Ecological characteristics of prawn culture fields in the Cochin area

Prawn culture by traditional method forms an important occupation for the people in these areas, especially in the Vypeen island. Though short term studies have been made on various aspects of prawn culture field and its ecology, a study of detailed nature covering perennial, seasonal, fields and canals between coconut plantation is lacking from these areas. This study will also enable to assess the relative productivity of different systems during different seasons and the influence of the environment on the production potentials. Therefore the present study is taken upto throw more light on the ecological characteristics of these fields with special emphasis on its primary, secondary and tertiary production. The present area of investigation includes the prawn culture fields adjacent to Cochin backwater. The Cochin backwater (O9° 58'N 76° 28'E) is a shallow semi-enclosed body of water of tropical estuary. A narrow gut, about 450 M wide forms its main connection with the Arabian sea and this region is subjected to regular tidal influenceertiary production.

Studies in molecular dynamics: new criteria for evaluation of intramolecular force fields

The present thesis deals with some studies in molecular dynamics using spectroscopic data. Two new approximation procedures the variable method and the average bonding energy criterion have been developed for a reliable calculation of molecular force fields and applied to several molecular species belonging to the xy2 type.

Nature and Ecological significance of Nutrient Regeneration in Different Prawn Culture Fields

The present work "Nature and Ecological Significance of Nutrient Regeneration in different Prawn Culture Fields" was undertaken to understand the seasonal variation of nutrients, nutrient cycling and primary productivity of the prawn culture systems. The main emphasis was to find the qualitative and quantitative estimates of distribution of total phosphorus, inorganic phosphorus, organic phosphorus, total nitrogen and nitrogen fractions in the water. The effect of nutrient cycling on primary productivity and concentration of metals also form one part of the study. The entire thesis comprise of only one major chapter with subchapters such as, Introduction (I), Review of Literature (2), Material and Methods (3), Results (14), Discussion (5), Executive Summary (6) and Biblio~ graphy (7)

Development and Deployment of Wireless Sensor Network in Paddy Fields of Kuttanad

The evolution of wireless sensor network technology has enabled us to develop advanced systems for real time monitoring. In the present scenario wireless sensor networks are increasingly being used for precision agriculture. The advantages of using wireless sensor networks in agriculture are distributed data collection and monitoring, monitor and control of climate, irrigation and nutrient supply. Hence decreasing the cost of production and increasing the efficiency of production. This paper describes the development and deployment of wireless sensor network for crop monitoring in the paddy fields of Kuttanad, a region of Kerala, the southern state of India.

An Investigation into OccasionalWhite Spot Syndrome Virus Outbreak in Traditional Paddy CumPrawn Fields in India

A yearlong (September 2009–August 2010) study was undertaken to find out possible reasons for occasional occurrence of White Spot Syndrome Virus (WSSV) outbreak in the traditional prawn farms adjoining Cochin backwaters. Physicochemical and bacteriological parameters of water and sediment from feeder canal and four shrimp farms were monitored on a fortnightly basis. The physicochemical parameters showed variation during the two production cycles and between the farms studied. Dissolved oxygen (DO) content of water fromfeeder canal showed low oxygen levels (as low as 0.8mg/L) throughout the study period. There was no disease outbreak in the perennial ponds. Poor water exchange coupled with nutrient loading from adjacent houses resulted in phytoplankton bloom in shallow seasonal ponds which led to hypoxic conditions in early morning and supersaturation of DO in the afternoon besides considerably high alkaline pH. Ammonia levels were found to be very high in these ponds.WSSV outbreak was encountered twice during the study leading to mass mortalities in the seasonal ponds. The hypoxia and high ammonia content in water and abrupt fluctuations in temperature, salinity and pH might lead to considerable stress in the shrimps triggeringWSSV infection in these traditional ponds

Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

Using Neural Network Classifier Support Vector Machine Regression for the prediction of Melting Point of Drug – like compounds

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576

Occurrence of filamentous algae and soil characteristics in the paddy fields of Kuttanad and Kole lands of Kerala

The present work is the study of filamentous algae in the paddy fields of Kuttanad and Kole lands of Kerala. This investigation was initiated by sampling of filamentous algae in Kuttanad during December 2010 to February 2011. A second phase of sampling was done from November 2011 to February 2012. The sampling periodicity corresponded to the crop growth starting from field preparation through sowing, and continued till the harvest. Sampling locations were selected from the active paddy cultivation regions of the six agronomic zones of Kuttanad. The numbers of sampling locations were proportional to the area of each zone. Algae of the Kole lands were collected during from October 2011 to January 2012. It was observed that blue-green algae dominated in both Kuttanad and Kole lands. Thirty two species of blue-green algae and eight species of green algae were identified from Kuttanad. The highest number of algal species was observed from Kayal lands in Kuttanad throughout the cropping season. Among the thirty two species of blue-green algae twenty five species are nonheterocystous and seven species are heterocystous. Twenty eight species of blue-green and six species of green algae were identified from Kole lands, and highest number of species was observed in Palakkal throughout the cropping season. Among the twenty eight species of blue-green algae collected from Kole lands twenty one species are non-heterocystous, and only seven species are heterocystous filamentous algae. Blooms of Spirogyra were observed during the second phase of sampling in Kuttanad and also in the Kole lands. The results of the germination study revealed that the extract of Spirogyra sp. inhibited seed germination and reduced seedling vigour. The growth of the treated seedlings was evaluated by pot experiments. The results clearly showed that Spirogyra sp. can negatively affect the seed germination, seedling vigour, and the yield of rice.

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.

Asymptotics of number fields and the Cohen-Lenstra heuristics

We study the asymptotics conjecture of Malle for dihedral groups Dl of order 2l, where l is an odd prime. We prove the expected lower bound for those groups. For the upper bounds we show that there is a connection to class groups of quadratic number fields. The asymptotic behavior of those class groups is predicted by the Cohen-Lenstra heuristics. Under the assumption of this heuristic we are able to prove the expected upper bounds.

Exact algorithms for p-adic fields and epsilon constant conjectures

We develop several algorithms for computations in Galois extensions of p-adic fields. Our algorithms are based on existing algorithms for number fields and are exact in the sense that we do not need to consider approximations to p-adic numbers. As an application we describe an algorithmic approach to prove or disprove various conjectures for local and global epsilon constants.

Organic inputs and farmers' management strategies in millet fields of western Niger

Research on soil fertility management in sub-Saharan Africa was criticized lately for largely ignoring farmers’ management strategies and the underlying principles. To fill this gap of knowledge, detailed interviews were conducted with 108 farm households about their rationale in managing the soil fertility of 307 individual fields in the agro-pastoral village territory of Chikal in western Niger. To amplify the farmers’ information on manuring and corralling practices, repeated measurements of applied amounts of manure were carried out within six 1-km^2 monitoring areas from February to October 1998. The interviews revealed that only 2% of the fields were completely fallowed for a period of 1–15 years, but 40% of the fields were at least partially fallowed. Mulching of crop residues was mainly practiced to fight wind erosion but was restricted to 36% of the surveyed fields given the alternative use of straw as livestock feed. Manure application and livestock corralling, as most effective tools to enhance soil fertility, were targeted to less than 30% of the surveyed fields. The application of complete fallow and manuring and corralling practices were strongly related to the households’ endowment with resources, especially with land and livestock. Within particular fields, measures were mainly applied to spots of poor soil fertility, while the restoration of the productivity of hard pans was of secondary importance. Given the limited spatial coverage of indigenous soil fertility measures and their strong dependence on farmers’ wealth, supplementary strategies to restrict the decline of soil fertility in the drought prone areas of Niger with their heavily weathered soils are needed.

Non-Born-Oppenheimer Dynamics of Hydrogen Molecules in Strong Laser-Fields

Die Arbeit behandelt die numerische Untersuchung von Wasserstoff-Moleküldynamik in starken Laserfeldern. Im Speziellen wird die Struktur von Ionisationsspektren bei Einfach-Photoionisation betrachtet. Korrelationen zwischen Elektron- und Kernbewegung werden identifiziert und mit Effekten in den Energiespektren in Verbindung gebracht. Dabei wird stets auf die Integration der zeitabhängigen Schrödingergleichung zurückgegriffen.