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The expansion of anthropogenic noise poses an emerging threat to the survival and reproductive success of various organisms. Previous investigations have focused on the detrimental effects of anthropogenic noise on the foraging behavior in some terrestrial and aquatic animals. Nevertheless, the role of airport noise in impairing foraging activities of most wild animals has been neglected. Here, we aimed to assess whether foraging behavior in free-living Japanese pipistrelle bats () can be disturbed by airport noise. We used audio recording to monitor foraging activities of bats at 11 sites around the runway of a municipal airport. We quantified noise level and spectra, aircraft activity, habitat type, nightly temperature, wind speed, and moon phase for each site. The analysis revealed that noise level and aircraft activity were significant negative predictors for the number of bat passes and feeding buzzes around the runway, even after controlling for the effects of other environmental factors. There was no marked spectral overlap between bat echolocation pulses and airport noise in the presence and absence of low-flying aircraft. The spectro-temporal parameters of echolocation vocalizations emitted by bats were dependent on noise level, aircraft activity, and habitat type. These results provide correlative evidence that airport noise can reduce foraging activities of wild pipistrelle bats. Our findings add to the current knowledge of adverse impacts of airport noise on foraging bats in artificial ecosystems and provide a basis for further research on the mechanisms behind noise pollution near airports.
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http://dx.doi.org/10.1002/ece3.8976 | DOI Listing |
Sensors (Basel)
August 2025
School of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China.
Driven by the increasing global population and rapid urbanization, aircraft noise pollution has emerged as a significant environmental challenge, impeding the sustainable development of the aviation industry. Traditional noise prediction methods are limited by incomplete datasets, insufficient spatiotemporal consistency, and poor adaptability to complex meteorological conditions, making it difficult to achieve precise noise management. To address these limitations, this study proposes a novel noise prediction framework based on a hybrid Convolutional Neural Network-Bidirectional Long Short-Term Memory-Attention (CNN-BiLSTM-Attention) model.
View Article and Find Full Text PDFInt J Environ Res Public Health
August 2025
Department of Architecture, National Institute of Technology, Ishikawa College, Tsubata 929-0392, Japan.
This study examines the impact of aircraft noise on annoyance and sleep disturbances among residents near Tan Son Nhat Airport in Ho Chi Minh City, Vietnam, from 2019 to 2023. It aims to assess the specific effects of aircraft noise exposure on sleep quality, as well as changes in exposure due to reduced air traffic during the COVID-19 pandemic. Surveys conducted before and during the pandemic revealed that, despite lower noise levels, residents continued to report high levels of annoyance, indicating a complex exposure-response relationship.
View Article and Find Full Text PDFSci Rep
August 2025
Department of Electrical Engineering, Dr. Shakuntala Misra National Rehabilitation University, Lucknow, India.
This study presents breakthrough mathematical formulations for UAV tracking that achieve 56.1% HOTA accuracy for targets with start-stop and irregular motion-a 65% improvement over traditional Kalman Filter approaches. Unmanned aerial vehicles face significant challenges when tracking targets exhibiting abrupt velocity changes, intermittent stops, and nonlinear trajectories due to motion discontinuities, occlusions, and environmental noise.
View Article and Find Full Text PDFSensors (Basel)
July 2025
School of Transportation, Southeast University, Nanjing 211189, China.
Traditional Foreign Object Debris (FOD) detection methods face challenges such as difficulties in large-size data acquisition and the ineffective application of detection algorithms with high accuracy. In this paper, image data augmentation was performed using generative adversarial networks and diffusion models, generating images of monitoring areas under different environmental conditions and FOD images of varied types. Additionally, a three-stage image blending method considering size transformation, a seamless process, and style transfer was proposed.
View Article and Find Full Text PDFSolid State Nucl Magn Reson
October 2025
CSIRO, Lucas Heights Science and Technology Centre, Lucas Heights, 2234, NSW, Australia.
The ability to rapidly detect the presence of narcotic substances in baggage and on personnel is a prime requirement in airports, mail distribution centres and mass screening portals. Nuclear Quadrupole Resonance (NQR) is well-suited to detect selected narcotics as the resonances can be highly discriminating of a given substance due to the presence of narrow, non-overlapping spectral lines. Furthermore, the transparency of non-conductive materials to radio frequency (RF) magnetic fields allows for NQR to measure bulk volumes without any sample preparation.
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