20 papers · ranked by Valyu relevance
Junqing Ma, Aiguo Song, Jing Xiao
Coupling errors are major threats to the accuracy of 3-axis force sensors. Design of decoupling algorithms is a challenging topic due to the uncertainty of coupling errors. The conventional nonlinear decoupling algorithms by a standard Neural Network (NN) are sometimes unstable due to overfitting. In order to avoid…
Mohsen Sadeghi, James N. Ingram, Daniel M. Wolpert, Ramesh Balasubramaniam
'Ramesh Balasubramaniam'] Sensorimotor learning typically shows generalization from one context to another. Models of sensorimotor learning characterize this with a fixed generalization function that couples learning between contexts. Here we examine whether such coupling is indeed fixed or changes with experience. We…
Christopher J. Vogl, Hui Wan, Carol S. Woodward, Quan M. Bui
Part I of this study discusses the motivation and empirical evaluation of a revision to the aerosol-related numerical process coupling in the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) to address the previously reported issue of strong sensitivity of the simulated dust aerosol…
Pratik Sachdeva, Ji Hyun Bak, Jesse Livezey, Christoph Kirst + 3 more
A key component to understanding the brain is determining the influence of groups of neurons on each other relative to other influences. In the brain, all neurons are driven by the activity of other neurons, some of which may be simultaneously recorded, but most are not. As such, models of neuronal activity need to…
Noga Mosheiff, Yoram Burak
Grid cells in the medial entorhinal cortex (mEC) encode position using a distributed representation across multiple neural populations (modules), each possessing a distinct spatial scale. The modular structure of the representation confers the grid cell neural code with large capacity. Yet, the modularity poses…
Giulio Ruffini, Edmundo Lopez-Sola, Raul Palma, Roser Sanchez-Todo + 3 more
Predictive coding frameworks suggest that neural computations rely on hierarchical error minimization, where sensory signals are evaluated against internal model predictions. However, the neural implementation of this inference process remains unclear. We propose that cross-frequency coupling (CFC) furnishes a…
Xianghai Sheng, Lee Thompson, Hrant Hratchian
This work evaluates the quality of exchange coupling constant and spin crossover gap calculations using density functional theory corrected by the Approximate Projection model. Results show that improvements using the Approximate Projection model range from modest to significant. This study demonstrates that, at least…
Hao Wang, Yangshuai Wang
Multiscale coupling methods are significant methodologies for the modeling and simulation of materials with defects, intending to achieve the (quasi-)optimal balance of accuracy and efficiency. The a posteriori analysis and corresponding adaptive algorithms play a crucial role in the efficient implementation of…
Barak Raveh, Liping Sun, Kate L. White, Tanmoy Sanyal + 11 more
Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide-and-conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each…
Rik Verbiest, Julian Koellermeier
Microflows like Knudsen pumps often include rarefied gases featuring different degrees of rarefaction. This different modeling complexity requires space- and time-adaptive rarefied gas models that resolve the physical effects efficiently in each subdomain of the microflow. Different-order moment models are effective at…
José Galaz, Maria Kazolea, Antoine Rousseau
We propose a one-way coupling model as a reference, which allows us to obtain an analytical solution, prove the well-posedness of the original coupled model and compute what we call the coupling error—a quantity that depends solely on the choice of transmission conditions at the interface. We prove that this coupling…
Kenric P. Nelson, Madalina Barbu, Brian J. Scannell
Neural network design has utilized flexible nonlinear processes which can mimic biological systems, but has suffered from a lack of traceability in the resulting network. Graphical probabilistic models ground network design in probabilistic reasoning, but the restrictions reduce the expressive capability of each node…
Lee Thompson, Hrant Hratchian, Xianghai Sheng
This work evaluates the quality of exchange coupling constant and spin crossover gap calculations using density functional theory corrected by the Approximate Projection model. Results show that improvements using the Approximate Projection model range from modest to significant. This study demonstrates that, at least…
Authors not listed
The rapid growth of worldwide computing power has transformed in silico chemistry into a discipline that is integrated into the daily work of many chemists. Nowadays, researchers find it increasingly straightforward to predict a wide range of molecular properties and chemi- cal processes at reasonable computational…
Houssem E. M. Triki, Fabienne Ribeyre, Fabrice Pinard, Marc Jaeger
Coupling plant growth model with pests and diseases (P&D) models, with consideration for the long-term feedback that occurs after the interaction, is still a challenging task nowadays. While a number of studies have examined various methodologies, none of them provides a generic frame able to host existing models and…
George Arampatzis, Markos A. Katsoulakis
In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo. Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the…
L. Mark Berliner, Radu Herbei, Christopher K. Wikle, Ralph F. Milliff + 1 more
'Ralph F. Milliff' 'Pablo Martin Rodriguez'] Advances in observational and computational assets have led to revolutions in the range and quality of results in many science and engineering settings. However, those advances have led to needs for new research in treating model errors and assessing their impacts. We…
Authors not listed
Moving bed reactors (MBRs) are widely used in various industrial processes, making the development of mathematical models crucial for their design, optimization, and control. This study presents a semi-analytical solution (SAS) for a lumped parameter kinetic and heat transfer model of a tubular MBR, where a first-order…
Carter J. Wilson, Bert L. de Groot, Vytautas Gapsys
In a protein, nearby titratable sites can be coupled: the (de)protonation of one may affect the other. The degree of this interaction depends on several factors and can influence the measured pKa. Here, we derive a formalism based on double free energy differences (ΔΔG) for quantifying the individual site pKa values of…
Marinho A. Lopes, Khalid Hamandi, Jiaxiang Zhang, Jennifer L. Creaser
Models of networks of populations of neurons commonly assume that the interactions between neural populations are via additive or diffusive coupling. When using the additive coupling, a population’s activity is affected by the sum of the activities of neighbouring populations. In contrast, when using the diffusive…