Browsing by Author "Gupta, R."

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Open Access
Bio-inspired magnetic beads for isolation of sperm from heterogenous samples ın forensic applications
(Elsevier BV, 2021-05) İnci, Fatih; Karaaslan, M. G.; Gupta, R.; Avadhani, A.; Öğüt, M. G.; Atila, E. E.; Duncan, G.; Klevan, L.; Demirci, U.
Rapid and efficient processing of sexual assault evidence will accelerate forensic investigation and decrease casework backlogs. The standardized protocols currently used in forensic laboratories require the continued innovation to handle the increasing number and complexity of samples being submitted to forensic labs. Here, we present a new technique leveraging the integration of a bio-inspired oligosaccharide (i.e., Sialyl‐LewisX) with magnetic beads that provides a rapid, inexpensive, and easy-to-use strategy that can potentially be adapted with current differential extraction practice in forensics labs. This platform (i) selectively captures sperm; (ii) is sensitive within the forensic cut-off; (iii) provides a cost effective solution that can be automated with existing laboratory platforms; and (iv) handles small volumes of sample (∼200 μL). This strategy can rapidly isolate sperm within 25 minutes of total processing that will prepare the extracted sample for downstream forensic analysis and ultimately help accelerate forensic investigation and reduce casework backlogs.
Open Access
Interest rate uncertainty and the predictability of bank revenues
(John Wiley & Sons, Ltd, 2022-06-24) Cepni, O.; Demirer, R.; Gupta, R.; Sensoy, Ahmet
This paper examines the predictive power of interest rate uncertainty over pre-provision net revenues (PPNR) in a large panel of bank holding companies (BHC). Utilizing a linear dynamic panel model based on Bayes predictor, we show that supplementing forecasting models with interest rate uncertainty improves the forecasting performance with the augmented model yielding lower forecast errors in comparison to a baseline model which includes unemployment rate, federal funds rate, and spread variables. Further separating PPNRs into two components that reflect net interest and non-interest income, we show that the predictive power of interest rate uncertainty is concentrated on the non-interest component of bank revenues. Finally, examining the point predictions under a severely stressed scenario, we show that the model can successfully predict the negative effect on overall bank revenues with a rise in the non-interest component of income during 2009:Q1. Overall, the findings suggest that stress testing exercises that involve bank revenue models can benefit from the inclusion of interest rate uncertainty and the cross-sectional information embedded in the panel of BHCs.