Spatial and temporal analysis of laser induced plasma from a polymer sample

Spatial and temporal analyses of the spectra of the laser induced plasma from a polytetrafluroethylene (PTFE) target obtained with the 1.06 mu m radiation from a Q-switched Nd:YAG laser have been carried out. The spatially resolved spectra of the plasma emission show that molecular bands of C2 (Swan bands) and CN are very intense in the outer regions of the plasma, whereas higher ionized states of carbon are predominant in the core region of the plasma emission. The vibrational temperature and population distribution in the different vibrational levels have been studied as a function of laser energy. From the time resolved studies, it has been observed that there exist fairly large time delays for the onset of emission from all the species in the outer region of the plasma. The molecular bands in each region exhibit much larger time delays in comparison to the ionic lines in the plasma.

Inter- State Variations in Productivity trends and Technological Change in Indian industry

The present study entitled ‘Inter-State Variations in Manufacturing Productivity and Technological Changes in India’ covers a period of 38 years from l960 tol998-99. The study is mainly based on ASI data. The study starts with a discussion of the major facilitating factors of industrialization, namely, historical forces, public policy and infrastructure facilities. These are discussed in greater details in the context of our discussion on Perrox’s (1998) ‘growth pole’ and ‘development pole’, Hirschman’s (1958) ‘industrial centers’ and Myrdal’s ‘spread effect’ Most of the existing literature more or less agrees that the process of industrialization has not been unifonn in all Indian states. There has been a decline in inter-state industrial disparities over time. This aspect is dealt at some length in the third chapter. An important element that deserves detailed attention is the intra-regional differences in industrialisation. Regional industrialisation implies the emergence of a few focal points and industrial regions. Calcutta, Bombay and Madras were the initial focal points. Later other centers like Bangalore, Amritsar, Ahemedabad etc. emerged as nodal points in other states. All major states account for focal points. The analysis made in the third chapter shows that industrial activities generally converge to one or two focal points and industrial regions have emerged out of the focal points in almost all states. One of the general features of these complexes and regions is that they approximately accommodate 50 to 75 percent of the total industrial units and workers in the state. Such convergence is seen hands in glow with urbanization. It was further seen that intra-regional industrial disparity comes down in industrial states like Maharashtra, Gujarat and Uttar Pradesh.

Biennial Metal Discrepancy In The Surface Sediment Of Cochin Estuarine System

This study gave the first report on the biennial metal divergence in the sediments of Cochin Estuarine system (CES). Surface sediments from 6 prominent regions of CES were sampled in 2009 and 2011 for the geochemical and environmental assessment of trace metals (Cd, Co, Cr, Cu, Pb Fe, Mg, Mn, Ni and Zn).Besides texture, total organic carbon (TOC) and CHNS were also done. The contamination and risk assessment were performed by determining geochemical indices. Comparison with sediment quality guidelines were done to assess the probability for ecotoxicological threat to the estuary. Results showed that the measured heavy metals had varied spatial distribution patterns, indicating that they had complex origins and controlling factors

Spatial analysis of C2 band emission from laser produced plasma

Time and space resolved spectroscopic studies of the molecular band emission from C2 are performed in the plasma produced by irradiating a graphite target with 1:06 m radiation from a Q-switched Nd:YAG laser. High-resolution spectra are recorded from points located at distances up to 15 mm from the target in the presence of ambient helium gas pressure. Depending on the laser irradiance, time of observation and position of the sampled volume of the plasma the features of the emission spectrum are found to change drastically. The vibrational temperature and population distribution in the different vibrational levels of C2 molecules have been evaluated as a function of distance for different time delays and laser irradiance. It is also found that the vibrational temperature of C2 molecules decreases with increasing helium pressure.

Spatial and time resolved analysis of CN bands in the laser induced plasma from graphite

Analysis of the emission bands of the CN molecules in the plasma generated from a graphite target irradiated with 1-06/~m radiation pulses from a Q-switched Nd:YAG laser has been done. Depending on the position of the sampled volume of the plasma plume, the intensity distribution in the emission spectra is found to change drastically. The vibrational temperature and population distribution in the different vibrational levels have been studied as function of distance from the target for different time delays with respect to the incidence of the laser pulse. The translational temperature calculated from time of flight is found to be higher than the observed vibrational temperature for CN molecules and the reason for this is explained.

Studies on rainfall variability and the influence of orography and land use on the climate of Peninsular India

The present study helped to understand the trend in rainfall patterns at smaller spatial scales and the large regional differences in the variability of rainfall. The effect of land use and orography on the diurnal variability is also understood. But a better understanding on the long term variation in rainfall is possible by using a longer dataset,which may provide insight into the rainfall variation over country during the past century. The basic mechanism behind the interannual rainfall variability would be possible with numerical studies using coupled Ocean-Atmosphere models. The regional difference in the active-break conditions points to the significance of regional studies than considering India as a single unit. The underlying dynamics of diurnal variability need to be studied by making use of a high resolution model as the present study could not simulate the local onshore circulation. Also the land use modification in this study, selected a region, which is surrounded by crop land. This implies the high possibility for the conversion of the remaining region to agricultural land. Therefore the study is useful than considering idealized conditions, but the adverse effect of irrigated crop is more than non-irrigated crop. Therefore, such studies would help to understand the climate changes occurred in the recent period. The large accumulation of rainfall between 300-600 m height of western Ghats has been found but the reason behind this need to be studied, which is possible by utilizing datasets that would better represent the orography and landuse over the region in high resolution model. Similarly a detailed analysis is needed to clearly identify the causative relations of the predictors identified with the predictant and the physical reasons behind them. New approaches that include nonlinear relationships and dynamical variables from model simulations can be included in the existing statistical models to improve the skill of the models. Also the statistical models for the forecasts of monsoon have to be continually updated.

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.