Studies on biochemical genetics of the grey mullet Mugil cephalus linnaeus

The thesis deals with the results of an investigation on the "BIOCHEMICAL GENETICS OF MUGIL CEPHALUS" from Cochin, Madras and Orissa. It is presented under the following major headings: Introduction, Review of Literature, Materials and Methods, Results, Discussions, Conclusions, Recommendations, Summary and References.The introduction gives a brief account of historical and modern back ground on the stock concept in fisheries research and management, followed by the importance and potential role of biochemical genetics in the identification of natural units of fisheries management. In the review of literature published reports relevant to biochemical genetics with special reference to that of general proteins and enzyme systems of fish populations were considered. A detailed account of the source of experimental specimens, mode of collection, transportation, sample extraction, gel preparation/gel electrophoresis, buffer systems, staining procedures of proteins/enzymes, standardization of experiments, interpretation of electrophoretic data using basic formulae etc. are given in the materials and methods section. Four important conclusions were drawn on the basis of the results of the present investigation. Three recommendations were also made on the basis of evaluation of the results.

Studies on some aspects of the reproductive physiology of the female grey mullet mugil cephalus l.

Aquaculture is the dynamic pursuit of production of organisms from water a process analogous to agriculture on land. The field of aquaculture is an emerging bioindustry, based upon the culture and husbandry of economically utilizable aquatic organisms. Of late, there has been a global upsurge for aquaculture, the main reasons for which include the requirement of protein source for the increasing world population, the decision by various world nations to increase the fish yield by developing unutilized or partially utilized water bodies and depletion of natural stock which is evident in recent years due to excessive exploitation .The present study has been taken up on the reproductive physiology of the female grey mullet, M. cephalus. The thesis is presented in seven chapters. In the present study, variations in the major biochemical parameters namely, moisture, proteins, lipids, carbohydrates cholesterol, carotenoid, ash, calcium and iron in four tissues E. muscle, liver, ovary and bloodserum of cephalus have been analysed at different maturity stages.

Studies on the digestive enzymes of the cultivable grey mullet liza parsia (hamilton buchanan, 1822)

Culturing of fish in captivity demands a detailed knowledge on well balanced diet and adequate feeding. Formulation and production of nutritionally balanced diets for fish require research, quality control and biological evaluation. It is often assuemed that what is ingested is also digested, but this is not always be the case. Digestion depends upon both the physical state of the food and the kind and quantity of enzymes in the digestive tract. The ability of fish to digest a particular component of diet can be ascertained by investigating the complement of digestive enzymes present along the digestive tract. Investigations on the basic digestive physiology will not only enhance our present knowledge on nutrition and feed development, but will also contribute in understanding the digestive functions of lower vertebrates. It is against this background that the present topic of investigation "Studies on the digestive enzymes of the cultivable grey mullet Liza parsia Hamilton Buchanan, l822" has been selected. The thesis is arranged and presented in eight chapters.

Grey Level Co-Occurrence Matrices: Generalisation And Some New Features

Grey Level Co-occurrence Matrices (GLCM) are one of the earliest techniques used for image texture analysis. In this paper we defined a new feature called trace extracted from the GLCM and its implications in texture analysis are discussed in the context of Content Based Image Retrieval (CBIR). The theoretical extension of GLCM to n-dimensional gray scale images are also discussed. The results indicate that trace features outperform Haralick features when applied to CBIR.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Studies on the utilization of selected species of Sharks

This thesis Entitled Studies on the Utilization of selected Species of sharks. The present study is the result of work carried out for 5 years, during the period from April, 1983 to March 1988. The materials were collected from the catches of the Government of India vessels, operated along the south west coast of India and landed in the Integrated Fisheries Project, Cochin—16. The sharks were caught by different types of gears such as bottom trawls, pelagic trawls, long line etc. A number of species of sharks were landed during this period and three species were selected for the present study namely Scoliodon palasorra (bleeker 1853, grey Shark), Carcharhinus limbatus (valenciennes 1839,black tip shark ) and centrophorus granulosus (bloch and schneider 1801 ,spiny shark). During this study period the quantity of shark utilized was 12,55,942 kg out of which 9.71% used for the production of Dressed shark; 36.21% for the production of Fillets; 49.09% converted into Dried shark and 4.99% was domesticallyy marketed as whole form. Besides this 526 kg of dried shark fin and 289.25 kg of shark fin rays were produced.The effect of Smoking of shark fillets and minced meat at different temperature were also studied during this period. Canning of cooked shark meat, smoked fillets and fish balls were carried out in media like brine, vegetable oil, tomato sauce etc. The quality of smoked fillets in vegetable oil was found superior to other canned products from shark meat.During this study an attempt was also made to evaluate the commercial processing of shark resources and found feasible.

Gut Associated Lactic Acid Bacteria Isolated from the Estuarine Fish Mugil cephalus: Molecular Diversity and Antibacterial Activities against Pathogens

In the present study we address the issue on gut associated lactic acid bacteria (LAB) isolated from the intestine of estuarine fish Mugil cephalus using de Man Rogossa and Sharpe (MRS) agar. LAB isolates were identified biochemically and screened for their ability to inhibit in vitro growth of various fish, shrimp and human pathogens. Most of the LAB isolates displayed an improved antagonism against fish pathogens compared to shrimp and human pathogens. Selected representative strains displaying high antibacterial activity were identified using 16S rRNA gene sequence analysis. Of the selected strains Lactobacillus brevis was the most predominant. Four other species of Lactobacillus, Enterobacter hormaechei and Enterobacter ludwigii were also identified. It was also observed that even among same species, considerable diversity with respect to substrate utilization persisted. Considering the euryhaline nature of grey mullet (Mugil cephalus), the LAB isolated from the gut possessed good tolerance to varying salt concentrations. This finding merits further investigation to evaluate whether the isolated LAB could be used as probiotics in various fresh and sea water aquaculture

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

Face Recognition using Probabilistic Neural Networks

In this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results

Face Recognition using Probabilistic Neural Networks

n this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results.

Raman spectra of KTP crystal in an in situ electric field

Raman spectra of the KTP single crystal are recorded in electric fields (dc and ac) applied along the polar axis c. Spectra with the laser beam focused near the cathode end, anode end and the centre of the crystal are recorded. The cathode end of the crystal develops a spot ‘grey track’ where the laser beam is focused after a lapse of 5 h from the application of a dc electric field of 38 V/cm. The spectra recorded at the cathode end after the application of field show variations in intensity of bands. A new band appears at 177 cm21. Changes in band intensities are explained on the basis of changes in polarizability of the crystal due to the movement of K1 ions along the polar axis. K1 ions accumulate at the cathode end, where the ‘Grey track’ formation occurs. The intensity enhancement observed for almost all bands in the ac field is attributed to the improvement of crystalline quality.

Texture Description of low grade and high grade Glioma using Statistical features in Brain MRIs

Low grade and High grade Gliomas are tumors that originate in the glial cells. The main challenge in brain tumor diagnosis is whether a tumor is benign or malignant, primary or metastatic and low or high grade. Based on the patient's MRI, a radiologist could not differentiate whether it is a low grade Glioma or a high grade Glioma. Because both of these are almost visually similar, autopsy confirms the diagnosis of low grade with high-grade and infiltrative features. In this paper, textural description of Grade I and grade III Glioma are extracted using First order statistics and Gray Level Co-occurance Matrix Method (GLCM). Textural features are extracted from 16X16 sub image of the segmented Region of Interest(ROI) .In the proposed method, first order statistical features such as contrast, Intensity , Entropy, Kurtosis and spectral energy and GLCM features extracted were showed promising results. The ranges of these first order statistics and GLCM based features extracted are highly discriminant between grade I and Grade III. In this study which gives statistical textural information of grade I and grade III Glioma which is very useful for further classification and analysis and thus assisting Radiologist in greater extent.

Development of Directionally Adaptive Techniques for Single Image Super-Resolution

Super Resolution problem is an inverse problem and refers to the process of producing a High resolution (HR) image, making use of one or more Low Resolution (LR) observations. It includes up sampling the image, thereby, increasing the maximum spatial frequency and removing degradations that arise during the image capture namely aliasing and blurring. The work presented in this thesis is based on learning based single image super-resolution. In learning based super-resolution algorithms, a training set or database of available HR images are used to construct the HR image of an image captured using a LR camera. In the training set, images are stored as patches or coefficients of feature representations like wavelet transform, DCT, etc. Single frame image super-resolution can be used in applications where database of HR images are available. The advantage of this method is that by skilfully creating a database of suitable training images, one can improve the quality of the super-resolved image. A new super resolution method based on wavelet transform is developed and it is better than conventional wavelet transform based methods and standard interpolation methods. Super-resolution techniques based on skewed anisotropic transform called directionlet transform are developed to convert a low resolution image which is of small size into a high resolution image of large size. Super-resolution algorithm not only increases the size, but also reduces the degradations occurred during the process of capturing image. This method outperforms the standard interpolation methods and the wavelet methods, both visually and in terms of SNR values. Artifacts like aliasing and ringing effects are also eliminated in this method. The super-resolution methods are implemented using, both critically sampled and over sampled directionlets. The conventional directionlet transform is computationally complex. Hence lifting scheme is used for implementation of directionlets. The new single image super-resolution method based on lifting scheme reduces computational complexity and thereby reduces computation time. The quality of the super resolved image depends on the type of wavelet basis used. A study is conducted to find the effect of different wavelets on the single image super-resolution method. Finally this new method implemented on grey images is extended to colour images and noisy images

Influence of Major Operational Parameters on Aerobic Granulation for the Treatment of Wastewater

Effective solids-liquid separation is the basic concept of any wastewater treatment system. Biological treatment methods involve microorganisms for the treatment of wastewater. Conventional activated sludge process (ASP) poses the problem of poor settleability and hence require a large footprint. Biogranulation is an effective biotechnological process which can overcome the drawbacks of conventional ASP to a great extent. Aerobic granulation represents an innovative cell immobilization strategy in biological wastewater treatment. Aerobic granules are selfimmobilized microbial aggregates that are cultivated in sequencing batch reactors (SBRs). Aerobic granules have several advantages over conventional activated sludge flocs such as a dense and compact microbial structure, good settleability and high biomass retention. For cells in a culture to aggregate, a number of conditions have to be satisfied. Hence aerobic granulation is affected by many operating parameters. The organic loading rate (OLR) helps to enrich different bacterial species and to influence the size and settling ability of granules. Hence, OLR was argued as an influencing parameter by helping to enrich different bacterial species and to influence the size and settling ability of granules. Hydrodynamic shear force, caused by aeration and measured as superficial upflow air velocity (SUAV), has a strong influence and hence it is used to control the granulation process. Settling time (ST) and volume exchange ratio (VER) are also two key influencing factors, which can be considered as selection pressures responsible for aerobic granulation based on the concept of minimal settling velocity. Hence, these four parameters - OLR, SUAV, ST and VER- were selected as major influencing parametersfor the present study. Influence of these four parameters on aerobic granulation was investigated in this work