Current Status of Crab Fishery in the Artisanal Sector along Gulf of Mannar and Palk bay Coasts

Among the exploited crustacean fishery resources, portunid crabs constitute a significant proportion in the landings along both the east and west coasts of India. From 4% in 1966 the composition of crabs gradually increased and reached 12% in 2006 showing an upward trend from year to year (Rao et al., 1973; Manissery and Radhakrishnan, 2003). This steady increase in the landings of crabs is mainly attributed to the intensification of fishing operation using different types of modern gears and also due to the exploration of new fishing grounds in deeper waters targeting crabs in order to meet the ever increasing demand for the processed crab meats in the domestic as well as in the international markets

The prebiotic evolutionary advantage of transferring genetic information from RNA to DNA.

In the early 'RNA world' stage of life, RNA stored genetic information and catalyzed chemical reactions. However, the RNA world eventually gave rise to the DNA-RNA-protein world, and this transition included the 'genetic takeover' of information storage by DNA. We investigated evolutionary advantages for using DNA as the genetic material. The error rate of replication imposes a fundamental limit on the amount of information that can be stored in the genome, as mutations degrade information. We compared misincorporation rates of RNA and DNA in experimental non-enzymatic polymerization and calculated the lowest possible error rates from a thermodynamic model. Both analyses found that RNA replication was intrinsically error-prone compared to DNA, suggesting that total genomic information could increase after the transition to DNA. Analysis of the transitional RNA/DNA hybrid duplexes showed that copying RNA into DNA had similar fidelity to RNA replication, so information could be maintained during the genetic takeover. However, copying DNA into RNA was very error-prone, suggesting that attempts to return to the RNA world would result in a considerable loss of information. Therefore, the genetic takeover may have been driven by a combination of increased chemical stability, increased genome size and irreversibility

Spectrum of two-dimensional su(2)su(2) gauge theories coupled to massless fermions in integer representations

The spectra of two-dimensional $su(2)$ gauge theories coupled to a single massless Majorana fermion in integer representations, $J$, are numerically investigated using the Discrete Light-Cone Hamiltonian. The primary aim is to understand the presence of massless states for $J>2$ in spite of the absence of a continuous symmetry. After comparing to existing results for $J=1$ (adjoint fermions), we present results for $J=2,3,4$. As expected, for $J=2$ there are no massless states but in contrast to the $J=1$ theory, the lightest state is a boson. We find exact zero modes in the bosonic and fermionic sector for all values of total momentum for $J=3$ and $J=4$ and, in each sector, the number of zero modes grows with the value of the total momentum. In addition to the spectrum, we present results on the particle number and momentum fraction distributions and argue for a separation of bulk states from edge states.Comment: 21 pages, 6 figure

Identification of Proximal and Isolated Aluminum Heteroatoms in Zeolites by Infrared Spectroscopy

High demand for energy production and limited fossil fuel reserves are two factors that motivate intense research for new alternative energy resources. While we are still far from completely moving to renewable energy solutions, a new solution that replaces crude oil and coal with shale gas is currently under investigation. For this modern technology, new zeolite catalysts need to be developed for the conversion of light hydrocarbons gases to liquid transportation fuels. These catalysts are of special interest in the production of liquid fuels since they exhibit high reaction rates, molecular sieving properties and selectivity behavior. In this work, the effect of sequential ion exchange on the K/Al ratio of ZSM-5, CHA and FER zeolites was investigated. This was done using a 0.5M KNO3 solution to exchange NH4 ions with K ions on the zeolite framework. CHA zeolites used in this work were synthesized and characterized using X-ray diffraction. On the other hand, atomic adsorption spectroscopy was used to determine the K/Al ratio on ZSM-5, FER and CHA zeolites. Our results show that the potassium uptake on the zeolite does not change significantly with sequential ion exchange

Symbolic Exploration of Transition Hierarchies

In formal design verification, successful model checking is typically preceded by a laborious manual process of constructing design abstractions. We present a methodology for partially - and in some cases, fully - bypassing the abstraction process. For this purpose, we provide to the designer abstraction operators which, if used judiciously in the description of a design, structure the corresponding state space hierarchically. This structure can then be exploited by verification tools, and makes possible the automatic and exhaustive exploration of state spaces that would otherwise be out of scope for existing model checkers. Specifically, we present the following contributions: - A temporal abstraction operator that aggregates transitions and hides intermediate steps. Mathematically, our abstraction operator is a function that maps a flat transition system into a two-level hierarchy where each atomic upper-level transition expands into an entire lower-level transition system. For example, an arithmetic operation may expand to a sequence of bit operations. - A BDD-based algorithm for the symbolic exploration of multi-level hierarchies of transition systems. The algorithm traverses a level-n transition by expanding the corresponding level-(n-1) transition system on-the-fly. The level-n successors of a state are determined by computing a level-(n-1) reach set, which is then immediately released from memory. In this fashion, we can exhaustively explore hierarchically structured state spaces whose flat counterparts cause memory overflows. - We experimentally demonstrate the efficiency of our method with three examples - a multiplier, a cache coherence protocol, and a multiprocessor system. In the first two examples, we obtain significant improvements in run times and peak BDD sizes over traditional state-space search. The third example cannot be model checked at all using conventional methods (without manual abstractions), but can be analyzed fully automatically using transition hierarchies

मान्नार खाडी के ज्वारीय क्षेत्र में स्थापित नितलस्थ पिंजरों में पेनिअस सेमिसलकाटस का पालन

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Short term energy forecasting techniques for virtual power plants

YesThe advent of smart meter technology has enabled periodic monitoring of consumer energy consumption. Hence, short term energy forecasting is gaining more importance than conventional load forecasting. An Accurate forecasting of energy consumption is indispensable for the proper functioning of a virtual power plant (VPP). This paper focuses on short term energy forecasting in a VPP. The factors that influence energy forecasting in a VPP are identified and an artificial neural network based energy forecasting model is built. The model is tested on Sydney/ New South Wales (NSW) electricity grid. It considers the historical weather data and holidays in Sydney/ NSW and forecasts the energy consumption pattern with sufficient accuracy

Genetic diversity in cocoa (Theobroma cacao L.) plus trees in Tamil Nadu by simple sequence repeat (SSR) markers

The range of polymorphism of about 27 cocoa plus trees screened in the major cocoa growing regions of Tamil Nadu were assessed using 10 simple sequence repeat (SSR) markers. The gene diversity, genetic differentiation and genetic similarities were analyzed for the cocoa trees. The number of alleles detected by different primers ranged from 0 to 3 and the level of polymorphism was 0 to 100%. The polymorphism information content (PIC) value ranged from 0.000 to 0.677. The higher the PIC value, the more informative was the SSR marker. Hence, primer mTcCIR33 was found to be highly informative. The Jaccard’s similarity coefficient for the SSR data set varied from 0.39 to 1.00. The SSR marker profiles resulted in nine clusters at nearly 54% similarity. From this study, it could be inferred that the diversity exists in cocoa plantations in Tamil Nadu and can be exploited in crop improvement research.Keywords: Cocoa, simple sequence repeat (SSR) markers, polymorphism, genetic diversity, breeding.African Journal of BiotechnologyVol. 12(30), pp. 4747-475

A hybrid approach of anfis—artificial bee colony algorithm for intelligent modeling and optimization of plasma arc cutting on monel™ 400 alloy

This paper focusses on a hybrid approach based on genetic algorithm (GA) and an adaptive neuro fuzzy inference system (ANFIS) for modeling the correlation between plasma arc cutting (PAC) parameters and the response characteristics of machined Monel 400 alloy sheets. PAC experiments are performed based on box-behnken design methodology by considering cutting speed, gas pressure, arc current, and stand-off distance as input parameters, and surface roughness (Ra), kerf width (kw), and micro hardness (mh) as response characteristics. GA is efficaciously utilized as the training algorithm to optimize the ANFIS parameters. The training, testing errors, and statistical validation parameter results indicated that the ANFIS learned by GA outperforms in the forecasting of PAC responses compared with the results of multiple linear regression models. Besides that, to obtain the optimal combination PAC parameters, multi-response optimization was performed using a trained ANFIS network coupled with an artificial bee colony algorithm (ABC). The superlative responses, such as Ra of 1.5387 µm, kw of 1.2034 mm, and mh of 176.08, are used to forecast the optimum cutting conditions, such as a cutting speed of 2330.39 mm/min, gas pressure of 3.84 bar, arc current of 45 A, and stand-off distance of 2.01 mm, respectively. Furthermore, the ABC predicted results are validated by conducting confirmatory experiments, and it was found that the error between the predicted and the actual results are lower than 6.38%, indicating the adoptability of the proposed ABC in optimizing real-world complex machining processes