Applied Mathematics and Numerical Analysis Seminar 

We present, analyse and simulate a model for predator-prey interaction with hunger structure. The model consists of a nonlocal transport equation for the predator, coupled to an ODE for the prey. We deduce a system of 3 ODEs for some integral quantities of the transport equation, which generalises some classical Lotka-Volterra systems. By taking an asymptotic regime of fast hunger variation, we find that this system provides new interpretations and derivations of several variations of the classical Lotka--Volterra system, including the Holling-type functional responses. We next establish a well-posedness result for the nonlocal transport equation by means of a fixed-point method. Finally, we show that in the basin of attraction of the nontrivial equilibrium, the asymptotic behaviour of the original coupled PDE-ODE system is completely described by solutions of the ODE system [SIAM J. Appl. Math., 80(6), 2631-2656 (2020)].

In this talk we overview the mathematical continuous and discrete models in use in Mathematical epidemiology. We analyse the evolution of COVI-19 in Portugal.

Mathematical analysis is a useful tool to give insights in very different mathematical biology problems.

In this talk we will consider predator-prey and competition population dynamics models. We will give an overview of recent results in the case of seasonally forced models not entering in technical details.

First of all we consider predator-prey models with or without Allee effect and prove results on extinction or persistence. We will give some examples such as models including competition among predators, prey-mesopredator-superpredator models and Leslie-Gower systems. When Allee effect is considered, we deal with the cases of strong and weak Allee effect.

Then we consider competition models of two species giving conditions for the extinction of one or both species and for coexistence.

This talk is based in joint works with I. Coelho, M. Garrione, C. Soresina and E. Sovrano.

References:

[1] I. Coelho and C. Rebelo, Extinction or coexistence in periodic Kolmogorov systems of competitive type, submitted.

[2] M. Garrione and C. Rebelo, Persistence in seasonally varying predator-prey systems via the basic reproduction number, Nonlinear Analysis: Real World Applications, 30, (2016) 73-98.

[3] C. Rebelo and C. Soresina, Coexistence in seasonally varying predator-prey systems with Allee effect, Nonlinear Anal. Real World Appl. 55 (2020), 103140, 21 pp.

The high number and diversity of microbial strains circulating in host populations pose challenges to human health and have inspired extensive research on the mechanisms that maintain such biodiversity. While much of the theoretical work focuses on strain-specific and cross-immunity interactions, another less explored mode of pairwise interaction is via altered susceptibilities to co-colonization (co-infection) in hosts already colonized by one strain. Diversity in such interaction coefficients enables strains to create dynamically their niches for growth and persistence, and 'engineer' their common environment. How such a network of interactions with others mediates collective coexistence remains puzzling analytically and computationally difficult to simulate. Furthermore, the gradients modulating stability-complexity regimes in such multi-player endemic systems remain poorly understood.

In this seminar I will present results from an epidemiological study where we analyze mathematically such an interacting system and the eco-evolutionary dynamics that emerge. Adopting a slow-fast dynamic decomposition of the original SIS model, we obtain a model reduction coinciding with a version of the replicator equation from evolutionary game theory. This enables us to highlight the key coexistence principles and the critical shifts in multi-strain dynamics potentiated by mean-field gradients.

The Gielis Transformation (GT) defines measures and unit elements specific to the shape, extending Euclidean geometry and challenging current notions of curvature, complexity and entropy. Global anisotropies or (quasi-) periodic local deviations from isotropy or Euclidean perfection in many forms that occur in nature can be effectively dealt with by applying Gielis transformations to the basic forms that show up in Euclidean geometry, e.g. circle and spiral. Anisotropic versions of the classical constant mean curvature and minimal surfaces have been developed. In mathematical physics it has led to developing analytical solutions to a variety of boundary value problems with Fourier-like solutions for anisotropic domains.

GT have been used in over 100 widely different applications in science, education and technology. In the field of design and engineering they have been used, among others, for the optimization of wind turbine blades, antennas, metamaterials, nanoparticles and lasers.

In March 11th of 2020, the World Health Organization declared the COVID-19 global public health emergency a pandemic [1]. Since the appearance of the first cases in Wuhan, China, several countries have employed the use of mathematical and statistical techniques to ascertain the course of the disease spread. The most common mathematical tool available to model such phenomena are systems of differential equations. The most notable are the SIR and SEIR model first developed by Kermack and McKendrick (1927). These models have been used to study an array of different epidemic questions. At the start of the pandemic, these models were employed to nowcast and forecast the national spread of SARS-CoV-2 in China. In [2] the authors create scenarios of transmissibility reduction and mobility reduction associated with the measures employed by the Chinese government. Similar models were also used to estimate the proportion of susceptible individuals in a population, i.e. how much is the case ascertainment in a given country [3]. This topic is very important since it has been shown that a high percentage of infected individuals do not develop symptoms [4] but are still able to infect others [5]. The main purpose of these modelling techniques has been to evaluate the impact of contagion mitigation measures, such as the closure of schools and lockdowns [6].

In Portugal, the team at the department of epidemiology Instituto Nacional de Saúde Doutor Ricardo Jorge, has been, since the start of the epidemic developing reports with an array of different statistical and mathematical procedures [7], in order to present a clear picture of the evolution of the epidemic, with the objective of supporting public health policy making. Part of this work involved building a SEIR-type model with heterogeneous mixing among age groups. This model was key to provide some evidence on the impact of the lockdown in Portugal from March 22th until May 4th. Using data from google mobility reports [8], the model showed that a decrease in transmission was expect after the implementation of the lockdown, which was not yet noticeable due to the delay between infection and case notification.

With the increase, as of late, of the daily incidence of COVID-19 cases and with the opening of schools, public health decision makers need to know what will be the expected impact on the Portuguese health system, and what non-pharmaceutical-interventions (NPI) can be adapted in order to compensate for such increase. Several epidemiologist state that higher and faster contact tracing might be the best and most efficient measure to compensate for such increase. The team is currently developing a new model that takes into account several NPIs, such as contact tracing, case ascertainment, mask usage, shielding of vulnerable (elderly) individuals, and closure/opening of schools, among others. The main objective is to provide possible scenarios for the magnitude of the impact of these measures.

Joint work with:

• Maria Luísa Morgado, Departamento de Matemática, UTAD & CEMAT IST
• Paula Patrício, Centro de Matemática e Aplicações & Departamento de Matemática Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa
• Baltazar Nunes, Instituto Nacional de Saúde Doutor Ricardo Jorge

References

1. ECDC: Event Background-COVID-19.
2. Wu, J. T., Leung, K., & Leung, G. M. (2020). Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. The Lancet, 395(10225), 689–697. doi: 10.1016/s0140-6736(20)30260-9
3. Maugeri A, Barchitta M, Battiato S, Agodi A. Estimation of Unreported Novel Coronavirus (SARS-CoV-2) Infections from Reported Deaths: A Susceptible-Exposed-Infectious-Recovered-Dead Model. J Clin Med. 2020;9(5):1350. Published 2020 May 5. doi:10.3390/jcm9051350
4. Instituto Nacional de Saúde Dr. Ricardo Jorge (2020). Relatório de Apresentação dos Resultados Preliminares do Primeiro Inquérito Serológico Nacional COVID-19. Available: (acesso a 25/08/2020)
5. Huang L-S, Li L, Dunn L, He M. Taking. Account of Asymptomatic Infections in Modeling the Transmission Potential of the COVID-19 Outbreak on the Diamond Princess Cruise Ship. medRxiv. 2020:2020.04.22.20074286.
6. Prem, K., Liu, Y., Russell, T., Kucharski, A. J., Eggo, R. M., Davies, N., Jit, M. Klepac, P. (2020). The effect of control strategies that reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China. The Lancet Public Health. doi: 10.1101/2020.03.09.20033050
7. Nunes B, Caetano C, Antunes L, et al. Evolução do número de casos de COVID-19 em Portugal. Relatório de nowcasting. Inst. Nac. Saúde Doutor Ricardo Jorge. 2020;
8. Relatórios de mobilidade da comunidade da COVID19.

In this talk, we present a study on the oscillatory behaviour of the mixed type difference equation with variable coefficients$$\Delta x(n) = \sum_{i=1}^l p_i(n)x(\tau_i(n)) + \sum_{j=1}^m q_j(n)x(\sigma_j(n)),\, n \geq n_0.$$

The numerical simulation of non-Newtonian viscoelastic fluids flow is a challenging problem. One of the approaches being often adopted to stablize the numerical simulations is based on addition of stress diffusion term into the transport equations for viscoelastic stress tensor. The additional term affect the solution of the problem and special care should be taken to keep the modified model consistent with the original problem.

In this work it was analyzed in detail the influence of numerical stabilization using artificial stress diffusion and it was presented a new arternative. Instead of the classical addition of artificial stress diffusion term it was used the modified additional term which is only present during the transient phase and should vanish in when approaching the stationary case. The steady solution is not affected by such vanishing artificial term, however the stability of the numerical method is improved.

This is joint work with Tomás Bodnár (Institute of Mathematics, Czech Academy of Sciences and Faculty of Mechanical Engineering, Czech Technical University in Prague, Czech Republic).

In this seminar we will show a exact solution for a Benney-Lin equation type using mainly the Ince Transformation. We establish exact traveling waves solution to the nonlinear evolution equation Benney-Lin type.

Finite volume methods of third or higher order require a specific treatment of the boundary conditions when dealing with a non-polygonal domain that does not exactly fit with the mesh. We also face a similar situation with internal smooth interfaces sharing two subdomains. To address this issue, several technologies have been developed since the 90's such as the isoparamatric elements, the (ghost cells) immersed boundary and the inverse Lax-Wendroff boundary treatment among others. We propose a quick overview of the traditional methods and introduce the new Reconstruction of Off-site Data (ROD) method. Basically, the idea consists, first in definitively distinguishing the computational domain (cells or nodes where the solution is computed) to the physical one and, secondly, in "transporting" the boundary conditions prescribed on the real boundary to the computing domain. To this end, specific local polynomial reconstructions that contains a fingerprint of the boundary conditions are proposed and used to schemes that achieve up to sixth-order of accuracy. Several applications will be proposed in the context of the finite volume (flux reconstruction) and finite difference (ghost cells) for the convection diffusion equation and the Euler system.

We study how an imposed fluid flow — laminar or turbulent — modifies the transport properties of inertial particles (e.g. aerosols, droplets or bubbles), namely their terminal velocity, effective diffusivity, and concentration following a point-source emission.

Such quantities are investigated by means of analytical and numerical computations, as functions of the control parameters of both flow and particle; i.e., density ratio, inertia, Brownian diffusivity, gravity (or other external forces), turbulence intensity, compressibility degree, space dimension, and geometric/temporal properties.

The complex interplay between these parameters leads to the following conclusion of interest in the realm of applications: any attempt to model dispersion and sedimentation processes — or equivalently the wind-driven surface transport of floaters — cannot avoid taking into account the full details of the flow field and of the inertial particle.

We consider a class of parabolic free boundary problems with heterogeneous coefficients. We establish existence of a solution for this problem. We use a regularized problem for which we prove existence of a solution by applying the Tychonoff fixed point theorem. Then we pass to the limit to get a solution of our problem.

We study the existence and uniqueness of a solution for time order partial fractional differential equations with integral conditions. By using the method of energy inequalities, we find a priori estimates and the density of the range of the operator generated by given the problem.

Over the last decade, there have been dramatic advances in mathematical modeling, analysis and simulation techniques to understand fundamental mechanisms underlying multidisciplinary applications that involve multi-physics interactions. This work will present the results from projects that evolved from multidisciplinary applications of differential equations for multi-physics problems in biological, bio-inspired and engineering systems. Specifically, mathematical modeling and numerical methods for efficient computation of nonlinear interaction for coupled differential equation models that arise from applications such as flow-structure interactions to understand rupture of aneurysms to dynamics of micro-air vehicles as well as modeling dynamics of infectious disease to modeling social dynamics will be presented. Some theoretical results that validate the reliability and robustness of the computational methodology employed will also be presented. We will also discuss how such projects can provide opportunities for students and faculty at all levels to employ transformative research in multidisciplinary areas. Upcoming opportunities for undergraduate and graduate fellowships as well as research opportunities for faculty for collaborative proposals will also be discussed.

In the present work, a numerical method based on the modified hat functions is introduced for solving a class of fractional optimal control problems. In this scheme, the control and the fractional derivative of state function are considered as linear combinations of the modified hat functions. The Riemann–Liouville integral operator is used to give approximations for the state function and some of its derivatives. Using the properties of the considered basis functions, the fractional optimal control problem is easily reduced to solving a system of nonlinear algebraic equations. An error bound is presented for the approximate optimal value of the performance index obtained by the proposed method. Then the method is developed for solving a class of optimal control problems with inequality constraints. Finally, some illustrative examples are considered to demonstrate the effectiveness and accuracy of the proposed technique.

The main objective of this work is to study some classes of integral and integro-differential equations with regular and singular kernels. We introduce a wavelets method to solve a new class of Fredholm integral equations of the second kind with non symmetric kernel; we also apply a collocation method based on the airfoil polynomial to numerically solve an integro-differential equation of second order with Cauchy kernel.

In this work we present the method of fundamental solutions (MFS) in several contexts. We start with a more intuitive example and then we extend it to vectorial PDE's. We present the density results that justify our approach and then we use the MFS to solve the Stokes system in 2D and 3D. We deal with non-trivial domains and with different types of boundary conditions, namely the mixed Dirichlet-Neumann conditions. We will present several simulations that show the strengths of the method and some of the numerical difficulties found.

(Joint work with C. J. S. Alves and A. L. Silvestre)

Controlling the evolution and spread of antimicrobial resistance is a major global health priority. While the discovery of new antibiotics does not follow the rate at which new resistances develop, a more rational use of available drugs remains critical. In my work, I explore the role of host immunity in infection dynamics and control, hence as an important piece in the puzzle of antibiotic resistance management.

I will present two studies from my research on microbial dynamics, addressing processes that occur at the within- and between-host level.

The first study examines antibiotic resistance and treatment optimization for bacterial infections, quantifying the crucial role of host immune defenses at the single host level.

The second study presents a multi-strain epidemiological model applied to pneumococcus data before and after vaccination.

This framework allows for retrospective inference of strain interactions in co-colonization and vaccine efficacy parameters, and can be useful for comparative analyses across different immunized populations.

This talk presents an alternative boundary conditions setup for the numerical simulations of stable stratified flow. The focus of the tested computational setup is on the pressure boundary conditions on the artificial boundaries of the computational domain. The simple three dimensional test case deals with the steady flow of an incompressible, variable density fluid over a low smooth model hill. The Boussinesq approximation model is solved by an in-house developed high-resolution numerical code, based on compact finite-difference discretization in space and Strong Stability Preserving Runge-Kutta method for (pseudo-) time stepping.

This is a joint work with Philippe Fraunie, University of Toulon, France.

We report our work about the main necessary and sufficient conditions for weak lower semi-continuity of integral functionals in vector Calculus of Variations.

In particular we provide tools to investigate rank-one convexity of functions defined on $2\times 2$-matrices. Furthermore, we explore some consequences and examples.

We also explore the quasiconvexity condition in the case where the integrand of an integral functional is a fourth-degree homogeneous polynomial.