953 resultados para success factor


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Fluctuations in the K values of Nemipterus japonicus (Bloch) off Bombay coast were interpreted regarding sex, month and females maturity stage. These indicate differential growth rates in males and females. Males and females attain first maturity at 145 mm and 115 mm respectively, second maturity is attained by both the sexes at 195 mm. First spawning occurs when both are of 155 mm length and at second spawning males and females attain 215 and 205 mm of length respectively. The fish mature and breed at "O" year; the main spawning period is from August to November with peak spawning activities in October. It grows about 155 mm in first year at 12.91mm per month and about 215 mm in the second year at 5.0 mm per month on an average. Length-weight relationships for males and females are given. The rate of growth of females by weight was found to be slower below 150 mm, but faster than that of males above 150 mm specimens.

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Fishermen co-operatives can be a potent agency for bringing about the social and economic progress of the fishermen community. Streamlining of marketing procedures and provision of infrastructural facilities would result in lowering of production costs and increased benefits accruing to the producers. Another consequence will be an increase in fish yield whereby the problem of the nutritional food gap can be resolved. Success in cooperation is determined by diverse factors like effective leadership and management, loyal and informed members, availability of adequate and timely finance and infrastructure. Proximity to a large metropolis will also have a significant impact on the creation of a favourable environment.

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A study of planktonic foraminiferal assemblages from 19 stations in the neritic and oceanic regions off the Coromandel Coast, Bay of Bengal has been made using a multivariate statistical method termed as factor analysis. On the basis of abundance, 17 foraminiferal species, species were clustered into 5 groups with row normalisation and varimax rotation for Q-mode factor analysis. The 19 stations were also grouped into 5 groups with only 2 groups statistically significant using column normalisation and varimax rotation for R-mode analysis. This assemblage grouping method is suitable because groups of species/stations can explain the maximum amount of variation in them in relation to prevailing environmental conditions in the area of study.

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The length-weight relationship was calculated for the freshwater prawn Macrobrachium idae. About 150 specimens of M. idae (males 50, females 50 and 50 juveniles) were utilised for this study. The length-weight relationship was assessed separately for males, females and indeterminants. The regression equation for males, females and indeterminants showed significant differences whereas it was insignificant for males and females. The variations in length-weight relation between sexes and indeterminants were compared and discussed. The relationship between total length with carapace length and total length with rostral length were also determined.

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The length-weight relationship and condition factor of Mylopharyngodon spiceus were determined. The result of the study showed the dependence of weight (W) on the total length (L) in the following form: W= 0.006L(super 3.156) or in the logarithmic form Log W=- 2.1851 + 3.156 Log L. Standard errors of length and weight were 0.674 cm and 3.214 g respectively. The co-efficient correlation "r" was found to be 0.972 which indicated that the relationship between length and body weight of the fish was highly significant. The t-test also indicated that the correlation between length and weight was significant. The range and mean value of condition factor (K) were 0.865 to 1.041 and 0.958 respectively.

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A nonparametric Bayesian extension of Factor Analysis (FA) is proposed where observed data $\mathbf{Y}$ is modeled as a linear superposition, $\mathbf{G}$, of a potentially infinite number of hidden factors, $\mathbf{X}$. The Indian Buffet Process (IBP) is used as a prior on $\mathbf{G}$ to incorporate sparsity and to allow the number of latent features to be inferred. The model's utility for modeling gene expression data is investigated using randomly generated data sets based on a known sparse connectivity matrix for E. Coli, and on three biological data sets of increasing complexity.