Namur Institute For Complex Systems

Francesco Piazza (University of Orléans)
2017-04-25 13:00 - 14:00 (Europe/Paris) | Seminar room, Rempart de la Vierge 8, Namur, 1170
Title: Diffusion of small ligands in complex confining and reactive landscapes:
the geometry of chemoreception.
Abstract:
The rate constant that describes the diffusive encounter/reaction between a particle
and a large sphere can be computed easily by solving the stationary diffusion
(i.e. Laplace) equation for the particle density with appropriate boundary conditions
imposed on the surface of the sphere. In one classic, text-book example, this calculation is
used to estimate the binding rate constant of a ligand to a receptor-covered cell.
But what happens if the particles are diffusing in the presence of many reactive boundaries
of different strength (intrinsic reaction rate), which compete for the same ligands and amidst
a landscape of inert obstacles? In spite of the apparent overwhelming complexity, the same mathematical framework as the two-body problem can be used to solve the N-body problem exactly, by resorting to addition theorems for the appropriate fundamental solutions of the Laplace equation.
This powerful mathematical framework allows one to investigate fundamental issues
that are central in cell biology and modern nano-sciences, such as how the specific geometric
configurations of many reactive boundaries shape the overall reaction rate constant.
We will illustrate several examples, including applications to the study of ligand binding
to arrays of receptors on the surface of a cell and the action of many nano-catalysts embedded within a core-shell nano-reactor.

Jan Baert (UGent)
2017-05-02 13:00 - 14:00 | Seminar room, Rempart de la Vierge 8, Namur, 1170
Title: Environmental dependency of biodiversity effects on ecosystem functioning
Abstract: Expanding human activities are increasingly interfering with Earth’s biogeochemical cycles. This has led to unprecedented global changes in biodiversity and environmental conditions. In the past 3 decades, ecologists have principally been focusing on whether the functioning of an ecosystem depends on the number of species it contains. There is now ample evidence that biodiversity-ecosystem functioning relationships are generally positive, and ecosystem function provisioning is at risk by biodiversity loss. However, evidence is also mounting that the relationship between biodiversity and ecosystem functioning, and therefore also the consequences of biodiversity changes, depend on the environmental conditions. In my work, I ai to explain how biodiversity-ecosystem functioning relationships are affected by changes in environmental conditions. Theoretical models are thereby combined with microcosm experiments to demonstrate how environmental changes lead to predictable changes in biodiversity effects on ecosystem functioning, and how these changes depend the type of species interactions and species sensitivities to environmental changes. As such, the presented framework offers new insights in the combined effect of upcoming biodiversity and environmental changes for ecosystem function provisioning.

Nikos Kouvaris ( University Pompeu Fabra)
2017-05-09 13:00 - 14:00 | Seminar room, Rempart de la Vierge 8, Namur, 1170
Title: Pattern formation in bistable networks: Theory and applications to chemical reactions

Abstract:
Self-organization processes in complex networks is an interdisciplinary research field with great theoretical interest and many potential applications in chemistry and biology. Stationary localized patterns constitute a classical example of self-organization; they can spontaneously be generated by the Turing mechanism, as it has been reported in both continuous and networked media. However, an alternative mechanism for the emergence of stationary patterns in networks was recently discovered [1-4]. We have experimentally demonstrated and theoretically analyzed that bistable networks can support a rich variety of stationary patterns determined by the network architecture and the initial conditions [2,3]. By applying a localized perturbation to a network node or a subset of nodes, we demonstrate the subsequent spreading, pinning, or retraction of the activations; such analysis enables the characterization of the formation of stationary patterns of localized activity. Weak coupling results in trivial pinned states where the activation is stationary. At strong coupling, a uniform state is expected with active or inactive elements at small or large nodes degree, respectively. Nontrivial stationary spatial patterns, corresponding to an activation pinning, are predicted to occur at nodes with intermediate degrees and at intermediate coupling strengths. The results are confirmed in experiments with networks of coupled bistable electrochemical reactions. Although our experimental system is actually more complex than the simplifying assumptions under which the theory was constructed, the results show a surprisingly good agreement. This indicates that the found pattern formation mechanism is robust and generic.
In this talk we discuss theoretical and experimental studies with bistable chemical reactions organized in tree [1,2] and star [3] networks. These results are relevant for large random networks [2]. Mechanisms for the control and deliberate design of such patterns [4] will also be considered.
References:
———–
1. N. E. Kouvaris, H. Kori and A. S. Mikhailov, PLoS ONE 7, e45029 (2012).
2. N. E. Kouvaris, M. Sebek, A. S. Mikhailov and I. Z. Kiss, Angew. Chem. Int. Ed., 55, 13267-13270 (2016).
3. N. E. Kouvaris, M. Sebek, A. Iribarne, A. Diaz-Guilera and I. Z. Kiss, Phys. Rev. E 95, 042203 (2017).
4. N. E. Kouvaris and A. S. Mikhailov, Europhys. Lett. 102, 16003 (2013).

Stefano Berti (University of Lille)
2017-05-23 13:00 - 14:00 | Seminar room, Rempart de la Vierge 8, Namur, 1170
Title: Reaction-transport systems in heterogeneous environments and population dynamics
Abstract: Understanding the conditions ensuring the persistence of a population or determining the efficiency of its invasion into a new territory are issues of primary importance in population biology. A convenient conceptual framework to study these problems from a theoretical point of view is offered by reaction-transport equations. Taking this modeling approach, in the first part of the talk I present a study on the evolution of a population in a heterogeneous environment in the presence of advection. The habitat consists of a periodic alternation of favorable and unfavorable patches where the population grows according to logistic dynamics and dies at a fixed rate, respectively. I show that the population can survive and invade the habitat only above a critical size of the favorable patches and below a critical velocity of the medium. I characterize the survival/extinction transition, and I present some analytical and numerical results on the invasion speed. Then, I discuss some limitations of this description, extending the analysis to a model with a growth term accounting for decreased reproductive power at low population densities. The phenomenology of this model is found to be richer when varying the advection intensity.
In the second part of the talk I discuss some effects of discreteness and demographic stochasticity on the extinction dynamics of a population confined in a favorable patch (an oasis) surrounded by a deadly environment. For this purpose, I introduce an individual-based reaction-diffusion model and investigate its behavior focusing on the average time to extinction and on the quasistationary distribution of the number of individuals that sets in for large enough patch sizes.

Yannick de Decker (ULB)
2017-05-30 13:00 - 14:00 | Seminar room, Rempart de la Vierge 8, Namur, 1170
Canceled

Arnaud Dufays (University of Laval)
2017-06-01 13:00 - 14:00 | Seminar room, Rempart de la Vierge 8, Namur, 1170
Title : A new approach to volatility modeling: the High-Dimensional Markov model
Abstract : A new model — the high-dimensional Markov (HDM) model — is proposed for financial returns and their latent variances. It is also applicable to model directly realized variances. Volatility is modeled as a product of three components: a Markov chain driving volatility persistence, an independent discrete process capable of generating jumps in the volatility, and a predictable (data-driven) process capturing the leverage effect. The Markov chain and jump components allow volatility to switch abruptly between thousands of states. The transition probability matrix of the Markov chain is structured in such a way that the multiplicity of the second largest eigenvalue can be greater than one. This distinctive feature generates a high degree of volatility persistence. The statistical properties of the HDM model are derived and an economic interpretation is attached to each component. In-sample results on six financial time series highlight that the HDM model compares favorably to the main existing volatility processes. A forecasting experiment shows that the HDM model significantly outperforms its competitors when predicting volatility over time horizons longer than five days.

Matteo Polettini (University of Luxembourg)
2017-06-06 13:00 - 14:00 | Seminar room, Rempart de la Vierge 8, Namur, 1170
Title: Effective thermodynamics according to a marginal observer
Abstract:
The celebrated Fluctuation Theorem, quantifying the extent of breakage of time reversibility in nonequilibrium systems, pivots on the fact that all currents contributing to the dissipation rate of a system are known. What instead if only some currents are measurable? In general, the marginal probabilities of fewer currents do not satisfy the full fluctuation symmetry. However, still many claims can be sustained. We provide a general theory of fluctuation relations for the marginal p.d.f. of the currents of a Markov jump process, based on the mathematics of the “marginally time-reversed” generator. At the physical level, the theory has implications regarding the fluctuation-dissipation relations for systems that are only locally at equilibrium, i.e., such that certain currents vanish while all others are arbitrarily far from equilibrium. In particular, we are able to prove nonequilibrium Green-Kubo relations, the violation of the Onsager symmetry, and to provide higher-order signatures of nonequilibrium behavior.

Pierre-Antoine Absil (UCL)
2017-06-13 13:00 - 14:00 | Seminar room, Rempart de la Vierge 8, Namur, 1170
Title: Averaging diffusion tensors

Abstract:
This talk concerns the problem of averaging a collection of symmetric positive-definite (SPD) matrices. Generally speaking, averaging methods are required notably to aggregate several noisy measurements of the same object, or to compute the mean of clusters in k-means clustering algorithms, or as a subtask in higher-level tasks such as curve fitting. The problem of averaging SPD matrices arises for example in medical imaging (denoising and segmentation tasks in Diffusion Tensor Imaging), mechanics (elasticity tensor computation), and in video tracking and radar detection tasks. Among several possible definitions for the mean of SPD matrices (including the straightforward arithmetic mean), the “Karcher mean” (specifically the least-squares mean in the sense of the so-called affine-invariant metric) is of widespread interest in the research literature, since it possesses several pleasant properties while being challenging to compute. In this talk, we will review recent advances in iterative methods that converge to the Karcher mean, and in methods that approach it using limited resources.
This work is in collaboration with Xinru Yuan and Kyle Gallivan (Florida State University), Wen Huang (Rice University), and Estelle Massart and Julien Hendrickx (UCLouvain).

Jérôme Kunegis (NaXys)
2017-06-27 13:00 - 14:00 | Seminar room, Rempart de la Vierge 8, Namur, 1170
Title: The New KONECT Project at the University of Namur
Abstract: In this talk I give an overview of the KONECT project, and highlight some of its applications. The KONECT Project is a project to collect, analyse and disseminate network datasets as used in various fields of research such as network science, web science, etc. The name “KONECT” stands for “Koblenz Network Collection” as the project was initiated at the University of Koblenz-Landau (Germany), but is now maintained at the University of Namur in parallel with my move to this university. This talk will give a motivation for the need of such a project, highlighting the benefits of performing research on large sets of network datasets, and why the motto of KONECT is “Everything is a Network”. I will also briefly present recent papers by myself and colleagues that have made use of the KONECT corpus. Finally, I will give a brief introduction to the Stu build automation tool that I wrote in order to manage the highly parallel and structurally complex computations in KONECT.

Marco Sansottera (University of Milan)
2017-06-30 13:00 - 14:00 | Seminar room, Rempart de la Vierge 8, Namur, 1170
Title: Quasi-convexity of the Hamiltonian for non Harmonic or non Keplerian
central potentials.
Abstract:
We consider the planar central motion with a real analytic potential. We
prove that the corresponding Hamiltonian, when written in action angle
variables, is almost everywhere quasiconvex, the only exceptions being
the Keplerian and the Harmonic potentials. We deduce persistence of most
KAM tori for the perturbed planar system. We also deduce a Nekhoroshev
type stability result for the perturbed spatial central motion. Such a
latter result covers also the case where the central system is put in
interaction with a slow system.

Alex Matzkin (CNRS/Université de Cergy-Pontoise)
2017-07-06 11:00 - 12:00 | CH12
Title: Can the properties of a quantum system vanish?
Abstract:
The Weak Measurements approach is a framework based on implementing non-destructive, non-perturbing measurements on a quantum system as the system evolves from an initially prepared state to a final state obtained by performing a standard measurement. The result of a weak measurement is called the “weak value” of the weakly measured observable. Weak values have peculiar features. In particular, a vanishing weak value means that the corresponding system property cannot be found at the location where the observable was weakly measured. This may have striking consequences, like not being able to detect a particle inside an interferometer although it went in and out, or observing a spatial separation between a particle and one of its properties. I will describe situations in which quantum properties appear to “vanish” and I will put forward an explanation based on the analysis of null weak values.

VBIH (Virtual Belgium in Health) - Presentation of the results
2017-10-30 09:00 - 12:00 | E11

Duccio Fanelli (University of Florence, Italy)
2017-11-02 13:00 - 14:00 | E25
Title: Noise-driven neuromorphic tuned amplifier
Abstract: Living systems execute an extraordinary plethora of complex functions, that result from the intertwined interactions among key microscopic actors. Positive and negative feedbacks appear to orchestrate the necessary degree of macroscopic coordination, by propagating information to distant sites while supporting the processing steps that underly categorization and decision making. Excitatory and inhibitory circuits play, in this respect, a role of paramount importance. As an example, networks of excitatory and inhibitory neurons constitute the primary computational units in the brain cortex and can adjust to different computational modalities, as triggered by distinct external stimuli. The genetic regulation also relies on sophisticated inhibitory and excitatory loops. Working in this context, we shall here discuss a minimal model for a discrete collection of agents in mutual interaction via excitatory and inhibitory loops, bearing universality traits in light of its inherent simplicity. Endogenous-noise stemming from finite size corrections induces quasi-cyclic dynamics that display unusual long-range correlations, persisting over arbitrary large network structures. When the excitatory and inhibitory species are distributed on a directed network, the internal noise seeds giant quasi-cycles, with tunable frequency and amplitude. The system spontaneously behaves as an effective, stochastic driven pacemaker, a non-trivial self-organized dynamics that hold general interest, for its fundamental to applied implications. The phenomenon is characterized analytically. The theoretical prediction is corroborated by direct stochastic simulations.

naXys Board meeting
2017-11-09 12:10 - 13:30 | E25

Olivier Deparis (UNamur)
2017-11-10 13:00 - 14:00 | E22
Title: Alternative expression of the Bloch wave group velocity using the Sturm-Liouville formalism applied to electromagnetic wave propagation in periodic dielectric media

Astero Provata (National Center for Scientific Research Demokritos, Athens)
2017-11-16 13:00 - 14:00 | E25
Title: The influence of the network connectivity in the spatial patterns of chimera states
Abstract: Chimera states emerge in systems of nonlocally coupled identical oscillators and are characterized by the coexistence of alternating coherent and incoherent domains. These hybrid states appear unexpectedly since all elementary oscillators in the network are identical and are identically coupled. A characteristic feature of chimera states is their mean frequency profile: In the coherent regions, all elements have equal, constant mean phase velocity, while in the incoherent ones the frequency profiles take arc shapes. Here we present synchronization properties leading to chimera states in networks of coupled neuronal oscillators. To understand the influence of connectivity in the chimera form we investigate the Leaky Integrate and Fire (LIF) model under different connectivity architectures. In the case of nonlocal connectivity, we show evidence of a coexistence state where multileveled chimera patterns are formed and they coexist with domains consisting of near-threshold elements. The oscillating elements form complex mean phase velocity profiles while the potentials of the near-threshold elements present small fluctuations and never drop to the resting state. We study different synchronization patterns in the parameter space of the LIF system when the oscillators are nonlocally coupled in 1, 2 and 3 spatial dimensions. We also investigate the effects of different connectivity schemes: nonlocal connectivity, reflecting coupling, diagonal or hierarchical (fractal) connectivity.
– Tsigkri-DeSmedt, N.D., Hizanidis, J., Schöll, E., Hövel, P., Provata, A.
Chimeras in leaky integrate-and-fire neural networks: effects of reflecting connectivities,
European Physical Journal B 90(7),139 (2017).
– Tsigkri-DeSmedt, N.D., Hizanidis, J., Hövel, P., Provata, A.
Multi-chimera states and transitions in the Leaky Integrate-and-Fire model with nonlocal and hierarchical connectivity,
European Physical Journal: Special Topics 225(6-7), pp. 1149-1164 (2016).
– Schmidt, A., Kasimatis, T., Hizanidis, J., Provata, A., Hövel, P.
Chimera patterns in two-dimensional networks of coupled neurons
Physical Review E 95(3),032224 (2017).

Yérali Gandica (UNamur)
2017-11-23 13:00 - 14:00 | E25
Title: Language as a signature of collective identity: Wikipedia editing across twelve languages

Marco Sansottera (University of Milan)
2017-11-30 13:00 - 14:00 | E25
Title: On the continuation of degenerate periodic orbits via normal form: full dimensional resonant tori
Abstract: We reconsider the classical problem of the continuation of degenerate periodic orbits in Hamiltonian systems. In particular we focus on periodic orbits that arise from the breaking of a completely resonant maximal torus. We here propose a suitable normal form construction that allows to identify and approximate the periodic orbits which survive to the breaking of the resonant torus. Our algorithm allows to treat the continuation of approximate orbits which are at leading order degenerate, hence not covered by classical averaging methods. We discuss possible future extensions and applications to localized periodic orbits in chains of weakly coupled oscillators.

Henri Vanhomwegen (UNamur)
2017-12-07 13:00 - 14:00 | E25
Title: Mutual funds styles distinctiveness and financial performance insights from Europe
Asbtract: Do mutual funds following a same style adopt similar investment strategies? Are these potential differences more salient over certain periods? What drives a mutual fund to be distinct from its peers? Does it pay? Those are central questions for both academics and market practitioners that we aim to address in this paper. More generally, we propose to study the degree of commonality among European equity mutual funds over time, and its impact on financial performance. To this end, we use several market-based measures of commonality among 4957 European equity mutual fund returns over the 1999-2016 period. We pay a particular attention to the computation of adequate metrics, the so-called « strategy distinctiveness index » applying up-to-date techniques from statistics and machine learning to generate clusters of mutual funds associated to “styles”, from which we can gauge how similar or distinct a mutual fund is from its peers (i.e. the mutual funds belonging to the same cluster or style). Our results show marked changes in the level of commonality over time, distinctiveness among European mutual funds decreasing sharply before the crisis before going up and eventually reaching a new low in the recent months. We find strong evidence regarding the contribution of fund-level as well as cluster characteristics to strategy distinctiveness. Turning to financial performance, our results show a strong and robust, positive impact of strategy distinctiveness on financial performance.

Sébastien Clesse (UCL - UNamur)
2017-12-14 13:00 - 14:00 | E22
Title: Is Dark Matter made of Primordial Black Holes?
Abstract: The detection of gravitational waves by Advanced-LIGO/VIRGO has opened a wide new field of astronomy. Strangely, the merging rate of massive black holes was found to be compatible with the rate expected if they constitute the Dark Matter. This has revived the interest for Primordial Black Holes (PBH) formed in the early Universe constituting a fraction or even the totality of Dark Matter . This scenario is however well constrained by other astrophysical observations. I will review the pros and cons of this scenario, in the view of the most recent results and observations, and I will emphasize how PBH Dark Matter could resolve some long-standing cosmological and astrophysical puzzles. The presentation will be understandable by a broad audience of mathematicians, physicists and students.

Anthony Hendrickx
2017-12-21 13:00 - 14:00 | E25
Title: Algorithme génétique et Rotifères Bdelloïdes: les mathématiques au service de la biologie
Résumé: Existant depuis 1962, les algorithmes génétiques se sont toujours basés sur un mode de reproduction sexuée, la reproduction asexuée entraînant une accumulation de mutations délétères, censée provoquer l’extinction de l’espèce. Cependant, l’espèce du Bdelloïde, malgré son mode de reproduction asexuée, survit depuis des dizaines de millions d’années dans des milieux extrêmes et variés. Cette incroyable faculté semble être expliquée par l’observation, chez cette espèce, de phénomènes connus sous les noms de conversion génique et transfert horizontal. L’objectif de ce mémoire était de modéliser, sous forme d’algorithmes génétiques, l’évolution asexuée du Rotifère Bdelloïde, afin d’étudier l’importance et l’influence de ces deux phénomènes. Des relations mathématiques connues en génétique, liant taux de mutation, longueur d’ADN et taux de conversion génique, sont retrouvées numériquement, permettant de valider et de simplifier notre modélisation. L’utilité du phénomène de conversion génique, permettant de rendre nos algorithmes plus stables, robustes et précis qu’un algorithme génétique classique, est ensuite démontrée. Enfin, l’importance du mécanisme de transfert horizontal, améliorant l’efficacité du modèle asexué, est mise en évidence, permettant d’envisager un algorithme plus efficace que les modèles classiques.

Justin Buhendwa Nyenyezi (UNamur)
2018-01-25 13:00 - 14:00
Title: Polynomial preconditioners versus matrix-splitting preconditioners for linear systems arising in 3D medical image registration
Abstract: Many methods exist to solve large sparse linear systems. However, a given method may perform well for a particular problem while it may not work as well for another [2]. For designing ecient system solvers, one may analyze structures of general operators or matrices used by the algorithms. In non-rigid medical image registration, matrices are derived from physical principles, modelled as Partial Dierential Equations (PDEs). Although these systems are often sparse and structured, they are very large and ill-conditioned. Thus, their solvers are time consuming and their complexity in operation counts is polynomial. As a consequence, fast and superfast direct methods reveal numerical instabilities and thus lead to breakdowns or inaccurate solutions. The most used alternative are iterative system solvers that enable a reduction of the number of expensive operations such as matrix-vector products and thus a speed up of the registration process. Although iterative solvers provide only an approximation of the solution, they are well suited for very large systems when cheap and well suited preconditioners are available. Preconditioners may be stationary (Jacobi, Gauss-Seidel or SOR) and non-stationary (e.g, polynonmial or low-rank inverse approximation).
In this study, we are especially interested in benchmarking [3, 4] iterative system solvers on a large set of 3D medical images. These system solvers are based on the Conjugate Gradient method but dierent from the preconditioning techniques [6, 5] . The ongoing results conrm [4] that there is no single system solver that is the best for all the problems. However, the results indicate which solver has the highest probability of being the best within a factor f ∈ [1, ∞[ and considering a limited computional budget in terms of time and storage require-
ments.
References
[1] Oseledets, Ivan and Tyrtyshnikov, Eugene and Zamarashkin, Nickolai. Evaluation of optimization methods for nonrigid medical image registration using mutual information and B-splines. Image Processing, IEEE Transactions on, 16:12,28792890, 2007.
[2] Barrett, Richard and & all. Templates for the solution of linear systems: building blocks for iterative methods. SIAM , 1994.
[3] Moré, Jorge J and Wild, Stefan M. Benchmarking derivative-free optimization algorithms. SIAM Journal on Optimization , 20:1,172191, 2009.
[4] Gould, Nicholas and Scott, Jennifer. The State-of-the-Art of Preconditioners for Sparse Linear Least-Squares Problems. ACM Transactions on Mathematical Software (TOMS) , 43:4,36, 2017.
[5] Nocedal, Jorge and Wright, Stephen J. Numerical optimization. Springer New York , 2, 2006.
[6] SAAD,Yousef Iterative methods for sparse linear systems. Society for Industrial and Applied Mathematics , 2003.

Eve-Aline Dubois (UNamur)
2018-02-15 13:00 - 14:00 | E25
Titre: The early times of stationary cosmologies
Abstract: The Steady-state model of Bondi and Gold, on the one hand, and Hoyle’s model on the other hand are the most famous examples of stationary cosmologies. However, they are actually quite different in terms of motivations and content and were not the only stationary models. In this talk, we will look back at the very beginning of relativistic cosmology and the first stationary cosmological models. They were lead by various motivations and suggest a surprising phenomenon: creation of matter. From Einstein to Hoyle, we will follow the different stationary cosmologies, their development and their interplay.

François Lamoline (UNamur)
2018-02-20 13:00 - 14:00 | E25
Title: Well-Posedness of Boundary Controlled and Observed Stochastic Port-Hamiltonian systems
Abstract: On finite-dimensional spaces, the well-posedness is not a concern and is usually not even mentioned. However, on infinite-dimensional spaces, establishing the well-posedness is of paramount importance and paves the way for dealing with control/estimation, transfer function, etc. In this talk, stochastic port-Hamiltonian systems on infinite-dimensional spaces governed by Ito stochastic differential equations and with boundary control and observation operators are introduced and some properties of this new class of systems are studied. They are an extension of stochastic port-Hamiltonian systems defined on a finite-dimensional state space. The concept of well-posedness in the sense of Weiss and Salamon is generalized to the stochastic context. Under this extended definition, stochastic port-Hamiltonian systems are shown to be well-posed. The theory is illustrated on an example of a vibrating string subject to a Hilbert-space valued Gaussian white noise process.

naXys extended Board meeting
2018-02-22 13:00 - 14:00 | E25

Alexandre Bovet (UNamur - UCL)
2018-03-01 13:00 - 14:00 | E25
Title: Opinion dynamics and fake versus traditional news influence in Twitter
Abstract: We investigate the opinion of Twitter users during the 2016 US elections using a large scale dataset of more than 170 millions tweets. We develop a method to infer the opinion of Twitter users regarding the candidates by using a combination of natural language processing of the tweet contents, machine learning classification and analysis of the hashtags co-occurrence network. We study the temporal social networks formed by the interactions among millions of Twitter users and infer the support of each user to the presidential candidates. The resulting Twitter opinion trend follows the New York Times National Polling Average, which represents an aggregate of hundreds of independent traditional polls, with remarkable accuracy.
Going beyond the daily opinion analysis and analyzing the level of activity, the repartition of the supporters between the strongly connected giant component and the rest of the network and the daily fluctuations in the number of users reveal a clear dichotomy between the behavior of supporters of each candidate. Although Clinton supporters are the majority in Twitter, Trump supporters are generally more active and more constant in their support, while Clinton supporters are less active and show their support only occasionally.
To understand the role of information diffusion on Twitter opinion dynamics, we consider tweets containing URLs directing to news outlet websites. In particular, we compare websites known to diffuse fake news compared to traditional, fact-based, news outlets. We find that 29% of the tweets linking to news outlets points to websites containing fake or extremely biased news. Analyzing the information diffusion networks, we find that user diffusing fake news form more connected and less heterogeneous networks than users in traditional news diffusion networks. While influencers of traditional news outlets are journalists and public figures with verified Twitter accounts, most influencers of fake news and extremely biased websites are unknown users or users with deleted Twitter accounts. Finally, an analysis of the activity dynamics of influencers reveals that influencers of tradition news are driving the most part of Twitter while fake news influencers are, in fact, mostly driven by the activity of Trump supporters.

Alexey Medvedev (UNamur)
2018-03-08 13:00 - 14:00 | E25
Title: Modelling structure and predicting dynamics of discussion threads in online boards using Hawkes processesAbstract: Online social platforms provide a fruitful source of information about social interaction. Depending on the platform, various tree-like cascading patterns emerge as a consequence of such interaction. For example, on Twitter or on Facebook people interact via resharing messages, which turns into cascade trees of reshares, in email networks people forward messages to their peers resulting in trees of email forwards, in online boards like Digg or Reddit people interact via discussing particular posts, which leaves a trace of discussion trees. The two main questions arise: what is the shape of these cascades and how to predict the dynamics of their evolution? The question of evolution of discussion threads is now gradually being understood. By now researchers studied only the structural evolution of discussion trees and the dynamical properties are left out of consideration. Nevertheless, there was proposed a sort of a mean-field model for dynamics and structure, however by the design the model has limited utility in practice. We consider cascades given by discussion trees of posts in online board Reddit. The dataset of Reddit discussion threads consists of all posts and comments submitted to Reddit from Jan, 2008 till Jan, 2015. The dataset in total contains more than 150 million posts and around 1.4 billion comments. We propose a model of discussion trees generation based on the self-exciting Hawkes processes, which represents both the tree structure and temporal information. We use the dataset of Reddit discussion threads to show that structurally trees resemble Galton-Watson trees with a special root offspring distribution, and distinct the cases when the dynamics of comments attraction can be well predicted using Hawkes processes.

Jean Teyssandier (Cornell University, USA)
2018-03-29 13:00 - 14:00 | E25
Title: Orbital evolution during planet-⁠disc interactions
Abstract: The origin and wide distribution of eccentricities and inclinations in planetary systems remains to be explained, in particular in the context of planet-disc interactions. In this talk I will present a study of the evolution of eccentricity in discs and planets that combines methods from celestial mechanics and hydrodynamics, and takes the form of a linear secular theory. I will compare the predictions of this linear theory against direct hydrodynamical simulations and show how eccentricity can grow. I will discuss what these results imply for the orbital structure of protoplanetary discs and young planetary systems. I will also discuss how moderate inclinations can be generated via similar mechanisms.

Julien Petit (Ecole Royale Militaire - UNamur)
2018-04-10 13:00 - 14:00 | E22
Title : Peculiarities of reaction and diffusion on temporal networks
Abstract: A common assumption in the ever-increasing literature on network-defined dynamical systems is to view the underlying graph as a static entity. In many cases however, the temporal properties of the network – its fluctuating links and appearing and vanishing nodes – prove critical.
This presentation is firstly meant as an overview of linear (diffusion) processes on temporal networks. After a survey of recent methods and results, we subsequently focus on a random walk model with lasting node-to-node interactions. Relying on analytics and numerics, we discuss how the Markov property of the process is lost even when using memoryless probability distributions for the model-driven edges dynamics, and the independent nodes processes.
If time permits and in an attempt to highlight other results about systems evolving on top of temporal networks, and which stem from the intrinsic network dynamics, we finally consider a generic nonlinear model. In particular, this setting allows us to discuss pattern formation and oscillations death in reaction-diffusion systems through the Turing mechanism, under the assumption of a fast-varying periodic topology.

Aivar Sootla (University of Oxford)
2018-04-19 13:00 - 14:00 | E25
Title: Applications of Monotone Systems Theory to Synthetic Biology
Abstract: In this talk, we will discuss some mathematical problems arising in the fast developing field of synthetic biology. Synthetic biology is concerned with creating genetically modified bacteria for the production of useful chemical compounds (e.g., drugs, bio-degradable plastic, fuels etc), for detecting viruses, toxins or prohibited substances (e.g. in a biological sample, water supply), and even for new methods of drug delivery. Due to complexity and variability of bacterial systems modelling presents a serious challenge. Furthermore, quantitative data analysis is impeded by technological and physical constraints, therefore scientists often rely on qualitative analysis of their designs. From the modelling perspective, qualitative analysis is not always straightforward unless models have specific properties. We will argue that a class of models called monotone can offer effective tools for qualitative analysis of biological processes. Monotone systems often appear in biological modelling and possess a powerful property: a partial order in their trajectories. Partial order enables a number of stability results, which are crucial for simplified analysis and control of nonlinear systems. Equipped with the Koopman operator framework, we present methods for analysis and control of monotone systems, which are computationally efficient and can provide answers for a range of parameters.
