Resilient Multi-range Radar Detection System for Autonomous Vehicles: A New Statistical Method

© 2023 Crown. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Critical issues with current detection systems are their susceptibility to adverse weather conditions and constraint on the vertical field view of the radars limiting the ability of such systems to accurately detect the height of the targets. In this paper, a novel multi-range radar (MRR) arrangement (i.e. triple: long-range, medium-range, and short-range radars) based on the sensor fusion technique is investigated that can detect objects of different sizes in a level 2 advanced driver-assistance system. To improve the accuracy of the detection system, the resilience of the MRR approach is investigated using the Monte Carlo (MC) method for the first time. By adopting MC framework, this study shows that only a handful of fine-scaled computations are required to accurately predict statistics of the radar detection failure, compared to many expensive trials. The results presented huge computational gains for such a complex problem. The MRR approach improved the detection reliability with an increased mean detection distance (4.9% over medium range and 13% over long range radar) and reduced standard deviation over existing methods (30% over medium range and 15% over long-range radar). This will help establishing a new path toward faster and cheaper development of modern vehicle detection systems.Peer reviewe

Review and Analysis of Magnetic Energy Harvesters: A Case Study for Vehicular Applications

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/Energy harvesting (EH), as an enabling technology of energy derivation from ambient sources, has attracted much research attention in wireless sensor network (WSN) context. The magnetic energy harvester (MEH) introduces ambient energy harvesters' most promising technological development. This paper presents a review and analysis of MEH applications in WSN like vehicular systems and technologies. The successful approaches are introduced and classified based on technical characteristics and working principles. The fundamentals of their operation are discussed in detail, and the power points of each method are reviewed. To select the optimal energy harvester, in this work a case study is provided for feeding navigational sensors mounted on a rotating wheel of vehicles. Finally, the performance of the developed MEH model is evaluated and discussed for harvesting energy at the rotating wheels of a ground vehicle. To offer electromagnetic field analysis of the studied MEH, the simulations are performed in Ansys Maxwell software for further harvested power evaluation.Peer reviewe

Concurrent Findings of Achalasia and Duodenal Duplication in a Down Syndrome Patient

The association between Down syndrome and gastrointestinal anomalies such as duodenal and esophageal atresia, tracheoesophageal fistulas, and Hirschsprung's disease is well documented. More recently, an association between Down syndrome and achalasia was reported. In this report, we describe a 48-year-old woman with a history of Down syndrome who presented with dysphagia. Work-up of the dysphagia showed not only achalasia but also a duodenal duplication. To our knowledge, there have been no reports of Down syndrome associated with duodenal duplication. Whether this finding is simply a coincidence or whether duodenal duplication is associated with Down syndrome will need to be determined with future studies

Duodenal Microbiome and Serum Metabolites Predict Hepatocellular Carcinoma in a Multicenter Cohort of Patients with Cirrhosis.

BackgroundHepatocellular carcinoma (HCC) is rapidly increasing in the U.S. and is a leading cause of mortality for patients with cirrhosis. Discovering novel biomarkers for risk stratification of HCC is paramount. We examined biomarkers of the gut-liver axis in a prospective multicenter cohort.MethodsPatients with cirrhosis without a history of HCC were recruited between May 2015 and March 2020 and prospectively followed at 3 tertiary care hospitals in Los Angeles. Microbiome analysis was performed on duodenal biopsies and metabolomic analysis was performed on serum samples, collected at the time of enrollment. Optimal microbiome-based survival analysis and Cox proportional hazards regression analysis were used to determine microbiota and metabolite associations with HCC development, respectively.ResultsA total of 227 participants with liver cirrhosis contributed a total of 459.58 person-years of follow-up, with 14 incident HCC diagnoses. Male sex (HR = 7.06, 95% CI = 1.02-54.86) and baseline hepatic encephalopathy (HE, HR = 4.65, 95% CI = 1.60-13.52) were associated with developing HCC over follow-up. Adjusting for age, sex, baseline HE, and alkaline phosphatase, an increased risk of HCC were observed for participants with the highest versus lowest three quartiles for duodenal Alloprevotella (HR = 3.22, 95% CI = 1.06-9.73) and serum taurocholic acid (HR = 6.87, 95% CI = 2.32-20.27), methionine (HR = 9.97, 95% CI = 3.02-32.94), and methioninesulfoxide (HR = 5.60, 95% CI = 1.84-17.10). Being in the highest quartile for Alloprevotella or methionine had a sensitivity and specificity for developing HCC of 85.71% and 60.56%, respectively, with an odds ratio of 10.92 (95% CI = 2.23-53.48).ConclusionAlloprevotella and methionine, methioninesulfoxide, and taurocholic acid predicted future HCC development in a high-risk population of participants with liver cirrhosis