Fractionation and bioavailability of phosphorus in a tropical estuary, Southwest India

Phosphorus fractionation was employed to find the bioavailability of phosphorus and its seasonal variations in the Panangad region of Cochin estuary, the largest estuarine system in the southwest coast of India. Sequential extraction of the surficial sediments using chelating agents was taken as a tool for this. Phosphate in the water column showed seasonal variations, with high values during the monsoon months, suggesting external runoff. Sediment texture was found to be the main factor influencing the spatial distribution of the geochemical parameters in the study region. Similarly, total phosphorus also showed granulometric dependence and it ranged between 319.54 and 2,938.83 μg/g. Calcium-bound fraction was the main phosphorus pool in the estuary. Significant spatial variations were observed for all bioavailable fractions; iron-bound inorganic phosphorus (5.04–474.24 μg/g), calcium-bound inorganic phosphorus (11.16–826.09 μg/g), and acidsoluble organic phosphorus (22.22–365.86 μg/g). Among the non-bioavailable phosphorus, alkalisoluble organic fraction was the major one (51.92– 1,002.45 μg/g). Residual organic phosphorus was K. R. Renjith (B) · N. Chandramohanakumar · M. M. Joseph Department of Chemical Oceanography, School of Marine Sciences, Cochin University of Science and Technology, Kochi 682016, Kerala, India e-mail: renjithaqua@gmail.com comparatively smaller fraction (3.25–14.64% of total). The sandy and muddy stations showed distinct fractional composition and the speciation study could endorse the overall geochemical character. There could be buffering of phosphorus, suggested by the increase in the percentage of bioavailable fractions during the lean premonsoon period, counteracting the decreases in the external loads. Principal component analysis was employed to find the possible processes influencing the speciation of phosphorus in the study region

Extraction of Glucan from Acremonium Diospyri and Its Application in Macrobrachium Rosenbergii Larval Rearing System Along With Bacterians as Microspheres

Present work is aimed at development of an appropriate microbial technology for protection of larvae of macrobrachium rosenbergii from disease and to increase survival rate in hatcheries. Application of immunostimulants to activate the immune system of cultured animals against pathogen is the widely accepted alternative to antibiotics in aquaculture. The most important immunostimulant is glucan. Therefore a research programme entitled as extraction of glucan from Acremonium diospyri and its application in macrobrachium rosenbergii larval rearing system along with bacterians as microspheres. The main objectives of the study are development of aquaculture grade glucan from acremonium diospyri, microencapsulated drug delivery system for the larvae of M. rosenbergii and microencapsulated glucan with bacterian preparation for the enhanced production of M. rosenbergii in larval rearing system. Based on the results of field trials microencapsulated glucan with bacterin preparation, it is concluded that the microencapsulated preparation at a concentration of 25g per million larvae once in seven days will enhance the production and quality seed of M. rosenbergii.

INVESTIGATIONS ON THE SOLVENT EXTRACTION AND LUMINESCENCE OF LANTHANOIDS WITH MIXTURES OF HETEROCYCLIC β- DIKETONE S AND VARIOUS NEUTRAL OXO-DONORS

The thesis entitled “ Investigations on the solvent extraction and luminescence of lanthanoids with mixtures of heterocyclic β-diketone S and various neutral oxo-donors” embodies the results of investigations carried out on the solvent extraction of trivalent lanthanoids with various heterocyclic β-diketones in the presence and absence of neutral oxo-donors and also on the luminescent studies of Eu3+-heterocyclic β-diketonate complexes with Lewis bases. The primary objective of the present work is to generate the knowledge base, especially to understand the interactions of lanthanoid-heterocyclic β-diketonates with various macrocyclic ligands such as crown ethers and neutral organophosphorus extractants , with a view to achieve better selectivity. The secondary objective of this thesis is to develop novel lanthanoid luminescent materials based on 3-phenyl-4-aroyl-5-isoxazolones and organophosphorus ligands, for use in electroluminescent devices. In the beginning it describes the need for the development of new mixed-ligand systems for the separation of lanthanoids and the development and importance of novel luminescent lanthanoid- β-diketonate complexes for display devices. The syntheses of various para substituted derivatives of 4-aroyl-5-isoxazolones and their characterization by various spectroscopic techniques are described. It also investigate the solvent extraction behaviour of trivalent lanthanoids with 4-aroyl-5-isoxazolones in the presence and absence of various crown ethers such as 18C6, DC18C6, DB18C6 and B18C6. Elemental analysis, IR and H NMR spectral studies are used to understand the interactions of crown ethers with 4-aroyl-5-isoxazolonate complexes of lanthanoids. The synergistic extraction of trivalent lanthanoids with sterically hindered 1-phenyl-3-methyl-4-pivaloyl-5-pyrazolone in the presence of various structurally related crown ethers are studied. The syntheses, characterization and photyphysical properties of Eu3+-4-aroyl-5-isoxazolonate complexes in the presence of Lewis bases like trictylphosphine oxide or triphenylphosphine oxide were studied.

Intervariability of Phosphorus Speciation in Selected Mangrove Ecosystems Around the Greater Cochin

Mangrove forests are best developed on tropical shorelines where there is an extensive intertidal zone, with an abundant supply of fine-grained sediment. It receives a mixture of liable and refractory organic and inorganic phosphorus compounds from the overlying water and the surrounding landmasses. Organic phosphorus is not available for mangrove plant nutrition. While inorganic phosphate represents the largest potential pool of plant-available and which are bound in the form of Ca, Fe and Al phosphate. It deals with the scientific investigations on mangrove systems in the Kerala coastline and to investigate nutrient distribution of mangrove ecosystems of greater Cochin area. It discusses the description of study areas such as Murikkumpadam-Vypeen Island and Aroor. Then it deals with the spatial and seasonal distribution of dissolved ammonia, nitrite, nitrate, inorganic phosphate, organic phosphate and the total phosphorus in surface waters of mangrove fringed creeks. Then it discusses the geochemical compositions of mangrove-fringed sediments and also the chemical speciation of phosphorus in sediment cores.

Synergistic solvent extraction of Thorium(IV) and Uranium(VI) with β-diketones in presence of oxo-donors

The thesis entitled “Synergistic solvent extraction of Thorium(IV) and Uranium(VI) with β-diketones in presence of oxo-donors” embodies the results of the investigations carried out on the extraction of thorium(IV) an uranium(VI) with heterocyclic β-diketones in the presence and absence of various macrocyclic ligands and neutral organophosphorus extractants. The objective of this work is to generate the knowledge base to achieve better selectivity between thorium(IV) and uranium(VI) by understanding the interactions of crown ethers or neutral organophosphorus extractants with metal-heterocyclic β-diketonate complexes. Para-substituted 1-phenyl-3-methyl-4-aroyl-5-pyrazolones, namely,1-phenyl-3-methyl-4-(4-fluorobenzoyl)-5-pyrazolone (HPMFBP) and 1-phenyl-3-methyl-4-(4-toluoyl)-5-pyrazolone (HPMTP) were synthesized and characterized by elemental analysis, IR and H NMR spectral data. The synthesized ligands have been utilized for the extraction of thorium(IV) and uranium(VI) from nitric acid solutions in the presence and absence of various crown ethers. Thorium(IV) and uranium(VI) complexes with HPMPP(1-Phenyl-3-methyl-4-pivaloyl-5-pyrazolone) and neutral organophosphorus extractants were synthesized and characterized by IR and P NMR spectral data to further understand the interactions of neutral organophosphorus extractants with metal-chelates. Solid complexes of thorium(IV) and uranium(VI) with para-substituted 4-aroyl-5-isoxazolones and crown ethers were isolated and characterized by various spectroscopic techniques to further clarify the nature of the extracted complexes.

OFFLINE AND ONLINE SOLID PHASE EXTRACTION/PRECONCENTRATION OF INORGANICS

Solid phase extraction (SPE) is a powerful technique for preconcentration/removal or separation of trace and ultra trace amounts of toxic and nutrient elements. SPE effectively simplifies the labour intensive sample preparation, increase its reliability and eliminate the clean up step by using more selective extraction procedures. The synthesis of sorbents with a simplified procedure and diminution of the risks of errors shows the interest in the areas of environmental monitoring, geochemical exploration, food, agricultural, pharmaceutical, biochemical industry and high purity metal designing, etc. There is no universal SPE method because the sample pretreatment depends strongly on the analytical demand. But there is always an increasing demand for more sensitive, selective, rapid and reliable analytical procedures. Among the various materials, chelate modified naphthalene, activated carbon and chelate functionalized highly cross linked polymers are most important. In the biological and environmental field, large numbers of samples are to be analysed within a short span of time. Hence, online flow injection methods are preferred as they allow extraction, separation, identification and quantification of many numbers of analytes. The flow injection online preconcentration flame AAS procedure developed allows the determination of as low as 0.1 µg/l of nickel in soil and cobalt in human hair samples. The developed procedure is precise and rapid and allows the analysis of 30 samples per hour with a loading time of 60 s. The online FI manifold used in the present study permits high sampling, loading rates and thus resulting in higher preconcentration/enrichment factors of -725 and 600 for cobalt and nickel respectively with a 1 min preconcentration time compared to conventional FAAS signal. These enrichment factors are far superior to hitherto developed on line preconcentration procedures for inorganics. The instrumentation adopted in the present study allows much simpler equipment and low maintenance costs compared to costlier ICP-AES or ICP-MS instruments.

Statistical signal extraction using stable processes

The standard models for statistical signal extraction assume that the signal and noise are generated by linear Gaussian processes. The optimum filter weights for those models are derived using the method of minimum mean square error. In the present work we study the properties of signal extraction models under the assumption that signal/noise are generated by symmetric stable processes. The optimum filter is obtained by the method of minimum dispersion. The performance of the new filter is compared with their Gaussian counterparts by simulation.

Optimization of Process Parameters for the Extraction of Gelatin from the Skin of Freshwater Fish and the Evaluation of Physical anal Chemical Characteristics

Faculty of Marine Sciences,Cochin University of Science and Technology

Nutrient Mobility in Chalakudy River,Typified With Riparian Buffer Zone and Its Adjoining Estuary:Spatiotemporal Manifestation

This study was aimed at to characterize the spatio-temporal trends in the distributional characteristics of various species of nitrogen and phosphorus as well as to elucidate the factors and processes aflecting these nutrients in the dissolved, particulate and sedimentary phases of a river estuarine system. The main area of study is Chalakudy river in Kerala, which is a fresh water system originating from Anamalai hills and ending at Arabian Sea. Its basin is between I00 05 ’ to I00 35’ North latitude and 76” 15 ’ to 760 55’ East longitude. Being a riparian bufler zone, the dynamics of nutrient mobility tend to be more complex and variable in this river-estuarine system.The diflerent species of nitrogen estimated from the filtrate were nitrite-N, nitrateN, ammonia-N, urea-N, total nitrogen and residual nitrogen. The diflerent forms of phosphorus estimated from the filtrate were phosphate-P, total-P and residualP. Pre weighed sediments as well as particulate matter were analysed for quantijying nitrite-N, nitrate-N, ammonia-N and urea-N. Total nitrogen was estimated after digestion with potassium persulfate. Fractionation of phosphorus in sediment/particulate matter was performed by applying sequential extraction procedure. The dijferent forms of phosphorus thus estimated were loosely bound (exchangeable) P, Fe/Al bound P, polyphosphates, Ca bound P and refractory P. Sedimental total P was also measured directly by applying digestion method.The analyses carried out in this bimonthly annual survey have revealed specific information on the latent factors influencing the water quality pattern ofthe river. There was dependence among the chemical components of the river sediment and suspended matter, reflecting the water quality. A period of profound environmental change occurred and changes in various species had been noted in association with seasonal variations in the waterway, especially following enhanced river runoff during the monsoon. The results also successfully represented the distribution trend of nutrients during the rainy as well as dry season. Thus, the information gathered in this work will also be beneficial for those interested or involved in river management, conservation, regulation and policy making in regional and national levels.

“Improved Feature Extraction and Classification Techniques for Multispectral Brain Magnetic Resonance Images”

Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.

Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations

COMBINED FEATURE EXTRACTION TECHNIQUES AND NAIVE BAYES CLASSIFIER FOR SPEECH RECOGNITION

Speech processing and consequent recognition are important areas of Digital Signal Processing since speech allows people to communicate more natu-rally and efficiently. In this work, a speech recognition system is developed for re-cognizing digits in Malayalam. For recognizing speech, features are to be ex-tracted from speech and hence feature extraction method plays an important role in speech recognition. Here, front end processing for extracting the features is per-formed using two wavelet based methods namely Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Naive Bayes classifier is used for classification purpose. After classification using Naive Bayes classifier, DWT produced a recognition accuracy of 83.5% and WPD produced an accuracy of 80.7%. This paper is intended to devise a new feature extraction method which produces improvements in the recognition accuracy. So, a new method called Dis-crete Wavelet Packet Decomposition (DWPD) is introduced which utilizes the hy-brid features of both DWT and WPD. The performance of this new approach is evaluated and it produced an improved recognition accuracy of 86.2% along with Naive Bayes classifier.

A Comparative Study of Wavelet Based Feature Extraction Techniques in Recognizing Isolated Spoken Words

Speech is a natural mode of communication for people and speech recognition is an intensive area of research due to its versatile applications. This paper presents a comparative study of various feature extraction methods based on wavelets for recognizing isolated spoken words. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. This work includes two speech recognition methods. First one is a hybrid approach with Discrete Wavelet Transforms and Artificial Neural Networks and the second method uses a combination of Wavelet Packet Decomposition and Artificial Neural Networks. Features are extracted by using Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Training, testing and pattern recognition are performed using Artificial Neural Networks (ANN). The proposed method is implemented for 50 speakers uttering 20 isolated words each. The experimental results obtained show the efficiency of these techniques in recognizing speech