Complex interactions call for the sharing of information between different entities. In a recent paper, we introduced a combinatoric model which concretizes this idea via a string-matching rule. The model was shown to lend itself to analysis regarding certain topological features of the network. In this paper, we will introduce a statistical physics description of this network in terms of a Potts model. We will give an explicit mean-field treatment of a special case that has been proposed as a model for gene regulatory networks, and derive closed-form expressions for the topological coefficients. Simulations of the hidden variable network are then compared with numerically integrated results.
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http://dx.doi.org/10.1063/1.2743613 | DOI Listing |
Front Nutr
December 2024
Changshu Key Laboratory of Medical Artificial Intelligence and Big Data, Suzhou, Jiangsu, China.
Heliyon
October 2024
Department Mathematics and Computer Science, Faculty of Science and Technology, University of Nouakchott, Nouakchott, Mauritania.
The rapid increase of online educational content has made it harder for students to find specific information. E-learning recommender systems help students easily find the learning objects they require, improving the learning experience. The effectiveness of these systems is further improved by integrating deep learning with multi-agent systems.
View Article and Find Full Text PDFSensors (Basel)
November 2024
Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan 420008, Russia.
This study is devoted to creating a neural network technology for assessing metal accumulation in the body of a metropolis resident with short-term and long-term intake from anthropogenic sources. Direct assessment of metal retention in the human body is virtually impossible due to the many internal mechanisms that ensure the kinetics of metals and the wide variety of organs, tissues, cellular structures, and secretions that ensure their functional redistribution, transport, and cumulation. We have developed an intelligent multi-neural network model capable of calculating the content of metals in the human body based on data on their environmental content.
View Article and Find Full Text PDFSci Rep
November 2024
Computer Science Department, Faculty of Computers and Information, Mansoura University, Mansoura, 35516, Egypt.
Food Chem
February 2025
College of Agriculture, Heilongjiang Bayi Agricultural University, DaQing 163319, China.
Rapid detection of corn moisture content(MC) during maturity is of great significance for field cultivation, mechanical harvesting, storage, and transportation management. However, cumbersome operation, time-consuming and labor-intensive operation were the bottleneck in the traditional drying process and dielectric parameter method. Thus, to overcome the above problems, a rapid detection method for corn MC based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) combined with temporal convolutional network-bidirectional gated recurrent unit (TCN-BiGRU) model.
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