Nitrifying Bioreactors Integrated into Shrimp and Prawn Hatchery Systems: Molecular Characterization of the Nitrifying Consortia,Reactor Kinetics, Modeling and Validation

National Centre for Aquatic Animal Health, Cochin University of Science and Technology

Kinetics of martensitic transitions in Cu-Al-Mn under thermal cycling: Analysis at multiple length scales

In this paper we study the evolution of the kinetic features of the martensitic transition in a Cu-Al-Mn single crystal under thermal cycling. The use of several experimental techniques including optical microscopy, calorimetry, and acoustic emission, has enabled us to perform an analysis at multiple scales. In particular, we have focused on the analysis of avalanche events (associated with the nucleation and growth of martensitic domains), which occur during the transition. There are significant differences between the kinetics at large and small length scales. On the one hand, at small length scales, small avalanche events tend to sum to give new larger events in subsequent loops. On the other hand, at large length scales the large domains tend to split into smaller ones on thermal cycling. We suggest that such different behavior is the necessary ingredient that leads the system to the final critical state corresponding to a power-law distribution of avalanches.

Development of plant tissue culture of Plumbago rosea Linn. for enhanced production of secondary metabolites

P rosea syn. Indica belong to the family of plumbaginaceae, is an important medicinal plant, cultivated widely in India. The roots of these plant are generally used for medicinal purposes mainly as diuretic, germicidal, vessicant, and abortifacient. It is also used for anaemia, diarrhea, leprosy and common wart. The bark of the root contains orange yellow pigment named plumbagin, a crystalline substance, belongs to the class of naphthoquinone. Its chemical structure is 5-hydroxy 2-methyl 1,4naphthoquinone. Apart from P rosea, P zeylanica, P europea, Drosera and Drosophyllum also contains plumbagin. The most exploited source of plumbagin is, of course, P. rosea roots. The roots contain O.9mg/ g D.Wt. of plumbagin in the roots. These plants grow very slowly and the roots suitable for plumbagin extraction can be obtained only after several years of growth. The productivity of the plant is also rather poor. The focus of the present study was to develop alternative strategies to obtain plumbagin. The tissue culture of P rosea for micropropagation has been studied

Culture and growth kinetics of selected nanoplankters

The present study on naoplankton is based on the isolation and development of unialgai culturas from the inshore waters at Cochin. characterization of their growth assimilation products. ecophysioiogy and evaluation of nutritional quality. The work was carried out during the period 1980-1983. The nanoplankters were isolated and grown in the labratory as batch cultures to study the increase in cell population, the photosynthetic pigment: ana physioiogical activity. The chemical composition of these organisms and their rate of excretion were also determined. The environmental factors physical and chemical that influence the growth of these Cultures were defined by conducting independentexperiments. These cultures of the isolated nanoplankters have raised indoor and fed to the larvae of edible oyster to test their suitability as live-food.

Kinetics and mechanism of urea - formaldehyde and related reactions

Urea-formaldehyde resins find numerous applications in adhesive, textile finishing and moulded plastic industries. Kinetic investigations of the reactions of urea and its related compounds with formaldehyde in aqueous acid, alkaline and neutral media have been carried out. A thin—layer chromatographic method was developed for the separation and estimation of the products of these reactions. Using this technique the various initial steps in the reactions were analysed and the rate constants have been determined.

Development of a cell culture system from the ovarian tissue of African catfish Clarias gariepinus

A growth medium with Leibovitz-15 L-15.as the base, supplemented with foetal bovine serum 10% vrv., fish muscle extract 10% vrv., prawn muscle extract 10% vrv., lectin concanavalin A. 0.02 mg mly1., lipopolysaccharide 0.02 mg mly1., glucose D 0.2 mg mly1., ovary extract 0.5% vrv.and prawn haemolymph 0.5%. has been formulated with 354"10 mOsm for the development and maintenance of a cell culture system from the ovarian tissue of African catfish, Clarias gariepinus. For its subculturing, a cell dissociationrextracting solution, composed of equal portions of trypsin phosphate versene glucose TPVG. containing 0.0125% wrv.trypsin and 25% vrv.non-enzymatic cell dissociation solution 1 and 2, has also been developed with which the cell culture can be passaged 15 times after which they cease to multiply and consequently perish. The cell cultures can be maintained for 12–15 days without fluid change between the passages. This is the first report of a cell culture system from the ovarian tissues of African catfish

Spectral clustering independent component analysis for tissue classification from brain MRI

A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches in abnormal tissue extraction. First, input multispectral MRI is divided into different clusters by a spectral distance based clustering. Then, Independent Component Analysis (ICA) is applied on the clustered data, in conjunction with Support Vector Machines (SVM) for brain tissue analysis. Normal and abnormal datasets, consisting of real and synthetic T1-weighted, T2-weighted and proton density/fluid-attenuated inversion recovery images, were used to evaluate the performance of the new method. Comparative analysis with ICA based SVM and other conventional classifiers established the stability and efficiency of SC-ICA based classification, especially in reproduction of small abnormalities. Clinical abnormal case analysis demonstrated it through the highest Tanimoto Index/accuracy values, 0.75/98.8%, observed against ICA based SVM results, 0.17/96.1%, for reproduced lesions. Experimental results recommend the proposed method as a promising approach in clinical and pathological studies of brain diseases

Brain Tissue Classification from Multispectral MRI by Wavelet based Principal Component Analysis

In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.

Wavelet based Independent Component Analysis for Multispectral Brain Tissue Classification

Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an effective method for source signals separation from multispectral MR data. However, it often fails to extract the local features like small abnormalities, especially from dependent real data. A multisignal wavelet analysis prior to ICA is proposed in this work to resolve these issues. Best de-correlated detail coefficients are combined with input images to give better classification results. Performance improvement of the proposed method over conventional ICA is effectively demonstrated by segmentation and classification using k-means clustering. Experimental results from synthetic and real data strongly confirm the positive effect of the new method with an improved Tanimoto index/Sensitivity values, 0.884/93.605, for reproduced small white matter lesions

Area and Volume Calculation of Necrotic Tissue regions of heart using Interpolation

This paper attempts to develop an improved tool, which would read two dimensional(2D) cardiac MRI images and compute areas and volume of the scar tissue. Here the computation would be done on the cardiac MR images to quantify the extent of damage inflicted by myocardial infarction on the cardiac muscle (myocardium) using Interpolation

Cure Kinetics and Sorption Characteristics of Neoprene-Based Rubber Ferrite Composites

Rubber ferrite composites were prepared by incorporating nickel ferrite in a neoprene rubber matrix. Kinetics of the cure reaction were determined from the rheometric torque values and found to follow first-order kinetics. Analysis of the swelling behavior of the rubber ferrite composites in toluene elucidates the mechanism of solvent penetration and sorption characteristics, and reveals the extent of the physical interaction of the ferrite particles with the neoprene rubber matrix. Mechanical properties of rubber ferrite composites were determined, which support the reinforcing nature of nickel ferrite to the neoprene rubber matrix. These results show that magnetic composites with the required processing safety can be prepared economically by incorporating higher amounts of nickel ferrite in the neoprene rubber matrix

Study of chemical properties and evaluation of collagen in mantle, epidermal connective tissue and tentacle of Indian Squid, Loligo duvauceli Orbigny

The chemical composition and evaluation of Indian squid (Loligo duvauceli) mantle, epidermal connective tissue and tentacle is investigated in this current study. It is observed that squid mantle contains 22.2% total protein; 63.5% of the total protein is myofibrillar protein. The unique property of squid myofibrillar protein is its water solubility. Squid mantle contains 12.0% total collagen. Epidermal connective tissue has highest amounts of total collagen (17.8%). SDS-PAGE of total collagen identified high molecular weight α-, β- and γ- sub-chains. Amino acid profile analysis indicates that mantle and tentacle contain essential amino acids. Arginine forms a major portion of mantle collagen (272.5 g/100 g N). Isoleucine, glutamic acid and lysine are other amino acids that are found in significantly high amounts in the mantle. Sulphur containing cystine is deficit in mantle collagen. Papain digest of mantle and epidermal connective tissue is rich in uronic acid, while papain digest, collagenase digest and urea digest of epidermal connective tissue has significant amounts of sialic acid (25.2, 33.2 and 99.8 μmol /100 g, respectively). PAS staining of papain digest, collagenase digest and urea digest also identify the association of hexoses with low molecular weight collagen fragments. Histochemical sectioning also emphasized the localized distribution of collagen in epidermal and dermal region and very sparse fibres traverse the myotome bundles

Effects of dietary lipid source on growth, digestibility and tissue fatty acid composition of Heterobranchus longifilis fingerlings

One of the major problems facing aquaculture is the inadequate supply of fish oil mostly used for fish feed manufacturing. The continued growth in aquaculture production cannot depend on this finite feed resources, therefore, it is imperative that cheap and readily available substitutes that do not compromise fish growth and fillet quality be found. To achieve this, a 12-week feeding trial with Heterobranchus longifilis fed diets differing in lipid source was conducted. Diets were supplemented with 6% lipid as fish oil, soybean oil, palm oil, coconut oil, groundnut oil and melon seed oil. Triplicate groups of 20 H. longifilis were fed the experimental diets two times a day to apparent satiation, over 84 days. Growth, digestibility, and muscle fatty acid profile were measured to assess diet effects. At the end of the study, survival, feed intake and hepatosomatic index were similar for fish fed experimental diets. However, weight gain, SGR and FCR of fish fed soybean oil-based diet was significantly reduced. Apparent nutrient digestibility coefficients were significantly lower in fish fed soybean, coconut and groundnut oil-based diets. Fillet and hepatic fatty acid compositions differed and reflected the fatty acid compositions of the diets. Docosahexaenoic acid (22:6n-3), 20:5n-3 and 20:4n-6 were conserved in vegetable oils-based diets fed fish possibly due to synthesis of HUFA from 18:3n-3 and 18:4n-6. Palm oil diet was the least expensive, and had the best economic conversion ratio. The use of vegetable oils in the diets had positive effect on growth and fillet composition of H. longifilis.

Segmentation of Brain Tissue from Magnetic Resonance Images

Segmentation of medical imagery is a challenging problem due to the complexity of the images, as well as to the absence of models of the anatomy that fully capture the possible deformations in each structure. Brain tissue is a particularly complex structure, and its segmentation is an important step for studies in temporal change detection of morphology, as well as for 3D visualization in surgical planning. In this paper, we present a method for segmentation of brain tissue from magnetic resonance images that is a combination of three existing techniques from the Computer Vision literature: EM segmentation, binary morphology, and active contour models. Each of these techniques has been customized for the problem of brain tissue segmentation in a way that the resultant method is more robust than its components. Finally, we present the results of a parallel implementation of this method on IBM's supercomputer Power Visualization System for a database of 20 brain scans each with 256x256x124 voxels and validate those against segmentations generated by neuroanatomy experts.