The recurrent flooding during monsoon and subsequent waterlogging in the northern Bihar plains and the magnitude of losses due to these hazards indicate the continuing vulnerability of the region to flood and waterlogging. Management of floods and waterlogging hazards in highly flood-prone regions of India, including Bihar state has been largely response oriented with little or no attention to mitigation and preparedness. This paper presents a method for spatial, Geographic Information Systems-based assessment of flood and waterlogging vulnerability and risk in northern Bihar plains. Multitemporal satellite data was used to evaluate the area statistics and dynamics of waterlogging over the period from 1975 to 2008. The flood proneness is evaluated at district level with reference to flood inundation during a period from 1998 to 2008. Census data were used to examine the socio-economic characteristics of the region through computation of population density, cultivators, agricultural labourers, sex ratio, children in age group 0-6 years and literates. The geohazard map derived by combining area prone to waterlogging and flood inundation was multiplied with socio-economic vulnerability map to derive the flood-waterlogging risk map of the region. The result shows that flood and water-logging pose highest risk to the central districts in the northern Bihar plains with 50.95% of the total area under high and very high risk.

The baculovirus expression vector system (BEVS) is an emerging tool for the production of recombinant proteins, vaccines and bio-pesticides. However, a system-level understanding of the complex infection process is important in realizing large-scale production at a lower cost. The entire baculovirus infection process is summarized as a combination of various modules and the existing mathematical models are discussed in light of these modules. This covers a systematic review of the present understanding of virus internalization, viral DNA replication, protein expression, budded virus (BV) and occlusion-derived virus (ODV) formation, few polyhedral (FP) and defective interfering particle (DIP) mutant formation, cell cycle modification and apoptosis during the viral infection process. The corresponding theoretical models are also included. Current knowledge regarding the molecular biology of the baculovirus/insect cell system is integrated with population balance and mass action kinetics models. Furthermore, the key steps for simulating cell and virus densities and their underlying features are discussed. This review may facilitate the further development and refinement of mathematical models, thereby providing the basis for enhanced control and optimization of bioreactor operation.

Globally, the COVID-19 pandemic has become a threat to humans and to the socioeconomic systems they have developed since the industrial revolution. Hence, governments and stakeholders call for strategies to help restore normalcy while dealing with this pandemic effectively. Since till now, the disease is yet to have a cure; therefore, only risk-based decision making can help governments achieve a sustainable solution in the long term. To help the decisionmakers explore viable actions, we propose a risk-based assessment framework for analyzing COVID-19 risk to areas, using integrated hazard and vulnerability components associated with this pandemic for effective risk mitigation. The study is carried on a region administrated by Jaipur municipal corporation (JMC), India. Based on the current understanding of this disease, we hypothesized different COVID-19 risk indices (C19Ri) of the wards of JMC such as proximity to hotspots, total population, population density, availability of clean water, and associated land use/land cover, are related with COVID-19 contagion and calculated them in a GIS-based multicriteria risk reduction method. The results showed disparateness in COVID-19 risk areas with a higher risk in north-eastern and south-eastern zone wards within the boundary of JMC. We proposed prioritizing wards under higher risk zones for intelligent decision making regarding COVID-19 risk reduction through appropriate management of resources-related policy consequences. This study aims to serve as a baseline study to be replicated in other parts of the country or world to eradicate the threat of COVID-19 effectively.

The novel coronavirus (COVID-19) has unleashed havoc across different countries and was declared a pandemic by the World Health Organization. Since certain evidences indicate a direct relationship of various viruses with the weather (temperature in particular), the same is being speculated about COVID-19; however, it is still under investigation as the pandemic is advancing the world over. In this study, we tried to analyze the spread of COVID-19 in the Indian subcontinent with respect to the local temperature regimes from March 9, 2020, to May 27, 2020. To establish the relation between COVID-19 and temperature in India, three different ecogeographical regions having significant temperature differences were taken into consideration for the analysis. We observed that except Maharashtra, Rajasthan and Kashmir showed a significantly positive correlation between the number of COVID-19 cases and the temperature during the period of study. The evidences based on the results presented in this research lead us to believe that the increasing temperature is beneficial to the COVID-19 spread, and the cases are going to rise further with the increasing temperature over India. We, therefore, conclude that the existing data, though limited, suggest that the spread of COVID-19 in India is not explained by the variation of temperature alone and is most likely driven by a host of other factors related to epidemiology, socioeconomics and other climatic factors. Based on the results, it is suggested that temperature should not be considered as a yardstick for planning intervention strategies for controlling the COVID-19 pandemic.

Three-dimensional in vitro spheroids are a reliable model to study tumor biology and drug toxicity. However, inconsistencies exist in terms of seeding cell density that governs spheroid size and shape, influencing the experimental outcome. We investigated the effect of varying cell densities using glioblastoma cells on tumorsphere formation and their responsiveness to drug treatment. Our results demonstrated that in comparison with spheroids formed with lower cell density, spheroids formed with higher cell density were not only larger in size but also had a larger necrotic core surrounded by a higher number of quiescent cells and were irresponsive to drug treatment. Our study highlights the importance of predetermination of cell density to obtain desired/appropriate spheroid size to produce consistent and reliable data on drug toxicity studies in tumor cells.

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