Molecular Realism in Default Models for Information Theories of Hydrophobic Effects

This letter considers several physical arguments about contributions to hydrophobic hydration of inert gases, constructs default models to test them within information theories, and gives information theory predictions using those default models with moment information drawn from simulation of liquid water. Tested physical features include: packing or steric effects, the role of attractive forces that lower the solvent pressure, and the roughly tetrahedral coordination of water molecules in liquid water. Packing effects (hard sphere default model) and packing effects plus attractive forces (Lennard-Jones default model) are ineffective in improving the prediction of hydrophobic hydration free energies of inert gases over the previously used Gibbs and flat default models. However, a conceptually simple cluster Poisson model that incorporates tetrahedral coordination structure in the default model is one of the better performers for these predictions. These results provide a partial rationalization of the remarkable performance of the flat default model with two moments in previous applications. The cluster Poisson default model thus will be the subject of further refinement.Comment: 5 pages including 3 figure

The effect of within-crop habitat manipulations on the conservation biological control of aphids in field-grown lettuce

Within-crop habitat manipulations have the potential to increase the biological control of pests in horticultural field crops. Wildflower strips have been shown to increase the abundance of natural enemies, but there is little evidence to date of an impact on pest populations. The aim of this study was to determine whether withincrop wildflower strips can increase the natural regulation of pests in horticultural field crops. Aphid numbers in plots of lettuce grown adjacent to wildflower strips were compared with those in plots grown in the absence of wildflowers. The presence of wildflower strips led to a decrease in aphid numbers on adjacent lettuce plants during June and July, but had less impact in August and September. The decrease in aphid numbers was greatest close to the wildflower strips and, the decrease in aphid numbers declined with increasing distance from the wildflower strips, with little effect at a distance of ten metres. The main natural enemies found in the crop were those that dispersed aerially, which is consistent with data from previous studies on cereal crops. Analysis and interpretation of natural enemy numbers was difficult due to low recovery of natural enemies, and the numbers appeared to follow changes in aphid abundance rather than being directly linked to the presence of wildflower strips. Cutting the wildflower strips, to remove floral resources, had no impact on the reduction in aphid numbers achieved during June and July, but decreased the effect of the wildflower strips during August and September. The results suggest that wildflower strips can lead to increased natural regulation of pest aphids in outdoor lettuce crops, but more research is required to determine how this is mediated by natural enemies and how the impact of wildflower strips on natural pest regulation changes during the growing season

Different approaches on pre harvest forecasting of wheat yield

Agriculture is backbone of Indian economy, contributing about 40 per cent towards the Gross National Product and provide livelihood to about 70 per cent of the population. According to the national income published in Economic survey 2014-15, by the CSO, the share of agriculture in total GDP is 18 percent in 2013-14. The Rabi crops data released by the Directorate of Economics and Statistics recently indicates that the total area coverage has declined; area under wheat has gone down by 2.9 per cent. Therefore needs to be do research to study weathersituation and effect on crop production. Pre harvest forecasting is true essence, is a branch of anticipatory sciences used for identifying and foretelling alternative feasible future. Crop yield forecast provided useful information to farmers, marketers, government agencies and other agencies. In this paper Multiple Linear Regression (MLR) Technique and discriminant function analysis were derived for estimating wheat productivity for the district of Varanasi in eastern Uttar Pradesh. The value of Adj. R2 varied from 0.63 to 0.94 in different models. It is observed that high value of Adj. R2 in the Model-2 which indicated that it is appropriate forecast model than other models, also the value of RMSE varied from minimum 1.17 to maximum 2.47. The study revealed that MLR techniques with incorporating technical and statistical indicators (Model 2) was found to be better for forecasting of wheat crop yield on the basis of both Adjusted R2 and RMSE values