How subprime lending emerged in minority neighbourhoods

It is a commonly held belief that subprime lenders, who issue loans to risky borrowers, provide credit to high-risk communities that would not be able to get credit from low-risk lenders. Eglė Jakučionytė and Swapnil Singh challenge this view. They show that policy changes introduced in 1995 by US institutions Fannie Mae and Freddie Mac increased securitisation costs for lending in minority neighbourhoods. Prime lenders moved out and, with less competition, subprime lenders managed to enter these minority neighbourhoods with greater ease

Ruptured Primary Ovarian Ectopic Pregnancy: A rare case report

Primary ovarian pregnancy occurs quite rarely and that too usually in young highly fertile multiparous women. Risk factors include previous pelvic inflammatory disease, IUD use, endometriosis, and assisted reproductive technologies. Its presentation often is difficult to distinguish from that of tubal ectopic pregnancy. We report a case where a young Second gravida with previous LSCS presented with two months amenorrhea along with abdominal pain presented to us and was diagnosed as ectopic pregnancy and was confirmed intra-operatively and histopathologically as primary ovarian pregnancy, managed successfully with laparotomy followed by partial ovariectomy.

Assessment of Pressure Based Solver in Resolving Complex Shock Wave Phenomenon

This study presents a critical assessment of a pressure-based solver (PBS) in resolving complex interactions of shocks, turbulent structures etc.. The canonical problem chosen to be resolved in this study is of mode staging in axisymmetric supersonic jet screech. The screech phenomenon exhibits staging behavior characterized by frequency and azimuthal structure changes at specific frequencies. The PBS simulations in the popular ANSYS Fluent software-suite were validated against numerical work and experimental measurements, and results were analyzed. Simulations are performed on supersonic jets which emits dual high frequency screech tones at particular Mach numbers. At lower end of these supersonic Mach numbers, the flow can involve vanishingly weak shock strengths which is routinely captured in experiments and by density based solvers in literature. The limitations of the pressure-based solver in resolving complex shock flow phenomena and predicting mode staging are highlighted at vanishingly weak Mach numbers, emphasizing the need for further investigation given the recent popularity of such solvers for all Mach numbers including in high-speed flow.Comment: 14th Asian Computational Fluid Dynamics Conference, 30th October - 02nd November, 2023, Bengalur

A randomized study comparing rectally administered misoprostol after spinal anesthesia versus intramuscular oxytocin for prevention of postpartum hemorrhage in caesarean section

Background: Post-Partum Hemorrhage (PPH) is the commonest cause of maternal death worldwide. Studies suggest that the use of Misoprostol may be beneficial in clinical settings where oxytocin is unavailable. However studies are limited that show its use in prevention of PPH in high risk pregnancy involving elective caesarean section. Therefore our aim of study is to compare the effectiveness of rectal misoprostol with intramuscular oxytocin in the prevention of postpartum hemorrhage in cesarean sections.Methods: In a double-blind randomized controlled trial, 200 pregnant women who had cesarean sections were assigned into two groups: to receive either oxytocin intramuscularly or misoprostol rectally after spinal anesthesia.Results: There was no significant difference between the two groups about change in postpartum hemoglobin, need for blood transfusion and incidence of PPH. We also did not observe any significant difference in any side effects.  Conclusions: Misoprostol may be considered as an alternative for oxytocin in low resource clinical settings.

Machine Learning for Microcontroller-Class Hardware -- A Review

The advancements in machine learning opened a new opportunity to bring intelligence to the low-end Internet-of-Things nodes such as microcontrollers. Conventional machine learning deployment has high memory and compute footprint hindering their direct deployment on ultra resource-constrained microcontrollers. This paper highlights the unique requirements of enabling onboard machine learning for microcontroller class devices. Researchers use a specialized model development workflow for resource-limited applications to ensure the compute and latency budget is within the device limits while still maintaining the desired performance. We characterize a closed-loop widely applicable workflow of machine learning model development for microcontroller class devices and show that several classes of applications adopt a specific instance of it. We present both qualitative and numerical insights into different stages of model development by showcasing several use cases. Finally, we identify the open research challenges and unsolved questions demanding careful considerations moving forward.Comment: Accepted for publication at IEEE Sensors Journa