Biochemical effects of ethanol on oreochromis mossambicus (Peters)

The present study dealt with the haematological, biochemical and istopathological impacts of different sub lethal concentrations of ethanol on a euryhaline teleost Oreochromis In05.s‘ambicu.5' (Peters).Studies carried out using GC indicated an increase in blood ethanol oncentration of the fish which mainly arose due to fishes entering into a state of hypoxia which explains ethanol production as an ubiquitous “anaerobic” end product, which gets accumulated whenever metabolic demand exceeds the mitochondrial oxidative potential. The very low amount of ethanol detected in the control group ofO mossambicns was mainly due to the activity of microorganisms in the gut ofO. Nzossambicus.Oedcma observed in the present study, is a defense mechanism that reduces the branchial superficial area of the fish which comes in contact with the external milieu. These mechanisms also increase the diffusion barrier to the pollutant. Dilation of the blood vessels is due to increased permeability helping in the free passage of ethanol into the blood stream. Telangiectasis observed explains the state of asphyxia of the fish when subjected to ethanol toxicity indicating acute respiratory distress. Gill aneurysm observed indicates impaired respiratory function. This is related to the rupture of the pillar cells which results in an increased blood flow inside the lamellae, causing dilation of the blood vessel or even aneurysm of gill.The present findings warrant future studies to explore A'T'Pases as possible biomarkers of pollutant exposure in ecotoxicology. This study indicated that O. mossambicus when exposed for 7 and 21 days to ethanol was under tremendous stress and parameters employed in this study can be adapted for future investigations as biomarkers of damage caused by ethanol to aquatic organisms. The present study revealed that O. mossambicus is sensitive to sub lethal concentrations of ethanol.

CBIR Using Local and Global Properties of Image Sub-blocks

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation and finding the corner density in each partition. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). Euclidean distance measure is used for computing the distance between the features of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Pathological changes in Fenneropenaeus indicus experimentally infected with white spot virus and virus morphogenesis

To demonstrate pathological changes due to white spot virus infection in Fenneropenaeus indicus, a batch of hatchery bred quarantined animals was experimentally infected with the virus. Organs such as gills, foregut, mid-gut, hindgut, nerve, eye, heart, ovary and integument were examined by light and electron microscopy. Histopathological analyses revealed changes hitherto not reported in F. indicus such as lesions to the internal folding of gut resulted in syncytial mass sloughed off into lumen, thickening of hepatopancreatic connective tissue with vacuolization of tubules and necrosis of rectal pads in hindgut. Virus replication was seen in the crystalline tract region of the compound eye and eosinophilic granules infiltrated from its base. In the gill arch, dilation and disintegration of median blood vessel was observed. In the nervous tissues, encapsulation and subsequent atrophy of hypertrophied nuclei of the neurosecretory cells were found. Transmission electron microscopy showed viral replication and morphogenesis in cells of infected tissue. De novo formed vesicles covered the capsid forming a bilayered envelop opened at one end inside the virogenic stroma. Circular vesicles containing nuclear material was found fused with the envelop. Subsequent thickening of the envelop resulted in the fully formed virus. In this study, a correlation was observed between the stages of viral multiplication and the corresponding pathological changes in the cells during the WSV infection. Accordingly, gill and foregut tissues were found highly infected during the onset of clinical signs itself, and are proposed to be used as the tissues for routine disease diagnosis.

Mathematical Morphology on Hypergraphs Using Vertex-Hyperedge Correspondence

The focus of this paper is to develop computationally efficient mathematical morphology operators on hypergraphs. To this aim we consider lattice structures on hypergraphs on which we build morphological operators. We develop a pair of dual adjunctions between the vertex set and the hyperedge set of a hypergraph , by defining a vertex-hyperedge correspondence. This allows us to recover the classical notion of a dilation/erosion of a subset of vertices and to extend it to subhypergraphs of . This paper also studies the concept of morphological adjunction on hypergraphs for which both the input and the output are hypergraphs

Morphological filtering on hypergraphs

The focus of this article is to develop computationally efficient mathematical morphology operators on hypergraphs. To this aim we consider lattice structures on hypergraphs on which we build morphological operators. We develop a pair of dual adjunctions between the vertex set and the hyper edge set of a hypergraph H, by defining a vertex-hyperedge correspondence. This allows us to recover the classical notion of a dilation/erosion of a subset of vertices and to extend it to subhypergraphs of H. Afterward, we propose several new openings, closings, granulometries and alternate sequential filters acting (i) on the subsets of the vertex and hyperedge set of H and (ii) on the subhypergraphs of a hypergraph

Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques

This paper describes a novel framework for automatic segmentation of primary tumors and its boundary from brain MRIs using morphological filtering techniques. This method uses T2 weighted and T1 FLAIR images. This approach is very simple, more accurate and less time consuming than existing methods. This method is tested by fifty patients of different tumor types, shapes, image intensities, sizes and produced better results. The results were validated with ground truth images by the radiologist. Segmentation of the tumor and boundary detection is important because it can be used for surgical planning, treatment planning, textural analysis, 3-Dimensional modeling and volumetric analysis