Seminar by Esteban Moro
14:00h, 27-07-2023 (Eduard Fontserè)
Title: Understanding urban networks resilience through behavioral mobility data.
Abstract: The economic and social progress of our urban areas, our institutions, and our jobs depend on the diversity and resilience of the social fabric in cities. Despite their importance, several major forces erode the diversity and strength of those social connections: from income or racial segregation to differences in education and job access. In this talk, I will present our recent work to understand the fragility of the complex network of social connections and interactions in cities through the analysis of behavioral mobility data and its relationship with networked inequalities in experienced segregation, access to healthy food, labor markets, or adaptation to the recent pandemic.
Material:
* Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19 [NatHumBehavior].
* Universal resilience patterns in labor markets [NatCommunications]
* Mobility patterns are associated with experienced income segregation in large US cities [NatCommunications].
* You are where you eat: Effect of mobile food environments on fast food visits [medRxiv]
Bio:
Esteban Moro is a researcher, data scientist, and professor at MIT Connection Science and Universidad Carlos III (UC3M) in Spain. He has published extensively throughout his career (more than 100 articles) and has led many projects funded by government agencies and private companies. Esteban’s work lies in the intersection of big data and computational social science, with particular attention to human dynamics, collective intelligence, social networks, and urban mobility in problems like viral marketing, natural disaster management, or economic segregation in cities. He has received numerous awards for his research, including the “Shared University Award” from IBM in 2007 for his research in modeling viral marketing in social networks and the “Excellence in Research” Awards in 2013 and 2015 from UC3M. Esteban’s work appeared in major journals, including Nature, PNAS, and Science Advances, and is regularly covered by media outlets The Atlantic, The Washington Post, The Wall Street Journal, and El País (Spain).
Seminar «Dynamics on networks through the lens of spectral and information theories»
12:00h, 07-07-2022 (Aula 3.20 Dpt. Materia Fisica Condensada, Fisica UB)
Dr. Antoine Allard, Université Laval, Québec, Canada
Dijous 7 a les 12:00, aula 3.20
Title: Dynamics on networks through the lens of spectral and information theories
A central topic in network science is the study of the interplay between the global behavior of complex systems and the structure of the local interactions among their constituents. In this talk, I will briefly present two recent projects in which we develop methods to study this structure-behavior relationship in complex systems. The first project uses spectral theory to effectively reduce the dimension of the system of coupled ODEs describing the evolution of a dynamical process taking place on a network [1]. The second project exploits the tools of information theory to unveil a non-reciprocal relation between how much knowing about the network structure informs us about the evolution of a dynamical process (predictability), and how much knowing about the dynamical process (i.e. time series) informs us about the network it is evolving on [2].
[1]: https://arxiv.org/abs/2206.11230
[2]: https://arxiv.org/abs/2206.04000
Consolider Seminar by Rubén Pérez-Carrasco: Effects of cell cycle variability on stochastic gene expression
12:00h, 29-03-2022 (Sala Eduard Fontseré, Física UB)
Title: Effects of cell cycle variability on stochastic gene expression
Date: 29 March 2022, 12h
Speaker: Rubén Pérez-Carrasco (Imperial College London)
Abstract:
Many models of stochastic gene expression do not incorporate a cell cycle description. I will show how this can be tackled analytically by studying how mRNA fluctuations are influenced by DNA replication for a prescribed cell cycle duration stochasticity. Results show that omitting cell cycle details can introduce significant errors in the predicted mean and variance of gene expression for prokaryotic and eukaryotic organisms, reaching a 25% error in the variance for mouse fibroblasts. Furthermore, we can derive a negative binomial approximation to the mRNA distribution, indicating that cell cycle stochasticity introduces similar fluctuations to bursty transcription. Finally, I will show how disregarding cell cycle stochasticity can introduce inference errors in transcription rates bigger than 10%.
Seminar by Juan Fernández-Gracia (IFISC): Characterising and modeling of the ocean microbiome… and twitter?
12:00h, 28-03-2022 (Aula 3.20, Departament Física de la Matèria Condensada, Física UB)
Abstract: Microorganisms like bacteria, archaea and eukaryotes coexist in large and complex ecosystems. Actually, microbial communities form the largest and more diverse ecosystems on the planet. Understanding their composition and which mechanisms lead to and maintain those compositions is of crucial importance for example if we want to understand associated changes in function of distinct microbiomes. Furthermore the interactions among their individuals are diverse, encompassing mutualism, commensalism, or competition. Measuring these interactions in direction and strength at a large scale is a challenging process that requires a combination of data analysis and modeling, which shouldn’t ignore the dynamic nature of the abundances of different species. Here we use data on microbial species abundances first to characterize the microbiome composition in the global ocean and estimate the total microbial richness, for which we derive some scaling relations with the sampling effort and relate them to the form of the abundance distributions. Then we will jump to the question of inferring interactions among different species and we will present two methods, namely a static one based on non-linear correlation measures of abundances across samples; and a dynamic one, based on a generalized Lotka-Volterra set of equations. Finally, we will conclude with a glimpse on how to apply ecological theories to data on social activities, in particular to conversations in twitter.
Seminaris Complèxica-17
17:30h, 30-01-2020 (Aula 3.20 Departament Física de la Matèria Condensada, Física UB)
Abstract: Microorganisms like bacteria, archaea and eukaryotes coexist in large and complex ecosystems. Actually, microbial communities form the largest and more diverse ecosystems on the planet. Understanding their composition and which mechanisms lead to and maintain those compositions is of crucial importance for example if we want to understand associated changes in function of distinct microbiomes. Furthermore the interactions among their individuals are diverse, encompassing mutualism, commensalism, or competition. Measuring these interactions in direction and strength at a large scale is a challenging process that requires a combination of data analysis and modeling, which shouldn’t ignore the dynamic nature of the abundances of different species. Here we use data on microbial species abundances first to characterize the microbiome composition in the global ocean and estimate the total microbial richness, for which we derive some scaling relations with the sampling effort and relate them to the form of the abundance distributions. Then we will jump to the question of inferring interactions among different species and we will present two methods, namely a static one based on non-linear correlation measures of abundances across samples; and a dynamic one, based on a generalized Lotka-Volterra set of equations. Finally, we will conclude with a glimpse on how to apply ecological theories to data on social activities, in particular to conversations in twitter.
Seminar by Guillermo García [University of Turku]
14:30h, 28-01-2020 (Aula 3.20)
Seminar by Guillermo García [University of Turku]
DATE: 28 January 2020 (14:30h)
PLACE: Aula 3.20, 3rd floor, Faculty of Physics (Dpt.Física de la Matèria Condensada)
TITLE: Pairwise tomography networks for many-body quantum systems
ABSTRACT: We introduce the concept of pairwise tomography networks to characterise quantum properties in many-body systems and demonstrate an efficient protocol to measure them experimentally. Pairwise tomography networks are generators of multiplex networks where each layer represents the graph of a relevant quantifier such as, e.g., concurrence, quantum discord, purity, quantum mutual information, or classical correlations. We propose a measurement scheme to perform two-qubit tomography of all pairs showing exponential improvement in the number of qubits N with respect to previously existing methods. We illustrate the usefulness of our approach for device characterisation and quantum simulations.
Seminar by Dr. Hugues Chaté [Physics of active matter: A personal overview]
12:00h, 03-12-2019 (Eduard Fonseré, Física, UB)
TITLE: Physics of active matter: A personal overview
SPEAKER: Hugues Chaté (CEA-Saclay & Beijing CSRC, PRL Editoral Board)
DATE: December 3, 2019 at 12.00h
PLACE: Sala Eduard Fontserè
ABSTRACT: Active matter consists of elementary units producing mechanical work to move themselves or to displace other objects. In other words, active matter is about systems maintained out-of-equilibrium «in the bulk», burning energy to produce directed, persistent motion. This very general definition covers all kinds of situations at all scales: groups of animal or robots, collective of cells and micro-organisms, active colloids and phoretic swimmers, mixtures of biofilaments and motor proteins. Most active matter systems exhibit surprising if not spectacular emerging collective properties that we are only starting to understand. In this talk, I will strive to give a synthetic and organized overview of what is still a fast-growing field. This overview will however be rather personal, drawing mostly from my own work. A large part if the talk will be devoted to presenting experimental results obtained mostly on living active matter, which should be of interest to biologists.
DataPolitik 2019
19:00h, 28-11-2019 (Edifici Històric i Facultat de Física)
Los días 28 y 29 Noviembre se celebrará el evento DataPolitik2019, 1a Jornada sobre política y comunicación en la era del big-data, organizada por la asociación Heurístca con el grupo de investigación Tecnopolítica – IN3/UOC y la colaboración del LID y del UBICS. Esta jornada quiere ser una invitación al diálogo interdisciplinar y a la puesta en común de perspectivas metodológicas, visiones sociopolíticas, resultados concretos y líneas de investigación acerca de cómo los entornos digitales han cambiado la estructura de la comunicación y las gramáticas de interacción social. Un primer paso para constituir espacios en los que la ciencia de la comunicación, la sociología, la politología y la ciencia de los sistemas complejos, entre otras disciplinas, colaboren para mejorar nuestra comprensión de lo que ocurre en las plataformas sociales. El día 28 se celebrará una mesa redonda con la participación de Carina Bellver (storyData Barcelona – periodismo de datos), Frederic Guerrero-Solé (UPF – doctor en comunicación pública) Jordi Muñoz Mendoza (UB – politólogo). La mesa redonda será moderada por Luce Prignano (Héuristica/UBICS – científica de redes). El día 29 será dedicado a la presentación de estudios y proyectos y al debate. Para proponer una ponencia es necesario rellenar el formulario online antes del 13 de Nobiembre.
Los idiomas principales del workshop son el catalán y el castellano, pero propuestas en inglés también son bien recibidas. El evento es gratuito y abierto a quien quiera acudir.
Link a la web: https://lid.decidim.barcelona/conferences/DataPolitik?locale
Matter, Life, and Society: An Overview in Complex Systems Perspectives
12:00h, 25-11-2019 (Aula Seminari 3.20, Dept. Física de la Matèria Condensada, Facultat de Física, Barcelona)
Speaker: Prof. MooYoung Choi, Department of Physics and Astronomy,
Seoul National University
Title: Matter, Life, and Society: An Overview in Complex Systems Perspectives
Abstract: Every object we experience with our sensory organs is a many-particle system consisting of a large number of elements interacting with each other, and the collective behavior of the whole system emerges via cooperative phenomena due to the interactions. In nature, many-particle systems often exhibit so-called complexity at the boundary between order and disorder, and tend to have self-organized structure under the influence of the environment. From this viewpoint of the complex system, not only traditional matter but also life and society are complex systems composed of many elements; life or social phenomena can be interpreted as the collective properties emerging from the interactions between elements. In this overview, we will briefly examine the physical meaning of complex systems and introduce some studies of matter, life, and society in the complex systems perspectives. Instances include glucose regulation, neural networks, urban morphology, and transportation networks.
Seminar by Prof. Kai Ruffing
11:00h, 24-10-2019 (Facultat de Geografia i Història de la Universitat de Barcelona, Aula 220)
Seminari del Prof. Kai Ruffing (Universitat de Kassel) el dijous 24 d’octubre de 2019 a la Facultat de Geografia i Història de la Universitat de Barcelona, Aula 220, amb el títol ‘Produzione, commercio e consumo di vino nell’Egitto romano’.
CLabB Seminar, Reconstructing dynamical networks via feature ranking (MG Leguina)
15:00h, 17-10-2017 (Room 3.20 3rd floor, Departament de Física de la Matèria Condensada, Facultat de Física, Marti i Franques 1)
Title: Reconstructing dynamical networks via feature ranking Speaker: Marc Grau Leguina, Wyss Center Postdoctoral Fellow, Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Switzerland
Abstract: Empirical data on real complex systems are becoming increasingly available. Parallel to this is the need for new methods of reconstructing (inferring) the structure of networks from time- resolved observations of their node-dynamics. The methods based on physical insights often rely on strong assumptions about the properties and dynamics of the scrutinized network. Here, we use the insights from machine learning to design a new method of network reconstruction that essentially makes no such assumptions. Specifically, we interpret the available trajectories (data) as “features” and use two independent feature ranking approaches—Random Forest and RReliefF—to rank the importance of each node for predicting the value of each other node, which yields the reconstructed adjacency matrix. We show that our method is fairly robust to coupling strength, system size, trajectory length, and noise. We also find that the reconstruction quality strongly depends on the dynamical regime.
Link to the paper: M. G. Leguia, Z. Levnajic, L. Todorovski, and B. Zenko, “Reconstructing dynamical networks via feature ranking,” Chaos 29, 093107 (2019) https://doi.org/10.1063/1.5092170
Seminari Internacional, ‘Roman agrarian & viticultural landscapes-geospatial analysys, statistics & predictive modelling: case studies research’
Seminari Internacional: ‘Roman agrarian & viticultural landscapes-geospatial analysys, statistics & predictive modelling: case studies research’.
Es durà a terme el proper dilluns 14 d’octubre de 2019 a la Facultat de Geografia i Història de la Universitat de Barcelona i el dimarts 15 d’octubre de 2019 al Parc Arqueològic Cella Vinaria-Centre Enoturístic i Arqueològic de Vallmora de Teià (Maresme).
Pots decarregar-te el programa detallat aquí.
Seminar by Dra. Caterina Pedersini
Sala de Graus – Aula Miquel Siguan , Facultat de Psicologia , Campus Mundet
Title: ESTIMATION OF FUNCTIONAL CONNECTIVITY WITH fMRI
Objective: Review of some algorithms used to estimate functional connectivity networks from fMRI signal and resting-state situations.