ANFIS-based soft computing models for forecasting effective drought index over an arid region of India

Drought is a natural hazard that is characterized by a low amount of precipitation in a region. In order to evaluate the drought-related issues that cause chaos for human well-being, drought indices have become increasingly important. In this study, the monthly precipitation data from 1964 to 2013 (about 50 years) of the Jodhpur district in the drought-prone Rajasthan state of India was used to derive the effective drought index (EDI). The machine learning models hybridized with evolutionary optimizers such as the genetic algorithm adaptive neuro-fuzzy inference system (GA-ANFIS) and particle swarm optimization ANFIS (PSO-ANFIS) were used in addition to the generalized regression neural network (GRNN) to predict the EDI index. Using the partial autocorrelation function (PACF), models for forecasting the monthly EDI were constructed with 2-, 3- and 5-input combinations to evaluate their outcomes based on various performance indices. The results of the different combination models were compared. With reference to 2-input and 3-input combination models, both GA-ANFIS and PSO-ANFIS show better performance results with R2 = 0.75, while among the models with 5-input combination, GA-ANFIS depicts better performance results compared to other models with R2 = 0.78. The results are presented suitably with the aid of scatter plots, Taylor's diagram and violin plots. Overall, the GA-ANFIS and PSO-ANFIS models outperformed the GRNN model. HIGHLIGHTS Effective drought index (EDI) was predicted using soft computing techniques.; Hybrid machine learning algorithms were used.; GA-ANFIS, PSO-ANFIS and GRNN paradigms were used.; The EDI of an arid region in India was used for prediction.; Precipitation data was used for computing the EDI of drought-prone areas.

Organic Poultry Farming in India- issues and approaches

In the last few decades poultry industry has transformed from mere back yard poultry to commercial farm, but the issues of food safety and quality remains unaddressed. Hence, organic poultry farming has become as an approach to address these issues. This paper attempts to discuss the various issues of organic farming along with necessary interventions required in poultry breeding, feeding, housing and health care management under Indian Scenario. Further, necessary policy interventions were also suggested in order to promote organic poultry farming. [Vet. World 2011; 4(6.000): 273-277

5-(1-Aryl-3-(thiophen-2-yl)-1H-pyrazol-4-yl)-1H-tetrazoles: Synthesis, structural characterization, Hirshfeld analysis, anti-inflammatory and anti-bacterial studies

A series of novel 5-(1-aryl-3-(thiophen-2-yl)-1H-pyrazol-4-yl)-1H-tetrazoles 7(h-s) were designed and synthesized. Structural characterization was done by spectral and single crystal X-ray studies. The intermolecular interactions of compound 7n were quantified and visualized using Hirshfeld surface analysis. Structures of newly synthesized compounds were docked into active site of COX-2 enzyme PDB: 1CX2, 3.0 Å X-ray resolution and plausible binding modes were compared with standard drug Celecoxib. The results of molecular docking prompted the pharmacological studies for further optimization of identified selective inhibition. The compounds 7k, 7m, 7n, and 7q-s have shown excellent anti-inflammatory activity and compounds 7i, 7k, 7l, 7n, and 7s have exhibited anti-bacterial inhibitory potency in enzyme based assays