INVESTIGATIONS ON THE STRESS EFFECTS OF PETROLEUM HYDROCARBONS ON METAPENAEUS DOBSON (MIERS)

The present investigation has addressed the effects of PHC contaminated culture medium on the morphology, physiology and behaviour of shrimps. The shrimp Metapenaeus dobsoni is an important member of the crustacean animal community abounding the oil contaminated benthic regions of Cochin backwater system. Since it is known that true pollutants can disrupt the sustainability of ecosystems by its effect on species, populations and communities,a representative species was used for the study. The results discussed in this work is bound to help in understanding the ecotoxicant resistance that the animal may display under toxic conditions compared to dynamic steady-state systems in nature.

Investigations on the stress effects of petroleum hydrocarbons on Metapenaeus dobsoni (Miers)

The present investigation has addressed the eflects of PHC contaminated culture medium on the morphology, physiology and behaviour of shrimps] The shrimp Metapenaeus dobsoni is an important member of the crustacean animal community abounding the oil contaminated benthic regions of Cochin backwater system. Since it is known that true pollutants can disrupt the sustainability of ecosystems by its eflect on species, populations and communities, a representative species was used for the study. The results discussed in this work is bound to help in understanding the ecotoxicant resistance that the animal may display under toxic conditions compared to aynamic steaay-state systems in nature

Detection of Flock Movement in Spatio-Temporal Database using Clustering Techniques - an Experience

In this paper, moving flock patterns are mined from spatio- temporal datasets by incorporating a clustering algorithm. A flock is defined as the set of data that move together for a certain continuous amount of time. Finding out moving flock patterns using clustering algorithms is a potential method to find out frequent patterns of movement in large trajectory datasets. In this approach, SPatial clusteRing algoRithm thrOugh sWarm intelligence (SPARROW) is the clustering algorithm used. The advantage of using SPARROW algorithm is that it can effectively discover clusters of widely varying sizes and shapes from large databases. Variations of the proposed method are addressed and also the experimental results show that the problem of scalability and duplicate pattern formation is addressed. This method also reduces the number of patterns produced