need to be characterized. Our experiments on 15 different gates show that we needed only 23 models to predict the leakage across 126 input vector combinations. We investigate the use of neural networks for the combined PVT model, for the stacks, which can capture the effect of inter die, intra gate variations, supply voltage(0.6-1.2 V) and temperature (0 - 100degC) on leakage. Results show that neural network based stack models can predict the PDF of leakage current across supply voltage and temperature accurately with the average error in mean being less than 2% and that in standard deviation being less than 5% across a range of voltage, temperature.

Unified Vdd Vth Optimization Based DVFM Controller for a Logic Block

In this paper analytical expressions for optimal Vdd and Vth to minimize energy for a given speed constraint are derived. These expressions are based on the EKV model for transistors and are valid in both strong inversion and sub threshold regions. The effect of gate leakage on the optimal Vdd and Vth is analyzed. A new gradient based algorithm for controlling Vdd and Vth based on delay and power monitoring results is proposed. A Vdd-Vth controller which uses the algorithm to dynamically control the supply and threshold voltage of a representative logic block (sum of absolute difference computation of an MPEG decoder) is designed. Simulation results using 65 nm predictive technology models are given.