Genetic characterization of Indian type O FMD virus 3A region in context with host cell preference

The 3A region of foot-and-mouth disease virus has been implicated in host range and virulence. For example, amino acid deletions in the porcinophilic strain (O/TAW/97) at 93-102 aa of the 153 codons long 3A protein have been recognized as the determinant of species specificity. In the present study, 18 type 0 FMDV isolates from India were adapted in different cell culture systems and the 3A sequence was analyzed. These isolates had complete 3A coding sequence (153 aa) and did not exhibit growth restriction in cells based on species of origin. The 3A region was found to be highly conserved at N-terminal half (1-75 aa) but exhibited variability or substitutions towards C-terminal region (80-153). Moreover the amino acid substitutions were more frequent in recent Indian buffalo isolates but none of the Indian isolates showed deletion in 3A protein, which may be the reason for the absence of host specificity in vitro. Further inclusive analysis of 3A region will reveal interesting facts about the variability of FMD virus 3A region in an endemic environment. (C) 2010 Elsevier B.V. All rights reserved.

Monetary Policy, Stock Price Misalignments and Macroeconomic Instability

Perhaps the most fundamental prediction of financial theory is that the expected returns on financial assets are determined by the amount of risk contained in their payoffs. Assets with a riskier payoff pattern should provide higher expected returns than assets that are otherwise similar but provide payoffs that contain less risk. Financial theory also predicts that not all types of risks should be compensated with higher expected returns. It is well-known that the asset-specific risk can be diversified away, whereas the systematic component of risk that affects all assets remains even in large portfolios. Thus, the asset-specific risk that the investor can easily get rid of by diversification should not lead to higher expected returns, and only the shared movement of individual asset returns – the sensitivity of these assets to a set of systematic risk factors – should matter for asset pricing. It is within this framework that this thesis is situated. The first essay proposes a new systematic risk factor, hypothesized to be correlated with changes in investor risk aversion, which manages to explain a large fraction of the return variation in the cross-section of stock returns. The second and third essays investigate the pricing of asset-specific risk, uncorrelated with commonly used risk factors, in the cross-section of stock returns. The three essays mentioned above use stock market data from the U.S. The fourth essay presents a new total return stock market index for the Finnish stock market beginning from the opening of the Helsinki Stock Exchange in 1912 and ending in 1969 when other total return indices become available. Because a total return stock market index for the period prior to 1970 has not been available before, academics and stock market participants have not known the historical return that stock market investors in Finland could have achieved on their investments. The new stock market index presented in essay 4 makes it possible, for the first time, to calculate the historical average return on the Finnish stock market and to conduct further studies that require long time-series of data.

Genetic algorithm for satellite customer assignment

The problem of assigning customers to satellite channels is considered. Finding an optimal allocation of customers to satellite channels is a difficult combinatorial optimization problem and is shown to be NP-complete in an earlier study. We propose a genetic algorithm (GA) approach to search for the best/optimal assignment of customers to satellite channels. Various issues related to genetic algorithms such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. A comparison of this approach with the standard optimization method is presented to show the advantages of this approach in terms of computation time

Nonlinear intrinsic instability of solid propellant combustion including gas-phase thermal inertia

The problem of homogeneous solid propellant combustion instability is studied with a one-dimensional flame model, including the effects of gas-phase thermal inertia and nonlinearity. Computational results presented in this paper show nonlinear instabilities inherent in the equations, due to which periodic burning is found even under steady ambient conditions such as pressure. The stability boundary is obtained in terms of Denison-Baum parameters. It is found that inclusion of gas-phase thermal inertia stabilizes the combustion. Also, the effect of a distributed heat release in the gas phase, compared to the flame sheet model, is to destabilize the burning. Direct calculations for finite amplitude pressure disturbances show that two distinct resonant modes exist, the first one near the natural frequency as obtained from intrinsic instability analysis and a second mode occurring at a much higher driving frequency. It is found that er rn in the low frequency region, the response of the propellant is significantly affected by the specific type of gas-phase chemical heat-release model employed. Examination of frequency response function reveals that the role of gas-phase thermal inertia is to stabilize the burning near the first resonant mode. Calculations made for different amplitudes of driving pressure show that the mean burning rate decreases with increasing amplitude. Also, with an increase in the driving amplitude, higher harmonics are generated in the burning rate.

Adhesion-Induced Instability in Asperities

Adhesive forces between two approaching asperities will deform the asperities, and under certain conditions this will result in a sudden runaway deformations leading to a jump-to-contact instability. We present finite element-based numerical studies on adhesion-induced deformation and instability in asperities. We consider the adhesive force acting on an asperity, when it is brought near a rigid half-space, due to van der Waals interaction between the asperity and the half-space. The adhesive force is considered to be distributed over the volume of the asperity (body force), thus resulting in more realistic simulations for the length scales considered. Iteration scheme based on a ``residual stress update'' algorithm is used to capture the effect of deformation on the adhesion force, and thereby the equilibrium configuration and the corresponding force. The numerical results are compared with the previous approximate analytical solutions for adhesion force, deformation of the asperity and adhesion-induced mechanical instability (jump-to-contact). It is observed that the instability can occur at separations much higher,and could possibly explain the higher value of instability separation observed in experiments. The stresses in asperities, particularly in case of small ones, are found to be high enough to cause yielding before jump -to-contact. The effect of roughness is considered by modeling a spherical protrusion on the hemispherical asperity.This small-scale roughness at the tip of the asperities is found to control the deformation behavior at small separations, and hence are important in determining the friction and wear due to the jump-to-contact instability.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Genetic Heterogeneity in Wild Isolates of Cellular Slime Mold Social Groups

This study addresses the issues of spatial distribution, dispersal, and genetic heterogeneity in social groups of the cellular slime molds (CSMs). The CSMs are soil amoebae with an unusual life cycle that consists of alternating solitary and social phases. Because the social phase involves division of labor with what appears to be an extreme form of "altruism", the CSMs raise interesting evolutionary questions regarding the origin and maintenance of sociality. Knowledge of the genetic structure of social groups in the wild is necessary for answering these questions. We confirm that CSMs are widespread in undisturbed forest soil from South India. They are dispersed over long distances via the dung of a variety of large mammals. Consistent with this mode of dispersal, most social groups in the two species examined for detailed study, Dictyostelium giganteum and Dictyostelium purpureum, are multi-clonal.

Cognitive Functioning in Alcohol and Other Substance Use Disorders in Young Adulthood : A Genetic Epidemiological Study

Alcohol and other substance use disorders (SUDs) result in great costs and suffering for individuals and families and constitute a notable public health burden. A multitude of factors, ranging from biological to societal, are associated with elevated risk of SUDs, but at the level of individuals, one of the best predictors is a family history of SUDs. Genetically informative twin and family studies have consistently indicated this familial risk to be mainly genetic. In addition, behavioral and temperamental factors such as early initiation of substance use and aggressiveness are associated with the development of SUDs. These familial, behavioral and temperamental risk factors often co-occur, but their relative importance is not well known. People with SUDs have also been found to differ from healthy controls in various domains of cognitive functioning, with poorer verbal ability being among the most consistent findings. However, representative population-based samples have rarely been used in neuropsychological studies of SUDs. In addition, both SUDs and cognitive abilities are influenced by genetic factors, but whether the co-variation of these traits might be partly explained by overlapping genetic influences has not been studied. Problematic substance use also often co-occurs with low educational level, but it is not known whether these outcomes share part of their underlying genetic influences. In addition, educational level may moderate the genetic etiology of alcohol problems, but gene-environment interactions between these phenomena have also not been widely studied. The incidence of SUDs peaks in young adulthood rendering epidemiological studies in this age group informative. This thesis investigated cognitive functioning and other correlates of SUDs in young adulthood in two representative population-based samples of young Finnish adults, one of which consisted of monozygotic and dizygotic twin pairs enabling genetically informative analyses. Using data from the population-based Mental Health in Early Adulthood in Finland (MEAF) study (n=605), the lifetime prevalence of DSM-IV any substance dependence or abuse among persons aged 21—35 years was found to be approximately 14%, with a majority of the diagnoses being alcohol use disorders. Several correlates representing the domains of behavioral and affective factors, parental factors, early initiation of substance use, and educational factors were individually associated with SUDs. The associations between behavioral and affective factors (attention or behavior problems at school, aggression, anxiousness) and SUDs were found to be largely independent of factors from other domains, whereas daily smoking and low education were still associated with SUDs after adjustment for behavioral and affective factors. Using a wide array of neuropsychological tests in the MEAF sample and in a subsample (n=602) of the population-based FinnTwin16 (FT16) study, consistent evidence of poorer verbal cognitive ability related to SUDs was found. In addition, participants with SUDs performed worse than those without disorders in a task assessing psychomotor processing speed in the MEAF sample, whereas no evidence of more specific cognitive deficits was found in either sample. Biometrical structural equation models of the twin data suggested that both alcohol problems and verbal ability had moderate heritabilities (0.54—0.72), and that their covariation could be explained by correlated genetic influences (genetic correlations -0.20 to -0.31). The relationship between educational level and alcohol problems, studied in the full epidemiological FT16 sample (n=4,858), was found to reflect both genetic correlation and gene-environment interaction. The co-occurrence of low education and alcohol problems was influenced by overlapping genetic factors. In addition, higher educational level was associated with increased relative importance of genetic influences on alcohol problems, whereas environmental influences played a more important role in young adults with lower education. In conclusion, SUDs, especially alcohol abuse and dependence, are common among young Finnish adults. Behavioral and affective factors are robustly related to SUDs independently of many other factors, and compared to healthy peers, young adults who have had SUDs during their life exhibit significantly poorer verbal cognitive ability, and possibly less efficient psychomotor processing. Genetic differences between individuals explain a notable proportion of individual differences in risk of alcohol dependence, verbal ability, and educational level, and the co-occurrence of alcohol problems with poorer verbal cognition and low education is influenced by shared genetic backgrounds. Finally, various environmental factors related to educational level in young adulthood moderate the relative importance of genetic factors influencing the risk of alcohol problems, possibly reflecting differences in social control mechanisms related to educational level.

Karyotype instability in the ponerine ant genus Diacamma

The queenless ponerine ant Diacamma ceylonense and a population of Diacamma from the Nilgiri hills which we refer to as `nilgiri', exhibit interesting similarities as well as dissimilarities. Molecular phylogenetic study of these morphologically almost similar taxa has shown that D ceylonense is closely related to `nilgiri' and indicates that `nilgiri' is a recent diversion in the Diacamma phylogenetic tree. However, there is a striking behavioural difference in the way reproductive monopoly is maintained by the respective gamergates (mated egg laying workers), and there is evidence that they are genetically differentiated, suggesting a lack of gene flow To develop a better understanding of the mechanism involved in speciation of Diacamma, we have analysed karyotypes of D. ceylonense and `nilgiri' In both, we found surprising inter-individual and intra-individual karyotypic mosaicism. The observed numerical variability, both at intra-individual and inter-individual levels, does not appear to have hampered the sustainability of the chromosomal diversity in each population under study Since the related D. indicum, displays no such intra-individual or inter-Individual variability whatsoever under identical experimental conditions, these results are unlikely to he artifacts. Although no known mechanisms can account for the observed karyotypic variability of this nature, we believe that the present findings on the ants under study would provide opportunities for exciting new discoveries concerning the origin, maintenance and significance of intra-individual and inter-individual karyotypic mosaicism.

Molecular features of colorectal cancer predisposition and progression

Both inherited genetic variations and somatically acquired mutations drive cancer development. The aim of this thesis was to gain insight into the molecular mechanisms underlying colorectal cancer (CRC) predisposition and tumor progression. Whereas one-third of CRC may develop in the context of hereditary predisposition, the known highly penetrant syndromes only explain a small fraction of all cases. Genome-wide association studies have shown that ten common single nucleotide polymorphisms (SNPs) modestly predispose to CRC. Our population-based sample series of around thousand CRC cases and healthy controls was genotyped for these SNPs. Tumors of heterozygous patients were analyzed for allelic imbalance, in an attempt to reveal the role of these SNPs in somatic tumor progression. The risk allele of rs6983267 at 8q24 was favored in the tumors significantly more often than the neutral allele, indicating that this germline variant is somatically selected for. No imbalance targeting the risk allele was observed in the remaining loci, suggesting that most of the low-penetrance CRC SNPs mainly play a role in the early stages of the neoplastic process. The ten SNPs were further analyzed in 788 CRC cases, 97 of which had a family history of CRC, to evaluate their combined contribution. A significant association appeared between the overall number of risk alleles and familial CRC and these ten SNPs seem to explain around 9% of the familial clustering of CRC. Finding more CRC susceptibility alleles may facilitate individualized risk prediction and cancer prevention in the future. Microsatellite instability (MSI), resulting from defective mismatch repair function, is a hallmark of Lynch syndrome and observed in a subset of all CRCs. Our aim was to identify microsatellite frameshift mutations that inactivate tumor suppressor genes in MSI CRCs. By sequencing microsatellite repeats of underexpressed genes we found six novel MSI target genes that were frequently mutated in 100 MSI CRCs: 51% in GLYR1, 47% in ABCC5, 43% in WDTC1, 33% in ROCK1, 30% in OR51E2, and 28% in TCEB3. Immunohistochemical staining of GLYR1 revealed defective protein expression in homozygously mutated tumors, providing further support for the loss of function hypothesis. Another mutation screening effort sought to identify MSI target genes with putative oncogenic functions. Microsatellites were similarly sequenced in genes that were overexpressed and, upon mutation, predicted to avoid nonsense-mediated mRNA decay. The mitotic checkpoint kinase TTK harbored protein-elongating mutations in 59% of MSI CRCs and the mutant protein was detected in heterozygous MSI CRC cells. No checkpoint dysregulation or defective protein localization was observable however, and the biological relevance of this mutation may hence be related to other mechanisms. In conclusion, these two large-scale and unbiased efforts identified frequently mutated genes that are likely to contribute to the development of this cancer type and may be utilized in developing diagnostic and therapeutic applications.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Determinants of Cognitive Impairment in Old Age and Their Genetic Architecture

Cognitive health is of central importance for independent and balanced old age, while memory disorders represent the leading cause of intensive and long-term care among the Finnish elderly. The aims of this study were to analyse the effect of height, body mass index, weight change, metabolic conditions and coffee drinking in midlife on cognitive performance in old age among a sample of 2606 Finnish twins aged 65 years or older who had participated in a telephone interview to assess their cognitive status. Since coffee drinking associates with several metabolic conditions and Finns are known to be the greatest consumers of coffee in the world, the heritability and stability of coffee drinking was analysed in the whole Older Finnish Twin Cohort (n=10716). In order to investigate the association between height and cognitive performance in a population with more supportive childhood living conditions, a total of 2161 Danish twins were included in this study. A greater height was found to clearly associate with better cognitive performance in Finnish subjects, but less so among the Danish sample, which may reflect the childhood environmental differences between these cohorts. In the Finnish subjects, there was greater variance in cognitive performance among shorter subjects, and environmental factors were found to play a greater role in their cognitive performance, whereas the cognitive performance of taller participants was mainly explained by genetic factors. Midlife metabolic variables that were found to be significantly associated with a poorer cognitive performance in old age included a higher body mass index and three metabolic conditions: cardiovascular disease, hypertension and, most significantly of all, diabetes. Moreover, both weight gain and loss, even to a lesser degree than suggested previously, were found to be associated with poorer cognition. Furthermore, evidence of a causal relationship between midlife cardiovascular disease and cognitive performance in old age was demonstrated among discordant twin pairs. Conversely, no effect of coffee drinking in midlife on cognitive performance in old age was observed, although coffee drinking was demonstrated to be stable in the study population. The heritability of coffee drinking was found to differ across sexes and age groups, being 51% in men and 52% in women in the whole study population. This study supports the contention that cognitive performance in old age reflects the effects of multiple genetic and environmental exposures, including their complex interactions during the life-span. The demonstrated associations and evidence of a causal pathway between potentially preventable exposures and poorer cognitive performance highlight the importance of preventive medicine.

A sufficient criterion for Rayleigh-Taylor instability of incompressible viscous three-layer flow

Using normal mode analysis Rayleigh-Taylor instability is investigated for three-layer viscous stratified incompressible steady flow, when the top 3rd and bottom 1st layers extend up to infinity, the middle layer has a small thickness δ. The wave Reynolds number in the middle layer is assumed to be sufficiently small. A dispersion relation (a seventh degree polynomial in wave frequency ω) valid up to the order of the maximal value of all possible Kj (j less-than-or-equals, slant 0, K is the wave number) in each coefficient of the polynomial is obtained. A sufficient condition for instability is found out for the first time, pursuing a medium wavelength analysis. It depends on ratios (α and β) of the coefficients of viscosity, the thickness of the middle layer δ, surface tension ratio T and wave number K. This is a new analytical criterion for Rayleigh-Taylor instability of three-layer fluids. It recovers the results of the corresponding problem for two-layer fluids. Among the results obtained, it is observed that taking the coefficients of viscosity of 2nd and 3rd layers same can inhibit the effect of surface tension completely. For large wave number K, the thickness of the middle layer should be correspondingly small to keep the domain of dependence of the threshold wave number Kc constant for fixed α, β and T.