Indian Institute of Technology Ropar

About: Indian Institute of Technology Ropar is a education organization based out in Ropar, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 1014 authors who have published 2878 publications receiving 35715 citations.

Anticipating the Novel Coronavirus Disease (COVID-19) Pandemic

Abstract: The COVID-19 outbreak was first declared an international public health, and it was later deemed a pandemic. In most countries, the COVID-19 incidence curve rises sharply over a short period of time, suggesting a transition from a disease-free (or low-burden disease) equilibrium state to a sustained infected (or high-burden disease) state. Such a transition is often known to exhibit characteristics of "critical slowing down." Critical slowing down can be, in general, successfully detected using many statistical measures, such as variance, lag-1 autocorrelation, density ratio, and skewness. Here, we report an empirical test of this phenomena on the COVID-19 datasets of nine countries, including India, China, and the United States. For most of the datasets, increases in variance and autocorrelation predict the onset of a critical transition. Our analysis suggests two key features in predicting the COVID-19 incidence curve for a specific country: (a) the timing of strict social distancing and/or lockdown interventions implemented and (b) the fraction of a nation's population being affected by COVID-19 at that time. Furthermore, using satellite data of nitrogen dioxide as an indicator of lockdown efficacy, we found that countries where lockdown was implemented early and firmly have been successful in reducing COVID-19 spread. These results are essential for designing effective strategies to control the spread/resurgence of infectious pandemics.

Analytical Approach for Common Mode EMI Noise Analysis in Dual Active Bridge Converter

Abstract: The increased demand for high power density converters resulted in increased EMI. This is addressed by considering all the converter parasitics along the noise propagation path. In this paper, the analytical approach for common mode (CM) noise analysis of dual active bridge (DAB) converter is presented. The dv/dt of CM voltage that excites the parasitic capacitances are the main source of CM noise. This CM noise is analysed by calculating the change in CM voltage from one state to another state for single phase shift technique (SPST) measured at LISN terminals. The CM noise for symmetrical and asymmetrical inductor and parasitic capacitors are also analysed using this approach. The analysis is thoroughly verified in LTspice with the parasitics measured from the hardware prototype.

Anticipating regime shifts in gene expression: The case of an autoactivating positive feedback loop.

Abstract: Considerable evidence suggests that anticipating sudden shifts from one state to another in bistable dynamical systems is a challenging task; examples include ecosystems, financial markets, and complex diseases. In this paper, we investigate the effects of additive, multiplicative, and cross-correlated stochastic perturbations on determining the regime shifts in a bistable gene regulatory system, which gives rise to two distinct states of low and high concentrations of protein. We obtain the stationary probability density and mean first-passage time of the system. We show that increasing the additive (multiplicative) noise intensity induces a regime shift from a low (high) to a high (low) protein concentration state. However, an increase in the cross-correlation intensity always induces regime shifts from a high to a low protein concentration state. For both bifurcation-induced (often called the tipping point) and noise-induced (called stochastic switching) regime shifts, we further explore the robustness of recently developed critical-down-based early warning signal (EWS) indicators (e.g., rising variance and lag-1 autocorrelation) on our simulated time-series data. We identify that using EWS indicators, prediction of an impending bifurcation-induced regime shift is relatively easier than that of a noise-induced regime shift in the considered system. Moreover, the success of EWS indicators also strongly depends upon the nature of the noise.