Kerala Libraries Network (KELNET): a Proposal

Visualizes the conceptual framework and propose the development of a Kerala Library Network (KELNET) by exploring and exploiting the available and the existing social infrastructures, social softwares, open standards and technologies

Gravitons and Dark Matter in Universal Extra Dimensions

Models of Universal Extra Dimensions (UED) at the TeV scale lead to the presence of Kaluza Klein (KK) excitations of the ordinary fermions and bosons of the Standard Model that may be observed at hadron and lepton colliders. A conserved discrete symmetry, KK-parity, ensures the stability of the lightest KK particle (LKP), which, if neutral, becomes a good dark matter particle. It has been recently shown that for a certain range of masses of the LKP a relic density consistent with the experimentally observed one may be obtained. These works, however, ignore the impact of KK graviton production at early times. Whether the G^1 is the LKP or not, the G^n tower thus produced can decay to the LKP, and depending on the reheating temperature, may lead to a modification of the relic density. In this article, we show that this effect may lead to a relevant modification of the range of KK masses consistent with the observed relic density. Additionally, if evidence for UED is observed experimentally, we find a stringent upper limit on the reheating temperature depending on the mass of the LKP observed.Comment: References added. 38 pages, 18 figures. Submitted to Phys. Rev.

Basics of sample collection, preservation and species identification of finfish

Fisheries are one of the most important renewable resources. With increasing fishing pressure, the only option left for the sustainability of fisheries is their rational management. Proper management is possible with a thorough knowledge of the dynamics of the fish stocks. For a meaningful study of the dynamics, knowledge of natural history of the species is necessary and this in turn can be acquired by the correct identification of fish species. This assumes greater importance in tropical seas where, a multitude of closely related and morphologically similar species occur. The role of taxonomy and proper identification cannot be overstressed in studies of population dynamics. Acquaintance with the main species should be such that there should no errors in identification of them in any special form such as racial differentiation, abnormalities, malformation due to decay or disease. As to species of less importance collections and observations can be made for taxonomic studies which will be useful in future. Species identification study is also a step towards understanding the bewildering biodiversity that characterizes in the marine ecosystem

Stabilized Lateritic Blocks Reinforced With Fibrous Coir Wastes

Tropical countries are rich in lateritic soil, a naturally available raw material for building construction. But its potential in block making is not yet satisfactorily explored. This paper focuses on an experimental investigation for improvising stabilized lateritic blocks (SLB) with coir cutting wastes from coir industry as reinforcing elements. Lateritic soil used in this study showed a higher percentage of clay content. Hence it was pre-stabilized with sand and cement. Blocks were prepared by stabilizing it further with waste fibrous additives and tested for strength and durability. Considerable improvement in strength (compressive strength @19% and tensile strength @ 9%) and durability characteristics were exhibited by the new fiber reinforced lateritic blocks (FRLB) with fiber content of 0.5%. These blocks can be successfully proposed for load bearing construction and as well as for earthquake resistant structure

Kerala Libraries Network (KELNET): a Proposal

Visualizes the conceptual framework and propose the development of a Kerala Library Network (KELNET) by exploring and exploiting the available and the existing social infrastructures, social softwares, open standards and technologies

Relative importance of Farmers’ Characteristics in Predicting their Knowledge about Indigenous Agricultural Practices

This study was conducted to identify the farmers’ characteristics that act as factors in influencing their knowledge on indigenous agricultural practices. The study was conducted in the state of Kerala among 40 farmers each of ten selected horticultural crops. Step wise regression analysis and multiple linear regression analysis were employed to identify the influencing factors. The study revealed that age, farm power status, innovativeness, rational orientation, communication status, and social participation status positively influence knowledge of farmers on indigenous agricultural practices whereas material status, educational status, and family status were the important characteristics of farmers negatively influencing the knowledge of indigenous practices

Prediction and classification for GPCR sequences based on ligand specific features

Functional identification of G-Protein Coupled Receptors (GPCRs) is one of the current focus areas of pharmaceutical research. Although thousands of GPCR sequences are known, many of them are orphan sequences (the activating ligand is unknown). Therefore, classification methods for automated characterization of orphan GPCRs are imperative. In this study, for predicting Level 1 subfamilies of GPCRs, a novel method for obtaining class specific features, based on the existence of activating ligand specific patterns, has been developed and utilized for a majority voting classification. Exploiting the fact that there is a non-promiscuous relationship between the specific binding of GPCRs into their ligands and their functional classification, our method classifies Level 1 subfamilies of GPCRs with a high predictive accuracy between 99% and 87% in a three-fold cross validation test. The method also tells us which motifs are significant for class determination which has important design implications. The presented machine learning approach, bridges the gulf between the excess amount of GPCR sequence data and their poor functional characterization