The conventional voter model is modified so that an agent's switching rate depends on the 'age' of the agent-that is, the time since the agent last switched opinion. In contrast to previous work, age is continuous in the present model. We show how the resulting individual-based system with non-Markovian dynamics and concentration-dependent rates can be handled both computationally and analytically. The thinning algorithm of Lewis and Shedler can be modified in order to provide an efficient simulation method. Analytically, we demonstrate how the asymptotic approach to an absorbing state (consensus) can be deduced. We discuss three special cases of the age-dependent switching rate: one in which the concentration of voters can be approximated by a fractional differential equation, another for which the approach to consensus is exponential in time, and a third case in which the system reaches a frozen state instead of consensus. Finally, we include the effects of a spontaneous change of opinion, i.e., we study a noisy voter model with continuous ageing. We demonstrate that this can give rise to a continuous transition between coexistence and consensus phases. We also show how the stationary probability distribution can be approximated, despite the fact that the system cannot be described by a conventional master equation.
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http://dx.doi.org/10.3390/e24101331 | DOI Listing |
PLoS One
January 2025
School of Social Research, Renmin University of China, Beijing, China.
The reform of rural collective property rights system is of great significance for protecting the collective asset rights and interests of villagers, activating rural resource elements, and achieving rural revitalization. This study is based on 284 village committee questionnaires and 7451 villager questionnaires from 10 provinces in China, and uses multi-layer linear regression models to explore the impact of the reform of rural collective property rights system on villagers' public participation. Research has found that:(1) the reform of rural collective property rights system that has been completed at the rural level can significantly enhance the public participation of villagers, including total participation (β = 0.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Engineering, Université de Moncton, Moncton, NB, E1A3E9, Canada.
Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. This research employs parallel and sequential ensemble ML approaches paired with feature selection techniques to boost classification accuracy.
View Article and Find Full Text PDFJ Neural Eng
January 2025
Department of Electrical and Computer Engineering, Stony Brook University, 211 Light Engineering, Stony Brook University, Stony Brook, NY 11794, Stony Brook, New York, 11794, UNITED STATES.
Objective Key challenges in upper limb prosthetics include a lack of effective control systems, the often invasive surgical requirements of brain-controlled limbs, and prohibitive costs. As a result, disuse rates remain high despite potential for increased quality of life. To address these concerns, this project developed a low cost, noninvasive transhumeral neuroprosthesis-operated via a combination of electroencephalography (EEG) signals and head gestures.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Physics, University of Calcutta, Kolkata, West Bengal, India.
We present a model of opinion formation where an individual's opinion is influenced by interactions with a group of agents. The model introduces a novel bias mechanism that favors one opinion, a feature not previously explored. In the absence of bias, the system reduces to a mean field voter model.
View Article and Find Full Text PDFEntropy (Basel)
December 2024
School of Mathematical and Physical Sciences, Macquarie University, Sydney, NSW 2109, Australia.
The density classification (DC) task, a computation which maps global density information to local density, is studied using one-dimensional non-unitary quantum cellular automata (QCAs). Two approaches are considered: one that preserves the number density and one that performs majority voting. For number-preserving DC, two QCAs are introduced that reach the fixed-point solution in a time scaling quadratically with the system size.
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