Aerial predators adopt a variety of different hunting styles, with divergent flight morphologies typically adapted either to high-speed interception or manoeuvring through clutter, but how are their sensorimotor systems tuned in relation to habitat structure and prey behavior? Falcons intercept prey at high-speed using the same proportional navigation guidance law as homing missiles. This classical guidance law works well in the open, but performs sub-optimally against highly-manoeuvrable targets, and may not produce a feasible path through the cluttered environments frequented by hawks and other raptors. Here we identify the guidance law of n = 5 Harris' Hawks Parabuteo unicinctus chasing erratically manoeuvring artificial targets. Harris' Hawks use a mixed guidance law, coupling low-gain proportional navigation with a low-gain proportional pursuit element. This guidance law promotes tail-chasing and is not thrown off by erratic manoeuvres, making it well suited to the hawks' natural hunting style, involving close pursuit of agile prey through clutter.
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http://dx.doi.org/10.1038/s41467-019-10454-z | DOI Listing |
Sci Rep
December 2024
School of Marxism, China University of Political Science and Law (CUPL), Beijing, 100091, China.
To improve students' understanding of physical education teaching concepts and help teachers analyze students' cognitive patterns, the study proposes an association learning-based method for understanding physical education teaching concepts using deep learning algorithms, which extracts image features related to teaching concepts using convolutional neural networks. Moreover, a neurocognitive diagnostic model based on hypergraph convolution is constructed to mine the data of students' long-term learning sequences and identify students' cognitive outcomes. The findings revealed that the highest accuracy of the association graph convolutional neural network was 0.
View Article and Find Full Text PDFSci Rep
December 2024
School of Physics and Astronomy, University of Minnesota, Minneapolis, MN, 55455, USA.
Quantum computers promise a qualitative speedup in solving a broad spectrum of practical optimization problems. The latter can be mapped onto the task of finding low-energy states of spin glasses, which is known to be exceedingly difficult. Using D-Wave's 5000-qubit quantum processor, we demonstrate that a recently proposed iterative cyclic quantum annealing algorithm can find deep low-energy states in record time.
View Article and Find Full Text PDFRecent calls have been made for equity tools and frameworks to be integrated throughout the research and design life cycle -from conception to implementation-with an emphasis on reducing inequity in artificial intelligence (AI) and machine learning (ML) applications. Simply stating that equity should be integrated throughout, however, leaves much to be desired as industrial ecology (IE) researchers, practitioners, and decision-makers attempt to employ equitable practices. In this forum piece, we use a critical review approach to explain how socioecological inequities emerge in ML applications across their life cycle stages by leveraging the food system.
View Article and Find Full Text PDFJMIR Rehabil Assist Technol
December 2024
College of Arts, Business, Law, Education and IT, Victoria University, Footscray Park, Australia.
Background: Evidence suggests that individuals with motor neuron disease (MND), a terminal illness, find enjoyment and social connection through video games. However, MND-related barriers can make gaming challenging, exacerbating feelings of boredom, stress, isolation, and loss of control over daily life.
Objective: We scoped the evidence to describe relevant research and practice regarding what may help reduce difficulties for people with MND when playing video games.
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