Determinants of creativity and innovation in science, art and technology  (DCIS) Session 2

Chair: Vittorio Loreto

 15006 How creative, participatory and innovation strategies can improve the quality of scientific research? [abstract] Abstract: We will explain and discuss several experiences where artistic and creative practices can drive ambitious scientific research. We will focuss on topics and actions directly related to complex systems science to exemplify all their potentialities. We will describe how participatory strategies, public engagement, community processes and wide multidisciplinary teams are able to transform an ordinary research activity into a complete experience where impact and outputs are multiple, diverse and long-lasting. The list of actors involved should necessary include artists, designers, public agencies or administrations, and then must also take place in uncommon places such as museums, cultural spaces and public spaces. Working with many actors and building tailored-made research collectives have the capacity to raise shared concerns, to address societal challenges in a novel and innovative way, and to enhance the value of the results by publicly discussing and sharing the whole research cycle. Close Josep Perello 15007 From Innovation to Diversification: A Simple Competitive Model [abstract] Abstract: Few attempts have been proposed in order to describe the statistical features and historical evolution of the export bipartite matrix countries/products. An important standpoint is the introduction of a products network, namely a hierarchical forest of products that models the formation and the evolution of commodities. In the present article, we propose a simple dynamical model where countries compete with each other to acquire the ability to produce and export new products. Countries will have two possibilities to expand their export: innovating, i.e. introducing new goods, namely new nodes in the product networks, or copying the productive process of others, i.e. occupying a node already present in the same network. In this way, the topology of the products network and the country-product matrix evolve simultaneously, driven by the countries push toward innovation. Close Riccardo Di Clemente 15008 Identifying the Features of Popular and Significant Artworks in Popular Music Production [abstract] Abstract: In the world of artistic production there is a constant struggle to achieve fame and popularity. This fierce competition between artistic creations results in the emergence of highly popular elements that are usually well remembered throughout the years, while many other works that did not achieve that status are long-forgotten. However, there is another level of importance that must be considered in order to have a more complete picture of the system. In fact many works that have influenced the production itself, both due to their aesthetic and cultural value, might have not been or might not be popular anymore. Due to their relevance for the whole artistic production, it is important to identify them and save their memory for obvious cultural reasons. In this paper we focus on the duality between popularity and significance in the context of popular music, trying to understand the features of music albums belonging to one or both of these classes. Close Bernardo Monechi 15009 Social networks evolution with old and and new ties: how our social horizon grows [abstract] Abstract: By means of user-generated data gathered on Last.fm, an on-line catalog of music albums, we define a growing conceptual space in the form of a network of tags representing the evolution of music production during the years. We use this network in order to define a set of general metrics, characterizing the features of the albums and their impact on the global music production. We then use these metrics to implement an automated prediction method of both the commercial success of a creation and its belonging to expert-made lists of particularly significant and important works. We show that our metrics are not only useful to asses such predictions, but can also highlight important differences between culturally relevant and simply popular products. Finally, our method can be easily extended to other areas of artworks creation. Close Raffaella Burioni

Information Processing in Complex Systems  (IPCS) Session 2

Chair: Rick Quax

 45010 Quantum Complexity [abstract] Abstract: I intend to review several notions of classical complexity and discuss how they might be quantized. The standard technique from quantum information is to measure a given quantum system whose complexity we want to know and then apply the classical measures to the resulting classical statistics. In order to obtain the quantum complexity we finally optimize (minimize or maximize) over all classically obtained results. However, it might be more appropriate to measure quantum complexity directly, i.e. not going via classical statistics. How might that be done? I also discuss complexity from the perspective of how difficult it is to make entangled states. This will lead me introduce the concept of quantum macroscopicity. Close Vlatko Vedral 45009 The classical-quantum divergence of complexity in the Ising spin chain [abstract] Abstract: Most interesting systems in nature are often complex, lying in the region between order and randomness. Even though the idea of complexity is understood intuitively, it lacks a formal mathematical description. The statistical complexity, defined by Crutchfield as the minimum information required by a classical model to statistically simulate a process, serves to quantify complexity. Here, we show that the same idea of complexity behaves differently in the quantum information regime. We introduce the quantum statistical complexity as the minimum information required by a quantum model to statistically simulate a process, and show that it exhibits drastically different qualitative behavior when applied to the same system - the 1D Ising spin chain. Thus, we illustrate that the notion of what is complex depends on the information theory used to describe it. Close Whei Yeap Suen, Jayne Thompson, Andrew Garner, Vlatko Vedral and Mile Gu 45011 Occam's Quantum Strop [abstract] Abstract: A stochastic process's statistical complexity stands out as a fundamental property: the minimum information required to synchronize one process generatorto another. How much information is required, though, when synchronizing over aquantum channel? Recent work demonstrated that representing causal similarity as quantum state-indistinguishability provides a quantum advantage. We generalize this to synchronization and offer a sequence of constructions that exploit extended causal structures, finding substantial increase of the quantum advantage. We demonstrate that maximum compression is determined by the process's cryptic order---a classical, topological property closely allied to Markov order, itself a measure of historical dependence. We introduce an efficient algorithm that computes the quantum advantage and close noting that the advantage comes at a cost---one trades off prediction for generation complexity. Close John Mahoney, James Crutchfield and Cina Aghamohammadi 45012 Classification of time-symmetry breaking in quantum walks on graphs [abstract] Abstract: Most interesting systems in nature are often complex, lying in the region between order and randomness. Even though the idea of complexity is understood intuitively, it lacks a formal mathematical description. The statistical complexity, defined by Crutchfield as the minimum information required by a classical model to statistically simulate a process, serves to quantify complexity. Here, we show that the same idea of complexity behaves differently in the quantum information regime. We introduce the quantum statistical complexity as the minimum information required by a quantum model to statistically simulate a process, and show that it exhibits drastically different qualitative behavior when applied to the same system - the 1D Ising spin chain. Thus, we illustrate that the notion of what is complex depends on the information theory used to describe it. Quantum walks on graphs represent an established model capturing essential physics behind a host of natural and synthetic phenomena. Quantum walks have further been proven to provide a universal model of quantum computation and have been shown to capture the core underlying physics of several biological processes in which quantum effects play a central role. A 'single particle quantum walker' moves on a graph, with dynamics governed by Schrödinger's equation and quantum theory predicts the probability of a walker to transition between the graphs' nodes. Any quantum process in finite dimensions can be viewed as a single particle quantum walk. Until recently, quantum walks implicitly modeled only probability transition rates between nodes which were symmetric under time inversion. Breaking this time-reversal symmetry provides a new arena to consider applications of this symmetry breaking and to better understand its foundations. The main application discovered so far is that this symmetry breaking can be utilized as a passive means to control and direct quantum transport. A subtle interplay between the assignment of complex Hamiltonian edge weights and the geometry of the underlying network has emerged in a sequence of studies. This interplay has been central to several works, but in the absence of definitive statements, past work has only produced criteria for a process on a graph to be time-symmetric. Leaving the classification problem and its implications, open. Here we provide a full classification of the Hamiltonians which enable the breaking of time-reversal symmetry in their induced transition probabilities. Our results are furthermore proven in terms of the geometry of the corresponding Hamiltonian support graph. We found that the effect can only be present if the underlying support graph is not bipartite whereas certain bipartite graphs give rise to transition probability suppression, but not broken time-reversal symmetry. These results fill an important missing gap in understanding the role this omnipresent effect has in quantum information science. Close Jacob Turner and Jacob Biamonte 45008 The Ambiguity of Simplicity [abstract] Abstract: A system’s apparent simplicity depends on whether it is represented classically or quantally. This is not so surprising, as classical and quantum physics are descriptive frameworks built on different assumptions that capture, emphasize, and express different properties and mechanisms. What is surprising is that, as we demonstrate, simplicity is ambiguous: the relative simplicity between two systems can change sign when moving between classical and quantum descriptions. Thus, notions of absolute physical simplicity—minimal structure or memory—at best form a partial, not a total, order. This suggests that appeals to principles of physical simplicity, via Ockham’s Razor or to the “elegance” of competing theories, may be fundamentally subjective, perhaps even beyond the purview of physics itself. It also presents a challenge to using quantum computers for statistical inference. Fortunately, experiments are now beginning to probe measures of simplicity, creating the potential to directly test for ambiguity. Close James Crutchfield, Cina Aghamohammadi and John Mahoney 45007 Increasing excess entropy in the approach towards equilibrium in a reversible Ising dynamics model [abstract] Abstract: Dynamic models of spin systems, based on microscopic reversibility and conserved energy, have been used for simulation of the Ising model and the approach towards equilibrium. The equilibrium is here determined by the set of distributions, over configurations of finite blocks of spins, with increasing sizes, that with the given energy constraint maximises the entropy density. Since also the entropy density is conserved in such a dynamics, a natural question is whether the full equilibrium is really reached and how? We investigate this question in detail by making an information-theoretic analysis of the one-dimensional, infinite lattice version of the Q2R model. Its two-dimensional version has been extensively used for simulation of the two-dimensional Ising model. Starting from a low entropy state, with appropriate statistics, it is shown that despite the conserved entropy, if entropy is estimated only from finite size block statistics, entropy appears to be increasing and the equilibrium state for the given energy is approached. By showing how the excess entropy increases during this process, it is clarified how local order is transformed into correlation information over increasing distances, explaining the apparent entropy increase and the approach towards equilibrium. The findings are discussed in the broader context of reversible microscopic dynamics, macroscopic irreversibility, and the second law of thermodynamics. Close Kristian Lindgren and Eckehard Olbrich 45005 Mutual information reveals lower-level mechanisms, aiding higher level predictability [abstract] Abstract: I will present some recent work on Shannon information theory applied to natural complex systems. As part of this we have developed a new correlation length function based on mutual information. I will discuss how it aids predictability of complex systems by detecting underlying mechanisms of change. One example I will present is a glass former, and I will discuss how this far-from-equilibrium many-particle system is representative of many other complex systems. Close Karoline Wiesner 45013 Unbounded memory advantage in stochastic simulation using quantum mechanics [abstract] Abstract: Simulations using real quantities on a digital computer require a trade-off between the precision to which these quantities are stored, and the memory required to store them. The limit of the simulation's precision is hence limited by the internal memory available to the simulator. In this presentation, I shall demonstrate using tools from statistical complexity theory and its quantum extensions that quantum information processing allows the simulation of stochastic processes to arbitrarily high precision at a finite memory cost. This demonstrates the unbounded memory advantage that a quantum computer can exhibit over its best possible classical counterpart when used for stochastic simulations. Close Andrew Garner, Qing Liu, Jayne Thompson, Vlatko Vedral and Mile Gu

Workshop on Open & Citizen Data Science  (WOCD) Session 2

Chair: Thomas Maillart

 33007 Open Infrastructure for Open Science [abstract] Abstract: Opening the scientific process for creating knowledge needs opening the access to a number of diverse resources like scientific instruments, scientific data, digital services, software tools, knowledge and expertise, all needed in some form to conduct research. These elements can be regarded as infrastructural resources that are essential inputs to the research process. Making these resources open and shareable require the adoption of standards, the right legal frameworks and license, and clear rules for access. There is also the crucial aspect of defining the appropriate governance and management mechanisms that ensure their long term maintenance and availability. This presentation tackles commoning as the social practice suitable to create systems to manage these shared resources and provides examples in the area of open science. It also identifies some of the current challenges with particular focus on the digital infrastructures. Close Sergio Andreozzi 33008 Overview of Citizen Science Models, Practices and Impacts [abstract] Abstract: Ibercivis (www.ibercivis.es) is the national foundation of Citizen Science in Spain that promotes and supports Citizen Science experiments and studies, delivering services to the communities as well as deploying our own tools and experiences. Our main approach to public engagement is to promote the uptake of Citizen Science tools to enrich research by changing current approaches to scientific challenges and by incorporating knowledge from outside the academia. In the last years, we are facing a boom of Citizen Science practices all around the world. Only from Ibercivis we have deployed more than 50 experiments with over 40 different research groups from different areas of knowledge, reaching over 50.000 volunteers. Our set of experiments include volunteer computing (e.g. simulation of nuclear fusion devices using http://boinc.berkeley.edu), volunteer sensing (e.g. odour nuisances reports http://digitalearthlab.jrc.ec.europa.eu/mygeoss/results3.cfm), volunteer thinking (e.g. stem cells images analysis cellspotting.socientize.eu), participatory experiments (e.g. human behavior in dilemma dilema.ibercivis.es), or collective intelligence projects (e.g. collectivemusicexperiment.eu) among others. One of the main drivers of this scenario is the digitally enabled transformation of the interactions between science and society, facing an unprecedent scale of nature and range of collaborators. We find several models of public engagement in science and contributions occur individually as well as collectively, in all the steps of the scientific workflow. There is a need of having a clear picture of the situation in Europe. Addressing this at national scale, we created the Observatory of Citizen Science in Spain (www.ciencia-ciudadana.es) to monitor the growth of such initiatives, catalogue them and analyze different impacts. Ibercivis was promoted from the BIFI Institute of the University of Zaragoza and includes research institutions and science funders, namely MINECO, CSIC, CIEMAT, Gobierno de Arag?n and Fundaci?n Zaragoza Ciudad del Conocimiento. We are part of the steering committee of the European Citizen Science Association, linking with responsible research and innovation. Since 2012 we coordinate the European project Socientize (www.socientize.eu) which delivered the White Paper on Citizen Science for Europe, referenced as a flagship document for the Citizen Science policy making. In this presentation we will present a significant set of these projects and we will present their outcomes from scientific, educational, political and technological perspectives. Close Fermin Serrano, Jesus Clemente, Mari Carmen Ibañez, Eduardo Lostal, Francisco Sanz 33009 Herding Cats in Gentoo Linux [abstract] Abstract: Between 2001 and 2005, I had the privilege and honour of leading and guiding Gentoo Linux's development teams. That was a period of high growth for Gentoo -- our userbase went from less than a thousand users (about ~750 in the #gentoo IRC channel), to over 1.5 million by 2003. This massive mushrooming of the userbase made its effects felt throughout the project. Due to the nature of the technology and the ethos of the project, Gentoo rapidly started to become the Linux distribution for every kind of situation. Several projects launched within Gentoo -- many of them around supporting different hardware, including: PPC, Sparc, IA64, Arm, and others. Communities formed to help people speaking specific languages (Spanish, French, and Polish were amongst the pioneer communities). Each group had developers within the project, and users interacting with those developers. Interactions (user-user, dev-dev, user-dev) happened in many fora: IRC, email lists, Gentoo Forums, as well as a number of third party online destinations for Linux geeks. Gentoo-fever was all around. We got made fun of: in forums comments everywhere, satirical websites popped up, and of course, our users were die-hard defenders of The Gentoo Way. The challenge of guiding this growth, and considering the perspectives of (at our peak) 250 developers, fell onto the leadership team. As part of that team, I underwent my own growth -- as a developer, a colleague, a friend, and a human being. I would like to tell you my story. Close Seemant Kullen 33010 Enhancing Online Community Building & Long-Term Production with Co-Located Events [abstract] Abstract: Nearly all online communities organize co-located meetings, such as conferences, un-conferences, and hackathons. These events are short, fast-paced, yet they are intended to enable social interactions and fast-circulation of informal knowledge between attendants. There is however a dearth of knowledge on the contribution of co-located events to community enhancement and long-term online production. Here, I study a community of astrophysicists involved in open and reproducible data science. Over the span of data collected (4 years), five co-located meetings were organized. Each meeting triggered contrasted immediate effects regarding collaboration, but all of them had significant long-term enhancing effects on community building and online knowledge production. These results illustrate how punctual co-located meetings change the way contributors engage with their community once they have resumed their routine work online. Close Thomas Maillart 33011 Using the Blockchain for Reproducible, Transparent and Trustworthy Science [abstract] Abstract: Scientific studies are often not reproducible and trustworthy due to false or exaggerated research findings. This current issue creates a bias in which successful studies are often only published through the use of dishonest scientific practices. To approach this issue, a research project has been set up to investigate how the reproducibility and trustworthiness of scientific studies can be improved with the use of the blockchain technology. The blockchain technology has shown adequate results in terms of progressing and logging transactions for the Bitcoin protocol and will be examined within this project for the purpose of logging and tracking preannounced studies. This is the thesis design for the master project ?Using the Blockchain for Reproducible and Trustworthy Science?. First will be explained what the problem statement and context is and how the project is related to other work. Secondly, the research question and the subquestions will be defined, followed by a research methodology that will be used during the research phase. The last section introduces a planning, i.e. a roadmap, that is developed for the project. Close Ilias Elmzouri 33012 Un-conference Breakout Session 33013 Presentations from breakout sessions 33014 Wrap-up

Territorial Intelligence for Multi-level Equity and Sustainability  (TIME) Session 2

Chair: Celine Rozenblat

 38004 "Perma-circularity" as a systemic framework for autonomizing and linking territories [abstract] Abstract: I will take a critical stance towards the ?Smart? fashion that seems to be sweeping transition thinking these days. As trendy as it is, ?Smart? is very often linked with a techno-fix, eco-modernist vision for the future to which I have trouble subscribing. Our task, no doubt shared by most in the TIMES group, is to arrive at systemic solutions anchored in what was for a long time known as ?appropriate technologies? ? neither high nor low tech, but a smart combination of both, with a foremost objective in mind: to build a world in which humanity as a whole has a permanent ecological footprint of one planet, and to do so under socially and economically equitable circumstances. Given current population trends, this cannot be done within the current high-tech capitalist market system, or with a ?circular economy? still predicated on (green) growth. We need a ?perm-circular? economy that combines re-territorialization, re-localization, and a huge global reduction in material flows together with new, more ?sober" ways of linking territories. I will try to present some useful ideas about how to implement such an economy, drawing inspiration in particular from permaculture, bioregionalism, the ?Municipalist? school of anarchistic democracy, and the ?Territorialist? school of sustainability. Close Christian Arnsperger (University of Lausanne) 38005 Toward an ecological revolution for recycling greenhouse gaz, renewing food production and water use by using biodiversity of ecological systems [abstract] Abstract: Human-driven environmental load accumulated over the centuries is causing irreversible shift to ecosystems and pushing humanity's footprint out of planetary boundaries. These dilemmas of coupled social-ecological systems evoke essential challenge of complex systems science, in terms of multi-scale application to the management of real world. Open complex systems that lies in the nature of this challenge requires the openness and diversity in scientific methodologies, in every aspect of theoretical, empirical, methodological, and institutional organizations. Here I review recent activities on establishing a sustainable farming system with multi-scale synergy with environmental and human health, and outline how open complex systems view could integrate divided disciplines and provide interface for management in a transient process. Important propositions for flagship TIMES could be delivered in order to support transversal initiative of young researchers thinking globally. Close Masatoshi Funabashi (Sony Computer science Laboratory) 38006 Global Systems Science and Dynamical Hyper-networks in turbulent?TIMES [abstract] Abstract: The Global Systems Science (GSS) community is trying to develop new ways for complex systems science to support local and global policy in the context of?new methods in data science and modeling and the great need to engage and include citizens in policy processes [1][2][3]. GSS is perfectly aligned with the TIMES Flagship. ?The four main pillars of GSS are: 1. Policy at all levels, from individuals to the world: policy problems at global and national scales.?How can we know which, if any, proposed policy options will work? 2. The new, interdisciplinary approach: how the science of complex social, economic, political, biological, physical and environmental systems can inform policy makers in their work. 3. Data science and computational modeling for policy makers:?the use of??policy informatics? ? the new, policy-oriented methods of modeling complex systems on computers. 4. Citizen engagement:? the behavior of social systems emerges bottom-up, from the interactions of individuals and institutions, in the context of top-down policy constraints - individual citizens must be involved in decision making and policy formulation. In this context of GSS?the talk will briefly discuss how multilevel dynamic?hyper-networks can be used in TIMES [4].?The TIMES Flagship is an exemplar project of Global System Science. Close Jeff Johnson (The Open University UK) 38007 Reconstruct multi-level territory dynamics with complex networks and self-organizing multi-agent systems [abstract] Abstract: The paper will present one of the first possible applications of TIMES. One of the main characteristics of complexity is the emergence of properties due to dynamical processes. Our objective is to contribute to the formalization of these emergent properties studying dynamical structures. The structures of complexity proposed here, are interaction systems as the core of self-organization mechanisms. Dynamical networks are efficient tools to express some local or global properties of evolving topology. They capture structural aspects of complex systems representing entities as nodes and interactions between them as links. This contribution presents adaptive algorithms for complex networks dynamics, leading to identify emergent organizations in these networks. One of this algorithms, named AntCo2, is bio-inspired by social insect system behavior and lead to detect emergent structures inside complex networks. Some applications are presented relating to urban morphodynamics analysis of the communication networks of the city. Practical study cases are developed (i) to analyze network vulnerability in case of urban technological risk, using multi-scale measures on dynamical complex systems and (ii) to reconstruct the complexity of logistic corridors as interface between port and metropolitan systems. ?The simulations and results detailed in this presentation, are powered by the GraphStream Library which is a java package for dynamic complex networks (http://graphstream-project.org). Close Cyrille Bertelle (University of Le Havre, France) 38008 Personalized Open Education for the Masses, for a?Personalized Open Lifelong Education ecosystem [abstract] Abstract: Open Education is developing at high speed as Massive Open Online Courses. However, education cannot sum up ?to providing online courses. It is necessary to also provide social interaction between students and the tutors in order to create a real educational ecosystem. This is what is sought with POEM, a Personalized Open Education for the Masses ecosystem, that uses complex systems in order to involves students and teachers in lifelong learning. Close Pierre Collet (University of Strasbourg, France) 38009 Smart Cities: Ethical issues investigated from a complex systems perspective [abstract] Abstract: We aim to investigate, from a complex systems perspective, ethical issues related to: (i) privacy; (ii) the unauthorized handling, for commercial purposes, of digital traces left by users in smart houses and cities; (iii) the possibility of using ubiquitous information and data correlations to predict and prevent undesirable human social actions related to security and human rights. Problems (i) ? (iii) will be analysed from an inter/transdisciplinary perspective in order to identify, on the one hand, the privacy and ethical concerns during the stage of collection of ubiquitous information in smart environments, and, on the other hand, the possibility of identifying the ideological features of the selected data, which could be used for surveillance and commercial purposes. An evolutionary perspective of Ethics will be presented, according to which moral habits are emergent properties of social affordances embodied in human social interactions. (Social affordances are ?...dispositional collective properties that indicate possibilities of action provided to organisms by other organisms that share co-evolutionary histories ? (Gibson, 1986, McArthur & Baron, 1983)). Close Maria Eunice Quilici Gonzalez & Mariana Claudia Broens (UNESP, FAPESP, CNPq, Brazil)

EvoEvo (Evolution of Evolution)  (EOE) Session 2

Chair: Guillaume Beslon

 16007 Evolution of Evolvable Systems (invited talk) [abstract] Abstract: I shall survey experimental and theoretical results from an ERC Advanced project with that name (https://www.parmenides-foundation.org/research/projects/evoevo/). I shall focus on three issues: (1) Experimental approach to infrabiological systems, (2) Major transitions theory 2.0 (especially the filial transitions), (3) Learning in evolution versus Evolution in learning. Close Eors Szathmary (Parmenides Center for the Concecptual Foundations of Science, Pullach/Munich, Germany) 16008 In-silico experimental evolution highlights the influence of environmental seasonality on bacterial diversification [abstract] Abstract: http://www.evoevoeu/download/evoevo_workshop_2016/EvoEvo2016_Rocabert.pdf Close Charles Rocabert (INRIA Grenoble-Rhône Alpes, FR) 16009 Evolution of r- and K-selected species of Virtual Microbes: a case study in a simple fluctuating 2-resource environment [abstract] Abstract: http://www.evoevo.eu/download/evoevo_workshop_2016/EvoEvo2016_vanDijk.pdf Close Bram van Dijk (Utrecht University, NL) 16010 Modeling the co-evolutionary dynamics of the Lobaria pulmonaria lichen symbiosis [abstract] Abstract: http://www.evoevo.eu/download/evoevo_workshop_2016/EvoEvo2016_Adams.pdf Close Julia Adams (Wellesley College, US) 16011 EvoMachina: a novel evolutionary algorithm inspired by bacterial genome reorganisation [abstract] Abstract: http://www.evoevo.eu/download/evoevo_workshop_2016/EvoEvo2016_Hoverd.pdf Close Tim Hoverd (University of York and York Centre for Complex Systems Analysis, UK) 16012 Evolution towards extinction in replicase models: inevitable unless… [abstract] Abstract: http://www.evoevo.eu/download/evoevo_workshop_2016/EvoEvo2016_Hickinbotham.pdf Close Simon Hickinbotham (University of York, UK) 16013 Physical interaction with automated music composition platforms [abstract] Abstract: http://www.evoevo.eu/download/evoevo_workshop_2016/EvoEvo2016_Abernot.pdf Close Jonas Abernot (INRIA Grenoble-Rhône Alpes)

Non-stationarity and ergodicity in Economic and Financial Systems  (NCEF) Session 1

Chair: Francesco Caravelli

 47000 When is equilibrium a reasonable assumption? [abstract] Abstract: Abstract: Equilibrium in economics is based on the assumption that agents? actions are consistent with their beliefs, and usually means convergence to a fixed point in the Close Doyne Farmer 47001 Complexity Economics and the Synergy of Game Theory: Higher Order Dependencies for out of Equilibrium Economics [abstract] Abstract: In an article entitled Complexity Economics: A Different Framework for Economic Thought (W.B. Arthur, 2013) Brian Arthur discusses ?Complexity Economics? and the basis of economic theory if neoclassical economics is to be replaced by a non-equilibrium, dynamic and process focused understanding of economics in which neoclassical equilibrium, if it exists at all, is a special case. The importance of finding an alternative approach comes from the difficulties classical economics has in explaining economic processes: historical contingencies, learning, innovations, and the imperfections of human perception and decision-making. In this talk I present some preliminary work on an interpretation of game theory as ?interacting logic gates? for which Nash Equilibrium is only a subset of possible outcomes. This model addresses Arthur?s point regarding the economy as a massively parallel system of concurrent and recurrent behaviour that is ?perpetually 'computing' itself?. The information theoretical measure of synergy is applied to data from a behavioural economics experiment to practically demonstrate how the whole can be different from the sum of the parts in applied economics. Close Mike Harré 47002 Emergence of Cooperative Long-Term Market Loyalty in Double Auction Markets [abstract] Abstract: Loyal buyer-seller relationships can arise by design, e.g. when a seller tailors a product to a specific market niche to accomplish the best possible returns, and buyers respond to the dedicated efforts the seller makes to meet their needs. We ask whether it is possible, instead, for loyalty to arise spontaneously, and in particular as a consequence of repeated interaction and co-adaptation among the agents in a market. We devise a stylized model of double auction markets and adaptive traders that incorporates these features. Traders choose where to trade (which market) and how to trade (to buy or to sell) based on their previous experience. We find that when the typical scale of market returns (or, at fixed scale of returns, the intensity of choice) become higher than some threshold, the preferred state of the system is segregated: both buyers and sellers are segmented into subgroups that are persistently loyal to one market over another. We characterize the segregated state analytically in the limit of large markets: it is stabilized by some agents acting cooperatively to enable trade, and provides higher rewards than its unsegregated counterpart both for individual traders and the population as a whole. Close Aleksandra Aloric, Peter Sollich, Peter McBurney, Tobias Galla 47003 Economics without assuming ergodicity [abstract] Abstract: The mathematics of randomness began in the 1650s, with imagined parallel worlds where all possible events coexist. Economics immediately adopted the new concepts, especially expectation values, as its most basic foundation. The 1700s saw challenges to the nascent economic formalism but found patches, notably utility theory, to keep it alive. In the 1870s the mathematics of randomness took a leap forward with Maxwell and Boltzmann realising that an average across parallel worlds may not be reflective of an average over time. These developments made the earlier patches unnecessary, but by this time the formalism had become too established to adapt. Boltzmann coined the term ergodicity??, and questioned the meaning of expectation values. The following century saw great refinements and mathematical formalisation of the concept of ergodicity. Over the last few decades we have seen much interest in what happens when ergodicity is absent. In my talk I will ask this question in the context of economic thinking. Economics, broadly, is based on the assumption of noisy growth, which is mathematised with non-stationary non-ergodic models, most famously geometric Brownian motion. Close Ole Peters 47004 Optimal growth strategies with carrying capacity [abstract] Abstract: I will discuss the problem of determining optimal portfolios and general strategies, while taking into account their market impact, i.e. the effect of the position taken on the prices of the assets involved. I will examine the case of ordinary (multivariate) Gaussian diffusion and the one of jump diffusions, with a brief analysis of the structure of the general case. The Kelly criterion and other objectivefunctions can then be reexamined in this broader context. Close Lorenzo Sindoni 47005 Far from equilibrium: Wealth reallocation in the United States [abstract] Abstract: Studies of wealth inequality often assume that an observed wealth distribution reflects a system in equilibrium, a constraint rarely tested empirically. In this talk we introduce a simple model that allows equilibrium without assuming it. To geometric Brownian motion we add reallocation: all individuals contribute in proportion to their wealth and receive equal shares of the amount collected. We fit the reallocation rate parameter required for the model to reproduce observed wealth inequality in the United States from 1917 to 2012 and find that this rate was positive until the 1980s, after which it became negative and of increasing magnitude. With negative reallocation or even with the positive reallocation rates observed, equilibration is impossible or too slow to be practically relevant. Therefore, studies which assume equilibrium must be treated skeptically. Currently the system is best described by a negative reallocation rate. Each time we observe it, we see a snapshot of a distribution in the process of diverging. It is much like taking a photo of an explosion in space, whose finite extent tells us nothing of the eventual distance between pieces of debris. Studies that assume equilibrium are incapable of detecting the dramatic conditions one finds without this assumption. Close Yonatan Berman, Ole Peters, Alexander Adamou 47006 Financial Networks [abstract] Abstract: In this talk I will present the basics of the network approach in order to evaluate the resilience of a financial network to shocks and distresses, quantify the probability of contagion in an interbank network, individuate early-warning signals of upcoming financial crises and reconstruct missing interbank linkages (in monopartite, bipartite and multiplex networks). Close Guido Caldarelli 47007 The organization of the interbank network [abstract] Abstract: The properties of the interbank market have been discussed widely in the literature. However a proper model selection between alternative organizations of the network in a small number of blocks, for example bipartite, core-periphery, and modular, has not been performed. In this paper, by inferring a Stochastic Block Model on the e-MID interbank market in the period 2010-2014, we show that in normal conditions the network is organized either as a bipartite structure or as a three community structure, where a group of intermediaries mediates between borrowers and lenders. In exceptional conditions, such as after LTRO, one of the most important unconventional measure by ECB at the beginning of 2012, the most likely structure becomes a random one and only in 2014 the e-MID market went back to a normal bipartite organization. By investigating the strategy of individual banks, we show that the disappearance of many lending banks and the strategy switch of a very small set of banks from borrower to lender is likely at the origin of this structural change. Close Paolo Barucca, Fabrizio Lillo

Social and Economic Change as a Complex Dynamical System  (SEC) Session 2

Chair: Matthieu Cristelli

 2005 Identifying booms and busts in housing prices with heterogeneous expectations [abstract] Abstract: We develop a behavioral model for housing prices with heterogeneous expectations, with fundamental buying prices linked to housing rental levels to fundamental buying prices. Using quarterly data we estimate the model parameters for eight different countries, US, UK, NL, JP, CH, ES, SE and BE. We find that the data support heterogeneity in expectations, with temporary endogenous switching between fundamental mean-reverting and trend-following beliefs based on their relative performance. For all countries we identify temporary, long lasting house price bubbles, amplified by trend extrapolation, and crashes reinforced by mean-reverting expectations. The qualitative predictions of such non-linear models are very different from standard linear benchmarks, with important policy implications. The fundamental price becomes unstable, e.g. when the interest rate is set too low or mortgage tax deductions too high, giving rise to multiple non-fundamental equilibria and/or global instability. We also discuss estimation of similar non-linear switching models to other time series, such as stock? prices, commodity prices, exchange rates and inflation. Close Cars Hommes 2006 A complex systems lens on Dutch energy transition policy [abstract] Abstract: The Netherlands has generally been a laggard in tackling the energy transition, to the extent that a judge Dutch State is acting unlawfully by not contributing its proportional share to preventing a global warming. A 2015?report (in Dutch)?co-authored with the?Netherlands Scientific Council for Government Policy (WRR) argues that a contributing cause to this state of affairs is from policy makers looking at the energy system in too much isolation. The report is a practical case study how taking a complex systems lens to the problem, may open the path to different and innovative approaches to Dutch energy transition policy. Close Roland Kupers 2007 The essential role of time in information filtering [abstract] Abstract: Network-based metrics are commonly applied in a wide range of real-world problems, such as ranking, recommendation, and information spreading. Classical methods inspired by physical processes (like diffusion) often neglect the temporal order of interactions and, as a consequence, turn out to be highly ineffective when applied to systems evolving in time which is particularly worrying as most real systems fall in this category. To devise improved and well founded metrics, it is critical to understand the nature of the shortcomings of classical methods in evolving systems. In this presentation, we focus on the problems of ranking and recommendation in growing complex networks. For both problems, we show that by understanding the temporal patterns of the studied systems and unveiling the consequent lack of performance of classical metrics, we are able to design time-dependent methods that significantly outperform their static counterparts in singling out the most valuable items in the system. In the case of ranking, we use growing network models to show that PageRank centrality metrics systematically exhibit a temporal bias towards old or recent nodes depending on the temporal scales of node aging. We introduce a rescaled score which is built on the PageRank score and at the same time it is not biased by node age. We use real and model data and show that the rescaled score allows us to identify high-quality nodes earlier than with other metrics. In the case of recommendation, we use data from Netflix, Yelp and Digg to show that classical methods tend to favor old nodes and, as a consequence, systematically fail to identify recent items that will be collected by users in the future. We design a new time-aware method built on network growth patterns and show that it markedly outperforms its static counterpart. The findings presented here support the idea that time-aware modifications of existing metrics can lead to improved results in finding the most valuable information in diverse real systems. Close Manuel Mariani 2008 Information Sharing in collective behavior? [abstract] Abstract: In animal collective behavior, interactions between individuals and between an agent and the environment are usually seen to be ?through information?propagation. Cooperations can emerge with or without information sharing.? The information propagation in ants, fish and birds seems to be the?crucial?mechanism that regulates the global behavior of the crowd. This talk will introduce the research related to?information?functioning in collective?groups?and several recent works that demonstrate interesting collective patterns with information sharing playing pivotal roles. Close Zhangan Han 2009 The Short- and Long-Run Damages of Fiscal Austerity: Keynes beyond Schumpeter [abstract] Abstract: In this work we analyze the short- and long-run effects of fiscal austerity policies, employing an agent-based?model populated by heterogeneous, boundedly-rational firms and banks. The model, in line with the family of?"Keynes+Schumpeter" formalism, is able to account for a wide array of macro and micro empirical regularities.?In particular, it endogenously generates self-sustained growth patterns together with persistent economic?fluctuations punctuated by deep downturns. On the policy side, we find that austerity policies considerably?harm the economy, by increasing output volatility, unemployment, and the incidence of crises. In addition, they?depress innovation and the diffusion of new technologies, thus reducing long-run productivity and GDP growth.?Finally, we show that "discipline-guided" fiscal rules are self-defeating, as they do not stabilize public finances,?but, on the contrary, they disrupt them. Close Andrea Roventini 2010 The Scientific Competitiveness of Nations: a network analysis [abstract] Abstract: We use citation data of scientific articles produced by individual nations in different scientific domains to build a bipartite country - scientific domains network to determine the structure and efficiency of national research systems. We characterize the scientific fitness of each nation ?that is, the competitiveness of its research system?and the complexity of each scientific domain by means of a non-linear iterative algorithm able to assess quantitatively the advantage of scientific diversification. We find that technological leading nations, beyond having the largest production of scientific papers and the largest number of citations, do not specialize in a few scientific domains. Rather, they diversify as much as possible their research system. On the other side, less developed nations are competitive only in scientific domains where also many other nations are present. Diversification thus represents the key element that correlates with scientific and technological competitiveness. A remarkable implication of this structure of the scientific competition is that the scientific domains playing the role of ?markers? of national scientific competitiveness are those not necessarily of high technological requirements, but rather addressing the most ??sophisticated?? needs of the society. We complement this analysis with a correlation study between the scientific impact of a nation with a normalized measure of RD funds and the level of internationalization. Close Andrea Gabrielli 2011 How to measure, manage and eliminate systemic risk in the financial system [abstract] Abstract: Systemic risk in financial markets arises largely through the interconnectedness of agents through financial contracts. We show that the systemic risk level of every agent in the system can be quantified by simple network measures. With actual central bank data for Austria and Mexico we are able to compute the expected systemic losses of the economy, a number that allows us to estimate the true cost of a financial crises. We can further show with real data that it is possible to compute the systemic risk contribution of every single financial transaction to the financial system. Based on these findings, we suggest a smart financial transaction tax that taxes the systemic risk contribution of individual transactions. This tax provides an incentive for market participants to trade financial assets in a way that effectively restructures financial networks so that contagion events become impossible.?It is possible to show the existence of a systemically risk-free equilibrium under this smart tax. More intuitively, with the help of an agent based model we can demonstrate that the Systemic Risk Tax practically eliminates the network-driven systemic risk in a system. Close Stephan Thurner 2012 Dynamics of rapid innovation [abstract] Abstract: We introduce a model of innovation in which products are composed of distinct components and new components are adopted one at a time. We show that the number of products we can make now gives a distorted view of the number we can make in the future: simple products get over-represented, and complex products under- represented. By applying this at the component level, we derive a strategy for making far-sighted innovation choices that increase the rate of innovation. We apply our strategy to real data from three different sectors?language, gastronomy and mobile technology.? Close Thomas Fink

Hot Topics in the Study of Complex Systems in Asia  (HTCS) Session 1

Chair: Siew Ann CHEONG

 29000 Modeling the activity of the entire primate brain: A meso-scale dynamical perspective [abstract] Abstract: Nonlinear dynamics of interactions between clusters of neurons via complex networks lie at the base of all brain activity. How such communication between brain regions gives rise to the rich behavioral repertoire of the organism has been a long-standing question. In this talk, we will explore this question by looking at the simulations of collective dynamics of a detailed network of cortical areas in the Macaque brain recently compiled from the CoCoMac database, as well as, a model of global coupled brain regions used as a benchamrk. To understand the large-scale dynamics of the brain, we simulate it at the mesoscopic level with each node representing a local region of cortex, comprising between 10^3-10^6 neurons. The dynamical behavior of each such region has been described using a phenomenological model consisting of a pool of excitatory neurons coupled to a pool of inhibitory neurons, which exhibits oscillations over a large range of parameter values. Coupling these regions according to the Macaque cortical network produces activation patterns strikingly similar to those observed in recordings from the brain. Our results help to connect recent experimental findings of the olfactory system and suggest that a part of the complicated activity patterns seen in the brain may be explained even without a full knowledge of its wiring diagram. Close Sitabhra Sinha (Institute of Mathematical Sciences, INDIA) 29001 A Generalized Betweenness for Studying Network Performance against Perturbations [abstract] Abstract: Betweenness is an important network property to study system performance against perturbations (such as random natural disasters and intended terrorism attacks). Traditionally, betweenness of a node/link is defined as how many times the node/link appears as intermediate node/link in all shortest paths between nodes. Traditional betweenness can help to answer how likely the 1st best paths between nodes will be cut off by perturbations. However, in reality, it is more concerned with a general situation, i.e., how likely those paths whose lengths are within a given range will be affected by perturbations. For instance, for a researcher to attend a conference, whether the 1st best path is available is not important at all, and instead, whether s/he can arrive on time is the key. Unfortunately, this general situation has barely been discussed in literature. To assess network performance in the general situation, we propose a generalized betweenness which is mathematically defined as how many times a node/link appears as intermediate node/link in all those paths whose lengths are within a given range. No existing method can effectively calculate the generalized betweenness, because it is difficult to find out, between every pair of nodes in a network, all those paths whose lengths are within a given range. By modifying a newly reported nature-inspired method, i.e., ripple-spreading algorithm (RSA), it becomes possible to calculate the generalized betweenness. Surprisingly, the proposed RSA can effectively find out all those paths whose lengths are within a given range by just a single run of ripple relay race. This work makes progress towards the general performance assessment of a network system against perturbations. Close Xiaobing Hu (Beijing Normal University, CHINA) 29002 Understanding the organization of cities from route analysis [abstract] Abstract: Urban street structure is a snapshot of the human mobility and an important medium facilitating the human interaction. Previous studies have analyzed the topology and morphology of street structure in various ways; fractal patterns, complex spatial network and so on. In practical term, it is also important to discuss how street networks are used by people. There are studies analyzing the efficiency, accessibility and road usage in the street networks too. In those studies, people usually investigate routes, either empirical routes or theoretical routes, to understand the functionality of the network. The travel route is a good proxy to understand the street structure and city attributes from user perspective. It is a selected path from the whole network by people or under the given standard, so it reveals how people use the networks. The selected route is also influenced by various factors such as spatial pattern and travel demand of city. Thus studying the empirical or theoretical optimal routes can help us understand the urban characteristics which are often hidden. For instance, fastest routes show the distribution of traffic in a city as well as the street structure. In this paper, we analyze the geometric property of routes to understand the geometry of practical street network where hierarchy and traffic is included. We use the two types of optimal routes collected from time minimizing algorithm and distance minimizing algorithm via the OpenStreetMap API. We suggest a new metric, center-philic level, to measure how much a route is bent toward the city center. We measured the center-philic level of a number of route within 30km radius from the center. By analyzing the center-philic level for different location of routes, we can understand and simplify the geometry of street network based on the center. The center-philic level patterns for two different algorithms can also reveal the effect of street hierarchy and traffic. In urban transportation, we can imagine two forces competing each other. By the agglomeration of business and people inside of city, street networks become denser around the center area to satisfy the demand. Such centralized street networks attract traffic toward inside of city. However many cities have arterial roads located outside of city to disperses the traffic concentrated on the inside of city. The arterial roads act as another force pulling traffic toward outside of the city. This tendency is well captured by our suggested metric. We firstly compare the general average center-philic level of both shortest and fastest routes to point out the fundamental difference between them. Later we analyze the center-philic level of individual cities and discuss how the metric can explain the street layout and street hierarchy. Close Minjin Lee (Sungkyunkwan University, KOREA), Hugo Serrano Barbosa (University of Rochester, USA), Gourab Ghoshal (University of Rochester, USA), Petter Holme (Sungkyunkwan University, KOREA) 29003 Integration of Network Analysis into Power-grid Analysis: sustainability and stability [abstract] Abstract: Network analysis has become a powerful tool to analyze complex systems over wide range of topics. For last two decades, researchers have made much progress particularly in the topics of disease spreading, social interaction, biological metabolism, neural network, urban mobility, etc. However, energy system has yet been plentifully covered. In this talk, we seek to apply network theory into electric power systems. Firstly, we integrate network analysis into environmental impact analysis. We introduce energy distance in order to estimate the greenhouse gas emissions of electricity transmission taking both the amount of electricity consumption and transmission distance into account. Secondly, we analyze the functional stability of power grids. The stable synchronization of power-grid nodes is the essential condition for the secure electric power systems. We investigate the transition of the synchronization stability of power-grid nodes and classify nodes based on the transition patterns. We conclude that network analysis is a good complement for energy system analysis. Close Heetae Kim (Sungkyunkwan University, KOREA), Sang Hoon Lee (KAIST, KOREA), Petter Holme (Sungkyunkwan University, KOREA) 29004 A new scientific collaboration network model [abstract] Abstract: Scientific collaboration plays an important role in the knowledge production and scientific development. The researchers have constructed several network models of scientific collaboration. In traditional collaboration network, two scientists are linked if they have coauthored one paper. However, this construction of network undervalues the role of the first author. In this paper, we propose a new collaboration network model considering the importance of the partnership between the first author and others. We make an empirical analysis based on the data of American Physical Society (APS). The?results?show?that?there?are??some? differences?of properties?between?the?new?network?and?the?traditional?one. And the node importance is studied on the new network to identify potential researchers. Close Ying Fan, Zhangang Han (Beijing Normal University, CHINA) 29005 Fusion of nations, fusion of disciplines: network evolution in nuclear fusion research [abstract] Abstract: Nuclear fusion research, which originated from atomic weapon developments by USA and USSR, attracts public attention as a promising energy source for the future. After the Cold War, Nations have collaborated in order to build research capacity in nuclear fusion. ITER (International Thermonuclear Experimental Reactor) is an example of big science' projects at the international level. Scientists from different disciplines involve in the project. The goal of our study is to investigate collaboration structure of nuclear fusion research and its evolution through an open access bibliometric database, Microsoft Academic Graph (MAG). We examine not only scientific journal citations but also the impact of IAEA Fusion Energy Conference on the research field. Dynamics of co-authorship networks reveal how nations take part and collaborate in nuclear fusion research. We expect that this study would be helpful for managing research activities and for suggesting national S&T policies. Close Hyunuk Kim, Inho Hong, and Woo-Sung Jung (POSTECH, KOREA) 29006 The robustness of spatially embedded and coupled infrastructure networks under localized attacks [abstract] Abstract: In the real world, infrastructure networks such as communication networks, power grid networks, transportation networks, solidly underlie the development of the whole society. The structure of infrastructure networks become more and more complicate and always couple together to perform intact service capacity. There commonly exist dependency among components as well as sub-networks, which make failure propagation. Currently, numerous literatures focused on the vulnerability and robustness of classical complex networks (e.g. random network, regular network, small-world network and scale-free network) under malicious attacks or random attacks. As one kind of real-world networks, besides having the topological characteristic of classical complex network, infrastructure networks are restricted by social-economic and geographical factors, so that they have short length links and some of them are planar graphs. Infrastructure network distributes in a specific spatially geographical domain, which probably exposures to real-world localized attacks (such as natural disasters). Recently, investigation on spatially embedded infrastructure networks under localized attacks is getting more and more attention. But full consideration of spatial characteristic of nodes and links in the robustness investigation of infrastructure network is still a big challenge due to involving real-world factors. In this paper, we aim to study the robustness of spatially embedded and coupled infrastructure networks under localized attacks. We first generate different kinds of spatially embedded infrastructure networks. Then a density-based index is proposed to depict the spatial characteristic of infrastructure network, dependency links among sub-networks are placed according to geographical restriction. Localized attacks are described by the circles with different radius. Finally, numerical simulation is conducted and the result illustrates that the spatial characteristic of infrastructure network and location of dependency links have significant effect on the robustness of infrastructure network under localized attack. Close Saini Yang, Fuyu Hu, Weiping Wang (Beijing Normal University, CHINA) 29007 Exploring the Collective Mobility Pattern of Intra-Urban Taxi Passengers [abstract] Abstract: The study of human mobility patterns is of both theoretical and practical values in many aspects. For long-distance travels, a few research endeavors have shown that the displacements of human travels follow the power-law distribution. However, the intra-urban travels do not simply follow the same power-law of longer-distance travels. What?s more, controversies remain in the issue of the scaling law of human mobility in intra-urban areas. In this work we focus on the mobility pattern of taxi passengers by examining five datasets of the three metropolitans of New York, Dalian and Nanjing. Through statistical analysis, we find the mixed distribution of lognormal and power-law better explain both the displacement and the duration time of taxi trips, as well as the vacant time of taxicabs, in all the examined cities. The universality of scaling law of human mobility is subsequently discussed, in accordance with the data analytics. Close Ling Zhang (Dalian University of Technology, CHINA), Shuangling Luo (Dalian Maritime University, CHINA), Haoxiang Xia (Dalian University of Technology, CHINA) 29008 The Effects of Correlation between Influential Level and Threshold in Opinion Dynamics [abstract] Abstract: We live in a society, where people interact with each other. An individual's opinion is formed with a neighbor's opinion. How do people accept a different opinion? Threshold model is the most well-known and proved theoretical model for the question. The model assumes that a person receives a different opinion when the ratio of their neighbor, whose opinion is different with one's opinion, is higher than one's threshold for an acceptance. Much research has been conducted on the opinion dynamics in the society with 'threshold model', and diverse aspects of key features in opinion dynamics have been revealed by the model. Most of the researches related with the threshold model in opinion dynamics are placed in the homogeneous threshold assumption. It means every person has the same level of threshold for an acceptance of an opinion. The usefulness of this assumption is clear in terms of statistical analysis. Howeve, we all know that heterogenuity of threshold exists. Even the threshold has a relationship with social capital like the number of neighbors, which can be represented as the characteristic of a network structure. Surprisingly, investigation on the correlation between network structure and threshold has not been conducted well. In this study, we investigate the influence of the correlation between the number of neighbors (influential level) and individual threshold on opinion dynamics. Given the scale-free network, as the representative network model of society, we change a level of correlation ($\beta$) from negative (-1) to positive (+1): 'negative' ('positive') is for the case that small (large) degree node has high threshold. The minimum of a threshold is set to 0.5 since we assume that people change their opinion when there are people more than a half of their neighbor generally. Additionally, opinion is composed with 0 and 1, and 60% of people in the network has opinion 1 as an initial condition. In this setting, we conduct the opinion dynamics while changing the correlation with degree and threshold. We found that the importance of the correlation betwen degree and threshold as to opinion dynamics. In this result, negative correlation region spreads information to entire system, but the positive correlation has a finite steady state. Additionally, there is a transition point around 0.5 regarding to correlation level. So far, we are conducting a finite size scaling analysis to figure out the characteristic of the transition, however, we were able to deduce from this result, there could be a transition of the system. To see the specific origin of this asymmetric contagion, we measured fixation time and final opinion. Fixation time is the time the node is fixed its final opinion. Moreover, the tendency of fixation time changes in positive correlation around the critical point, which is close to 0.5. This point is very close with the transition point for opinion switching. It means there is a balanced dependency between influential level and threshold so that from the point, the system can be divided with two different regimes: one is the regime for threshold dominant effect, the other is for the confused information effect. Another interesting result is: low influential nodes start to fluctuate more with high degree of dependency. Even though they have low threshold with positive correlation, they still receive a lot of influences from high degree nodes so they confused with mixed information from high degree nodes. This result suggests that the correlation between network structure and threshold of an acceptance can be important for opinion formation. Since we often experience the effect of correlation between influential level and threshold, it is worth to stress out the meaning of result. We can interpret the result as follows: positive correlation with influential level and conservative characteristic can block the unification of opinion in less influential group so that the majority opinion could not reach the whole society. Close Eun Lee, Peter Holme (Sungkyunkwan University, KOREA) 29009 Inferring the model of ants movements and aggregation in circular region [abstract] Abstract: Inferring the model of animal movements and aggregation have been a long-term challenging task. Although numerous of realistic-looking models have been proposed, model-based methods often rely on untested assumptions. Besides, many sets of microscopic hypotheses can produce the same macroscopic behaviors, it is dubious that they uncovered the real inherent mechanism. In this work, we conducted experiments with ants in two-dimensional circular surface. We try to infer behavioral rules directly from experimental data instead of traditional model-based research strategy. By defining a new metric to measure the ants aggregation extent, we study the influence of edge ?wall? and other individual on ants aggregation. Instead of studying large groups from 50 to 150, we study small number of ants from 1 to 3. By analyzing and comparing the data, we proposed a simple yet effective model, which may help to account for the micro-foundation of ants aggregation and infer how they amplify aggregation extent in large groups. Close Yikun Xu, Zhangang Han (Beijing Normal University, CHINA) 29010 Multiple individuals tracking algorithm for fish in 2D space [abstract] Abstract: As the increasing interest in the investigation of collective motion of a group of animals, it is important to tracking multiple moving animals and acquiring their position over time and space. There are several studies that have tried to solve this problem and make this data acquisition automated. However, none of these studies has solved the problem very well and automatically tracking is very difficult thanks to the individual?s various shape, complex motion and frequent occlusion. There are several published algorithms working on this problem, usually aim at one special specie, zebra fish, for instance. However, these algorithms have very high demands on the video quality, such as high frame rates, high image resolution and steady background, some of them are very time-consuming. Here we have developed an integrated approach based on artificial neural networks that enables us to automatically extract individuals? trajectories from both high quality and low quality videos. First we combine a background subtraction method and artificial neural networks to effectively detect the individuals. Then we use a linear assignment model to track the individuals. At last, we build a function to measure the confidence coefficient for each frame to help correct the possible errors. We applied our method to track different fish videos, the results showed that our method has a high efficiency and accuracy in most situations. Close Qi Zhang, Li Jiang, Zhangang Han (Beijing Normal University, CHINA) 29011 A new measure based on information theory to quantify the co-ordination of fish groups [abstract] Abstract: Collective motion of fish is an interesting research field. There is an essential question that how to quantify the how collective a group is, namely, how to recognize that fish in the group are interacting. Generally, researchers quantify the strength of interaction between fish intuitively using the correlation of velocities or spins, and measure the whole group?s polarization and rotation, etc. to determine whether it?s synergetic. It is because researchers consider the animal group motions as multi-body physical phenomena. However, it poses a problem that if an animal group does not display a visible collective structure, these physical statistics will fail to recognize the underlying mechanism. We introduce a new measure based on differential mutual information from information theory to quantify the co-ordination. Information theory is used in many fields but rarely in the field of collective animal motion. The original mutual information is a value to measure the correspondence of two signals, if there is any correspondence between these two agents? moving, mutual information will reveal it, while old statistics like polarization fail if the relationship is strange. The new statistic will be compared with classical statistics like polarization and correlation on Couzin model and Vicsek model. We will try different parameters to analyze the properties of all these statistics. And we will show that the new statistic is more efficient than old statistics when the model displays confusion and has even efficiency when the model displays order. We record the trajectories of different amounts of Glass Goldfishes swimming in a tank with a radius of 40 centimeters. The new statistic is used to measure the co-ordination of the groups. We will show that the co-ordination grows while the fish amount grows. In short, we will illustrate that the new measure can be helpful to reveal the strength of the co-ordination in a group. Close Yinong Zhao, Zhangang Han (Beijing Normal University, CHINA)

Estimation of probability density functions in noisy complex ows  (EPD) Session 1

Chair: Fred Wubs

 3000 Estimation of Markov processes using operator eigenpairs [abstract] Abstract: Modeling the effective macroscopic dynamics of complex systems as noise-driven motion in a potential landscape has found its use for topics ranging from protein folding to the thermohaline ocean circulation. I will discuss the estimation of such models from timeseries, focussing on a methodology that makes use of the spectral properties (leading eigenpairs) of the Fokker-Planck operator associated with the diffusion process. This methodology is well suited to infer stochastic differential equations that give effective, coarse-grained descriptions of multiscale systems. I will discuss estimation of coordinate-dependent diffusion, subsampling, nonconstant sampling intervals and inference from non-equilibrium data. Close Daan Crommelin 3001 Mixing in Noisy Nonlinear Oscillators: Application to Low-Frequency Climate Variability [abstract] Abstract: Much can be learned about systems exhibiting complex dynamics by studying the evolution of probability densities rather than single trajectories. In the stochastic case, this evolution is governed by the transfer semigroup which allows to connect the correlation functions and power spectra to the Fokker-Planck equation. Here, we propose to approximate the transfer operators of high-dimensional systems by Markov operators on a reduced space. While these Markov operators do not in general constitute a semigroup, rigorous results can be obtained regarding their spectral properties, in particular allowing to reconstruct correlation functions and quantify mixing in the reduced space. The approach is applied to the study of the variability and the stability stochastic nonlinear oscillators exhibiting resonant behavior. New analytical and numerical results are found for the mixing spectrum of the Hopf bifurcation with additive noise, bringing new insights on the phenomena of noise-induced oscillations and phase diffusion. These results allow to give new interpretations on the stochastic dynamics of high-dimensional climate models and support the applicability of the method to the study of stochastic bifurcations. Close Alexis Tantet 3002 Deterministic Methods for Stochastically Forced PDEs [abstract] Abstract: In this talk I shall illustrate an approach to study the dynamics of stochastic PDEs (or more generally stochastic dynamical systems) with respect to parameters using deterministic continuation methods. In particular, I shall focus on the case of local fluctuations for the stochastic Allen-Cahn equation and explain the practical implementation as well as applications in various scientific disciplines. Close Christian Kuehn 3003 On the numerical solution of large-scale linear matrix equations [abstract] Abstract: Linear matrix equations such as the Lyapunov and Sylvester equations play an important role in the analysis of dynamical systems, in control theory, in eigenvalue computation, and in other scientific and engineering application problems. A variety of robust numerical methods exists for the solution of small dimensional linear equations, whereas the large scale case still provides a great challenge. In this talk we review several available methods, from classical ADI to recently developed projection methods making use of `second generation'' Krylov subspaces. All methods reply on the possible low-rank form of the given data. Both algebraic and computational aspects will be considered. Close Valeria Simoncini 3004 Studying critical transitions in stochastic ocean-climate models by solving Lyapunov equations [abstract] Abstract: Techniques from numerical bifurcation analysis are very useful when studying transitions between steady states of flows and the instabilities that are involved. In this presentation we discuss how we use parameter continuation in determining probability density functions of flows governed by stochastic partial differential equations near fixed points under small noise perturbations. We first discuss the traditional way of doing this by stochastically forced time forward simulation, and then show how this can also be done by solving generalized Lyapunov equations using a novel iterative method involving low-rank approximations. One of the advantages of this method is that preconditioning techniques that are known from iterative methods for linear systems can be used. We illustrate the capabilities of the method on a phenomenon in physical oceanography: the occurrence of multiple equilibria in the Atlantic Meridional Ocean Circulation. Close Sven Baars and Fred Wubs

Robustness, Adaptability and Critical Transitions in Living Systems  (RACT) Session 1

Chair: Samir Suweis

 11000 Introduction (5 min) 11001 TBA (35 min) [abstract] Abstract: TBA Close Elisa Benincà 11002 Predicting collapsing network entities before the tipping point (15 min) [abstract] Abstract: Considerable evidence suggests that there are generic signals that indicate whether a system is approaching a tipping point to a new state. These indicators, such as an increased auto- and cross-correlation, increased variance and increased skewness, can be derived from time series analysis of the systems state before the tipping point. An important question that is not addressed by these indicators is what the system will look like after it passed its tipping point. In this study, we propose a new method using principal component analysis, to predict the future ?post-tipping point? state of the system. We formulate a method that works on systems in which the new system state is separated from the current system state by an unstable equilibrium. This is a situation that can be observed in various ecological systems. We derived the method analytically and illustrated it with an example based on data generated using an ODE-model. For our model, the method correctly predicts which variables increase and decrease in value after the shift. We could show that it was robust for some difficult cases, such as differences in noise between variables and having variables in the system that are not part of the shift. We believe that this method is generally useful for a variety of complex systems that contain such a tipping point and is especially valuable if the knowledge of the future state can help deciding on prevention measures. Close Els Weinans, Ingrid van de Leemput, Jelle Lever and Rick Quax 11003 Environmental change influences ecological network structure on a global scale (15 min) [abstract] Abstract: Theoretical studies have indicated that nestedness of environmental perturbations, affect the nestedness and modularity of ecological networks. However, the effects of climate change and human activities on ecological networks are poorly understood. Here, we constructed a large dataset of ecological networks, including food-web, pollinator, and seed-dispersal networks, and used a spatial analysis approach to examine the effects of climate change and human activities on the structural patterns of food webs and mutualistic networks [1]. We found that ecological network structure is globally affected by climate change and human impacts, in addition to current climate. In pollination networks, for instance, nestedness increased and modularity decreased in response to increased human impacts. Modularity in seed-dispersal networks decreased with temperature change (i.e., warming), whereas food web nestedness increased and modularity declined in response to global warming. According to a theory, these results are an indication that mutualistic networks form in such a way as to enhance ecosystem stability against environmental changes or perturbations. Unlike in mutualistic networks, however, our results suggest that food-web stability decreases in response to environmental changes. Our findings enhance our understanding of the effects of environmental change on ecological communities.[1] Takemoto K, Kajihara K (2016) Human Impacts and Climate Change Influence Nestedness and Modularity in Food-Web and Mutualistic Networks. PLoS ONE 11(6): e0157929. doi:10.1371/journal.pone.0157929 Close Kazuhiro Takemoto 11004 A method for calculating an approximate analytical solution of a stochastic ecological model in space (5 min) [abstract] Abstract: As is observed very often in physics, the wide variety of natural phenomena at very large or very small scales follows some simple rules that can be understood and described via formulas and a rigorous mathematical formulation.In the last 60 years ecologists have been collecting census data from a wide variety of different ecosystems, and despite the striking diversity of shapes and forms, they highlighted how deep commonalities emerge over wide scales of space.Our research focuses on the spatial distribution of plant species in an environment, and involves analytical calculations of global patterns that can be measured. Its aim is to derive from a single theory a set of predictions, and possibly anticipate new and unexpected empirical discoveries (e.g. stochastic pattern formation, quasi-cycles,...).In this talk I will give a brief overview of an approach based on a Stochastic partial differential equation. We calculated an approximate analytical solution, and, comparing it to simulated data, we checked whether it is a good estimate of the true solution. We also showed how this approach can be used to tackle real ecological problems involving species distribution and biodiversity preservation. Close Fabio Peruzzo and Sandro Azaele 11005 TBA (35 min) [abstract] Abstract: TBA Close Sander Tans 11006 Investigating the collective behaviour of neurons in the brain: what can we do and what we cannot do (35 min) [abstract] Abstract: The brain has been shaped by evolution as a sophisticated information processing system capable to adapt behavioural outputs to the ever-changing ?real world? inputs in an efficient and robust manner. A key ingredient for such degree of adaptability and robustness is the peculiar brain organization, with neurons that are structurally and functionally connected through adaptive synapses to form a complex evolving architecture. The emergence of criticality in brain circuits has been proposed as an important signature of brain computation. However, assessing critical behaviour of neuronal circuits is posing severe experimental challenges. We will present most advanced neurotechnologies enabling the measurement of neuronal networks and brain circuits and discuss their advantages and limitations to investigate the emergence of patterns resulting from collective activity of neuronal populations.? Close Stefano Vassanelli 11007 Robustness of tissue structure to perturbations in mechanical forces (15 min) [abstract] Abstract: In order to study the robustness of tissue architecture to variation in the forces that contribute to tissue shape, we rely on the 2D cell-based numerical model of epithelium formation by Farhadifar and collaborators (1), but dynamics and boundary conditions where modified, as explained in Merzouki et al (2). We aim to understand whether perturbations in mechanical properties of cells will affect the size and regularity of tissues. For example, does variation among cells in the two key parameters normalized cell contractility (?) and membrane line tension (?) affect tissue architecture? This architecture can be quantified by the distribution of shapes and areas of cells.To find out, we allow these values to vary among cells during tissue growth. Specifically, we assign values drawn from a bivariate normal distribution with a given mean (?,?) and standard deviation (?(?),?(?)) to these parameters for every newly created cell in a growing tissue. In the absence of perturbations, different values of ? and ? lead to tissue structures that fall into a small number of classes. The most prominent distinction is that between stable tissue, where most cells have a preferred shape (e.g., hexagonal), and where deviations from the preferred shape distribution lead to unfavorable energy, and an unstable tissue, where deviations from a preferred shape do not have a strong energy cost. Our preliminary observations show that within these parameter regimes, tissues react very differently to perturbations. Below we show exemplary observations for two pairs of mean values of ? and ?. In the first (?=0.04 and ?=0), cells in the tissue adopt a stable hexagonal shape in the absence of perturbations. For the other pair (?=0.12 and ?=?0.8), the tissue is unstable and cells adopt a greater variety of shapes. We vary the extent of perturbation by varying the standard deviation (?(?),?(?)) 0.05 and 0.1, and also perform control simulations without perturbations, in which the standard deviation is zero.Surprisingly, we find that the distribution of cell shapes in unstable tissues is more robust to perturbation than that of stable tissues. In addition, the perturbations affect stable and unstable tissues differently in systematic ways. Specifically, perturbation of a stable tissue creates fewer 6-sided cells and more 4- and 7-sided cells when compared with the control. We define the mean shape of cells as the average number of edges among all the cells of the tissue, and observe that this mean shape is systematically reduced in response to perturbations. In contrast, for unstable tissues, perturbations cause fewer 4-sided, 6-sided and 8-sided cells, but more 5-sided and 7-sided cells. Overall, however, these changes compensate for one another, such that the mean shape of cells does not change greatly.Currently, we are studying possible explanations for this pattern, which suggests that the soft energy constraints of unstable tissues may convey an advantage in allowing cells to conserve their shape distribution to a greater extent. We are also studying potential molecular factors that could explain this pattern. In our next steps, we will explore the robustness of other phenotypes, such as cell area and cell regularity.References1 - Reza Farhadifar, Jens Christian R?per, Benoit Aigouy, Suzanne Eaton, and Frank J?licher. The influence of cell mechanics, cell-cell interactions, and proliferation on epithelial packing. Current biology: CB, 17 (24): 2095?104, (2007).2 - Aziza Merzouki, Orestis Malaspinas and Bastien Chopard. The properties of a cell-based numerical model of epithelium under stretching constraints. Soft Matter, in press, (2016). Close Charles De Santana, Aziza Merzouki, Orestis Malaspinas, Bastien Chopard and Andreas Wagner 11008 Closure (5 min)

Dynamics on and of Complex Networks IX / Mining and learning for complex networks  (DOAO) Session 2

Chair: Jean-Charles Delvenne

 43006 Discrimination in Human vs. Algorithmic Decision Making [abstract] Abstract: Algorithmic (data-driven) decision making is increasingly being used toassist or replace human decision making in a variety of domains rangingfrom banking (rating user credit) and recruiting (ranking applicants) tojudiciary (profiling criminals) and journalism (recommendingnews-stories). Against this background, in this talk, I will pose andattempt to answer the following high-level questions: (a) Can algorithmic decision making be discriminatory?(b) Can we detect discrimination in decision making?(c) Can we control algorithmic discrimination? i.e., can we make algorithmic decision more fair? Close Krishna P. Gummadi 43007 Understanding fashion as a complex network [abstract] Abstract: Fashion is a very fast moving business addressing many different target groups (style, age, occasion, status, ?). Hence, it is hard to predict what will be fashionable in the future. Originally, how these markets evolved was largely dictated by a relatively small set of players, such as designers, brands or celebrities. Nowadays, social media is to some extend changing the rules of play. Bloggers and other participants in social media are increasingly playing an important role in defining and spreading fashion trends. Zalando wants to take active part in this development. Some of our goals are to discover new influencers in the fashion world, match influencers to specific brands or advertising campaigns and to discover and to monitor emerging trends present in social media. To do this, we have to construct a large network of entities (such as bloggers, brands, magazines) to be able to analyze the dynamic behavior of the fashion world and answer the questions mentioned above. For this talk, we studied a very popular fashion platform with around 1M subscribers and 22M connections. We will address questions such as which geographical regions of the world are most active or if people tend to follow influential users from their same country or region. In addition, we will analyze if some of the standard properties of complex networks apply in our example, such as small world, scale free, etc. Close Julien Siebert 43008 Phase Transitions in the Growth of Spatial Networks? [abstract] Abstract: Spatially embedded complex networks, such as nervous systems, the Internet, and transportation networks, generally have nontrivial topological patterns of connections combined with nearly minimal wiring costs. We report here the empirical analysis of two databases describing respectively: 200 years of evolution of the road network in a large area located north of Milan (Italy), and the growth of the nervous system of the C. elegans from the moment of fertilization to adulthood. We discuss the basic mechanisms that drive the evolution of such two spatial networks. Close Vito Latora 43009 Stream Graphs and Link Streams for the Modeling of Interactions Over Time [abstract] Abstract: The structure and dynamics of interactions is crucial for many phenomena of interest, like contacts between individuals, data transfers, commercial exchanges, mobility, and many others. Analyzing such interactions classicaly relies on network analysis, which captures the structure of interactions, or on temporal series, which captures their dynamics. Both approaches have been extended in various ways to cope with the both structural and temporal nature of interactions, but current situation remains unsatisfactory. I will present here the modeling of interactions over time by stream graphs and link streams, which aims at unifying both aspects into a simple, efficient and intuitive way. It provides a language to deal with interactions over time, in a waysimilar to the language provided by network science for relations. Close Matthieu Latapy 43010 Syntactic Complexity of Web Search Queries through the Lenses of Language Models, Networks and Users [abstract] Abstract: Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication.Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication. Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication. Close Rishiraj Saha Roy

mathematical pharmacology  (MP) Session 2

Chair: Vivi Rottschafer

 24003 How do protein- and lipid-binding impact efficacy of drugs? [abstract] Abstract: When a drug enters the blood stream, on its way to a pharmaceutical target, it finds many proteins and lipids on its way which are eager to bind it and thus prevent it from reaching its destination. Whilst this may first adversely affect the beneficial effect of the drug, the drug bound to the proteins is not lost and may eventually still reach its target. We discuss a class of models proposed to study the impact of proteins and lipids on the efficacy of drugs, and show that affinity plays a key role in answering the question in the title. Close Bert Peletier 24004 Explaining unexpected multi-stationarity in a nonlinear model of prolactin response to antipsychotic medication [abstract] Abstract: Complexity of biological systems arises in part due to the nonlinearity of these systems. Mathematical models in biology and pharmacology often include this nonlinearity in the form of feedback mechanisms. Nonlinear models can hide interesting dynamic behaviours and as such warrant careful study. A case in point is a nonlinear model of prolactin (PRL) response to antipsychotic medication, which includes a positive feedback. Increased secretion of PRL is a side-effect of antipsychotic drugs. For repeated drug challenges, the intensity of the PRL response to the second drug challenge is lower than to the first challenge, if the duration between the two drug challenges is short. This implies that the intensity of the PRL response may be limited by a pool of PRL in a precursor compartment. The pharmacodynamics of PRL concentration in plasma has been modelled by means of a precursor-pool model which includes a positive feedback loop of plasma PRL on its own synthesis in the pool, making it a nonlinear system [1]. Even though the nonlinear model fits kinetic data from a small temporal window well, it results in unexplained multi-stationarity. We have used mathematical analysis to gain insight into this unexplained model behavior. We have shown that the nonlinearity has resulted in multiple steady states with different stability properties. Stability of each steady state, coupled with the pharmacokinetics of the drug, plays a role in determining which steady state is predicted by the model. We have been able to deduce a parametric restriction under which the desired steady state is stable [2]. The work highlights the importance of mathematical analysis in systems-pharmacological models.References:[1] Stevens J, Ploeger B, Hammarlund-Udenaes M, Osswald G, van der Graaf PH, Danhof M and de Lange ECM, Mechanism-based PKPD model for the prolactin biological system response following an acute dopamine inhibition challenge: quantitative extrapolation to humans. Journal of Pharmacokinetics and Pharmacodynamics. 2012;39(5):463-477.[2] Bakshi S, de Lange ECM, vd Graaf Piet H, Danhof M and Peletier LA, Understanding the behaviour of systems pharmacology models using mathematical analysis of differential equations - prolactin modelling as a case study. CPT: Pharmacometrics and Systems Pharmacology, 2016. Close Suruchi Bakshi, Elizabeth C. de Lange, Piet H. van der Graaf, Meindert Danhof, Lambertus A. Peletier. 24005 Retrospective Drug Testing: Can the Skin Provide a Record of Drug Taking History? [abstract] Abstract: Worldwide, noncompliance to drug regimens poses a significant challenge to effective treatment strategies. The WHO estimate that only 50% of patients living with chronic illness in developed countries adhere to prescribed treatment. In order to tackle this issue, an effective method of monitoring compliance is necessary.In this talk we consider reverse iontophoresis as a drug monitoring technique. This involves placing two electrodes on the skin and passing a small current between them, encouraging the movement of ions from the plasma to the skin surface where it is collected. It has been shown that prolonged systemic presence of a drug can result in a build-up of that drug in the skin which affects the reverse iontophoresis reading. We seek to determine, of the drug collected, how much has come from the skin and how much from the plasma.Our aim is to interpret reverse iontophoresis readings with particular interest in inferring the recent drug taking history of the patient. In order to do this a three model system is created: the first model predicts the systemic levels of the drug post administration, the second model describes the reservoir formation in the stratum corneum via a combination of diffusion and advection with cell movement and the third model, which is the focus of this talk, models the extraction of the reservoir via reverse iontophoresisOur extraction model takes the form of a coupled reaction-diffusion-convection system which is analysed to explore the importance of key model parameters, most notably binding rates, on the ability to effectively monitor drug levels using reverse iontophoresis across the skin. We go on to discuss the implications of our modelling and results for drug monitoring. Close Jennifer Jones, K.A. Jane White, M. Begoña Delgado-Charro and Richard H. Guy 24006 A control theory inspired semi-automated method to probe the response of quantitative system pharmacology models to different drug dosing schedules. [abstract] Abstract: Drug treatment schedules significantly influence the success of pharmacological intervention. Even though quantitative systems pharmacology (QSP) models are used to understand the interplay between the pharmacological system and drug action, their ability to guide drug treatment schedules is still underutilised.Here we adopt a method widely used in electrical and control engineering to inform on the timescales of QSP models in response temporal changes in oscillatory inputs. The frequency-domain response analysis (FRA) is based on the linearization of a nonlinear model around its steady states. FRA provides insights into the presence and magnitude of time-delays, the stability and performance of QSP models. Thus, FRA enables the identification of dosing frequencies for which the response of the QSP model is either amplified or attenuated. This facilitates not only the characterisation of QSP models but also aids the understanding of the pharmacological system and the optimisation of treatment schedules or the identification of signature profiles.By providing an interactive and semi-automated application based on R and the Shiny package we make FRA easy to use and accessible to everyone without the need to understand the underlying mathematics. Close Pascal Schulthess, Teun Post, James Yates, Piet Hein van der Graaf 24007 Systems Medicine of Renal Cancer Drug Resistance: Towards New Diagnostics and Therapy [abstract] Abstract: Renal cell carcinoma (RCC) is the 8th most common cancer in UK and the most lethal urological malignancy.Resistance to treatment is almost ubiquitous in advanced disease and urgently warrants further investigation.Five year survival is approximately 40% overall and <10% with metastasis [Nat Rev Urol 2011;8:255]. NoMethod is available to predict RCC response to targeted therapy, nor to accurately identify high-risk patientsfor entry into adjuvant trials. The current study bridges genotype and phenotype towards more effectiveclinical tools for renal cancer medicine. Genetic control is realized by complex relationships between manycomponents, including numerous uncharacterised genes and unknown context-specific functions [Cell2011;144:986]. At the single-cell level, phenotype is governed by many concurrent biochemical reactionsthat form pleiotropic networks with nested hierarchical structure, and hence modularity [Science2002;297:1551]. Systematic approaches to understand the properties of these networks and so inform controlof cell behaviour include static systems-wide functional gene networks and executable models. Modellingrestricted to prior knowledge misses components and interactions, limiting the representation scope. In orderto address this knowledge gap, we are reverse engineering context-specific modularised global genenetworks. This data driven approach spans molecular and clinical parameters.Four representative RCC cell lines were selected from a panel of sixteen for transcriptome profilingat multiple time points following exposure to sunitinib, a front line drug. These representative cell lines wereidentified by unsupervised learning with data on gene expression, mutational status and sunitinib sensitivity.Modularity analysis of the drug response time course with a novel algorithm (NetNC) identified regulatedfunctionally coherent subnetworks specific to cell line (e.g. drug-resistant) or condition (e.g. hypoxia). Thefigure shows a modularised sunitinib response network, which illuminates mechanisms of cell killing anddrug resistance. Sunitinib treatment elicits substantially fewer changed network modules in hypoxicconditions relative to 'normoxia' suggesting the action of sunitinib on canonical targets (e.g. VEGFR)simulates hypoxia in RCC, which may synergise with putative anti-angiogenic action in vivo. Interestingly,induction of an apoptosis regulation module was found only in a metastatic cell line in hypoxia, includingupregulation of canonical apoptosis inhibitors BCL2 and BCLXL. Focussed analysis of the apoptosispathway across the sunitinib response time course uncovered expression changes in regulatory genes for asecond cell line. Follow-up experiments investigated chemical abrogation of apoptosis resistance alongsidesunitinib treatment as a potentially synergistic combination therapy. Close Sonntag HJ, Stewart GD, O' Mahony F, Edwards-Hicks J, Laird A, Murphy LC, Pairo-Castineira E, Mullen P, Harrison DJ, Overton IM