Studies on the Effect of High Energy Ball Milling On the Structural, Electrical and Magnetic Properties of Some Normal Spinets in the Ultrafine Regime

The present work is an attempt to understand the characteristics of high energy ball milling on the structural, electrical and magnetic properties of some normal spinets in the ultra fine regime, Magnetism and magnetic materials have been a fascinating subject for the mankind ever since the discovery of lodestone. Since then, man has been applying this principle of magnetism to build devices for various applications. Magnetism can be classified broadly into five categories. They are diamagnetic, paramagnetic, ferromagnetic antiferromagnetic and ferrimagnetic. Of these, ferro and ferri magnetic materials assume great commercial importance due to their unique properties like appropriate magnetic characteristics, high resistivity and low eddy current losses. The emergence of nanoscience and nanotechnology during the last decade had its impact in the field of magnetism and magnetic materials too. Now, it is common knowledge that materials synthesized in the nanoregime exhibit novel and superlative properties with respect to their coarser sized counterparts in the micron regime. These studies reveal that dielectric properties can be varied appreciably by high-energy ball milling in nanosized zinc ferrites produced by coprecipitation method. A semi conducting behaviour was observed in these materials with the Oxygen vacancies acting as the main charge carrier for conduction, which was produced at the time of coprecipitation and milling. Thus through this study, it was possible to successfully investigate the finite size effects on the structural, electrical and magnetic properties of normal spinels in the ultra fine regime

Application of Biofloc Technology (BFT) in the nursery rearing and farming of giant freshwater prawn, Macrobrachium rosenbergii (deMan)

In India a study conducted by CIFE and CIBA (1997), concluded that shrimp farming does more good than harm and it is not eco-unfriendly (Krishnan and Birthal, 2002). Upsurge in coastal aquaculture activity induced by high profitability is reported to have caused adverse impacts on coastal ecosystems and social environments (Parthasarathy and Nirmala, 2000). The crustacean farming sector has received criticism for excessive use of formulated feed containing high protein, of which around 50% gets accumulated at the pond bottom as unconsumed (Avnimelech, 1999; Hari et al., 2004, 2006). The wasted feeds undergo the process of degradation and results in the release of toxic metabolites to the culture system. Reduction of protein in the feed, manipulation and utilisation of natural food in the culture system are the remedy for the above problems. But before reducing the feed protein, it should be confirmed that the feed with reduced protein is not affecting the growth and health of the cultured animal. In the present study, biofloc technology is identified as one of the innovative technologies for ensuring the ecological and environmental Sustainability and examines the compatibility of BFT for the sustainable aquaculture of giant prawn, M. rosenbergii. This thesis starts with a general introduction (Chapter-1), a brief review of the most relevant literature (Chapter-2), results of various experiments (Chapter-3-6), summary (Chapter-7) and recommendations and future research perspectives in the field of biofloc based aquaculture (Chapter – 8). The major objectives of this thesis are, to improve the ecological and economical sustainability of prawn farming by the applicationof BFT and to improve the nutrient utilisation in aquaculture systems.

" Nonlinear Signal Processing of Electroencephalogram .' Application in the Study of Neurodynamics. "

Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.