Informatics Publishing Limited

Shashank Singh ¹, R. S. Chauhan ¹

Affiliations
1 Department of Aquaculture, College of Fisheries G. B. Pant University of Agriculture and Technology, Pantnagar Uttarakhand-263145, IN

Abstract

Giant freshwater prawn, Macrobrachium rosenbergii, is a high value cultured aquatic species, commonly called as 'scampi' in trade circles. An experiment was conducted at Instructional Fish Farm of the College of Fisheries, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar in four rectangular earthen ponds each of the size of 0.033 ha in tarai agroclimatic regime of Uttarakhand. The stocking of PL 10 was done @ 60000/ha. The pre-stocking management of the ponds included dewatering, drying, liming, organic manuring and watering of ponds. The water quality parameters were monitored regularly. The larvae were fed with starter feed upto 60 days of rearing when the larvae attained average weight of around 4g. Thereafter, juveniles were fed with grower feed @ 5% body weight twice a day in two equal splitted doses. The sampling of the prawn was done at fortnightly intervals. The average weight of the prawn at the time of stocking was 0.04g while after 180 days of culture at the time of harvesting the prawn attained average weight of 25.37 ± 14.21g with 76.95% survival. The average absolute growth rate of 0.140 g/day and specific growth rate of 1.55% was achieved during the experimental period. The calculated gross production of 1183.159 kg prawn/ha/crop of 180 days was obtained. The result of the study inferred that the culture of giant freshwater prawn, M. rosenbergii, is feasible in tarai agroclimatic regime of Uttarakhand. The fish farmers of the area can earn their sustainable livelihood through scampi farming.

Keywords

Macrobrachium Rosenbergii, Growth, Survival, Production.

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Jitendra Kumar ¹, Jitesh Kumar ¹, Shashank Singh ¹, Vishnu Shukla ¹, Sudhir P. Singh ¹, Rakesh Tuli ¹

Affiliations
1 National Agri-Food Biotechnology Institute, Mohali 160 071, IN

Abstract

Wheat dwarf India virus (WDIV) is the first mastrevirus reported to have subgenomic molecules called satellites. To establish association of the satellites with WDIV across a variety of ecoclimatic conditions, a countrywide survey was carried out. WDIV and its associated satellites (alphasatellite and betasatellite) were identified in plant samples collected from each of the 14 field locations surveyed in the study. Though there were location- and variety-related differences in disease scale, most of the infected wheat cultivars in fields across the country carried both the satellites. The wide occurrence of WDIV disease complex in India suggests the need to assess how the spread of WDIV and its satellites can be limited in wheat fields.

Keywords

Alphasatellite, Atypical Mastrevirus, Betasatellite, Symptom Severity.

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Shashank Singh ¹, Gaurav Sharma ², K. A. Abdul Nazeer ³, Shalini Singh ²

Affiliations
1 IBM India Private limited, Bangalore, IN
2 School of Biochemical Engineering, IIT (BHU), Varanasi-221005, IN
3 NIT, Calicut, Kerala, IN

Abstract

The size and growth rate of biomedical literature creates new challenges for researchers who need to keep up to date. The objective of the present study was to design a pattern matching method for mining acronyms and their definitions from biomedical text by considering the space reduction heuristic constraints have been proposed and implemented. The constraints mentioned are spacious-reduction heuristic constraints which will reduce the search space and will extract most of the true positive cases. The evaluation has been done on MEDLINE abstracts. The results show that the proposed algorithm is faster and more efficient than the previous approaches, in term of space and time complexities. The algorithm has a very good Recall (92%), Precision (97%) and F-factor (94%). One improvement that can be done is to consider all kinds of acronyms definition patterns. This algorithm only considers acronym−definition pairs of the form Acronym (Definition) Definition (Acronym) pairs. Improving the algorithm requires additional study and may reduce the precision even though it may increase the recall. The Algorithm is space efficient too. Input text of any large size can be mined using this algorithm because it requires less memory space to execute.

Keywords

Biomedical Text, Medline, Recall, Precision, F-Factor, Acronym.

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