Browsing Mathematical Modelling with Multidisciplinary Applications (M3A) by Title
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The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism
(20170101)Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ... 
Key aspects for effective mathematical modelling of fractionaldiffusion in cardiac electrophysiology: A quantitative study
(202005)Microscopic structural features of cardiac tissue play a fundamental role in determining complex spatiotemporal excitation dynamics at the macroscopic level. Recent efforts have been devoted to the development of mathematical ... 
Kinetic Parameter Estimation from Spectroscopic Data for a MultiStage SolidLiquid Pharmaceutical Process
(20200807)Laboratory and process measurements from spectroscopic instruments are ubiquitous in pharma processes, and directly using the data can pose a number of challenges for kinetic model building. Moreover, scaling up from ... 
Lagged and instantaneous dynamical influences related to brain structural connectivity
(20151231)Contemporary neuroimaging methods can shed light on the basis of human neural and cognitive specializations, with important implications for neuroscience and medicine. Indeed, different MRI acquisitions provide different ... 
Largescale simulations of synthetic markets
(20151008)Highfrequency trading has been experiencing an increase of interest both for practical purposes within nancial institutions and within academic research; recently, the UK Government O ce for Science reviewed the state ... 
A leastsquares implicit RBFFD closest point method and applications to PDEs on moving surfaces
(201810)The closest point method (Ruuth and Merriman, J. Comput. Phys. 227(3):19431961, [2008]) is an embedding method developed to solve a variety of partial differential equations (PDEs) on smooth surfaces, using a closest point ... 
Lessons from Two Design–Build–Test–Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning
(20190101)The Design–Build–Test–Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabolic engineering framework that represents a more systematic and efficient ... 
Longitudinal variations of brain functional connectivity: A case report study based on a mouse model of epilepsy
(20151231)Brain Functional Connectivity (FC) quantifies statistical dependencies between areas of the brain. FC has been widely used to address altered function of brain circuits in control conditions compared to different pathological ... 
Lowtraffic limit and firstpassage times for a simple model of the continuous double auction
(201705)We consider a simplified model of the continuous double auction where prices are integers varying from 1 to $N$ with limit orders and market orders, but quantity per order limited to a single share. For this model, the ... 
Lyapunov functional techniques for the global stability analysis of a delayed SIRS epidemic model
(20121231)In this paper, we study the global dynamics of a delayed SIRS epidemic model for transmission of disease with a class of nonlinear incidence rates of the form βS(t)∫ 0 hf(τ)G(I(tτ))dτ. Applying Lyapunov functional techniques ... 
A Machine Learning Approach to Predict Metabolic Pathway Dynamics from Time Series Multiomics Data
(201805)New synthetic biology capabilities hold the promise of dramatically improving our ability to engineer biological systems. However, a fundamental hurdle in realizing this potential is our inability to accurately predict ... 
Machine learning framework for assessment of microbial factory performance
(20190101)Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess ... 
Manipulation of single electron spin in a GaAs quantum dot through the application of geometric phases: The Feynman disentangling technique
(20101231)The spin of a single electron in an electrically defined quantum dot in a twodimensional electron gas can be manipulated by moving the quantum dot adiabatically in a closed loop in the twodimensional plane under the ... 
Mathematical modelling as a tool to understand cell selfrenewal and differentiation
(20160101)Mathematical modeling is a powerful technique to address key questions and paradigms in a variety of complex biological systems and can provide quantitative insights into cell kinetics, fate determination and development ... 
Mathematical models for glioma growth and migration inside the brain
(202101)Gliomas are the most prevalent, aggressive, and invasive subtype of primary brain tumors, characterized by rapid cell proliferation and great infiltration capacity. De spite the advances of clinical research, these tumors ... 
Maximal regularity in $l_p$ spaces for discrete time fractional shifted equations
(20170501)In this paper, we are presenting a new method based on operatorvalued Fourier multipliers to \ characterize the existence and uniqueness of $\ell_p$solutions for discrete time fractional models in the form $$ ... 
Mechanism of hydrogen production via water splitting on 3CSiC's different surfaces: A firstprinciples study
(20141231)The reaction mechanism of producing hydrogen via water splitting on the different surfaces of cubic silicon carbide (3CSiC), the adsorption energy and the activation energy have been studied here by using density functional ... 
MesoGSHMC: A stochastic algorithm for mesoscale constant temperature simulations
(20111231)We consider the problem of timestepping/sampling for molecular and mesoscale particle dynamics. The aim of the work is to derive numerical timestepping methods that generate samples exactly from the desired target ... 
Metamodeling on detailed geography for accurate prediction of invasive alien species dispersal
(20191107)Invasive species are recognized as a significant threat to biodiversity. The mathematical modeling of their spatiotemporal dynamics can provide significant help to environmental managers in devising suitable control ... 
Metastable resting state brain dynamics
(20190906)Metastability refers to the fact that the state of a dynamical system spends a large amount of time in a restricted region of its available phase space before a transition takes place, bringing the system into another state ...