Estimation and Determinants of Chronic Poverty in India : An Alternative Approach

The paper conceptualizes chronic poverty by using the spaces of income and nutrition and estimates its incidence among states and social groups. It also aims to improve our understanding of the determinant of chronic poverty by considering economic, demographic and social factors. It attempts to answer the following questions : How important a determinant of chronic poverty is household income? What factors inhibit escape from chronic poverty? How different are the other poor from chronic poor? The analysis uses the unit level NSS and NFHS data.Chrinic Poverty, India

Estimation and determinants of chronic poverty in India: An Alternative approach

The paper conceptualizes chronic poverty by using the spaces of income and nutrition and estimates its incidence among states and social groups. It also aims to improve our understanding of the determinant of chronic poverty by considering economic, demographic and social factors. It attempts to answer the following questions: How important a determinant of chronic poverty is household income? What factors inhibit escape from chronic poverty? How different are the other poor from chronic poor? The analysis uses the unit level NSS and NFHS data.

Growth performance of the seabass Lates calcarifer (Blotch) in sea cage at Vizhinjam Bay along the south-west coast of India

The growth potential of the Asian seabass, Lates calcarifer in floating sea cage was assessed by rearing them in a large HDPE floating cage moored at Vizhinjam Bay, south-west coast of India. Seabass seed (mean weight and mean total length, 2.5 g and 53 mm respectively) were nursery reared in hapas in December 2008, fed on pellet feed and grown to an average size of 28 g and 135 mm in 60 days, with a survival rate of 60%. Subsequently, the juveniles were stocked into the cages at a stocking rate of 60 nos. m-3 in February 2009, fed on trash fish and reared for a period of 112 days during which they grew to an average size of 540 g and 328 mm. Weight gain per day increased from 0.2 g in December 2008 to 7.71 g in May 2009, while SGR decreased from 5.88 to 2.47. The hydrological parameters viz., temperature, pH, salinity, dissolved oxygen and microbial load recorded were at optimal levels for the normal growth of seabass. The results obtained indicated that cage culture of seabass in the sea can provide significant advantages in terms of faster growth and effective utilisation of water volume

Lithocysts as taxonomic markers of the species of Cordia L. (Boraginaceae)

Volume: 78Start Page: 260End Page: 26

Artificial neural network models for predicting soil thermal resistivity

Thermal properties of soils are of great importance in view of the modern trends of utilizing the subsurface for transmission of either heated fluids or high power currents. For these situations, it is essential to estimate the resistance offered by the soil mass in dissipating the heat generated through it. Several investigators have tried to develop mathematical and theoretical models to estimate soil thermal resistivity. However, it is evident that these models are not efficient enough to predict accurate thermal resistivity of soils. This is mainly due to the fact that thermal resistivity of soils is a complex phenomenon that depends upon various parameters viz., type of the soil, particle size distribution and its compaction characteristics (i.e., dry density and moisture content). To overcome this, Artificial Neural Network (ANN) models, which are based on experimentally obtained thermal resistivity values for clay, silt, silty-sand, fine- and coarse-sands, have been developed. Incidentally, these soils are the most commonly encountered soils in nature and exhibit entirely different characteristics. The thermal resistivity of these soils, corresponding to their different compaction states, was obtained with the help of a laboratory thermal probe and compared vis-a`-vis those obtained from the ANN model. The thermal resistivity of these soils obtained from ANN models and experimental investigations are found to match extremely well. The performance indices such as coefficient of determination, root mean square error, mean absolute error, and variance account for were used to control the performance of the prediction capacity of the models developed in this study. In addition to this, thermal resistivity of these soils obtained from ANN models were compared with those computed from the empirical relationships reported in the literature and were found to be superior. The study demonstrates the utility and efficiency of the ANN model for estimating thermal resistivity of soils.© Elsevie

Optimized high speed turning on Inconel 718 using Taguchi method based Grey relational analysis

269-275Inconel 718, a Nickel based super alloy which has wide applications in aerospace industry particularly in the hot sections of gas turbine engines due to their high temperature strength and corrosion resistance. It is known as being among the most difficult-to-cut materials. This paper presents an optimum process parameters (speed, feed and depth of cut) to minimize the cutting force, surface roughness and tool flank wear together in CNC high speed dry turning of Inconel 718 using Taguchi method based Grey relational analysis. The study involved nine experiments based on Taguchi orthogonal array and the result indicates that the optimal process parameters are 60 m/min for speed, 0.05 mm/rev for feed and 0.2 mm for depth of cut from the selected range. Also the significant process parameters have been found out for the above process optimization by performing ANOVA. Confirmation tests with the optimal levels of cutting parameters are carried out in order to illustrate the effectiveness of the method