Higher Himalayan catchments are often poorly monitored for hydrological activities involving flood flow prediction for the safety of riverside communities and the successful operation of hydropower projects. This study aimed to estimate the comparative performance of artificial neural network (ANN) based flow prediction models using 10 years of daily river flow data of Kaligandaki catchment at Kotagaun, Nepal, which is a snow-fed catchment in the Himalayan region. The flow prediction models were trained and tested at a hydrological station using the previous 3 days' river flow data to predict the 1-day ahead flow data. Eight different training functions were employed in an ANN model for comprehensive statistical assessment of accuracy and precision of each training function. The most significant and validated result obtained in this study is the comprehensive comparison of various training functions' performance, and identification )f the most efficient training function for the study case. Among the training functions investigated, the Levenberg-Marquardt backpropagation function exhibits the best performance for the model having Nash-Sutcliffe efficiency, root mean square error and mean absolute error values of 0.866, 209.578 and 75.422, respectively. This study provides a fundamental basis for accurate flow prediction of topographically challenged catchments where hydrological monitoring and data collection may be limited. In particular, r his model will help to improve early warning system, hydrological planning, and the safety of riverside communities in the Himalayan region.

Herbal drugs have been used since ancient times as medicines for the treatment of various diseases. Especially in countries like India many of herbal drugs and formulations are used in different practices of treatment like Ayurveda, Siddha and Unani. It is estimated that about 25% of all modern medicines are directly or indirectly derived from plants sources. The contribution of developing countries in global herbal business is very poor due to lack of quality control and standardization measures. There is lack of common standards and appropriate methods for evaluating Traditional Medicine to ensure the safety, efficacy and quality control. This indicates the importance and necessity to develop a standard operational procedure for the standardization of herbal drugs and formulations. Benchmarking the evaluation protocols including both quality control and quality assurance of herbal drugs would play a major role in providing highly reliable and effective herbals drugs and to attract international trade, thus generating revenue. The article highlights various problems being faced by developing countries and suggests a unique approach for the preparation of SOP/guidelines for the standardization of all herbal based formulations, also there is a need for systematic clinical trials of traditional plant based medicines to enhance global acceptance