Animal signals are constrained by the environment in which they are transmitted and the sensory systems of receivers. Detection of movement-based signals is particularly challenging against the background of wind-blown plants. The Australian lizard Amphibolurus muricatus has recently been shown to compensate for greater plant motion by prolonging the introductory tail-flicking component of its movement-based display. Here I demonstrate that such modifications to signal structure are useful because environmental motion lengthens the time lizard receivers take to detect tail flicks. The spatio-temporal properties of animal signals and environmental motion are thus sufficiently similar to make signal detection more difficult. Environmental motion, therefore, must have had an influence on the evolution of movement-based signals and motion detection mechanisms.
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http://dx.doi.org/10.1098/rsbl.2007.0422 | DOI Listing |
Small
January 2025
School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou, 215009, China.
Eutectogels are recently emerged as promising alternatives to hydrogels owing to their good environmental stability derived from deep eutectic solvents (DES). However, construction of competent eutectogels with both high conductivity and mechanical toughness is still difficult to achieve yet highly demanded. In this work, new LMNP-PEDOT-CMC-AA (LPCA) eutectogels are prepared using acrylic acid (AA) and carboxymethylcellulose sodium (CMC) as polymeric networks, liquid metal nanoparticle-poly(3,4-ethylenedioxythiophene) (LMNP-PEDOT) are added as multifunctional soft fillers.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Computer Science and Information Systems, College of Applied Sciences, AlMaarefa University, Diriyah, Riyadh, Saudi Arabia.
Reinforcement learning is a remarkable aspect of the artificial intelligence field with many applications. Reinforcement learning facilitates learning new tasks based on action and reward principles. Motion planning addresses the navigation problem for robots.
View Article and Find Full Text PDFPLoS One
January 2025
Colleage of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China.
Target tracking techniques in the UAV perspective utilize UAV cameras to capture video streams and identify and track specific targets in real-time. Deep learning UAV target tracking methods based on the Siamese family have achieved significant results but still face challenges regarding accuracy and speed compatibility. In this study, in order to refine the feature representation and reduce the computational effort to improve the efficiency of the tracker, we perform feature fusion in deep inter-correlation operations and introduce a global attention mechanism to enhance the model's field of view range and feature refinement capability to improve the tracking performance for small targets.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Graduate School of Media and Governance, Keio University, 5322 Endo, Fujisawa City, Kanagawa Prefecture, 252-0882, Japan. Electronic address:
The adoption of residential renewable energy is pivotal for achieving the 'Net Zero' goal, yet financial assessments of household investments in this area remain complex due to dynamic market conditions. This study introduces a novel closed-form financial valuation framework for residential solar photovoltaic (PV) systems, explicitly addressing the uncertainties of electricity market price fluctuations (market risk) and energy policy changes (policy risk) using Geometric Brownian Motion (GBM). A case study in France demonstrates the framework's application, revealing that the discount rate is the most influential factor in solar PV valuation, followed by system lifespan and policy-driven Feed-in Tariff (FiT) rates.
View Article and Find Full Text PDFHeliyon
July 2024
School of Physics, Changchun University of Science and Technology, Changchun, 130022, China.
To analyze the motion laws of a magnetic and elastic coupling system under the influence of various factors, this paper proposes a magnetic coupling pendulum based on spring pieces and magnets-a magnetic-mechanical oscillator. By fixing spring pieces onto two non-magnetic bases and attaching magnets to their upper ends, which repel each other, the potential energy during oscillation is expanded using Fourier series. Subsequently, Lagrange equations are solved to study the effects of the first two terms of potential energy.
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