Comparative Nucleotide and Amino Acid Sequence Analysis of the Sequence-Specific RNA-Binding Rotavirus Nonstructural Protein NSP3

NSP3, an acidic nonstructural protein, encoded by gene 7 has been implicated as the key player in the assembly of the 11 viral plus-strand RNAs into the early replication intermediates during rotavirus morphogenesis. To date, the sequence or NSP3 from only three animal rotaviruses (SA11, SA114F, and bovine UK) has been determined and that from a human strain has not been reported. To determine the genetic diversity among gene 7 alleles from group A rotaviruses, the nucleotide sequence of the NSP3 gene from 13 strains belonging to nine different G serotypes, from both humans and animals, has been determined. Based on the amino acid sequence identity as well as phylogenetic analysis, NSP3 from group A rotaviruses falls into three evolutionarily related groups, i.e., the SA11 group, the Wa group, and the S2 group. The SA 11/SA114F gene appears to have a distant ancestral origin from that of the others and codes for a polypeptide of 315 amino acids (aa) in length. NSP3 from all other group A rotaviruses is only 313 aa in length because of a 2-amino-acid deletion near the carboxy-terminus, While the SA114F gene has the longest 3' untranslated region (UTR) of 132 nucleotides, that from other strains suffered deletions of varying lengths at two positions downstream of the translational termination codon. In spite of the divergence of the nucleotide (nt) sequence in the protein coding region, a stretch of about 80 nt in the 3' UTR is highly conserved in the NSP3 gene from all the strains. This conserved sequence in the 3' UTR might play an important role in the regulation of expression of the NSP3 gene. (C) 1995 Academic Press, Inc.

On generating optimal signal probabilities for random tests: A genetic approach

Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed, A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance pf our GA-based approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms.

Origin of a trend in ECMWF wind analysis and its objective removal

The suitability of the European Centre for Medium Range Weather Forecasting (ECMWF) operational wind analysis for the period 1980-1991 for studying interannual variability is examined. The changes in the model and the analysis procedure are shown to give rise to a systematic and significant trend in the large scale circulation features. A new method of removing the systematic errors at all levels is presented using multivariate EOF analysis. Objectively detrended analysis of the three-dimensional wind field agrees well with independent Florida State University (FSU) wind analysis at the surface. It is shown that the interannual variations in the detrended surface analysis agree well in amplitude as well as spatial patterns with those of the FSU analysis. Therefore, the detrended analyses at other levels as well are expected to be useful for studies of variability and predictability at interannual time scales. It is demonstrated that this trend in the wind field is due to the shift in the climatologies from the period 1980-1985 to the period 1986-1991.

Sibling rivalry between seeds within a fruit: Some population genetic models

Competition between seeds within a fruit for parental resources is described using one-locus-two-allele models. While a �normal� allele leads to an equitable distribution of resources between seeds (a situation which also corresponds to the parental optimum), the �selfish� allele is assumed to cause the seed carrying it to usurp a higher proportion of the resources. The outcome of competition between �selfish� alleles is also assumed to lead to an asymmetric distribution of resources, the �winner� being chosen randomly. Conditions for the spread of an initially rare selfish allele and the optimal resource allocation corresponding to the evolutionarily stable strategy, derived for species with n-seeded fruits, are in accordance with expectations based on Hamilton�s inclusive fitness criteria. Competition between seeds is seen to be most intense when there are only two seeds, and decreases with increasing number of seeds, suggesting that two-seeded fruits would be rarer than one-seeded or many-seeded ones. Available data from a large number of plant species are consistent with this prediction of the model.

Primary Sequence That Determines the Functional Overlap between Mitochondrial Heat Shock Protein 70 Ssc1 and Ssc3 of Saccharomyces cerevisiae

The evolutionary diversity of the HSP70 gene family at the genetic level has generated complex structural variations leading to altered functional specificity and mode of regulation in different cellular compartments. By utilizing Saccharomyces cerevisiae as a model system for better understanding the global functional cooperativity between Hsp70 paralogs, we have dissected the differences in functional properties at the biochemical level between mitochondrial heat shock protein 70 (mtHsp70) Ssc1 and an uncharacterized Ssc3 paralog. Based on the evolutionary origin of Ssc3 and a high degree of sequence homology with Ssc1, it has been proposed that both have a close functional overlap in the mitochondrial matrix. Surprisingly, our results demonstrate that there is no functional cross-talk between Ssc1 and Ssc3 paralogs. The lack of in vivo functional overlap is due to altered conformation and significant lower stability associated with Ssc3. The substrate-binding domain of Ssc3 showed poor affinity toward mitochondrial client proteins and Tim44 due to the open conformation in ADP-bound state. In addition to that, the nucleotide-binding domain of Ssc3 showed an altered regulation by the Mge1 co-chaperone due to a high degree of conformational plasticity, which strongly promotes aggregation. Besides, Ssc3 possesses a dysfunctional inter-domain interface thus rendering it unable to perform functions similar to generic Hsp70s. Moreover, we have identified the critical amino acid sequence of Ssc1 and Ssc3 that can ``make or break'' mtHsp70 chaperone function. Together, our analysis provides the first evidence to show that the nucleotide-binding domain of mtHsp70s plays a critical role in determining the functional specificity among paralogs and orthologs across kingdoms.

Origin of the unconventional magnetoresistance in Sr(2)FeMoO6(6)

The unusual magnetoresistance (MR) behavior in Sr2FeMoO6, recently termed as spin-valve-type MR (SVMR), presents several anomalies that are little understood so far. The difficulty in probing the origin of this phenomenon, arising from the magnetic property of only a small volume fraction of the ferromagnetic bulk, is circumvented in the present study by the use of ac susceptibility measurements that are sensitive to the slope rather than the magnitude of the magnetization. The present study unravels a spin-glass (SG) like surface layer around each soft ferromagnetic (FM) grain of Sr2FeMoO6. It is also observed that there is a very strong exchange coupling between the two, generating ``exchange bias'' effect, which consequently creates the ``valve'', responsible for the unusual MR effects. Copyright (C) EPLA, 2011

On an exact populationary model of genetic algorithms

Genetic algorithms (GAs) are search methods that are being employed in a multitude of applications with extremely large search spaces. Recently, there has been considerable interest among GA researchers in understanding and formalizing the working of GAs. In an earlier paper, we have introduced the notion of binomially distributed populations as the central idea behind an exact ''populationary'' model of the large-population dynamics of the GA operators for objective functions called ''functions of unitation.'' In this paper, we extend this populationary model of GA dynamics to a more general class of objective functions called functions of unitation variables. We generalize the notion of a binomially distributed population to a generalized binomially distributed population (GBDP). We show that the effects of selection, crossover, and mutation can be exactly modelled after decomposing the population into GBDPs. Based on this generalized model, we have implemented a GA simulator for functions of two unitation variables-GASIM 2, and the distributions predicted by GASIM 2 match with those obtained from actual GA runs. The generalized populationary model of GA dynamics not only presents a novel and natural way of interpreting the workings of GAs with large populations, but it also provides for an efficient implementation of the model as a GA simulator. (C) Elsevier Science Inc. 1997.

Origin of carrier-type reversal in Pb-Ge-Se glasses: A detailed thermal, electrical, and structural study

A long-standing and important problem in glass science has been carrier-type reversal (CTR) in semiconducting glasses. This phenomenon is exhibited by Pb-Ge-Se glasses also. It has been addressed here by carrying out detailed electrical, thermal, and spectroscopic investigations. PbxGe42-xSe58 (x = 0-20) glasses were prepared by a two stage melt-quenching process and characterized using x-ray diffraction, high-resolution electron microscropy, and energy dispersive analysis of x-rays. Thermoelectric power and high-pressure electrical resistivity have been measured. IR, Raman, and X-ray adsorption near edge structure spectroscopies have been used for examining the glass structures as well as differential scanning calorimetry (DSC) for studying the thermal properties. A structural model based on the chemical nature of the constituents has been proposed to account for the observed properties of these glasses. Effect of Pb incorporation on local structures and qualitative consequences on the energy band structures of Ge-Se glasses has been considered. The p -->n transition has been attributed to the energetic disposition of the sp(3)d(2) band of Pb atoms, which is located closely above the lone pair band of selenium. This feature makes Pb unique in the context of p -->n transition of chalcogenide glasses. The model can be extended successfully to account for the CTR behavior observed in Bi containing chalcogenide glasses also.

Automatic decomposition of unstructured meshes employing genetic algorithms for parallel FEM computations

Parallel execution of computational mechanics codes requires efficient mesh-partitioning techniques. These mesh-partitioning techniques divide the mesh into specified number of submeshes of approximately the same size and at the same time, minimise the interface nodes of the submeshes. This paper describes a new mesh partitioning technique, employing Genetic Algorithms. The proposed algorithm operates on the deduced graph (dual or nodal graph) of the given finite element mesh rather than directly on the mesh itself. The algorithm works by first constructing a coarse graph approximation using an automatic graph coarsening method. The coarse graph is partitioned and the results are interpolated onto the original graph to initialise an optimisation of the graph partition problem. In practice, hierarchy of (usually more than two) graphs are used to obtain the final graph partition. The proposed partitioning algorithm is applied to graphs derived from unstructured finite element meshes describing practical engineering problems and also several example graphs related to finite element meshes given in the literature. The test results indicate that the proposed GA based graph partitioning algorithm generates high quality partitions and are superior to spectral and multilevel graph partitioning algorithms.

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.

Identification of delamination in composite beams using spectral estimation and a genetic algorithm

An efficient strategy for identification of delamination in composite beams and connected structures is presented. A spectral finite-element model consisting of a damaged spectral element is used for model-based prediction of the damaged structural response in the frequency domain. A genetic algorithm (GA) specially tailored for damage identification is derived and is integrated with finite-element code for automation. For best application of the GA, sensitivities of various objective functions with respect to delamination parameters are studied and important conclusions are presented. Model-based simulations of increasing complexity illustrate some of the attractive features of the strategy in terms of accuracy as well as computational cost. This shows the possibility of using such strategies for the development of smart structural health monitoring softwares and systems.

Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

The origin of degeneracies and crossings in the 1d Hubbard model

The paper is devoted to the connection between integrability of a finite quantum system and degeneracies of its energy levels. In particular, we analyse in detail the energy spectra of finite Hubbard chains. Heilmann and Lieb demonstrated that in these systems there are crossings of levels of the same parameter-independent symmetry. We show that this apparent violation of the Wigner-von Neumann noncrossing rule follows directly from the existence of nontrivial conservation laws and is a characteristic signature of quantum integrability. The energy spectra of Hubbard chains display many instances of permanent (at all values of the coupling) twofold degeneracies that cannot be explained by parameter-independent symmetries. We relate these degeneracies to the different transformation properties of the conserved currents under spatial reflections and the particle-hole transformation and estimate the fraction of doubly degenerate states. We also discuss multiply degenerate eigenstates of the Hubbard Hamiltonian. The wavefunctions of many of these states do not depend on the coupling, which suggests the existence of an additional parameter-independent symmetry.