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Data-Driven Framework for Uncovering Hidden Control Strategies in Evolutionary Analysis
Mathematical and Computational Applications, 2023 We devised a data-driven framework for uncovering hidden control strategies used by an evolutionary system described by an evolutionary probability distribution. This innovative framework enables deciphering of the concealed mechanisms that contribute to
Nourddine Azzaoui +2 more
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Behavior of the iterative ensemble-based variational method in nonlinear problems [PDF]
Nonlinear Processes in Geophysics, 2021 The behavior of the iterative ensemble-based data assimilation algorithm is discussed. The ensemble-based method for variational data assimilation problems, referred to as the 4D ensemble variational method (4DEnVar), is a useful tool for data ...
S. Nakano, S. Nakano
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Statistical models of fracture [PDF]
Advances in Physics, 2006 Disorder and long-range interactions are two of the key components that make material failure an interesting playfield for the application of statistical mechanics. The cornerstone in this respect has been lattice models of the fracture in which a network of elastic beams, bonds or electrical fuses with random failure thresholds are subject to an ...
Mikko J. Alava +2 more
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Mathematics, 2023 Synaptic transmission is the main process providing cross-connecting activity among neurons in the central nervous system (CNS). In the present study, the 3D mathematical model of a neuronal bouton with a cluster localization of glycine receptors (GlyRs)
Yaroslav R. Nartsissov +1 more
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Tweet Analysis for Enhancement of COVID-19 Epidemic Simulation: A Case Study in Japan
Frontiers in Public Health, 2022 The COVID-19 pandemic, which began in December 2019, progressed in a complicated manner and thus caused problems worldwide. Seeking clues to the reasons for the complicated progression is necessary but challenging in the fight against the pandemic.
Vu Tran, Tomoko Matsui, Tomoko Matsui
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IEEE Access, 2022 Hybrid recommendation, which is based on collaborative filtering and supplemented with auxiliary content information, is being actively researched due to its ability to overcome the cold-start problem.
Iwao Tanuma, Tomoko Matsui
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Rating Proportion-Aware Binomial Matrix Factorization for Collaborative Filtering
IEEE Access, 2023 Addressing biases in observed data is a major challenge in statistical and machine learning applications. This challenge also exists in recommendation systems, and various methods based on causal inference are being investigated.
Iwao Tanuma, Tomoko Matsui
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COVID-19 case prediction using emotion trends via Twitter emoji analysis: A case study in Japan
Frontiers in Public Health, 2023 IntroductionThe worldwide COVID-19 pandemic, which began in December 2019 and has lasted for almost 3 years now, has undergone many changes and has changed public perceptions and attitudes.
Vu Tran, Tomoko Matsui, Tomoko Matsui
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Frontiers in Genetics, 2022 Proteins need to interact with different ligands to perform their functions. Among the ligands, the metal ion is a major ligand. At present, the prediction of protein metal ion ligand binding residues is a challenge. In this study, we selected Zn2+, Cu2+,
Sixi Hao +13 more
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Frontiers in Genetics, 2022 The realization of many protein functions is inseparable from the interaction with ligands; in particular, the combination of protein and metal ion ligands performs an important biological function.
Shuang Xu +13 more
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