Haematological responses of green mussel Perna viridis (Linnaeus) to heavy metals copper and mercury

Department of Marine Biology, Microbiology and Biochemistry, Cochin University of Science and Technology

Toxicological effects of Copper and Mercury on the fish Macrones gulio (Hamilton-Buchanan)

Asha M. R This thesis Entitled Toxicological effects of copper and mercury on the fish macerones gulio (hamiloton – buchanan).Chapter 1. In this chapter, a broad outline of heavy metal uptake, requirement of a suitable bio — monitoring organism, criteria for a standard test fish, and suitability of Macrones gulig for the toxicological study are given. Chapter 2. This chapter deals with the lethal toxicity bioassays to find the 96 hr LC 50 of copper and mercury for the fish Macrones gglig. The experimental results indicated that of the two metals tested, copper was more toxic than mercury.Chapter 3. The effect of copper and mercury on the haemoglobin, haematocrit, erythrocyte count, MCV, MCH and MCHC was studied.Chapter 4. The glycogen and protein contents of liver and muscle after exposure to copper and mercury were studied. There was a significant decrease of glycogen in the liver and muscle of metal treated fishes.Chapter 5. The histopathological changes of the tissues like liver, kidney and gill after exposure to copper and mercury were studied.

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,

Environmental impact of sand mining

This thesis Entitled Environmental impact of Sand Mining :A case Study in the river catchments of vembanad lake southwest india.The entire study is addressed in nine chapters. Chapter l deals with the general introduction about rivers, problems of river sand mining, objectives, location of the study area and scope of the study. A detailed review on river classification, classic concepts in riverine studies, geological work of rivers and channel processes, importance of river ecosystems and its need for management are dealt in Chapter 2. Chapter 3 gives a comprehensive account of the study area - its location, administrative divisions, physiography, soil, geology, land use and living and non-living resources. The various methods adopted in the study are dealt in Chapter 4. Chapter 5 contains river characteristics like drainage, environmental and geologic setting, channel characteristics, river discharge and water quality of the study area. Chapter 6 gives an account of river sand mining (instream and floodplain mining) from the study area. The various environmental problems of river sand mining on the land adjoining the river banks, river channel, water, biotic and social / human environments of the area and data interpretation are presented in Chapter 7. Chapter 8 deals with the Environmental Impact Assessment (EIA) and Environmental Management Plan (EMP) of sand mining from the river catchments of Vembanad lake.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

The Impact of Integrated Marine Fisheries ‘Development Project Among the Artisanal Fishermen in Kerala

Despite various intervensions, artisanal fishermen remain one of the weaker sections in Kerala's society. Host of the welfare and developmental programmes introduced for them had produced very little impact on their living conditions. Further, they are unable to compete with mechanised sector for fishing. Host of the technological development which had taken place after Indo-Norvegean Project favoured the growth of mechanised sector. As a consequence of this, fishing become unviable for artisanal fishermen who propagate the idea of ” sustainable development” in the fishing industry. It is commonly believed that an integrated approach may help them to improve their living conditions substantially. In the light of the above background the scholar has made an attempt to study the impact of Integrated Marine Fisheries Development Project among artisanal fishermen in Kerala It is realised from the findings of the study that the most important needs of artisanal fishermen arecredit facilities and marketing support. Without marketing linkages effective credit management is not possible. Marketing activities and credit management are interdependent

Chemical Evaluation of Selected Organics and Trace Metals in the Mangrove Macroflora Of Cochin

Mangroves are considered to play a significant role in global carbon cycling. Themangrove forests would fix CO2 by photosynthesis into mangrove lumber and thus decrease the possibility of a catastrophic series of events - global warming by atmospheric CO2, melting of the polar ice caps, and inundation of the great coastal cities of the world. The leaf litter and roots are the main contributors to mangrove sediments, though algal production and allochthonous detritus can also be trapped (Kristensen et al, 2008) by mangroves due to their high organic matter content and reducing nature are excellent metal retainers. Environmental pollution due to metals is of major concern. This is due to the basic fact that metals are not biodegradable or perishable the way most organic pollutants are. While most organic toxicants can be destroyed by combustion and converted into compounds such as C0, C02, SOX, NOX, metals can't be destroyed. At the most the valance and physical form of metals may change. Concentration of metals present naturally in air, water and soil is very low. Metals released into the environment through anthropogenic activities such as burning of fossils fuels, discharge of industrial effluents, mining, dumping of sewage etc leads to the development of higher than tolerable or toxic levels of metals in the environment leading to metal pollution. Of course, a large number of heavy metals such as Fe, Mn, Cu, Ni, Zn, Co, Cr, Mo, and V are essential to plants and animals and deficiency of these metals may lead to diseases, but at higher levels, it would lead to metal toxicity. Almost all industrial processes and urban activities involve release of at least trace quantities of half a dozen metals in different forms. Heavy metal pollution in the environment can remain dormant for a long time and surface with a vengeance. Once an area gets toxified with metals, it is almost impossible to detoxify it. The symptoms of metal toxicity are often quite similar to the symptoms of other common diseases such as respiratory problems, digestive disorders, skin diseases, hypertension, diabetes, jaundice etc making it all the more difficult to diagnose metal poisoning. For example the Minamata disease caused by mercury pollution in addition to affecting the nervous system can disturb liver function and cause diabetes and hypertension. The damage caused by heavy metals does not end up with the affected person. The harmful effects can be transferred to the person's progenies. Ironically heavy metal pollution is a direct offshoot of our increasing ability to mass produce metals and use them in all spheres of existence. Along with conventional physico- chemical methods, biosystem approachment is also being constantly used for combating metal pollution

Applying Data mining using Statistical Techniques for Career Selection

For years, choosing the right career by monitoring the trends and scope for different career paths have been a requirement for all youngsters all over the world. In this paper we provide a scientific, data mining based method for job absorption rate prediction and predicting the waiting time needed for 100% placement, for different engineering courses in India. This will help the students in India in a great deal in deciding the right discipline for them for a bright future. Information about passed out students are obtained from the NTMIS ( National technical manpower information system ) NODAL center in Kochi, India residing in Cochin University of science and technology

A Data Mining Approach for the Identification of Adverse Drug Events (ADE) resulting from Drug-Drug Interactions (DDI) to improve pharmacovigilance

In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance