Model-driven optimal experimental design for calibrating cardiac electrophysiology models

Lei, Chon Lok; Clerx, Michael; Gavaghan, David J.; Mirams, Gary R.

doi:10.1016/j.cmpb.2023.107690

The non-local Lotka-Volterra system with a top hat kernel - Part 1: dynamics and steady states with small diffusivity (2023)
Journal Article
Billingham, J., & Needham, D. J. (2023). The non-local Lotka-Volterra system with a top hat kernel - Part 1: dynamics and steady states with small diffusivity. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 479(2277), Article 20230381. https://doi.org/10.1098/rspa.2023.0381

We study the dynamics of the non-local Lotka-Volterra system ut=Duuxx+u(1-φ - u-αv), vt=Dvvxx+v(1-φ - v-βu), where a star denotes the spatial convolution and the kernel φ is a top hat function. We initially focus on the case of small, equal diffusivi... Read More about The non-local Lotka-Volterra system with a top hat kernel - Part 1: dynamics and steady states with small diffusivity.

Reconstructing the Antarctic ice sheet shape at the Last Glacial Maximum using ice core data (2023)
Journal Article
Turner, F. E., Buck, C. E., Jones, J. M., Sime, L., Vallet, I. M., & Wilkinson, R. D. (2023). Reconstructing the Antarctic ice sheet shape at the Last Glacial Maximum using ice core data. Journal of the Royal Statistical Society: Series C, 72(5), 1493-1511. https://doi.org/10.1093/jrsssc/qlad078

The Antarctic ice sheet (AIS) is the Earth's largest store of frozen water; understanding how it has changed in the past allows us to improve our future projections of how it, and thus sea levels, may change. In this paper, we use previous reconstruc... Read More about Reconstructing the Antarctic ice sheet shape at the Last Glacial Maximum using ice core data.

Multiscale asymptotic analysis reveals how cell growth and subcellular compartments affect tissue-scale hormone transport (2023)
Journal Article
Kiradjiev, K. B., & Band, L. R. (2023). Multiscale asymptotic analysis reveals how cell growth and subcellular compartments affect tissue-scale hormone transport. Bulletin of Mathematical Biology, 85, Article 101. https://doi.org/10.1007/s11538-023-01199-4

Determining how cell-scale processes lead to tissue-scale patterns is key to understanding how hormones and morphogens are distributed within biological tissues and control developmental processes. In this article, we use multiscale asymptotic analys... Read More about Multiscale asymptotic analysis reveals how cell growth and subcellular compartments affect tissue-scale hormone transport.

Operations in connective K-theory (2023)
Journal Article
Vishik, A., & Merkurjev, A. (2023). Operations in connective K-theory. Algebra and Number Theory, 17(9), 1595–1636. https://doi.org/10.2140/ant.2023.17.1595

We classify additive operations in connective K-theory with various torsion-free coefficients. We discover that the answer for the integral case requires understanding of the ˆZ case. Moreover, although integral additive operations are topologically... Read More about Operations in connective K-theory.

Machine learning the dimension of a Fano variety (2023)
Journal Article
Kasprzyk, A. M., Coates, T., & Veneziale, S. (2023). Machine learning the dimension of a Fano variety. Nature Communications, 14, Article 5526. https://doi.org/10.1038/s41467-023-41157-1

Fano varieties are basic building blocks in geometry – they are ‘atomic pieces’ of mathematical shapes. Recent progress in the classification of Fano varieties involves analysing an invariant called the quantum period. This is a sequence of integers... Read More about Machine learning the dimension of a Fano variety.

Fundamental limitations to key distillation from Gaussian states with Gaussian operations (2023)
Journal Article
Lami, L., Mišta, L., & Adesso, G. (2023). Fundamental limitations to key distillation from Gaussian states with Gaussian operations. Physical Review Research, 5(3), Article 033153. https://doi.org/10.1103/PhysRevResearch.5.033153

We establish fundamental upper bounds on the amount of secret key that can be extracted from quantum Gaussian states by using only local Gaussian operations, local classical processing, and public communication. For one-way public communication, or w... Read More about Fundamental limitations to key distillation from Gaussian states with Gaussian operations.

Energetically efficient learning in neuronal networks (2023)
Journal Article
Pache, A., & van Rossum, M. C. (2023). Energetically efficient learning in neuronal networks. Current Opinion in Neurobiology, 83, Article 102779. https://doi.org/10.1016/j.conb.2023.102779

Human and animal experiments have shown that acquiring and storing information can require substantial amounts of metabolic energy. However, computational models of neural plasticity only seldom take this cost into account, and might thereby miss an... Read More about Energetically efficient learning in neuronal networks.

Strong convergence of an epidemic model with mixing groups (2023)
Journal Article
Ball, F., & Neal, P. (in press). Strong convergence of an epidemic model with mixing groups. Advances in Applied Probability, https://doi.org/10.1017/apr.2023.29

We consider an SIR (susceptible → infective → recovered) epidemic in a closed population of size n, in which infection spreads via mixing events, comprising individuals chosen uniformly at random from the population, which occur at the points of a Po... Read More about Strong convergence of an epidemic model with mixing groups.

On liftings of modular forms and Weil representations (2023)
Journal Article
STROMBERG, F. (2024). On liftings of modular forms and Weil representations. Forum Mathematicum, 36(1), 33-52. https://doi.org/10.1515/forum-2022-0353

We give an explicit construction of lifting maps from integral and half-integral modular forms to vector-valued modular forms for Weil representations associated with arbitrary isotropic subgroups and finite quadratic modules of even and odd signatur... Read More about On liftings of modular forms and Weil representations.

Towards the ultimate brain: Exploring scientific discovery with ChatGPT AI (2023)
Journal Article
Adesso, G. (2023). Towards the ultimate brain: Exploring scientific discovery with ChatGPT AI. AI Magazine, 44(3), 328-342. https://doi.org/10.1002/aaai.12113

This paper presents a novel approach to scientific discovery using an artificial intelligence (AI) environment known as ChatGPT, developed by OpenAI. This is the first paper entirely generated with outputs from ChatGPT. We demonstrate how ChatGPT can... Read More about Towards the ultimate brain: Exploring scientific discovery with ChatGPT AI.

Modelling calibration uncertainty in networks of environmental sensors (2023)
Journal Article
Smith, M. T., Ross, M., Ssematimba, J., Álvarez, M. A., Bainomugisha, E., & Wilkinson, R. (2023). Modelling calibration uncertainty in networks of environmental sensors. Journal of the Royal Statistical Society: Series C, Article qlad075. https://doi.org/10.1093/jrsssc/qlad075

Networks of low-cost environmental sensors are becoming ubiquitous, but often suffer from poor accuracies and drift. Regular colocation with reference sensors allows recalibration but is complicated and expensive. Alternatively, the calibration can b... Read More about Modelling calibration uncertainty in networks of environmental sensors.

Constructing Non-semisimple Modular Categories with Local Modules (2023)
Journal Article
Laugwitz, R., & Walton, C. (2023). Constructing Non-semisimple Modular Categories with Local Modules. Communications in Mathematical Physics, 403, 1363-1409. https://doi.org/10.1007/s00220-023-04824-4

We define the class of rigid Frobenius algebras in a (non-semisimple) modular category and prove that their categories of local modules are, again, modular. This generalizes previous work of Kirillov and Ostrik (Adv Math 171(2):183–227, 2002) in the... Read More about Constructing Non-semisimple Modular Categories with Local Modules.

Approaches to risk ratio estimation in a regression discontinuity design: Application to the prescription of statins for cholesterol reduction in UK primary care (2023)
Journal Article
Adeleke, M. O., O’Keeffe, A. G., & Baio, G. (2023). Approaches to risk ratio estimation in a regression discontinuity design: Application to the prescription of statins for cholesterol reduction in UK primary care. Statistical Methods in Medical Research, 32(10), 1994-2015. https://doi.org/10.1177/09622802231192958

In recent years regression discontinuity designs have been used increasingly for the estimation of treatment effects in observational medical data where a rule-based decision to apply treatment is taken using a continuous assignment variable. Most re... Read More about Approaches to risk ratio estimation in a regression discontinuity design: Application to the prescription of statins for cholesterol reduction in UK primary care.

Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings (2023)
Journal Article
Clark, A. P., Clerx, M., Wei, S., Lei, C. L., de Boer, T. P., Mirams, G. R., …Krogh-Madsen, T. (2023). Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings. EP-Europace, 25(9), Article euad243. https://doi.org/10.1093/europace/euad243

Aims Human-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have become an essential tool to study arrhythmia mechanisms. Much of the foundational work on these cells, as well as the computational models built from the resultant data,... Read More about Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings.

Detecting Massive Scalar Fields with Extreme Mass-Ratio Inspirals (2023)
Journal Article
Barsanti, S., Maselli, A., Sotiriou, T. P., & Gualtieri, L. (2023). Detecting Massive Scalar Fields with Extreme Mass-Ratio Inspirals. Physical Review Letters, 131(5), Article 051401. https://doi.org/10.1103/physrevlett.131.051401

We study the imprint of light scalar fields on gravitational waves from extreme mass-ratio inspirals—binary systems with a very large mass asymmetry. We first show that, to leading order in the mass ratio, any effects of the scalar on the waveform ar... Read More about Detecting Massive Scalar Fields with Extreme Mass-Ratio Inspirals.

Green Hyperbolic Complexes on Lorentzian Manifolds (2023)
Journal Article
Benini, M., Musante, G., & Schenkel, A. (2023). Green Hyperbolic Complexes on Lorentzian Manifolds. Communications in Mathematical Physics, 403, 699-744. https://doi.org/10.1007/s00220-023-04807-5

We develop a homological generalization of Green hyperbolic operators, called Green hyperbolic complexes, which cover many examples of derived critical loci for gauge-theoretic quadratic action functionals in Lorentzian signature. We define Green hyp... Read More about Green Hyperbolic Complexes on Lorentzian Manifolds.

Bayesian Predictive Inference Without a Prior (2023)
Journal Article
Berti, P., Dreassi, E., Leisen, F., Pratelli, L., & Rigo, P. (2023). Bayesian Predictive Inference Without a Prior. Statistica Sinica, 33(4), 2405-2429. https://doi.org/10.5705/ss.202021.0238

Let (Xn : n ≥ 1) be a sequence of random observations. Let σn(·) = P (Xn+1 ∈ · | X1, . . . , Xn) be the n-th predictive distribution and σ0(·)=P (X1 ∈ ·) the marginal distribution of X1. To make predictions on (Xn), a Bayesian forecaster only needs t... Read More about Bayesian Predictive Inference Without a Prior.

The Linear CS/WZW Bulk/Boundary System in AQFT (2023)
Journal Article
Benini, M., Grant-Stuart, A., & Schenkel, A. (2024). The Linear CS/WZW Bulk/Boundary System in AQFT. Annales Henri Poincaré, 25, 2251-2294. https://doi.org/10.1007/s00023-023-01346-6

This paper constructs in the framework of algebraic quantum field theory (AQFT) the linear Chern–Simons/Wess–Zumino–Witten system on a class of 3-manifolds M whose boundary ∂M is endowed with a Lorentzian metric. It is proven that this AQFT is equiva... Read More about The Linear CS/WZW Bulk/Boundary System in AQFT.

Model-driven optimal experimental design for calibrating cardiac electrophysiology models (2023)
Journal Article
Lei, C. L., Clerx, M., Gavaghan, D. J., & Mirams, G. R. (2023). Model-driven optimal experimental design for calibrating cardiac electrophysiology models. Computer Methods and Programs in Biomedicine, 240, Article 107690. https://doi.org/10.1016/j.cmpb.2023.107690

Background and Objective: Models of the cardiomyocyte action potential have contributed immensely to the understanding of heart function, pathophysiology, and the origin of heart rhythm disturbances. However, action potential models are highly nonlin... Read More about Model-driven optimal experimental design for calibrating cardiac electrophysiology models.

All Outputs (1645)