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The perception of beauty, though often subjective, is influenced by identifiable structural and spatial patterns that shape how individuals experience their surroundings. This study explores the roles of object variety and connections in scenic images in shaping perceptions of environmental aesthetics, using advanced computer vision techniques and regression analysis. Drawing on data from the Scenic-Or-Not project and leveraging the Segment Anything Model, we analysed landscape photographs to understand how object diversity and spatial arrangement affect aesthetic judgments. Our findings reveal a positive correlation between object diversity and perceived scenicness, emphasizing the importance of visual richness and complexity in enhancing scenic appeal. However, excessive object diversity can introduce visual clutter and diminish aesthetic value. Our analysis of object connections, measured through graph-based metrics like network density and clustering coefficient, reveals that denser and more interconnected arrangements enhance scenic appeal, while overly efficient local connections reduce visual interest. These results demonstrate the importance of balancing complexity, coherence and interconnectedness in scenic design. By situating these findings within established theoretical frameworks, this study provides insights for disciplines such as environmental science, urban planning and landscape management, offering guidance for creating environments that evoke positive aesthetic experiences while maintaining visual harmony and interest.
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http://dx.doi.org/10.1098/rsif.2025.0045 | DOI Listing |
Bioinspir Biomim
September 2025
Mechanical Intelligence (MI) Research Group, London South Bank University, 103 Borough Road, London, London, SE1 0AA, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
Conventional rigid grippers remain the most-used robotic grippers in industrial assembly tasks. However, they are limited in their ability to handle a diverse range of objects. This study draws inspiration from nature to address these limitations, employing multidisciplinary methods, such as computer-aided design, parametric modeling, finite element analysis, 3D printing, and mechanical testing.
View Article and Find Full Text PDFAdv Mater
September 2025
Departmant of Materials Science and Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
Microrobots are expected to push the boundaries of robotics by enabling navigation in confined and cluttered environments due to their sub-centimeter scale. However, most microrobots perform best only in the specific conditions for which they are designed and require complete redesign and fabrication to adapt to new tasks and environments. Here, fully 3D-printed modular microrobots capable of performing a broad range of tasks across diverse environments are introduced.
View Article and Find Full Text PDFDisabil Rehabil
September 2025
Occupational Performance Network, Sydney, Australia.
Purpose: Initial studies identified the Perceive, Recall, Plan and Perform Assessment (PRPP-A) as a cognitive assessment with potential for culturally safe use with Aboriginal and Torres Strait Islander peoples with neurocognitive impairments in the Northern Territory of Australia. This study examines construct and concurrent validity of the PRPP-A.
Methods: Data were collected from a medical record review.
J Vis
September 2025
Institute de Neurosciences de la Timone, Aix-Marseille Univ, CNRS, Marseille, France.
The visual systems of animals work in diverse and constantly changing environments where organism survival requires effective senses. To study the hierarchical brain networks that perform visual information processing, vision scientists require suitable tools, and Motion Clouds (MCs)-a dense mixture of drifting Gabor textons-serve as a versatile solution. Here, we present an open toolbox intended for the bespoke use of MC functions and objects within modeling or experimental psychophysics contexts, including easy integration within Psychtoolbox or PsychoPy environments.
View Article and Find Full Text PDFInt Dent J
September 2025
Department of Prosthodontics and Dental Implantology, King Faisal University, Al-Ahsa, Saudi Arabia. Electronic address:
Objective: To overcome the scarcity of annotated dental X-ray datasets, this study presents a novel pipeline for generating high-resolution synthetic orthopantomography (OPG) images using customized generative adversarial networks (GANs).
Methods: A total of 4777 real OPG images were collected from clinical centres in Pakistan, Thailand, and the U.S.