No abstract

Landslides are one of the most devastating and recurring natural disasters and have affected several mountainous regions across the globe. The Indian Himalayan region is no exception to landslide incidences affecting key economic sectors such as transportation and agriculture and often leading to loss of lives. As reflected in the global landslide dataset, most of the landslides in this region are rainfall triggered. The region is prone to 15% of the global rainfall-induced landslides, and thereby a review of the studies in the region is inevitable. The high exposure to landslide risk has made the Indian Himalayas receive growing attention by the landslides community. A review of landslides studies conducted in this region is therefore important to provide a general picture of the state-of-the-art, a reference point for researchers and practitioners working in this region for the first time, and a summary of the improvements most urgently needed to better address landslide hazard research and management. This article focuses on various studies ranging from forecasting and monitoring to hazard and susceptibility analysis. The various factors used to analyze landslide are also studied for various landslide zones in the region. The analysis reveals that there are several avenues where significant research work is needed such as the inclusion of climate change factors or the acquisition of basic data of highest quality to be used as input data for computational models. In addition, the review reveals that, despite the entire region being highly landslide prone, most of the studies have focused on few regions and large areas have been neglected. The aim of the review is to provide a reference for stakeholders and researchers who are currently or looking to work in the Indian Himalayas, to highlight the shortcomings and the points of strength of the research being conducted, and to provide a contribution in addressing the future developments most urgently needed to obtain a consistent advance in landslide risk reduction of the area.

The novel coronavirus (2019-nCoV) spike protein is a smart molecular machine that instigates the entry of coronavirus to the host cell causing the COVID-19 pandemic. In this study, a symmetry-information-loaded structure-based Hamiltonian is developed using recent Cryo-EM structural data to explore the complete conformational energy landscape of the full-length prefusion spike protein. The study finds the 2019-nCoV prefusion spike to adopt a unique strategy by undertaking a dynamic conformational asymmetry that results in two prevalent asymmetric structures of spike where one or two spike heads rotate up to provide better exposure to the host-cell receptor. A few unique interchain interactions are identified at the interface of closely associated N-terminal domain (NTD) and receptor binding domain (RBD) playing a crucial role in the thermodynamic stabilization of the up conformation of the RBD in the case of the 2019-nCoV spike. The interaction-level information decoded in this study may provide deep insight into developing effective therapeutic targets.

Consistently over the years, particularly during monsoon seasons, landslides and related geohazards in Bhutan are causing enormous damage to human lives, property, and road networks. The determination of thresholds for rainfall triggered landslides is one of the most effective methods to develop an early warning system. Such thresholds are determined using a variety of rainfall parameters and have been successfully calculated for various regions of the world at different scales. Such thresholds can be used to forecast landslide events which could help in issuing an alert to civic authorities. A comprehensive study on the determination of rainfall thresholds characterizing landslide events for Bhutan is lacking. This paper focuses on defining event rainfall-duration thresholds for Chukha Dzongkhag, situated in south-west Bhutan. The study area is chosen due to the increase in frequency of landslides during monsoon along Phuentsholing-Thimphu highway, which passes through it and this highway is a major trade route of the country with the rest of the world. The present threshold method revolves around the use of a power law equation to determine event rainfall-duration thresholds. The thresholds have been established using available rainfall and landslide data for 2004-2014. The calculated threshold relationship is fitted to the lower boundary of the rainfall conditions leading to landslides and plotted in logarithmic coordinates. The results show that a rainfall event of 24 h with a cumulated rainfall of 53 mm can cause landslides. Later on, the outcome of antecedent rainfall varying from 3-30 days was also analysed to understand its effect on landslide incidences based on cumulative event rainfall. It is also observed that a minimum 10-day antecedent rainfall of 88 mm and a 20-day antecedent rainfall of 142 mm is required for landslide occurrence in the area. The thresholds presented can be improved with the availability of hourly rainfall data and the addition of more landslide data. These can also be used as an early warning system especially along the Phuentsholing-Thimphu Highway to prevent any disruptions of trade. initiated due to heavy monsoon precipitation and aggravated due to the increase in human activities. The increasing number of landslide events in Bhutan can be attributed to complex geological conditions, steep slopes, climate change, type of soil, and tectonic activity. Landslides in Bhutan mostly occur during the monsoons during which the torrential rainfall leads to several flash floods and landslide triggering, cutting off many parts of south Bhutan from the rest.The relationship between the amount of rainfall associated with landslide occurrences is generally studied using either an empirical or physical based approach [4][5][6][7]. Physical process models are based on numerical models which study the relationship between rainfall, pore water pressure, soil type, and volumetric water content that can lead to slope instability. Such a study is usually site specific due to variation in soil prop...