HEAVY METAL TOXICITY IN BIVALVE- HISTOLOGICAL AND HISTOCHEMICAL ENQUIRY

Division of Marine Biology, Microbiology and Biochemistry, School of Marine Sciences, Cochin University of Science and Technology

BIOCHEMICAL GENETIC STUDIES ON THE OIL SARDINE, Sardinella longiceps (CUVIER AND VALENCIENNES, 1847) FROM SELECTED CENTRES OF THE WEST COAST OF INDIA

The main objective of the present investigation was to study the biochemical genetic variability within the species and genetic structure of its regional populations from west coast. Realising the recent report of occurrence of oil sardine fishery in east coast of India, population samples from Mandapam and Madras were also included in the present investigation. The original data gathered on the population genetics of the species have helped to interpret and evaluate the results objectively. The important conclusions drawn from a detailed discussions on the subject would throw some light on the probable process of problematic fluctuations in the abundance of oil sardine fishery of India. The academic and applied values of present discoveries need not be emphasised. The data used for the doctoral thesis were generated during the ICAR ad-hoc project on the "Population genetic studies on oil sardine, sardinella longiceps to identity distinct genetic stocks", carried out at CMFRI, Cochin during the years, 1988-1991

Nitrifying Bioreactors Integrated into Shrimp and Prawn Hatchery Systems: Molecular Characterization of the Nitrifying Consortia,Reactor Kinetics, Modeling and Validation

National Centre for Aquatic Animal Health, Cochin University of Science and Technology

Precursor nanoscale modulations in ferromagnets: Modeling and thermodynamic characterization

Using a Ginzburg-Landau model for the magnetic degrees of freedom with coupling to disorder, we demonstrate through simulations the existence of stripelike magnetic precursors recently observed in Co-Ni-Al alloys above the Curie temperature. We characterize these magnetic modulations by means of the temperature dependence of local magnetization distribution, magnetized volume fraction, and magnetic susceptibility. We also obtain a temperature-disorder strength phase diagram in which a magnetic tweed phase exists in a small region between the paramagnetic and dipolar phases.

Studies on the effect of toxic heavy metal mercury on the physiology and biochemistry of an estuarine crab Scylla serrata (Forskal)

This thesis Entitled studies on the effect of toxic heavy metal mercury on the physiology and biochemistry of an estuarine crab scylla serrata (Forskal). Evaluate the toxicity of three sub lethal concentrations of mercury, viz., 0.009 mg/l, 0.02 mg/1, and 0.04 mg/l on the mud crab, Scylla serrata through bioaccumulation, and depuration studies. To characterize the biochemical responses to the sub-lethal stress of mercury in chelate muscles, abdominal muscles, hepatopancreas and gills. To study the activity pattern of acid and alkaline phosphatases in mercury-exposed crabs. To evaluate the induced changes in these tissues through histopathological studies,The Cochin backwaters is one of the most productive and biologically active backwater systems, and is the habitat of varieties of fishes, mollusks, and crustaceans, though this water body also receives tons of effluents from factories located on the banks of the river, Periyar.To study the activity levels of acid and alkaline phosphatases in crabs, at three time periods, exposed to three sub lethal concentration of mercury,

‘Modeling and Analysis of Competing Risks Data’

there has been much research on analyzing various forms of competing risks data. Nevertheless, there are several occasions in survival studies, where the existing models and methodologies are inadequate for the analysis competing risks data. ldentifiabilty problem and various types of and censoring induce more complications in the analysis of competing risks data than in classical survival analysis. Parametric models are not adequate for the analysis of competing risks data since the assumptions about the underlying lifetime distributions may not hold well. Motivated by this, in the present study. we develop some new inference procedures, which are completely distribution free for the analysis of competing risks data.

Some Aspects of Domain Specific Conceptual Modeling for Simulation of Logistic Terminal Operations

When simulation modeling is used for performance improvement studies of complex systems such as transport terminals, domain specific conceptual modeling constructs could be used by modelers to create structured models. A two stage procedure which includes identification of the problem characteristics/cluster - ‘knowledge acquisition’ and identification of standard models for the problem cluster – ‘model abstraction’ was found to be effective in creating structured models when applied to certain logistic terminal systems. In this paper we discuss some methods and examples related the knowledge acquisition and model abstraction stages for the development of three different types of model categories of terminal systems

Modeling and Analysis of Two-Part Type Manufacturing Systems

This paper presents a model and analysis of a synchronous tandem flow line that produces different part types on unreliable machines. The machines operate according to a static priority rule, operating on the highest priority part whenever possible, and operating on lower priority parts only when unable to produce those with higher priorities. We develop a new decomposition method to analyze the behavior of the manufacturing system by decomposing the long production line into small analytically tractable components. As a first step in modeling a production line with more than one part type, we restrict ourselves to the case where there are two part types. Detailed modeling and derivations are presented with a small two-part-type production line that consists of two processing machines and two demand machines. Then, a generalized longer flow line is analyzed. Furthermore, estimates for performance measures, such as average buffer levels and production rates, are presented and compared to extensive discrete event simulation. The quantitative behavior of the two-part type processing line under different demand scenarios is also provided.

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Experimental Modeling and Control Strategies on an Open Mobile Robot Platform PRIM

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system

Factor saving innovations and factor income shares

We present an endogenous growth model where innovations are factor saving. Technologies can be changed paying a cost and technological change takes place only if the benefits are larger than the costs. Since the gains derived from factor saving innovations depend on factor abundance, biased innovations respond to changes in factors supply. Therefore, as an economy becomes more capital abundant agents try to use capital more intensively. Consequently, (a) the elasticity of output with respect to reproducible factors depends on the capital abundance of the economy and (b) the income share of reproducible factors increases as the economy grows. Another insight of the model is that in some economies the production function converges to an AK in the long run, while in others long-run growth is zero