An asymmetric cascaded H-Bridge inverters for generating 12-sided polygonal space vector diagrams for Motor drives

A new topology of asymmetric cascaded H-Bridge inverter is presented in this paper It consists of two cascaded H-bridge cells per phase. They are fed from isolated dc sources having a dc bus ratio of 1:0.366. Out of many space vectors possible from this circuit, only those are chosen that lie on 12-sided polygons. Thus, the overall space vector diagram produced by this circuit consists of multiple numbers of 12-sided polygons. With a proper PWM timing calculations based on these selected space vectors, it is possible to eliminate all the 6n +/- 1, (n = odd) harmonics from the phase voltage under all operating conditions. The switching frequency of individual H-Bridge cells is also substantially low. Extensive experimental results have been presented in this paper to validate the proposed concept.

The carboxy terminal WD domain of the pre-mRNA splicing factor Prp17p is critical for function

In Saccharomyces cerevisiae, Prp17p is required for the efficient completion of the second step of pre-mRNA splicing. The function and interacting factors for this protein have not been elucidated. We have performed a mutational analysis of yPrp17p to identify protein domains critical for function. A series of deletions were made throughout the region spanning the N-terminal 158 amino acids of the protein, which do not contain any identified structural motifs. The C-terminal portion (amino acids 160–455) contains a WD domain containing seven WD repeats. We determined that a minimal functional Prp17p consists of the WD domain and 40 amino acids N-terminal to it. We generated a three-dimensional model of the WD repeats in Prp17p based on the crystal structure of the [beta]-transducin WD domain. This model was used to identify potentially important amino acids for in vivo functional characterization. Through analysis of mutations in four different loops of Prp17p that lie between [beta] strands in the WD repeats, we have identified four amino acids, 235TETG238, that are critical for function. These amino acids are predicted to be surface exposed and may be involved in interactions that are important for splicing. Temperature-sensitive prp17 alleles with mutations of these four amino acids are defective for the second step of splicing and are synthetically lethal with a U5 snRNA loop I mutation, which is also required for the second step of splicing. These data reinforce the functional significance of this region within the WD domain of Prp17p in the second step of splicing.

Filtered density function for large eddy simulation of turbulent reacting flows

A methodology termed the “filtered density function” (FDF) is developed and implemented for large eddy simulation (LES) of chemically reacting turbulent flows. In this methodology, the effects of the unresolved scalar fluctuations are taken into account by considering the probability density function (PDF) of subgrid scale (SGS) scalar quantities. A transport equation is derived for the FDF in which the effect of chemical reactions appears in a closed form. The influences of scalar mixing and convection within the subgrid are modeled. The FDF transport equation is solved numerically via a Lagrangian Monte Carlo scheme in which the solutions of the equivalent stochastic differential equations (SDEs) are obtained. These solutions preserve the Itô-Gikhman nature of the SDEs. The consistency of the FDF approach, the convergence of its Monte Carlo solution and the performance of the closures employed in the FDF transport equation are assessed by comparisons with results obtained by direct numerical simulation (DNS) and by conventional LES procedures in which the first two SGS scalar moments are obtained by a finite difference method (LES-FD). These comparative assessments are conducted by implementations of all three schemes (FDF, DNS and LES-FD) in a temporally developing mixing layer and a spatially developing planar jet under both non-reacting and reacting conditions. In non-reacting flows, the Monte Carlo solution of the FDF yields results similar to those via LES-FD. The advantage of the FDF is demonstrated by its use in reacting flows. In the absence of a closure for the SGS scalar fluctuations, the LES-FD results are significantly different from those based on DNS. The FDF results show a much closer agreement with filtered DNS results. © 1998 American Institute of Physics.

Cryptic AUG is important for 48S ribosomal assembly during internal initiation of translation of coxsackievirus B3 RNA

We have investigated the possible role of a conserved cis-acting element, the cryptic AUG, present in the 5' UTR of coxsackievirus B3 (CVB3) RNA. CVB3 5' UTR contains multiple AUG codons upstream of the initiator AUG, which are not used for the initiation of translation. The 48S ribosomal assembly takes place upstream of the cryptic AUG. We show here that mutation in the cryptic AUG results in reduced efficiency of translation mediated by the CVB3 IRES; mutation also reduces the interaction of mutant IRES with a well characterized IRES trans-acting factor, the human La protein. Furthermore, partial silencing of the La gene showed a decrease in IRES activity in the case of both the wild-type and mutant. We have demonstrated here that the interaction of the 48S ribosomal complex with mutant RNA was weaker compared with wild-type RNA by ribosome assembly analysis. We have also investigated by chemical and enzymic modifications the possible alteration in secondary structure in the mutant RNA. Results suggest that the secondary structure of mutant RNA was only marginally altered. Additionally, we have demonstrated by generating compensatory and non-specific mutations the specific function of the cryptic AUG in internal initiation. Results suggest that the effect of the cryptic AUG is specific and translation could not be rescued. However, a possibility of tertiary interaction of the cryptic AUG with other cis-acting elements cannot be ruled out. Taken together, it appears that the integrity of the cryptic AUG is important for efficient translation initiation by the CVB3 IRES RNA.

Effective thermal conductivity of a heat generating rod bundle dissipating heat by natural convection and radiation

A numerical study of conjugate natural convection and surface radiation in a horizontal hexagonal sheath housing 19 solid heat generating rods with cladding and argon as the fill gas, is performed. The natural convection in the sheath is driven by the volumetric heat generation in the solid rods. The problem is solved using the FLUENT CFD code. A correlation is obtained to predict the maximum temperature in the rod bundle for different pitch-to-diameter ratios and heat generating rates. The effective thermal conductivity is related to the heat generation rate, maximum temperature and the sheath temperature. Results are presented for the dimensionless maximum temperature, Rayleigh number and the contribution of radiation with changing emissivity, total wattage and the pitch-to-diameter ratio. In the simulation of a larger system that contains a rod bundle, the effective thermal conductivity facilitates simplified modelling of the rod bundle by treating it as a solid of effective thermal conductivity. The parametric studies revealed that the contribution of radiation can be 38-65% of the total heat generation, for the parameter ranges chosen. Data for critical Rayleigh number above which natural convection comes into effect is also presented. (C) 2011 Elsevier B.V. All rights reserved.

Chimeras of Escherichia coli and Mycobacterium tuberculosis Single-Stranded DNA Binding Proteins: Characterization and Function in Escherichia coli

Single stranded DNA binding proteins (SSBs) are vital for the survival of organisms. Studies on SSBs from the prototype, Escherichia coli (EcoSSB) and, an important human pathogen, Mycobacterium tuberculosis (MtuSSB) had shown that despite significant variations in their quaternary structures, the DNA binding and oligomerization properties of the two are similar. Here, we used the X-ray crystal structure data of the two SSBs to design a series of chimeric proteins (m beta 1, m beta 1'beta 2, m beta 1-beta 5, m beta 1-beta 6 and m beta 4-beta 5) by transplanting beta 1, beta 1'beta 2, beta 1-beta 5, beta 1-beta 6 and beta 4-beta 5 regions, respectively of the N-terminal (DNA binding) domain of MtuSSB for the corresponding sequences in EcoSSB. In addition, m beta 1'beta 2(ESWR) SSB was generated by mutating the MtuSSB specific `PRIY' sequence in the beta 2 strand of m beta 1'beta 2 SSB to EcoSSB specific `ESWR' sequence. Biochemical characterization revealed that except for m beta 1 SSB, all chimeras and a control construct lacking the C-terminal domain (Delta C SSB) bound DNA in modes corresponding to limited and unlimited modes of binding. However, the DNA on MtuSSB may follow a different path than the EcoSSB. Structural probing by protease digestion revealed that unlike other SSBs used, m beta 1 SSB was also hypersensitive to chymotrypsin treatment. Further, to check for their biological activities, we developed a sensitive assay, and observed that m beta 1-beta 6, MtuSSB, m beta 1'beta 2 and m beta 1-beta 5 SSBs complemented E. coli Delta ssb in a dose dependent manner. Complementation by the m beta 1-beta 5 SSB was poor. In contrast, m beta 1'beta 2(ESWR) SSB complemented E. coli as well as EcoSSB. The inefficiently functioning SSBs resulted in an elongated cell/filamentation phenotype of E. coli. Taken together, our observations suggest that specific interactions within the DNA binding domain of the homotetrameric SSBs are crucial for their biological function.

Distributed Function Computation over Fields and Rings via Linear Compression of Sources

The setting considered in this paper is one of distributed function computation. More specifically, there is a collection of N sources possessing correlated information and a destination that would like to acquire a specific linear combination of the N sources. We address both the case when the common alphabet of the sources is a finite field and the case when it is a finite, commutative principal ideal ring with identity. The goal is to minimize the total amount of information needed to be transmitted by the N sources while enabling reliable recovery at the destination of the linear combination sought. One means of achieving this goal is for each of the sources to compress all the information it possesses and transmit this to the receiver. The Slepian-Wolf theorem of information theory governs the minimum rate at which each source must transmit while enabling all data to be reliably recovered at the receiver. However, recovering all the data at the destination is often wasteful of resources since the destination is only interested in computing a specific linear combination. An alternative explored here is one in which each source is compressed using a common linear mapping and then transmitted to the destination which then proceeds to use linearity to directly recover the needed linear combination. The article is part review and presents in part, new results. The portion of the paper that deals with finite fields is previously known material, while that dealing with rings is mostly new.Attempting to find the best linear map that will enable function computation forces us to consider the linear compression of source. While in the finite field case, it is known that a source can be linearly compressed down to its entropy, it turns out that the same does not hold in the case of rings. An explanation for this curious interplay between algebra and information theory is also provided in this paper.

Abstract Characteristic Function

The characteristic function for a contraction is a classical complete unitary invariant devised by Sz.-Nagy and Foias. Just as a contraction is related to the Szego kernel k(S)(z, w) = ( 1 - z(w)over bar)- 1 for |z|, |w| < 1, by means of (1/k(S))( T, T *) = 0, we consider an arbitrary open connected domain Omega in C(n), a kernel k on Omega so that 1/k is a polynomial and a tuple T = (T(1), T(2), ... , T(n)) of commuting bounded operators on a complex separable Hilbert spaceHsuch that (1/k)( T, T *) >= 0. Under some standard assumptions on k, it turns out that whether a characteristic function can be associated with T or not depends not only on T, but also on the kernel k. We give a necessary and sufficient condition. When this condition is satisfied, a functional model can be constructed. Moreover, the characteristic function then is a complete unitary invariant for a suitable class of tuples T.

Structure-function relationship in serine hydroxymethyltransferase

Serine hydroxymethyltransferase (SHMT), a pyridoxal-5V-phosphate (PLP)-dependent enzyme catalyzes thetetrahydrofolate (H4-folate)- dependent retro-aldol cleavage of serine to form 5,10-methylene H4-folate and glycine. The structure–function relationship of SHMT wasstudied in our laboratory initially by mutation of residues that are conserved in all SHMTs and later by structure-based mutagenesis of residues located in the active site. The analysis of mutants showed that K71, Y72, R80, D89, W110, S202, C203, H304, H306 and H356 residues are involved in maintenance of the oligomeric structure. The mutation of D227, a residue involved in charge relay system, led to the formation of inactive dimers, indicating that this residue has a role in maintaining the tetrameric structure and catalysis. E74, a residue appropriately positioned in the structure of the enzyme to carry out proton abstraction, was shown by characterization of E74Q and E74K mutants to be involved in conversion of the enzyme from an ‘open’ to ‘closed’ conformation rather than proton abstraction from the hydroxylgroup of serine. K256, the residue involved in the formation of Schiffs base with PLP, also plays a crucial role in the maintenance of the tetrameric structure. Mutation of R262 residue established the importance of distal interactions in facilitating catalysis and Y82 is not involved in the formaldehyde transfer via the postulated hemiacetal intermediate but plays a role in stabilizing the quinonoid intermediate.The mutational analysis of scSHMT along with the structure of recombinant Bacillus stearothermophilus SHMT and its substrate(s)complexes was used to provide evidence for a direct transfer mechanism rather than retro-aldol cleavage for the reaction catalyzed by SHMT.

A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

From anomalies in neat liquid to structure, dynamics and function in the biological world

Water brings its remarkable thermodynamic and dynamic anomalies in the pure liquid state to biological world where water molecules face a multitude of additional interactions that frustrate its hydrogen bond network. Yet the water molecules participate and control enormous number of biological processes in manners which are yet to be understood at a molecular level. We discuss thermodynamics, structure, dynamics and properties of water around proteins and DNA, along with those in reverse micelles. We discuss the roles of water in enzyme kinetics, in drug-DNA intercalation and in kinetic-proof reading ( the theory of lack of errors in biosynthesis). We also discuss how water may play an important role in the natural selection of biomolecules. (C) 2011 Elsevier B. V. All rights reserved.

Learning polyhedral classifiers using logistic function

In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimization problem, our method solves an unconstrained optimization problem. Our method is based on a logistic function based model for the posterior probability function. We propose an alternating optimization algorithm, namely, SPLA1 (Single Polyhedral Learning Algorithm1) which maximizes the loglikelihood of the training data to learn the parameters. We also extend our method to make it independent of any user specified parameter (e.g., number of hyperplanes required to form a polyhedral set) in SPLA2. We show the effectiveness of our approach with experiments on various synthetic and real world datasets and compare our approach with a standard decision tree method (OC1) and a constrained optimization based method for learning polyhedral sets.