Outputs (136)

Derivative-based Inference for Cell and Channel Electrophysiology Models (2022)
Presentation / Conference Contribution
Clerx, M., Augustin, D., Dale-Evans, A. R., & Mirams, G. R. (2022, September). Derivative-based Inference for Cell and Channel Electrophysiology Models. Presented at 2022 Computing in Cardiology Conference, Tampere, Finland (online)

Models of ionic currents or of the cardiac action potential (AP) are frequently calibrated by defining an error function that quantifies the mismatch between simulations and data, and using numerical optimisation to find the parameter values that min... Read More about Derivative-based Inference for Cell and Channel Electrophysiology Models.

Modelling the Effect of Intracellular Calcium in the Rundown of L-Type Calcium Current (2022)
Presentation / Conference Contribution
Agrawal, A., Clerx, M., Wang, K., Polonchuk, L., Gavaghan, D. J., & Mirams, G. R. (2022, September). Modelling the Effect of Intracellular Calcium in the Rundown of L-Type Calcium Current. Presented at 2022 Computing in Cardiology Conference, Tampere, Finland

The L-type calcium current (ICaL) is a key current of the heart playing an important role in the contraction of the cardiomyocyte. Patch-clamp recordings of ionic currents can be associated with a reduction of the current magnitude with time (termed... Read More about Modelling the Effect of Intracellular Calcium in the Rundown of L-Type Calcium Current.

Normalisation of Action Potential Data Recorded with Sharp Electrodes Maximises Its Utility for Model Development (2022)
Presentation / Conference Contribution
Barral, Y. S. H., Polonchuk, L., R. Mirams, G., Clerx, M., Page, G., Sweat, K., Abi-Gerges, N., Wang, K., & Gavaghan, D. J. (2022, September). Normalisation of Action Potential Data Recorded with Sharp Electrodes Maximises Its Utility for Model Development. Presented at 2022 Computing in Cardiology Conference, Tampere, Finland

In silico models of cardiomyocyte electrophysiology describe the various ionic currents and fluxes that lead to the formation of action potentials (APs). Experimental data used to create such models can be recorded in adult human cardiac trabeculae u... Read More about Normalisation of Action Potential Data Recorded with Sharp Electrodes Maximises Its Utility for Model Development.

Integrality of twisted L-values of elliptic curves (2022)
Journal Article
Wiersema, H., & Wuthrich, C. (2022). Integrality of twisted L-values of elliptic curves. Documenta Mathematica, 27, 2041-2066. https://doi.org/10.25537/dm.2022v27.2041-2066

Under suitable, fairly weak hypotheses on an elliptic curve E/Q and a primitive non-trivial Dirichlet character χ, we show that the algebraic L-value L (E, χ) at s = 1 is an algebraic integer. For instance, for semistable curves L (E, χ) is integral... Read More about Integrality of twisted L-values of elliptic curves.

Slepian eigenvalues as tunnelling rates (2022)
Journal Article
Creagh, S. C., & Gradoni, G. (2023). Slepian eigenvalues as tunnelling rates. Annals of Physics, 449, Article 169204. https://doi.org/10.1016/j.aop.2022.169204

We calculate the eigenvalues of an integral operator associated with Prolate Spheroidal Wave Functions (or Slepian functions) by interpreting them as tunnelling probabilities in an analogous quantum problem. Doing so allows us to extend a well-known... Read More about Slepian eigenvalues as tunnelling rates.

Likelihood-Free Dynamical Survival Analysis applied to the COVID-19 epidemic in Ohio (2022)
Journal Article
Klaus, C., Wascher, M., KhudaBukhsh, W. R., & Rempała, G. A. (2023). Likelihood-Free Dynamical Survival Analysis applied to the COVID-19 epidemic in Ohio. Mathematical Biosciences and Engineering, 20(2), 4103-4127. https://doi.org/10.3934/mbe.2023192

The Dynamical Survival Analysis (DSA) is a framework for modeling epidemics based on mean field dynamics applied to individual (agent) level history of infection and recovery. Recently, the DSA method has been shown to be an effective tool in analyzi... Read More about Likelihood-Free Dynamical Survival Analysis applied to the COVID-19 epidemic in Ohio.

On the maximum dual volume of a canonical Fano polytope (2022)
Journal Article
Balletti, G., Kasprzyk, A. M., & Nill, B. (2022). On the maximum dual volume of a canonical Fano polytope. Forum of Mathematics, Sigma, 10, Article e109. https://doi.org/10.1017/fms.2022.93

We give an upper bound on the volume vol(P*) of a polytope P* dual to a d-dimensional lattice polytope P with exactly one interior lattice point, in each dimension d. This bound, expressed in terms of the Sylvester sequence, is sharp, and is achieved... Read More about On the maximum dual volume of a canonical Fano polytope.

A continuum framework for phase field with bulk-surface dynamics (2022)
Journal Article
Espath, L. (2023). A continuum framework for phase field with bulk-surface dynamics. Partial Differential Equations and Applications, 4, Article 1. https://doi.org/10.1007/s42985-022-00218-8

This continuum mechanical theory aims at detailing the underlying rational mechanics of dynamic boundary conditions proposed by Fischer et al. (Phys Rev Lett 79:893, 1997), Goldstein et al. (Phys D Nonlinear Phenom 240:754–766, 2011), and Knopf et al... Read More about A continuum framework for phase field with bulk-surface dynamics.

GPT4 : The Ultimate Brain (2022)
Preprint / Working Paper
Adesso, G. GPT4 : The Ultimate Brain

We introduce a powerful general probabilistic theory, GPT4, that extends classical and quantum theories to include higher-dimensional probabilistic models. GPT4 results from the four-fold integration of GPT in physics (Generalized Probabilistic T... Read More about GPT4 : The Ultimate Brain.

Adjoint-aided inference of Gaussian process driven differential equations (2022)
Presentation / Conference Contribution
Gahungu, P., Lanyon, C. W., Álvarez, M. A., Smith, M. T., & Wilkinson, R. D. (2022, November). Adjoint-aided inference of Gaussian process driven differential equations. Presented at NeurIPS 2022: Thirty-sixth Conference on Neural Information Processing Systems, New Orleans, USA and online

Linear systems occur throughout engineering and the sciences, most notably as differential equations. In many cases the forcing function for the system is unknown, and interest lies in using noisy observations of the system to infer the forcing, as w... Read More about Adjoint-aided inference of Gaussian process driven differential equations.