Characterization and Ionic Conductivity Studies on Nano SiO2 Dispersed x NaNO3 - (1-x) Sr(NO3)2 Mixed System

ABSTRACT Variation of dc ionic conductivity with temperature and mole percent in dispersed mixed ionic conductors of Sodium and Strontium nitrates is presented. The host materials, mixed systems of NaNO3 and Sr(NO3)2 single crystals were grown by solution technique. The powders of different compositions of mixed systems were prepared and then dispersed with SiO2 (10nm) in a particular mole percent. Pellets were made at a pressure of about 5tonnes/sq.m. and sintered at 250 o C for 20hours. The room temperature X-ray diffraction patterns of dispersed systems show the co-existence of three phases. The Fourier Transform Infrared spectrum of dispersed systems in the wave number range from 400 to 4000 cm -1 show the existence of three phases and also confirms the existence of OHˉˉ band. In the dispersed systems the enhancement in conductivity is observed to increase with mole percent (m/o) with a threshold at 20.55 m/o where from enhancement starts falling with further increase in mole percent. The maximum enhancement at 20.55 m/o is observed to be above two orders of magnitude with respect to mixed system in the extrinsic conduction region. The enhancement of conductivity in these systems is explained using Maier's space charge model. The enhancement of conductivity in the dispersed systems is mainly attributed to the increased concentration defects in the space charge layer formed between the host material and the dispersoid. Further, the fall in conductivity may be due to the fall of total effective surface area of contact between the host and dispersoid materials

Facial expression (mood) recognition from facial images using committee neural networks

<p>Abstract</p> <p>Background</p> <p>Facial expressions are important in facilitating human communication and interactions. Also, they are used as an important tool in behavioural studies and in medical rehabilitation. Facial image based mood detection techniques may provide a fast and practical approach for non-invasive mood detection. The purpose of the present study was to develop an intelligent system for facial image based expression classification using committee neural networks.</p> <p>Methods</p> <p>Several facial parameters were extracted from a facial image and were used to train several generalized and specialized neural networks. Based on initial testing, the best performing generalized and specialized neural networks were recruited into decision making committees which formed an integrated committee neural network system. The integrated committee neural network system was then evaluated using data obtained from subjects not used in training or in initial testing.</p> <p>Results and conclusion</p> <p>The system correctly identified the correct facial expression in 255 of the 282 images (90.43% of the cases), from 62 subjects not used in training or in initial testing. Committee neural networks offer a potential tool for image based mood detection.</p

Gene Expression Based Leukemia Sub-Classification Using Committee Neural Networks

Analysis of gene expression data provides an objective and efficient technique for sub-classification of leukemia. The purpose of the present study was to design a committee neural networks based classification systems to subcategorize leukemia gene expression data. In the study, a binary classification system was considered to differentiate acute lymphoblastic leukemia from acute myeloid leukemia. A ternary classification system which classifies leukemia expression data into three subclasses including B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia and acute myeloid leukemia was also developed. In each classification system gene expression profiles of leukemia patients were first subjected to a sequence of simple preprocessing steps. This resulted in filtering out approximately 95 percent of the non-informative genes. The remaining 5 percent of the informative genes were used to train a set of artificial neural networks with different parameters and architectures. The networks that gave the best results during initial testing were recruited into a committee. The committee decision was by majority voting. The committee neural network system was later evaluated using data not used in training. The binary classification system classified microarray gene expression profiles into two categories with 100 percent accuracy and the ternary system correctly predicted the three subclasses of leukemia in over 97 percent of the cases

Isolation and evolutionary analysis of Australasian topotype of bluetongue virus serotype 4 from India

Bluetongue (BT) is a Culicoides-borne disease caused by several serotypes of bluetongue virus (BTV). Similar to other insect-borne viral diseases, distribution of BT is limited to distribution of Culicoides species competent to transmit BTV. In the tropics, vector activity is almost year long, and hence, the disease is endemic, with the circulation of several serotypes of BTV, whereas in temperate areas, seasonal incursions of a limited number of serotypes of BTV from neighbouring tropical areas are observed. Although BTV is endemic in all the three major tropical regions (parts of Africa, America and Asia) of the world, the distribution of serotypes is not alike. Apart from serological diversity, geography-based diversity of BTV genome has been observed, and this is the basis for proposal of topotypes. However, evolution of these topotypes is not well understood. In this study, we report the isolation and characterization of several BTV-4 isolates from India. These isolates are distinct from BTV-4 isolates from other geographical regions. Analysis of available BTV seg-2 sequences indicated that the Australasian BTV-4 diverged from African viruses around 3,500 years ago, whereas the American viruses diverged relatively recently (1,684 CE). Unlike Australasia and America, BTV-4 strains of the Mediterranean area evolved through several independent incursions. We speculate that independent evolution of BTV in different geographical areas over long periods of time might have led to the diversity observed in the current virus population

Full-genome sequencing as a basis for molecular epidemiology studies of bluetongue virus in India

Since 1998 there have been significant changes in the global distribution of bluetongue virus (BTV). Ten previously exotic BTV serotypes have been detected in Europe, causing severe disease outbreaks in naïve ruminant populations. Previously exotic BTV serotypes were also identified in the USA, Israel, Australia and India. BTV is transmitted by biting midges (Culicoides spp.) and changes in the distribution of vector species, climate change, increased international travel and trade are thought to have contributed to these events. Thirteen BTV serotypes have been isolated in India since first reports of the disease in the country during 1964. Efficient methods for preparation of viral dsRNA and cDNA synthesis, have facilitated full-genome sequencing of BTV strains from the region. These studies introduce a new approach for BTV characterization, based on full-genome sequencing and phylogenetic analyses, facilitating the identification of BTV serotype, topotype and reassortant strains. Phylogenetic analyses show that most of the equivalent genome-segments of Indian BTV strains are closely related, clustering within a major eastern BTV ‘topotype’. However, genome-segment 5 (Seg-5) encoding NS1, from multiple post 1982 Indian isolates, originated from a western BTV topotype. All ten genome-segments of BTV-2 isolates (IND2003/01, IND2003/02 and IND2003/03) are closely related (&gt;99% identity) to a South African BTV-2 vaccine-strain (western topotype). Similarly BTV-10 isolates (IND2003/06; IND2005/04) show &gt;99% identity in all genome segments, to the prototype BTV-10 (CA-8) strain from the USA. These data suggest repeated introductions of western BTV field and/or vaccine-strains into India, potentially linked to animal or vector-insect movements, or unauthorised use of ‘live’ South African or American BTV-vaccines in the country. The data presented will help improve nucleic acid based diagnostics for Indian serotypes/topotypes, as part of control strategies

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Not AvailableInvestigations were carried out to study the physiological and yield variability in sunflower lines at college farm, College of Agriculture, PJTSAU, Hyderabad during late rabi 2013-14. The material composed of four sunflower hybrids (GMU-337, GMU-437, EC-602063 and DRSF-113). Water stress imposed from 30-65 DAS resulted in decreased SCMR values, stomatal conductance, fluorescence, and photosynthetic rate. The analysis of variance revealed the presence of sufficient variability for physiological attributes. The genotype DRSF-113 showed maximum values for SPAD chlorophyll meter readings (31.5), stomatal conductance (193.5 mmol (H O) m-2 s-1), photosynthetic rate (25.5 μ moles CO m-2s-1), fluorescence 2 2 (Fv/ Fm) (0.565) and yield (1488 kg/ha) . The results also shown that the yield positively correlated with leaf greenness (SPAD chlorophyll meter readings) and fluorescence (Fv/ Fm). Based on the results, out of the four genotypes studied DRSF-113 and EC-602063 can be concluded as tolerant for moisture stress than genotypes GMU-337 and GMU-437.Not Availabl

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Not AvailableThe experiment with 39 sunflower genotypes screened by subjecting them to water stress in the laboratory by treating with PEG (poly ethylene glycol) solution at different concentrations viz., 0.0, -0.2, -0.4, -0.6, -0.8 MPa. root length, shoot length and seedling dry weight decreased with increase in osmotic stress. Increase in root length as a result of stress has also been observedNot Availabl