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  SCIENTIFIC PROGRAMS AND ACTIVITIES | 
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| November 4, 2025 | 
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 ABSTRACTSPatrizia Daniele, University of Catania, 
          IT: We outline the importance of the evolutionary variational inequalities 
          theory from the beginning in 1967 to the numerous applications in the 
          field of operational research, engineering, economy, finance. The study 
          of the evolutionary variational inequalities has been given a substantial 
          boost in the last decade when it was proved that dynamic economic, financial 
          and transportation equilibrium problems on networks can be expressed 
          by means of evolutionary variational inequalities. So we have the possibility 
          to follow the evolution in time of economic phenomena, since the theory 
          of evolutionary variational inequalities allows for the study of existence, 
          uniqueness and sensitivity analysis of the equilibrium trajectory. Also 
          the problem of the calculation of the solution in a time interval can 
          be solved by means of appropriate computational techniques and we present 
          two computational methods based on the discretization procedure. The 
          first one requires no regularity conditions on the solution and makes 
          use of the mean value operators. The second one requires the continuity 
          of the solutions and exploit the relation between the solutions to an 
          evolutionary variational inequality and the stationary points of a projected 
          dynamical system. Some numerical examples of traffic networks and spatial 
          price models will be presented too. It is well known (to those that know it well) that nonlinear dynamical 
          systems acting on points have corresponding to them linear operators 
          acting on functions. Systems of differential equations have corresponding 
          to them partial differential operators, and when these systems are stochastic, 
          the resulting partial differential operators lead to famous financial 
          math results such as the Black -Scholes equation. The topic of this 
          talk will be discrete dynamical systems, to which correspond the so-called 
          Perron-Frobenius Operator. After giving a quick review of this theory 
          I will use it to provide some results on weakly coupled logistic map 
          systems.   We will demonstrate how the paradigm of complex networks can be used 
          to model some aspects of the process of acquisition of the second language. 
          When learning a new language, knowledge of 3000-4000 of the most frequent 
          words appears to be a significant threshold, necessary to transfer reading 
          skills from the first to the second language. This threshold corresponds 
          to the transition from Zipf's law to a non-Zipfian regime in the rank-frequency 
          plot of words of the English language. Using a large dictionary, one 
          can construct a graph G representing this dictionary, and study topological 
          properties of subgraphs of G generated by the $k$ most frequent words 
          of the language. Since the vocabulary grows with time, one can also 
          think of this as a dynamical process in which $k$ increases as a function 
          of time. The clustering coefficient of subgraphs of G reaches a minimum 
          in the same place as the crossover point in the rank-frequency plot. 
          We conjecture that the coincidence of all these thresholds may indicate 
          a change in the language structure, which occurs when the vocabulary 
          size reaches about 3000-4000 words. Lattice differential equations consist of an infinite number of coupled 
          ODEs parametrized by a planar lattice (square and hexagonal being the 
          most popular) such as would be obtained by discretizing a planar system 
          of PDEs. We assume the system is homogeneous; that is, the ODEs at each 
          site are identical. Herb Kunze, University of Guelph A hyperbolic iterated function system (IFS) has a unique fixed point 
          that we refer to as its set attractor. To each point on the set attractor 
          we can associate a code that tells us the order in which we should apply 
          the IFS maps in order to reach or approach the point. By traveling through 
          code space and using the notion of fractal tops (a very recent idea 
          introduced by M. Barnsley), we connect the dynamics of two different 
          IFSs: we paint the points of (an approximation of) the attractor of 
          the first IFS by stealing colours from a digital image via the dynamics 
          of the second hyperbolic IFS. Besides developing assorted theory, I 
          will explore various examples and applications, producing some stunning 
          images along the way. Greg Lewis, University of Ontario Institute 
          of Technology: Mathematical models of fluid systems that isolate the effects of differential 
          heating and rotation are useful tools for studying the behaviour of 
          large-scale geophysical fluids, such as the Earth's atmosphere. In this 
          talk, I discuss the bifurcations of steady axisymmetric solutions that 
          occur in one such model that considers a fluid contained in a rotating 
          spherical shell. A differential heating of the fluid is imposed between 
          the pole and equator of the shell, and gravity is assumed follow axisymmetric 
          solutions through parameter space, and numerical approximations of normal 
          form coefficients are computed for a cusp bifurcation that acts as an 
          organizing centre for the observed dynamics. Pietro Lio, University of Cambridge, UK: During the HIV infection several quasispecies of the virus arise, which 
          are able to use different coreceptors, in particular the CCR5 and CXCR4 
          coreceptors (R5 and X4 phenotypes, respectively). The switch in coreceptor 
          usage has been correlated with a faster progression of the disease to 
          the AIDS phase. As several pharmaceutical companies are starting large 
          phase III trials for R5 and X4 drugs, models are needed to predict the 
          co-evolutionary and competitive dynamics of virus strains. We present 
          a model of HIV early infection which describes the dynamics of R5 quasispecies 
          and a model of HIV late infection which describes the R5 to X4 switch. 
          We report the following findings: after superinfection or coinfection, 
          quasispecies dynamics has time scales of several months and becomes 
          even slower at low number of CD4+ T cells. The curve of CD4+ T cells 
          decreases, during AIDS late stage, and can be described taking into 
          account the X4 related Tumor Necrosis Factor dynamics. Phylogenetic 
          inference of chemokine receptors suggests that virus mutational pathway 
          may generate R5 variants able to interact with chemokine receptors different 
          from CXCR4. This may explain the massive signalling disruptions in the 
          immune system observed during AIDS late stages and may have relevance 
          for vaccination and therapy. Xinzhi Liu, University of Waterloo With the rapid development of personal communications and the Internet, 
          information security has become an increasingly important issue of the 
          telecommunication industry. Recently, there has been tremendous worldwide 
          interest in exploiting chaos for secure communications. The idea is 
          to use chaotic systems as transmitters and receivers, where the message 
          signal is added to a chaotic carrier generated by the transmitter system 
          and it is recovered at the receiver through synchronization. This talk 
          will discuss the method of impulsive synchronization for chaos-based 
          secure communication systems in the presence of transmission delay and 
          sampling delay and the related theory of impulsive dynamical systems 
          with time delay, which provides the main framework for modeling the 
          error dynamics between the driving and response systems employed in 
          such communication systems. Marcus Pivato, Trent University: Let L:= Z^D be the D-dimensional lattice, and let A^L be the Cantor 
          space of L-indexed configurations in some finite alphabet A, with the 
          natural L-action by shifts. A `cellular automaton' is a continuous, 
          shift-commuting self-map F of A^L, and an `F-invariant subshift' is 
          a closed, F-invariant and shift-invariant subset X of A^L. Suppose x 
          is a configuration in A^L that is X-admissible everywhere except for 
          some small region we call a `defect'. It has been empirically observed 
          that such defects persist under iteration of F, and often propagate 
          like `particles' which coalesce or annihilate on contact. We construct 
          algebraic invariants for these defects, which explain their persistence 
          under F, and partly explain the outcomes of their collisions. Some invariants 
          are based on the cocycles of multidimensional subshifts; others arise 
          from the higher-dimensional (co)homology/homotopy groups for subshifts, 
          obtained by generalizing the Conway-Lagarias tiling groups and the Geller-Propp 
          fundamental group. Mary Pugh, Univerity of Toronto If ten genes affect an individual's height and one has a population 
          with average height 6'5" that is forced to live in low-ceilinged 
          caves, how might this selective pressure act at the genetic level of 
          individuals? What happens if the different genes have different magnitudes 
          of effect? A nonlocal diffusion model is constructed and studied for 
          the joint distribution of absolute gene effect sizes and allele frequencies 
          for genes contributing to an quantitative trait in a haploid population 
          where there is a selection pressure on the quantitative trait. We present a simple yet efficient dynamic system for real-time collision-free 
          robot path planning applicable to situations where targets and barriers 
          are permitted to move. The algorithm requires no prior knowledge of 
          target or barrier movements. In the static situation, where both targets 
          and barriers do not move, our algorithm is a dynamic programming solution 
          to the shortest path problem, but restricted by lack of global knowledge. 
          In this case the dynamic system converges in a small number of iterations 
          to a state where the minimal distance to a target is recorded at each 
          grid point, and our robot path-planning algorithm can be made to always 
          choose an optimal path. In the case that barriers are stationary but 
          targets can move, the algorithm always results in the robot catching 
          the target provided it moves at greater speed than the target, and the 
          dynamic system update frequency is sufficiently large. We also look 
          at how the algorithm can be modified to choose paths that not only reach 
          the target via the shortest possible route, but also shun obstacles. 
          The effectiveness of the algorithm is demonstrated through a number 
          of simulations. Gail Wolkowicz, McMaster University: After pointing out the problems with the classical delayed logistic 
          equation as a model of population growth, an alternative expression 
          for a delayed logistic equation is derived. It is assumed that the rate 
          of change of the population depends on three components: growth, death, 
          and intraspecific competition, with the delay in the growth component. 
          In our formulation, we incorporate the delay in the growth term in a 
          manner consistent with the rate of instantaneous decline in the population 
          given by the model. After a complete global analysis of the model, the 
          dynamics are compared with the dynamics of the classical logistic delay 
          differential equation model, the classical logistic ordinary differential 
          equations growth model, and various other more recent formulations. 
          Implications of our analysis for including delay in such models is also 
          discussed. This is joint work with Julien Arino and Lin Wang 
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