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Objective: Urban short underpass tunnels, characterized by steep longitudinal slopes, limited lengths, and abrupt light transitions, pose significant driving risks. This study aims to comprehensively investigate drivers' speed control behavior, visual adaptation processes, and mental workload mechanisms within such tunnels under real traffic conditions.
Methods: A real-vehicle experiment was conducted involving 35 drivers. Data on speed, acceleration, pupil area, and heart rate were collected. The experimental road segment was divided into five sections: entry, downhill, tunnel, uphill, and departure, to analyze driving behavior characteristics and psychophysiological responses systematically.
Results: Speed increased significantly in the downhill section and decreased notably in the uphill and departure sections. The tunnel section exhibited a high incidence of speeding, while the uphill section showed the most significant speed variability, both identified as high-risk zones for rear-end collisions. Regarding visual adaptation, drivers entered a dark adaptation ∼70 m before reaching the tunnel entrance, marked by a gradual increase in pupil area. Around 50 m before the tunnel exit, drivers transitioned to light adaptation, and the pupil area decreased rapidly. Mental workload analysis revealed that drivers' heart rates increased during the downhill section, peaked shortly after entering the tunnel, and gradually declined as light adaptation began. Further analysis showed that acceleration was negatively correlated with heart rate growth rate (HRG), while pupil area change rate (PAC) and vehicle speed positively correlated with HRG.
Conclusion: This study reveals that speed behavior, visual adaptation, and mental workload in urban short underpass tunnels vary significantly across road sections, with the tunnel and uphill sections posing the highest risk for rear-end collisions, highlighting the need for targeted tunnel design and traffic safety measures.
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http://dx.doi.org/10.1080/15389588.2025.2543500 | DOI Listing |
J Atten Disord
September 2025
Universidad Nacional Autónoma de México, Mexico.
Objective: Susceptibility to visual illusions is a consequence of the adaptation of the visual system, however, their perception or lack of it reflects differences in more general, global cognitive processes. Few studies have focussed on the susceptibility of individuals with attention-deficit/hyperactivity disorder (ADHD), even though visual impairment and percept differences have been thoroughly documented.
Method: The present study evaluated 75 children (ages 6.
Ther Innov Regul Sci
September 2025
Fiocruz Brasilia, ColLaboratory of Science, Technology, Innovation and Society (CTIS), Brasilia, DF, Brazil.
Purpose: To identify and review scientific evidence from experimental studies utilizing unmanned aerial vehicles (UAVs) to transport samples for the diagnosis of COVID-19 and tuberculosis (TB). This exploratory study aims to support the future development of UAVs for transporting biological samples within the Brazilian Unified Health System (SUS).
Methods: This scoping review defined its eligibility criteria using the PECO acronym, focusing on: Population: biological samples for diagnosing COVID-19 or TB; Exposure: UAV transportation; Comparator: land transportation; Outcomes: Cost, effectiveness, methods for sample preservation, flight parameters (time, altitude, speed, distance), and quality of transported samples.
J Bone Miner Res
September 2025
Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States.
Autosomal Dominant Osteopetrosis (ADO) is a rare, osteosclerotic disorder usually caused by missense variants in the CLCN7 gene, resulting in impaired osteoclastic bone resorption. Penetrance is incomplete and disease severity varies widely, even among relatives within the same family. Although ADO can cause visual loss, osteonecrosis, osteomyelitis, and bone marrow failure, the most common complication of ADO is fracture.
View Article and Find Full Text PDFSci Rep
September 2025
Fukushima Renewable Energy Institute, Koriyama, 963-0298, Japan.
This study proposes a novel and computationally efficient method for real-time identification and localization of power quality (PQ) disturbances in microgrids using dynamic Lissajous patterns formed by voltage and current waveforms. Each power disturbance-such as sag, swell, harmonic distortion, and transients-induces a unique geometric deformation in the Lissajous figure, which serves as a visual signature of the event. Key geometric and statistical features, including area, skewness, kurtosis, and centroid deviation, are extracted from these dynamic patterns to construct robust indices for classification.
View Article and Find Full Text PDFThis paper presents a novel multiscale signal processing framework for power quality disturbance (PQD) and cyber intrusion detection in smart grids, combining Non-Subsampled Contourlet Transform (NSCT), Split Augmented Lagrangian Shrinkage Algorithm (SALSA), and Morphological Component Analysis (MCA). A key innovation lies in an adaptive weighting mechanism within NSCT's directional sub bands, enabling dynamic energy redistribution and enhanced representation of both low-frequency anomalies (e.g.
View Article and Find Full Text PDF