To explore the association between occupational noise perception and cardiovascular disease (CVD), depression symptoms, as well as their comorbidity in occupational population and provide evidence for the prevention and control of physical and mental illnesses. A cross-sectional survey design was adopted, based on baseline data in population in 28 prefectures in Sichuan Province and Guizhou Province, and 33 districts (counties) in Chongqing municipality from Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during October to December 2021. A questionnaire survey was conducted to collect information about noise perception, depressive symptoms, and the history of CVD. Latent profile analysis model was used to determine identify noise perception type, and multinomial logistic regression analysis was conducted to explore the relationship between different occupational noise perception types and CVD, depression symptoms and their comorbidity. A total of 30 509 participants were included, the mean age was (36.6±10.5) years, and men accounted for 82.0%. The direct perception of occupational noise, psychological effects and hearing/sleep impact of occupational noise increased the risk for CVD, depressive symptoms, and their comorbidity. By using latent profile analysis, occupational noise perception was classified into four levels: low, medium, high, and very high. As the level of noise perception increased, the association with CVD, depressive symptoms, and their comorbidity increased. In fact, very high level occupational noise perception were found to increase the risk for CVD, depressive symptoms, and their comorbidity by 2.14 (95%: 1.73-2.65) times, 8.80 (95%: 7.91-9.78) times, and 17.02 (95% 12.78-22.66) times respectively compared with low-level occupational noise perception. Different types of occupational noise perception are associated with CVD and depression symptom, especially in the form of CVD complicated with depression symptom. Furthermore, the intensity of occupational noise in the work environment should be reduced to lower the risk for physical and mental health.
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http://dx.doi.org/10.3760/cma.j.cn112338-20230715-00009 | DOI Listing |
Despite its potential for label-free particle diagnostics, holographic microscopy is limited by specialized processing methods that struggle to generalize across diverse settings. We introduce a deep learning architecture leveraging human perception of longitudinal variation of diffracted patterns of particles, which enables highly generalizable analysis of 3D particle information with orders of magnitude improvement in processing speed. Trained with minimal synthetic and real holograms of simple particles, our method demonstrates exceptional performance across various challenging cases, including high particle concentrations, significant noise, and a wide range of particle sizes, complex shapes, and optical properties, exceeding the diversity of training datasets.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
Background: Cochlear implants (CI) with off-the-ear (OTE) and behind-the-ear (BTE) speech processors differ in user experience and audiological performance, impacting speech perception, comfort, and satisfaction.
Objectives: This systematic review explores audiological outcomes (speech perception in quiet and noise) and non-audiological factors (device handling, comfort, cosmetics, overall satisfaction) of OTE and BTE speech processors in CI recipients.
Methods: We conducted a systematic review following PRISMA-S guidelines, examining Medline, Embase, Cochrane Library, Scopus, and ProQuest Dissertations and Theses.
J Acoust Soc Am
January 2025
Department of Biology, University of Aarhus, Aarhus, 8000, Denmark.
Gransier and Kastelein [J. Acoust. Soc.
View Article and Find Full Text PDFTrends Hear
January 2025
Key Laboratory of Noise and Vibration Research, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China.
Wide dynamic range compression (WDRC) and noise reduction both play important roles in hearing aids. WDRC provides level-dependent amplification so that the level of sound produced by the hearing aid falls between the hearing threshold and the highest comfortable level of the listener, while noise reduction reduces ambient noise with the goal of improving intelligibility and listening comfort and reducing effort. In most current hearing aids, noise reduction and WDRC are implemented sequentially, but this may lead to distortion of the amplitude modulation patterns of both the speech and the noise.
View Article and Find Full Text PDFNeuroimage
January 2025
Department of Computer Science, University of Innsbruck, Technikerstrasse 21a, Innsbruck, 6020, Austria. Electronic address:
The objective of this study is to assess the potential of a transformer-based deep learning approach applied to event-related brain potentials (ERPs) derived from electroencephalographic (EEG) data. Traditional methods involve averaging the EEG signal of multiple trials to extract valuable neural signals from the high noise content of EEG data. However, this averaging technique may conceal relevant information.
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