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The Himalaya plays a vital role in regulating the freshwater availability for nearly a billion people living in the Indus, Ganga, and Brahmaputra River basins. Due to climate change and constantly evolving human-hydrosphere interactions, including land use/cover changes, groundwater extraction, reservoir or dam construction, water availability has undergone significant change, and is expected to change further in the future. Therefore, understanding the spatiotemporal evolution of the hydrological cycle over the Himalaya and its river basins has been one of the most critical exercises toward ensuring regional water security. However, due to the lack of extensivein-situmeasurements, complex hydro-climatic environment, and limited collaborative efforts, large gaps in our understanding exist. Moreover, there are several significant issues with available studies, such as lack of consistent hydro-meteorological datasets, very few attempts at integrating different data types, limited spatiotemporal sampling of hydro-meteorological measurements, lack of open access toin-situdatasets, poorly accounted anthropogenic climate feedbacks, and limited understanding of the hydro-meteorological drivers over the region. These factors result in large uncertainties in our estimates of current and future water availability over the Himalaya, which constraints the development of sustainable water management strategies for its river catchments hampering our preparedness for the current and future changes in hydro-climate. To address these issues, a partnership development workshop entitled “Water sEcurity assessment in rIvers oriGinating from Himalaya (WEIGH),” was conducted between the 07th and 11th September 2020. Based on the intense discussions and deliberations among the participants, the most important and urgent research questions were identified. This white paper synthesizes the current understanding, highlights, and the most significant research gaps and research priorities for studying water availability in the Himalaya.

Department of Chemistry, St. Stephen’s College, University of Delhi, Delhi-110 007, India Department of Chemistry, University of Delhi, Delhi-110 007, India Department of Chemistry, Shivaji College, University of Delhi, Delhi-110 027, India E-mail: ashokenzyme@gmail.com Manuscript received online 11 October 2019, revised and accepted 14 December 2019 Coumarin glycosides have shown immense potential for diverse biological activities and have been explored extensively as highly prospective biomolecules. In recent years, coumarin glycosides have been used as enzyme inhibitor molecules, environmentally-sensitive fluorescent sensors, the building material of single-excitation and dual emission graphene composite, fluorophore-tagged glycosides, molecule to assay enzyme activity on model bacterial strains, the nucleoside monomer unit for the photoswitchable formation of a DNA interstrand cross-link along with many other applications. In this review, we have compiled biochemically afforded coumarin glycosides obtained via mutagenic synthesis, chemo-enzymatic synthesis and hairy root culture system synthesis. This review will play the role of a reservoir of biochemically synthesized glycosylated coumarins and encourage medicinal chemists to explore the potential of these molecules as drug candidates and further biological applications.

This paper proposes a novel Wavelet Packet based feature extraction approach for the task of text independent speaker recognition. The features are extracted by using the combination of Mel Frequency Cepstral Coefficient (MFCC) and Wavelet Packet Transform (WPT).Hybrid Features technique uses the advantage of human ear simulation offered by MFCC combining it with multi-resolution property and noise robustness of WPT. To check the validity of the proposed approach for the text independent speaker identification and verification we have used the Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) respectively as the classifiers. The proposed paradigm is tested on voxforge speech corpus and CSTR US KED Timit database. The paradigm is also evaluated after adding standard noise signal at different level of SNRs for evaluating the noise robustness. Experimental results show that better results are achieved for the tasks of both speaker identification as well as speaker verification.