A Comparative study of Extra-Amniotic Saline Infusion (EASI), Foley’s Catheter and Prostaglandin E2(PGE2) gel for Pre-Induction Cervical Ripening

Introduction: Cervical ripening is essential for successful induction of labor. The aim of the study is to compare the efficacy, safety and cost-effectiveness of extra-amniotic saline infusion, Foley’s catheter and intra-cervical PGE2 gel for pre-induction cervical ripening. Methods: A total 150 women having indications of labor induction were randomly assigned equally into three groups: EASI, Foley’s catheter and PGE2 gel. Eligible full-term pregnancy with Bishop score 4 or less was recruited for the study. Computer generated randomization method and random numbers were used to allocate cases into three groups. Data were analyzed by SPSS. The induction to cervical ripening interval, induction to delivery time, changes in the Bishop Score, mode of delivery and cost were assessed. Results: Majority of the cases was primigravida (67.3%) and the most common indication of induction was postdated pregnancy (72%). The mean time for induction to cervical ripening interval was shorter in Foley’s catheter and EASI than PGE2 (6.92 & 5.69 vs 11.08 (P<0.006). Majority of cases in Foley’s catheter and EASI achieved the Bishop score of 7 or more within 24 hours of induction as compared to PGE2 (88% & 84% vs 54%, P<0.000). The mean induction to delivery time is found shorter in EASI and Foley’s catheter than PGE2 (14.95hrs &16.84hrs vs 23.18hrs). Conclusion: Foley’s catheter and extra-amniotic saline infusion (EASI) are the most efficacious, cost effective and safe methods of cervical ripening as compared to PGE2 gel. Keywords: Cervical ripening, induction of labor, EASI, PGE2,Foley’s catheter

D-STACK: High Throughput DNN Inference by Effective Multiplexing and Spatio-Temporal Scheduling of GPUs

Hardware accelerators such as GPUs are required for real-time, low-latency inference with Deep Neural Networks (DNN). However, due to the inherent limits to the parallelism they can exploit, DNNs often under-utilize the capacity of today's high-end accelerators. Although spatial multiplexing of the GPU, leads to higher GPU utilization and higher inference throughput, there remain a number of challenges. Finding the GPU percentage for right-sizing the GPU for each DNN through profiling, determining an optimal batching of requests to balance throughput improvement while meeting application-specific deadlines and service level objectives (SLOs), and maximizing throughput by appropriately scheduling DNNs are still significant challenges. This paper introduces a dynamic and fair spatio-temporal scheduler (D-STACK) that enables multiple DNNs to run in the GPU concurrently. To help allocate the appropriate GPU percentage (we call it the "Knee"), we develop and validate a model that estimates the parallelism each DNN can utilize. We also develop a lightweight optimization formulation to find an efficient batch size for each DNN operating with D-STACK. We bring together our optimizations and our spatio-temporal scheduler to provide a holistic inference framework. We demonstrate its ability to provide high throughput while meeting application SLOs. We compare D-STACK with an ideal scheduler that can allocate the right GPU percentage for every DNN kernel. D-STACK gets higher than 90 percent throughput and GPU utilization compared to the ideal scheduler. We also compare D-STACK with other GPU multiplexing and scheduling methods (e.g., NVIDIA Triton, Clipper, Nexus), using popular DNN models. Our controlled experiments with multiplexing several popular DNN models achieve up to 1.6X improvement in GPU utilization and up to 4X improvement in inference throughput

Participatory Ranking of Fodders in the Western Hills of Nepal

Fodder is an important source of feed of the ruminants in Nepal. In the mid hills of Nepal, farmers generally practice integrated farming system that combines crop cultivation with livestock husbandry and agroforestry. Tree fodders are good sources of protein during the forage and green grass scarcity periods especially in dry season. Local communities possess indigenous knowledge for the selection of grasses and tree fodders at different seasons in mid hills of western Nepal. A study was conducted on the perception of farmers with respect to selection of fodder species in eight clusters in Kaski and Lumjung districts that range 900-2000 meter above sea level and receive average precipitation of 2000- 4500mm per annum. During the fodder preference ranking, farmers prepared the inventory of fodders found around the villages and nearby forests and selected top ten most important fodders in terms of their availability, palatability, fodder yield, milk yield and milk fat yield. In total, 23 top ranking fodders species were selected from the eight clusters. These fodder species were also ranked using pairwise ranking and weighted scoring methods and ranking was done on the basis of merit numbers obtained from weighted scores. The analysis revealed Artocarpus lakoocha as best tree fodder followed by Ficus semicordata, Thysanolena maxima and Ficus calvata. Similarly, the calendar of fodders trees for lopping season and the best feeding time was prepared on the basis of farmers\u27 local knowledge. This study suggests strategies for promotion of locally preferred tree fodder species and supplementing tree fodder with feed in different seasons depending on their availability and local preferences

IVACS: Intelligent Voice Assistant for Coronavirus Disease (COVID-19) Self-Assessment

At the time of writing this paper, the world has around eleven million cases of COVID-19, scientifically known as severe acute respiratory syndrome corona-virus 2 (SARS-COV-2). One of the popular critical steps various health organizations are advocating to prevent the spread of this contagious disease is self-assessment of symptoms. Multiple organizations have already pioneered mobile and web-based applications for self-assessment of COVID-19 to reduce this global pandemic's spread. We propose an intelligent voice-based assistant for COVID-19 self-assessment (IVACS). This interactive assistant has been built to diagnose the symptoms related to COVID-19 using the guidelines provided by the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO). The empirical testing of the application has been performed with 22 human subjects, all volunteers, using the NASA Task Load Index (TLX), and subjects performance accuracy has been measured. The results indicate that the IVACS is beneficial to users. However, it still needs additional research and development to promote its widespread application

Cholecystectomy, gallstones, tonsillectomy, and pancreatic cancer risk: a population-based case-control study in minnesota

Background: Associations between medical conditions and pancreatic cancer risk are controversial and are thus evaluated in a study conducted during 1994–1998 in Minnesota. Methods: Cases (n=215) were ascertained from hospitals in the metropolitan area of the Twin Cities and the Mayo Clinic. Controls (n=676) were randomly selected from the general population and frequency matched to cases by age and sex. The history of medical conditions was gathered with a questionnaire during in-person interviews. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using unconditional logistic regression. Results: After adjustment for confounders, subjects who had cholecystectomy or gallstones experienced a significantly higher risk of pancreatic cancer than those who did not (OR (95% CI): 2.11 (1.32–3.35) for cholecystectomy and 1.97 (1.23–3.12) for gallstones), whereas opposite results were observed for tonsillectomy (0.67 (0.48–0.94)). Increased risk associated with cholecystectomy was the greatest when it occurred ⩽2 years before the cancer diagnosis (5.93 (2.36–15.7)) but remained statistically significant when that interval was ⩾20 years (2.27 (1.16–4.32)). Conclusions: Cholecystectomy, gallstones, and tonsillectomy were associated with an altered risk of pancreatic cancer. Our study suggests that cholecystectomy increased risk but reverse causality may partially account for high risk associated with recent cholecystectomy