21 research outputs found

    Role of hydrographical parameters and total organic carbon on mercury allocation along the riverine transect of Beypore, south-west coast of India

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    1419-1426Distribution of total mercury (THg) was carried out in the sediments of Beypore estuary. The THg concentration in surface sediments varied from 0.03 ppm to 0.17 ppm. The pollution index approach using contamination factor (CF) revealed that the sampling stations are moderately contaminated with respect to mercury. Further, the effects of hydrographical parameters (pH, salinity, dissolved oxygen) and total organic carbon (TOC) of the sediment were studied over the spatial distribution of mercury (Hg). Correlation analysis unveiled THg exhibited significant positive correlations with TOC (R=0.91) and salinity (R=0.744). However significant inverse correlation was observed between pH and Hg (R =-0.93). The C: N ratios suggest that the organic matter is labile in nature. Total organic carbon was found to control the distribution of Hg. It is the first base line study in this estuary

    Spatial variability of biochemical composition in coral reef sediments of Kavaratti and Pitti islands, Lakshadweep archipelago

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    369-378In this study, variability of biochemical composition in the surficial coral reef sediments of Kavaratti and Pitti islands in Lakshadweeep archipelago was investigated. Biochemical composition of sedimentary organic matter from the study area was characterized by the dominance of proteins in Pitti and carbohydrates in Kavaratti over lipids. The percentage ratio of the labile to total organic matter indicated that most of the deposited organic matter was refractory in both environments. The higher PRT:CHO ratios in Pitti sediments compared to that of Kavaratti indicated that in the former there was low dead organic matter accumulation. The lower LPD:CHO ratios estimated for sediments in both islands indicated low quality of labile organic matter to support benthic fauna

    Practical stability criteria for cellular neural networks

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