Unmanned aerial vehicles are rapidly advancing and becoming ubiquitous in an unlimited number of applications, from parcel delivery to people transportation. As unmanned aerial vehicle (UAV) markets expand, the increased acoustic nuisance on population becomes a more acute problem. Previous aircraft noise assessments have highlighted the necessity of a psychoacoustic metric for quantification of human audio perception. This study presents a framework for estimating propeller-based UAV auditory detection probability on the ground for a listener in a real-life scenario. The detection probability is derived by using its free-field measured acoustic background and estimating the UAV threshold according to a physiological model of the auditory pathway. The method is presented via results of an exemplar measurement in an anechoic environment with a single two- and five-bladed propeller. It was found that the auditory detection probability is primarily affected by the background noise level, whereas the number of blades is a less significant parameter. The significance of the proposed method lies in providing a quantitative evaluation of auditory detection probability of the UAV on the ground in the presence of a given soundscape. The results of this work are of practical significance since the method can aid anyone who plans a hovering flight mode.
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http://dx.doi.org/10.1121/10.0011546 | DOI Listing |
Sci Rep
December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
View Article and Find Full Text PDFIndian J Med Res
November 2024
Department of Laboratory Medicine, Jai Prakash Narayan Apex Trauma Center, All India Institute of Medical Sciences, New Delhi, India.
Background & objectives Surgical site infections (SSIs) are among the most prevalent healthcare-associated infections (HCAIs). They cause significant morbidity, leading to excess health expenditures and increased length of hospital stay. Despite a high population burden, data on post-discharge SSIs is lacking from low-and middle-income countries (LMICs).
View Article and Find Full Text PDFFront Public Health
December 2024
Department of Ophtalmology, Medical School, University of Pécs, Pécs, Hungary.
Background: Recent studies suggest that increased digital technology usage could be a factor in the rising occurrence and severity of headache episodes. The purpose of this cross-sectional study was to determine whether the severity of primary headaches (migraine and tension-type headache) is associated with problematic internet use taking many covariates into account.
Methods: We conducted an online cross-sectional survey using a quantitative, descriptive questionnaire, targeting university students enrolled in correspondence courses, aged 18 to 65.
Cureus
November 2024
Cardiology, National Institute of Cardiovascular Diseases, Karachi, PAK.
Introduction: Patients receiving renal transplants have weakened immune systems and are more vulnerable to lung infections.
Objectives: To determine the diagnostic accuracy of high-resolution computed tomography (HRCT) in detecting pneumocystis carinii in renal transplant patients presenting with pulmonary infection in a tertiary care transplant center, keeping bronchoalveolar lavage (BAL) as the gold standard.
Methods: This cross-sectional study was conducted at the Department of Radiology, Sindh Institute of Urology and Transplant, Karachi, from February 14, 2023, to August 13, 2023.
Front Immunol
December 2024
Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
Background And Objective: Neutrophil extracellular traps (NETs) with inflammatory risk are important contributors to cardiovascular disease, but no definitive information is available in large artery atherosclerotic (LAA) stroke. This study aims to investigate the association between NETs with related inflammatory biomarkers and prognosis of LAA stroke in the Chinese population.
Methods: A prospective study involving 145 LAA stroke cases and 121 healthy controls was conducted.
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