This study indicates that bacterial isolates from antral biopsies grown aerobically were P. fluorescens, and thus acid-tolerant bacteria other than H. pylori can also colonize the stomach and may be implicated in pathogenesis/protection.
The present investigation was carried out at Horticultural College and Research Institute, Venkataramannagudem, West Godavari Dist. (Andhra Pradesh). The experimental material comprised of 12 genotypes of Lablab purpureus collected from IIPR Kanpur and AICRP on pigeon pea Bangalore. A wide range of variability was reported in most of the characters. The highest genotypic coefficient of variation was recorded for number of pods per plant followed by pod yield per hectare and lowest in days to first pod harvest. Higher heritability estimates coupled with high genetic advance as per cent of mean were observed for all the characters except days to first harvest and pod width. Correlation coefficient analysis revealed that number of secondary branches per plant, number of inflorescences per plant, number of pods per inflorescence, number of pods per plant, number of seeds per pod, pod width, days to last harvest and 100 seed weight had the significant positive correlation with marketable green pod yield per plant. Path analysis revealed true relationship between yield and number of secondary branches per plant, number of pods per inflorescence and number of pods per plant and direct selection for these traits will be rewarding for yield improvement as correlation was due to direct effect of the characters. Hence, selection based on these characters could be effective in developing high yielding varieties of dolichos bean for coastal Andhra Pradesh.
Large amount of information available in distributed databases needs to be exploited by organizations in order to be competitive in the market. In order to exploit this information, queries are posed thereupon. These queries require efficient processing, which mandates devising of optimal query processing strategies that generate efficient query processing plans for a given distributed query. The number of possible query processing plans grows rapidly with increase in the number of sites used, and relations accessed, by the query. There is a need to generate efficient query processing plans from among all possible query plans. The proposed approach attempts to generate such query processing plans using genetic algorithm. The approach generates query plans based on the closeness of data required to answer the user query. The query plans having the required data residing in fewer sites, are considered more efficient, and are thus preferred, over query plans having data spread across a large number of sites. The query plans so generated involve minimum number of sites for answering the user query leading to efficient query processing. Further, experimental results show that the GA based approach converges quickly towards the optimal query processing plans for an observed crossover and mutation rate.
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