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Association Between Serum Levels of Perfluoroalkyl and Polyfluoroalkyl Substances and Dental Floss Use: The Double-Edged Sword of Dental Floss Use-A Cross-Sectional Study.
J Clin Periodontol
January 2025
Department of Pediatric Surgery, Children's Medical Center, The First Hospital of Jilin University, Changchun, China.
Background: Although evidence suggests that dental floss contains perfluoroalkyl and polyfluoroalkyl substances (PFASs), it is still uncertain whether the use of dental floss contributes to an increased risk of PFAS exposure.
Methods: We analysed data on serum PFAS concentrations and dental floss usage in a cohort of 6750 adults who participated in the National Health and Nutrition Examination Survey (NHANES) from 2009 to 2020. In our study, we used logistic regression, a survey-weighted linear model, item response theory (IRT) scores, inverse probability weights (IPWs) and sensitivity analysis to assess the potential impact of dental floss usage on human serum PFAS levels.
Application of PN Code in Time Delay Measurement of Telephone Network.
Sensors (Basel)
January 2025
National Time Service Center, Chinese Academy of Sciences, Xi'an 710600, China.
Telephone time service is a wired time service that transmits time signals through a telephone network, with the advantages of simple receiving equipment and wide coverage. But the performance of time service is not high, usually several milliseconds. The time delay measurement of the telephone network is an important factor limiting the improvement in timing performance.
View Article and Find Full Text PDFUncertainty-Aware Multimodal Trajectory Prediction via a Single Inference from a Single Model.
Sensors (Basel)
January 2025
Seamless Trans-X Lab (STL), School of Integrated Technology, Yonsei University, Incheon 21983, Republic of Korea.
In the domain of autonomous driving, trajectory prediction plays a pivotal role in ensuring the safety and reliability of autonomous systems, especially when navigating complex environments. Unfortunately, trajectory prediction suffers from uncertainty problems due to the randomness inherent in the driving environment, but uncertainty quantification in trajectory prediction is not widely addressed, and most studies rely on deep ensembles methods. This study presents a novel uncertainty-aware multimodal trajectory prediction (UAMTP) model that quantifies aleatoric and epistemic uncertainties through a single forward inference.
View Article and Find Full Text PDFAnalysis of Autonomous Penetration Testing Through Reinforcement Learning and Recommender Systems.
Sensors (Basel)
January 2025
Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Computer Science and Engineering, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor José García Santesmases, 9, Ciudad Universitaria, 28040 Madrid, Spain.
Conducting penetration testing (pentesting) in cybersecurity is a crucial turning point for identifying vulnerabilities within the framework of Information Technology (IT), where real malicious offensive behavior is simulated to identify potential weaknesses and strengthen preventive controls. Given the complexity of the tests, time constraints, and the specialized level of expertise required for pentesting, analysis and exploitation tools are commonly used. Although useful, these tools often introduce uncertainty in findings, resulting in high rates of false positives.
View Article and Find Full Text PDFIssues and Limitations on the Road to Fair and Inclusive AI Solutions for Biomedical Challenges.
Sensors (Basel)
January 2025
School of Mathematics, Physics and Computing, University of Southern Queensland, Springfield, QLD 4300, Australia.
Objective: In this paper, we explore the correlation between performance reporting and the development of inclusive AI solutions for biomedical problems. Our study examines the critical aspects of bias and noise in the context of medical decision support, aiming to provide actionable solutions. Contributions: A key contribution of our work is the recognition that measurement processes introduce noise and bias arising from human data interpretation and selection.
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