Characterization of strain in Si1-xGex films using multiple angle of incidence ellipsometry

In this letter we characterize strain in Si1-xGex based heterojunction bipolar transistors and modulation doped field effect transistors grown by rapid thermal chemical vapor deposition exploiting the phenomenon of strain-induced birefringence. The technique used is multiple angle of incidence ellipsometry at a wavelength of 670 nm to measure the ordinary and extraordinary refractive indices of the Si1-xGex films. We report measurements on thin fully strained films (with thicknesses less than the critical thickness) with Ge concentration varying from 9% to 40% with an accuracy of the order of 1 part in 10(4) and propose an empirical relation between the difference in the ordinary and extraordinary refractive indices (deltan) and the Ge concentration (x) given by deltan(x)=0.18x-0.12x(2). (C) 2000 American Institute of Physics. [S0003-6951(00)03948-6].

Transfer of saline tolerance from one strain of rice to another by injection of DNA

Direct injection of genomic DNA from salt tolerant cv. Pokkali into developing floral tillers on IR20 produced transgenic seeds similar to Pokkali in husk colour and which germinated well in 0.2 M NaCl and had a 4-6-fold higher proline content.

Intelligent prediction of the stress-strain response of intact and jointed rocks

An application of Artificial Neural Networks for predicting the stress-strain response of jointed rocks under different confining pressures is presented in this paper. Rocks of different compressive strength with different joint properties (frequency, orientation and strength of joints) are considered in this study. The database for training the neural network is formed from the results of triaxial compression tests on different intact and jointed rocks with different joint properties tested at different confining pressures reported by various researchers in the literature. The network was trained using a three-layered network with the feed-forward back propagation algorithm.About 85% of the data was used for training and the remaining 15% was used for testing the network. Results from the analyses demonstrated that the neural network approach is effective in capturing the stress-strain behaviour of intact rocks and the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different jointed rocks, whose intact strength varies from 11.32 MPa to 123 MPa, spacing of joints varies from 10 cm to 100 cm. and confining pressures range from 0 to 13.8 MPa. (C) 2010 Elsevier Ltd. All rights reserved.

Simultaneous Measurement of Strain and Temperature using Type I and Pre-strained Fiber Bragg Gratings

Strain and temperature sensitivities of a type I Bragg grating inscribed in a germania doped silica fiber, fabricated under normal conditions and zero strain, are compared with that of a Bragg grating inscribed under pre-strained condition. The results obtained reveal that the strain and temperature sensitivities of the two gratings are different. Based on these results, we demonstrate a technique which enables discrimination of strain and temperature in a Fiber Bragg Grating (FBG) with a linear response. The present technique allows for an easy implementation of the sensor by providing a direct access to the grating region in the fiber and demands only a simple interrogation system.

Slip line field analysis of a simple plane strain closed‐die forging

A slip line field is proposed for symmetrical single‐cavity closed‐die forging by rough dies. A compatible velocity field is shown to exist. Experiments were conducted using lead workpiece and rough dies. Experimentally observed flow and load were used to validate the proposed slip line field. The slip line field was used to simulate the process in the computer with the objective of studying the influence of flash geometry on cavity filling.

Characterization of a mercury-reducing Bacillus cereus strain isolated from the Pulicat Lake sediments, south east coast of India

Pulicat Lake sediments are often severely polluted with the toxic heavy metal mercury. Several mercury-resistant strains of Bacillus species were isolated from the sediments and all the isolates exhibited broad spectrum resistance (resistance to both organic and inorganic mercuric compounds). Plasmid curing assay showed that all the isolated Bacillus strains carry chromosomally borne mercury resistance. Polymerase chain reaction and southern hybridization analyses using merA and merB3 gene primers/probes showed that five of the isolated Bacillus strains carry sequences similar to known merA and merB3 genes. Results of multiple sequence alignment revealed 99% similarity with merA and merB3 of TnMERI1 (class II transposons). Other mercury resistant Bacillus species lacking homology to these genes were not able to volatilize mercuric chloride, indicating the presence of other modes of resistance to mercuric compounds.

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.

Design of an HA2-based Escherichia coli expressed influenza immunogen that protects mice from pathogenic challenge

Influenza HA is the primary target of neutralizing antibodies during infection, and its sequence undergoes genetic drift and shift in response to immune pressure. The receptor binding HA1 subunit of HA shows much higher sequence variability relative to the metastable, fusion-active HA2 subunit, presumably because neutralizing antibodies are primarily targeted against the former in natural infection. We have designed an HA2-based immunogen using a protein minimization approach that incorporates designed mutations to destabilize the low pH conformation of HA2. The resulting construct (HA6) was expressed in Escherichia coli and refolded from inclusion bodies. Biophysical studies and mutational analysis of the protein indicate that it is folded into the desired neutral pH conformation competent to bind the broadly neutralizing HA2 directed monoclonal 12D1, not the low pH conformation observed in previous studies. HA6 was highly immunogenic in mice and the mice were protected against lethal challenge by the homologous A/HK/68 mouse-adapted virus. An HA6-like construct from another H3 strain (A/Phil/2/82) also protected mice against A/HK/68 challenge. Regions included in HA6 are highly conserved within a subtype and are fairly well conserved within a clade. Targeting the highly conserved HA2 subunit with a bacterially produced immunogen is a vaccine strategy that may aid in pandemic preparedness.

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.

Prediction of Specimen Strain from Extensometer Deflection Measurements in a Direct Stress Fatigue Test Specimen under Static Tensile Loading

The displacement between the ridges situated outside the filleted test section of an axially loaded unnotched specimen is computed from the axial load and shape of the specimen and compared with extensometer deflection data obtained from experiments. The effect of prestrain on the extensometer deflection versus specimen strain curve has been studied experimentally and analytically. An analytical study shows that an increase in the slope of the stress-strain curve in the inelastic region increases the slope of the corresponding computed extensometer deflection versus specimen strain curve. A mathematical model has been developed which uses a modified length ¯ℓef in place of the actual length of the uniform diameter test section of the specimen. This model predicts the extensometer deflection within 5% of the corresponding experimental value. This method has been successfully used by the authors to evolve an iterative procedure for predicting the cyclic specimen strain in axial fatigue tests on unnotched specimens.

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.

Characterization of a mercury-reducing Bacillus cereus strain isolated from the Pulicat Lake sediments, south east coast of India

Pulicat Lake sediments are often severely polluted with the toxic heavy metal mercury. Several mercury-resistant strains of Bacillus species were isolated from the sediments and all the isolates exhibited broad spectrum resistance (resistance to both organic and inorganic mercuric compounds). Plasmid curing assay showed that all the isolated Bacillus strains carry chromosomally borne mercury resistance. Polymerase chain reaction and southern hybridization analyses using merA and merB3 gene primers/probes showed that five of the isolated Bacillus strains carry sequences similar to known merA and merB3 genes. Results of multiple sequence alignment revealed 99% similarity with merA and merB3 of TnMERI1 (class II transposons). Other mercury resistant Bacillus species lacking homology to these genes were not able to volatilize mercuric chloride, indicating the presence of other modes of resistance to mercuric compounds.