While the statics of many simple physical systems reproduce the striking number-theoretical patterns found in the phyllotaxis of living beings, their dynamics reveal unusual excitations: multiple classical rotons and a large family of interconverting topological solitons. As we introduce those, we also demonstrate experimentally for the first time Levitov's celebrated model for phyllotaxis. Applications at different scales and in different areas of physics are proposed and discussed.
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http://dx.doi.org/10.1103/PhysRevLett.102.186103 | DOI Listing |
J Voice
January 2025
Division of Phoniatrics, ENT University Hospital Graz, Medical University of Graz, Graz, Austria; Division of Physiology and Pathophysiology, Otto Loewi Research Center for Vascular Biology, Immunology and Inflammation, Medical University of Graz, Graz, Austria.
Int J Biol Macromol
January 2025
Jiangsu Co-Innovation Center for Efficient Processing and Utilization of Forest Resources, Jiangsu Provincial Key Lab Pulp & Paper Science and Technology, Nanjing Forestry University, Nanjing 210037, PR China. Electronic address:
Utilizing cellulose nanocrystals (CNCs) to mimic biological skin capable of converting external stimuli into optical and electrical signals represents a significant advancement in the development of advanced photonic materials. However, traditional CNC photonic materials typically exhibit static and singular optical properties, with their structural color and mechanical performance being susceptible to water molecules, thereby limiting their practical applications. In this study, CNC-based conductive elastomers with dynamic mechanochromism, fluorescence responsiveness, and enhanced water resistance were developed by incorporating carbon quantum dots (C QDs) and hydrophobic deep eutectic solvents (HDES) into CNC photonic films via an in-situ swelling-photopolymerization method.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Computer Science, King AbdulAziz University, Jeddah 21589, Saudi Arabia.
Traffic flow prediction is a pivotal element in Intelligent Transportation Systems (ITSs) that provides significant opportunities for real-world applications. Capturing complex and dynamic spatio-temporal patterns within traffic data remains a significant challenge for traffic flow prediction. Different approaches to effectively modeling complex spatio-temporal correlations within traffic data have been proposed.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
With the demand for high-safety, high-integration, and lightweight micro- and nano-electronic components, an MEMS electromagnetic energy-releasing component was innovatively designed based on the corona discharge theory. The device subverted the traditional device-level protection method for electromagnetic energy, realizing the innovation of adding a complex circuit system to the integrated chip through micro-nanometer processing technology and enhancing the chip's size from the centimeter level to the micron level. In this paper, the working performance of the MEMS electromagnetic energy-releasing component was verified through a combination of a simulation, a static experiment, and a dynamic test, and a characterization test of the tested MEMS electromagnetic energy-releasing component was carried out to thoroughly analyze the effect of the MEMS electromagnetic energy-releasing component.
View Article and Find Full Text PDFSensors (Basel)
January 2025
University-Industrial Cooperation Corps of HiVE Center, Wonkwang Health Science University, 514, Iksan-daero, Iksan-si 54538, Republic of Korea.
Virtual reality (VR) technology has gained popularity across various fields; however, its use often induces cybersickness, characterized by symptoms such as dizziness, nausea, and eye strain. This study investigated the differences in cybersickness levels and head movement patterns under three distinct VR viewing conditions: dynamic VR (DVR), static VR (SVR), and a control condition (CON) using a simulator. Thirty healthy adults participated, and their head movements were recorded using the Meta Quest 2 VR headset and analyzed using Python.
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