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Background: Everyday locomotion often requires that we navigate crowded and cluttered environments. Individuals navigating through nonconfined space will require a deviation from the straight path in order to avoid apertures smaller than 1.4 times their shoulder width. When in a crowd, humans will follow the behaviours of those directly in front of them, making changes to their walking speed and direction heading based on the changes made by the people they are following.
Research Question: The current study aimed to discover whether the decisions made by young adults regarding the passability of an aperture would be influenced by the presence of a leader completing the same nonconfined aperture crossing task.
Methods: Participants (N = 24) walked in a virtual reality environment along a 6.5 m pathway towards a goal while avoiding two virtual poles which created an aperture (0.8-1.8 times the participants' shoulder widths). For some trials, a sex-matched avatar (shoulder width of 0.8, 1.0, or 1.2 times the participants' shoulder widths) completed the aperture crossing task, using its own body-scaled information, ahead of the participant.
Results: Participants walked through apertures smaller than 1.4 times their shoulder width (i.e. critical point) regardless of avatars' independent behaviours. Participants began to deviate 3.69 m from the aperture on all trials that required a deviation and approached their goal at a slower speed when the avatar was present.
Significance: This study demonstrates that during a nonconfined aperture crossing task, individuals are not influenced by human following behaviours and will continue to make decisions based on their own body-scaled information.
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http://dx.doi.org/10.1016/j.gaitpost.2020.11.002 | DOI Listing |
Science
September 2025
Institut Terre et Environnement de Strasbourg UMR 7063, Université de Strasbourg, CNRS, Strasbourg, France.
Seismic waves from large earthquakes are known to trigger slip on distant faults, but the underlying mechanisms remain unclear. Using interferometric synthetic aperture radar and local geodetic and seismic data, we show that the 1000-kilometer-distant, February 2023 Kahramanmaraş earthquakes in southeastern Türkiye triggered deformation and/or eruption at 56 mud volcanoes and centimeter-scale aseismic slip on seven faults over tens of kilometers within the fluid-rich Kura Basin in the West Caspian region. This transient deformation event, with an equivalent moment magnitude of 6.
View Article and Find Full Text PDFSensors (Basel)
August 2025
Navigation and Ship Engineering College, Dalian Ocean University, Dalian 116023, China.
This study aims to develop an enhanced YOLO algorithm to improve the ship detection performance of synthetic aperture radar (SAR) in complex marine environments. Current SAR ship detection methods face numerous challenges in complex sea conditions, including environmental interference, false detection, and multi-scale changes in detection targets. To address these issues, this study adopts a technical solution that combines multi-level feature fusion with a dynamic detection mechanism.
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August 2025
School of Computer Science and Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China.
Cross-modal remote sensing object detection holds significant potential for around-the-clock applications. However, the modality differences between cross-modal data and the degradation of feature quality under adverse weather conditions limit detection performance. To address these challenges, this paper presents a novel cross-modal remote sensing object detection framework designed to overcome two critical challenges in around-the-clock applications: (1) significant modality disparities between visible light, infrared, and synthetic aperture radar data, and (2) severe feature degradation under adverse weather conditions including fog, and nighttime scenarios.
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August 2025
College of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
To address the challenging problem of multi-scale inshore-offshore ship detection in synthetic aperture radar (SAR) remote sensing images, we propose a novel deep learning-based automatic ship detection method within the framework of compositional learning. The proposed method is supported by three pillars: context-guided region proposal, prototype-based model-pretraining, and multi-model ensemble learning. To reduce the false alarms induced by the discrete ground clutters, the prior knowledge of the harbour's layout is exploited to generate land masks for terrain delimitation.
View Article and Find Full Text PDFLasers Surg Med
October 2025
Department of Dermatology, Veterans Health Administration, San Antonio, Texas, USA.
Objectives: Limited-cutaneous systemic sclerosis (lcSSc), formerly known as CREST syndrome (calcinosis, Raynaud phenomenon, esophageal dysmotility, scleroderma, and telangiectasias) is an auto-immune connective tissue disease characterized by cutaneous fibrosis and systemic fibrovascular dysfunction. The cutaneous fibrosis of lcSSc is commonly limited to acral sites, with perioral involvement seen in 70%-85% of cases. Patients often seek treatment of lcSSc-associated microstomia for functional and cosmetic purposes.
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