Interactions of linear dicationic molecules with lipid A: structural requisites for optimal binding affinity

The structural determinants of the binding affinity of linear dicationic molecules toward lipid A have been examined with respect to the distance between the terminal cationic functions, the basicity, and the type of cationic moieties using a series of spermidine derivatives and pentamidine analogs by fluorescence spectroscopic methods, The presence of two terminal cationic groups corresponds to enhanced affinity, A distinct sigmoidal relationship between the intercationic distance and affinity was observed with a sharp increase at 11 Angstrom, levelling off at about 13 Angstrom. The basicity (pK) and nature of the cationic functions are poor correlates of binding potency, since molecules bearing primary amino, imidazolino, or guanido termini are equipotent, The interaction of pentamidine, a bisamidine drug, with lipid A, characterized in considerable detail employing the putative intermolecular excimerization of the drug, suggests a stoichiometry of 1:1 in the resultant complex, The binding is driven almost exclusively by electrostatic forces, and is dependent on the ionization states of both lipid A and the drug, Under conditions when lipid A is highly disaggregated, pentamidine binds specifically to bis-phosphoryl- but not to monophosphoryl-lipid A indicating that both phosphate groups of lipid A are necessary for electrostatic interactions by the terminal amidininium groups of the drug, Based on these data, a structural model is proposed for the pentamidine-lipid A complex, which may be of value in designing endotoxin antagonists from first principles.

Optimal Resource Partitioning in a Military Conflict based on Lanchester Attrition Models

This paper develops a model for military conflicts where the defending forces have to determine an optimal partitioning of available resources to counter attacks from an adversary in two different fronts. The Lanchester attrition model is used to develop the dynamical equations governing the variation in force strength. Three different allocation schemes - Time-Zero-Allocation (TZA), Allocate-Assess-Reallocate (AAR), and Continuous Constant Allocation (CCA) - are considered and the optimal solutions are obtained in each case. Numerical examples are given to support the analytical results.

Delay optimal control algorithm for a multiaccess fading channel with peak power constraint

We consider an optimal power and rate scheduling problem for a multiaccess fading wireless channel with the objective of minimising a weighted sum of mean packet transmission delay subject to a peak power constraint. The base station acts as a controller which, depending upon the buffer lengths and the channel state of each user, allocates transmission rate and power to individual users. We assume perfect channel state information at the transmitter and the receiver. We also assume a Markov model for the fading and packet arrival processes. The policy obtained represents a form of Indexability.

Cloning by genomic PCR and production of peanut agglutinin in Escherichia coli

Using the polymerase chain reaction, the coding sequence for peanut agglutinin (PNA) was cloned and expressed in Escherichia coli. Amplified PNA is identical to previously reported cDNA, suggesting the absence of any introns in PNA gene. Recombinant (re-) PNA forms inclusion bodies in E. coli. Production of PNA was confirmed by probing Western blots with polyclonal anti-PNA immunoglobulin G. Inclusion bodies were solubilized with 6 M guanidine-HCl and renatured by rapid dilution in the presence of metal ions. The renatured lectin was then purified by affinity chromatography. The re-lectin shows carbohydrate-binding properties similar to the natural PNA. This expression system provides a model for future mutagenesis studies of the carbohydrate-binding site and thus facilitates ongoing efforts to explore the molecular basis for the specificity of lectin-carbohydrate interaction.

Pareto-optimal solutions for multi-objective optimization of fed-batch bioreactors using nondominated sorting genetic algorithm

Many optimal control problems are characterized by their multiple performance measures that are often noncommensurable and competing with each other. The presence of multiple objectives in a problem usually give rise to a set of optimal solutions, largely known as Pareto-optimal solutions. Evolutionary algorithms have been recognized to be well suited for multi-objective optimization because of their capability to evolve a set of nondominated solutions distributed along the Pareto front. This has led to the development of many evolutionary multi-objective optimization algorithms among which Nondominated Sorting Genetic Algorithm (NSGA and its enhanced version NSGA-II) has been found effective in solving a wide variety of problems. Recently, we reported a genetic algorithm based technique for solving dynamic single-objective optimization problems, with single as well as multiple control variables, that appear in fed-batch bioreactor applications. The purpose of this study is to extend this methodology for solution of multi-objective optimal control problems under the framework of NSGA-II. The applicability of the technique is illustrated by solving two optimal control problems, taken from literature, which have usually been solved by several methods as single-objective dynamic optimization problems. (C) 2004 Elsevier Ltd. All rights reserved.

Optimal Resource Partitioning in a Military Conflict based on Lanchester Attrition Models

This paper develops a model for military conflicts where the defending forces have to determine an optimal partitioning of available resources to counter attacks from an adversary in two different fronts. The Lanchester attrition model is used to develop the dynamical equations governing the variation in force strength. Three different allocation schemes - Time-Zero-Allocation (TZA), Allocate-Assess-Reallocate (AAR), and Continuous Constant Allocation (CCA) - are considered and the optimal solutions are obtained in each case. Numerical examples are given to support the analytical results.

Optimal threshold policies for admission control in communication networks via discrete parameter stochastic approximation

The problem of admission control of packets in communication networks is studied in the continuous time queueing framework under different classes of service and delayed information feedback. We develop and use a variant of a simulation based two timescale simultaneous perturbation stochastic approximation (SPSA) algorithm for finding an optimal feedback policy within the class of threshold type policies. Even though SPSA has originally been designed for continuous parameter optimization, its variant for the discrete parameter case is seen to work well. We give a proof of the hypothesis needed to show convergence of the algorithm on our setting along with a sketch of the convergence analysis. Extensive numerical experiments with the algorithm are illustrated for different parameter specifications. In particular, we study the effect of feedback delays on the system performance.

Cloning,overexpression and purification of functionally active Saccharomyces cerevisiae Hop1 protein from scherichia coli

One of the major limitations to the application of high-resolution biophysical techniques such as X-crystallography and spectroscopic analyses to structure-function studies of Saccharomyces cerevisiae Hop1 protein has been the non-availability of sufficient quantities of functionally active pure protein. This has, indeed, been the case of many proteins, including yeast synaptonemal complex proteins. In this study, we have performed expression screening in Escherichia coli host strains, capable of high-level expression of soluble S. cerevisiae Hop1 protein. A new protocol has been developed for expression and purification of S. cerevisiae Hop1 protein, based on the presence of hexa-histidine tag and double-stranded DNA-Cellulose chromatography. Recombinant S. cerevisiae Hop1 protein was >98% pure and exhibited DNA-binding activity with high-affinity to the Holliday junction. The availability of the recombinant HOP1 expression vector and active Hop1 protein would facilitate structure-function investigations as well as the generation of appropriate truncated and site-directed mutant proteins, respectively. (C) 2010 Elsevier Inc. All rights reserved.

Power Optimal Network-on-Chip Interconnect Design

A large part of today's multi-core chips is interconnect. Increasing communication complexity has made essential new strategies for interconnects, such as Network on Chip. Power dissipation in interconnects has become a substantial part of the total power dissipation. Techniques to reduce interconnect power have thus become a necessity. In this paper, we present a design methodology that gives values of bus width for interconnect links, frequency of operation for routers, in Network on Chip scenario that satisfy required throughput and dissipate minimal switching power. We develop closed form analytical expressions for the power dissipation, with bus width and frequency as variables and then use Lagrange multiplier method to arrive at the optimal values. We present a 4 port router in 90 nm technology library as case study. The results obtained from analysis are discussed.

Optimal non-linear reinforcement schemes for stochastic automata

Two optimal non-linear reinforcement schemes—the Reward-Inaction and the Penalty-Inaction—for the two-state automaton functioning in a stationary random environment are considered. Very simple conditions of symmetry of the non-linear function figuring in the reinforcement scheme are shown to be necessary and sufficient for optimality. General expressions for the variance and rate of learning are derived. These schemes are compared with the already existing optimal linear schemes in the light of average variance and average rate of learning.

Cloning, expression, purification, crystallization and preliminary X-ray crystallographic study of the putative SAICAR synthetase (PH0239) from Pyrococcus horikoshii OT3

The study of proteins involved in de novo biosynthesis of purine nucleotides is central in the development of antibiotics and anticancer drugs. In view of this, a protein from the hyperthermophile Pyrococcus horikoshii OT3 was isolated, purified and crystallized using the microbatch method. Its primary structure was found to be similar to that of SAICAR synthetase, which catalyses the seventh step of de novo purine biosynthesis. A diffraction-quality crystal was obtained using Hampton Research Crystal Screen II condition No. 34, consisting of 0.05 M cadmium sulfate hydrate, 0.1 M HEPES buffer pH 7.5 and 1.0 M sodium acetate trihydrate, with 40%(v/v) 1,4-butanediol as an additive. The crystal belonged to space group P3(1), with unit-cell parameters a = b = 95.62, c = 149.13 angstrom. Assuming the presence of a hexamer in the asymmetric unit resulted in a Matthews coefficient (V-M) of 2.3 angstrom(3) Da(-1), corresponding to a solvent content of about 46%. A detailed study of this protein will yield insights into structural stability at high temperatures and should be highly relevant to the development of antibiotics and anticancer drugs targeting the biosynthesis of purine nucleotides.

Optimal design of multiproduct batch chemical plant using NSGA-II

The optimal design of a multiproduct batch chemical plant is formulated as a multiobjective optimization problem, and the resulting constrained mixed-integer nonlinear program (MINLP) is solved by the nondominated sorting genetic algorithm approach (NSGA-II). By putting bounds on the objective function values, the constrained MINLP problem can be solved efficiently by NSGA-II to generate a set of feasible nondominated solutions in the range desired by the decision-maker in a single run of the algorithm. The evolution of the entire set of nondominated solutions helps the decision-maker to make a better choice of the appropriate design from among several alternatives. The large set of solutions also provides a rich source of excellent initial guesses for solution of the same problem by alternative approaches to achieve any specific target for the objective functions

Optimal Risk Adoption: A Real Options Approach

This study develops a real options approach for analyzing the optimal risk adoption policy in an environment where the adoption means a switch from one stochastic flow representation into another. We establish that increased volatility needs not decelerate investment, as predicted by the standard literature on real options, once the underlying volatility of the state is made endogenous. We prove that for a decision maker with a convex (concave) objective function, increased post-adoption volatility increases (decreases) the expected cumulative present value of the post-adoption profit flow, which consequently decreases (increases) the option value of waiting and, therefore, accelerates (decelerates) current investment.

Bank Run Risk and Optimal Reserves

We characterize the optimal reserves, and the generated probability of a bank run, as a function of the penalty imposed by the central bank, the probability of depositors’ liquidity needs, and the return on outside investment opportunities.