Elastic constant measurements of super ionic LiKSO4:Na single crystals

Elastic properties of sodium doped Lithium potassium sulphate, LiK0.9Na0.1SO4, crystal has been studied by ultrasonic Pulse Echo Overlap [PEO] technique and are reported for the first time. The controversy regarding the type of crystal found while growth is performed at 35 °C with equimolar fraction of Li2SO4H2O, K2SO4 and Na2SO4 has been resolved by studying the elastic properties. The importance of this crystal is that it exhibits pyroelectric, ferroelectric and electro optic properties. It is simultaneously ferroelastic and superionic. The elastic properties of LiK0.9Na0.1SO4 crystal are well studied by measuring ultrasonic velocity in the crystal in certain specified crystallographic directions and evaluating the elastic stiffness constants, compliance constants and Poisson’s ratios. The anisotropy in the elastic properties of the crystal are well explained by the pictorial representation of the surface plots of phase velocity, slowness and linear compressibility in a-b and a-c planes.

Electrical conductivity, dielectric constant and phase transitions in pure and doped diammonium hydrogen phosphate

DC and AC electrical conductivity measurements in single crystals of diammonium hydrogen phosphate along the c axis show anomalous variations at 174, 246 and 416 K. The low-frequency dielectric constant also exhibits peaks exactly at these temperatures with a thermal hysteresis of 13 degrees C for the peak at 416 K. These specific features of the electrical properties are in agreement with earlier NMR second-moment data and can be identified with three distinct phase transitions that occur in the crystal. The electrical conductivity values have been found to increase linearly with impurity concentration in specimens doped with a specific amount of SO42- ions. The mechanisms of the phase transition and of the electrical conduction process are discussed in detail.

Effect of deuteration on the electrical conductivity, dielectric constant and phase transitions in LiNH4SO4

Measurements of dc conductivity and dielectric constant show that deuteration causes an upward shift of the high temperature phase transition point from 186.5 to 191°C and a downward shift of the low temperature transition point from 10 to -1.5°C in LiNH4SO4. Mechanisms of phase transitions and of electrical transport in the crystal are discussed.

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

Sedimentological and Geotechnical Studies of Coastal Sediments of Central Kerala.

All over the world, several Quaternary proxy data have been used to reconstruct past sea levels, mainly radiocarbon or OSL dating of exposures of marine facies or shore line indicators (e.g. Carr et al., 2010) as well as paleoenvironmental indicators in lagoon or estuary sediments (e.g. Baxter and Meadows, 1999). Estuaries and deltas develop at river mouths during transgressive and regressive phases, respectively (Boyd et al., 1992). In particular, the postglacial Holocene sea-level rise has contributed importantly to the estuary-to-delta transition (Hori et al. 2004). By analyzing radiocarbon ages of the basal or near-basal sediments of the world’s deltas, Stanley and Warne (1994) showed that delta initiation occurred on a worldwide scale after about 8500–6500 years BP and concluded that the initiation was controlled principally by the declining rate of the Holocene sea-level rise. Worldwide there were different regional sea-level changes since the last glacial maximum (LGM) (Irion et al., 2012). Along the northern Canadian coast, for example, sea level has been falling throughout the Holocene due to the glacial rebound of the crust after the last glaciation (Peltier, 1988). This is comparable to the development in Scandinavia (Steffen and Kaufmann, 2005) where sea level drops today. From about Virginia/USA to Mexico there is a constant sea-level rise similar to the Holocene sea-level development of the southern North Sea (e.g. Vink et al., 2007). From the border of Ceará/Rio Grande do Norte down to Patagonia, indicators of Holocene sea level point to a level that was up to 5 m higher than today's mean sea level (Angulo et al., 1999; Martin et al., 2003; Caldas et al., 2006a, b)

Identification of models using failure rate and mean residual life of doubly truncated random variables

In this paper, we study the relationship between the failure rate and the mean residual life of doubly truncated random variables. Accordingly, we develop characterizations for exponential, Pareto 11 and beta distributions. Further, we generalize the identities for fire Pearson and the exponential family of distributions given respectively in Nair and Sankaran (1991) and Consul (1995). Applications of these measures in file context of lengthbiased models are also explored

Characterization of low dielectric constant polyaniline thin film synthesized by ac plasma polymerization technique

Polyaniline thin films were prepared by ac plasma polymerization technique. Capacitance, dielectric loss, dielectric constant and ac conductivity of these films were investigated in the frequency range from 100 Hz to 1MHz and in the temperature range from 300 to 373 K. Capacitance and dielectric loss decreased with frequency and increased with temperature. This type of behaviour was found to be in good agreement with an existing model. The ac conductivity σ(ω) was found to vary as ωs with the index s 1. Annealing of polyaniline thin films in high vacuum at 373K for 1 h was found to reduce the dielectric loss. FTIR studies reveal that the aromatic ring is retained in the polyaniline thin films, which enhances the thermal stability of the polymer films

Plasma Assisted Deposition Technique for Synthesis of low Dielectric Constant Polyanisidine Thin Films

Plasma Science, 2002. ICOPS 2002. IEEE Conference Record-Abstracts. The 29th IEEE International Conference on

Dominant Mean Percentage Score Factors Of The Consumer Purchase Behaviour Of Passenger Cars

Globalization and liberalization, with the entry of many prominent foreign manufacturers, changed the automobile scenario in India, since early 1990’s. World Leaders in automobile manufacturing such as Ford, General Motors, Honda, Toyota, Suzuki, Hyundai, Renault, Mitsubishi, Benz, BMW, Volkswagen and Nissan set up their manufacturing units in India in joint venture with their Indian counterpart companies, by making use of the Foreign Direct Investment policy of the Government of India, These manufacturers started capturing the hearts of Indian car customers with their choice of technological and innovative product features, with quality and reliability. With the multiplicity of choices available to the Indian passenger car buyers, it drastically changed the way the car purchase scenario in India and particularly in the State of Kerala. This transformed the automobile scene from a sellers’ market to buyers’ market. Car customers started developing their own personal preferences and purchasing patterns, which were hitherto unknown in the Indian automobile segment. The main purpose of this paper is to come up with the identification of possible parameters and a framework development, that influence the consumer purchase behaviour patterns of passenger car owners in the State of Kerala, so that further research could be done, based on the framework and the identified parameters.

ECG Noise Removal using GA tuned Sign-Data Least Mean Square Algorithm

Adaptive filter is a primary method to filter Electrocardiogram (ECG), because it does not need the signal statistical characteristics. In this paper, an adaptive filtering technique for denoising the ECG based on Genetic Algorithm (GA) tuned Sign-Data Least Mean Square (SD-LMS) algorithm is proposed. This technique minimizes the mean-squared error between the primary input, which is a noisy ECG, and a reference input which can be either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input. Noise is used as the reference signal in this work. The algorithm was applied to the records from the MIT -BIH Arrhythmia database for removing the baseline wander and 60Hz power line interference. The proposed algorithm gave an average signal to noise ratio improvement of 10.75 dB for baseline wander and 24.26 dB for power line interference which is better than the previous reported works