DM - GISC - Comunicaciones en Congresos y otros eventos

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Exotic liquid crystalline phases in monolayers of vertically vibrated granular particles
(Taylor & Francis, 2023-05-05) Martínez-Ratón, Yuri; Velasco, E.; Agencia Estatal de Investigación (España); Ministerio de Ciencia e Innovación (España)
Vibrated monolayers of granular particles confined into horizontal cavities form a variety of fluid patterns with orientational order that resemble equilibrium liquid-crystal phases. In some cases, one can identify nematic and smectic patterns that can be understood in terms of classical statistical mechanics of hard bodies. Low aspect ratio cylinders project as rectangles and form uniaxial, or 2-atic, and tetratic, or 4-atic, nematic phases. Other polygonal particles may exhibit different liquid-crystal phases, in general p-atic phases, of higher symmetries. We give a brief summary of theoretical work on rectangles and triangles, and provide some experimental results on vibrated monolayers. In the case of equilateral triangles, the theory predicts an exotic triatic phase, or 6-atic phase, with six-fold symmetry and three equivalent directors. The right-angled triangles exhibit a 4-atic phase with strong octatic (8-atic) correlations. Experiments on cylinders show 4-atic textures and, even more remarkable, geometric frustration caused by confinement excites topological defects, which seem to follow the same topological rules as standard liquid crystals. Some of our findings can be understood with the help of simulations of hard particles subject to thermal equilibrium, although standard Density-Functional Theories fail to account for the correct equilibrium phases in some cases.
Nonlinear theory of ion-induced solid flow
(2018-10-09) Muñoz-García, Javier; Cuerno, Rodolfo; Castro Ponce, Mario
In this contribution, we present a nonlinear theory thatextends previous results and describes the dynamics of the morphology during subsequent, nonlinearstages of its time evolution.
Around a table: social lubricants for trust building
(2016-07-08) Brañas, Pablo; Cabrales Goitia, Antonio; Mateu, Guillermo; Sánchez, Angel; Sutan, Ángela
Social interactions increased trust and trustworthiness very significantly in all-male groups, but not so in all-female groups. The effect was significantly bigger when only drinks were available (both water and wine), whereas adding food decreased the (still significant with respect to the no interaction baseline) effect of only drinks in all male groups. Interestingly, the positive effect of social interactions on trust for males was not reflected on negotiations, where the efficiency is reduced by the presence of interactions.
Nonlinear theory of ion-induced solid flow
(2018-08-12) Muñoz-García, Javier; Cuerno, Rodolfo; Castro Ponce, Mario
Ion beam sputtering (IBS) is a powerful technique employed to induce surface nanopatterns over relatively large areas for a wide range of materials [1]. This approach has many applications in modern technology like magnetic storage, quantum device design or, for example, producing the selective attachment of specific molecules to substrates, with implications in biology and catalysis.
Nanoscale pattern formation: an interplay between hard and soft condensed matter physics
(2017-06-25) Cuerno, Rodolfo
This talk will attempt a brief overview on the interplay between hard and soft condensed matter physics with respect to the formation of nanoscale-sized patterns...
Nanoscale pattern formation: an interplay between hard and soft condensed matter physics
(Sociedad Mexicana de Ciencia y Tecnología de Superficies y Materiales A.C., 2018-09-24) Cuerno, Rodolfo
This talk will attempt an overview on the interplay between hard and soft condensed matter physics with respect to the formation of nanoscale-sized patterns...
Neutral evolution and the acceleration of the molecular clock
(2015-02-04) Cuesta, José A.
Large sets of genotypes give rise to the same phenotype because phenotypic expressionis highly redundant. Accordingly, a population can accept mutations without alteringits phenotype, as long as the genotype mutates into another one on the same set. Bylinking every pair of genotypes that are mutually accessible through mutation, geno-types organize themselves into neutral networks (NN). These networks are known to beheterogeneous and assortative, and these properties affect the evolutionary dynamics ofthe population. By studying the dynamics of populations on NN with arbitrary topol-ogy we analyze the effect of assortativity, of NN (phenotype) fitness, and of networksize. We find that the probability that the population leaves the network is smallerthe longer the time spent on it. This progressive "phenotypic entrapment" entails asystematic increase in the overdispersion of the process with time and an accelerationin the fixation rate of neutral mutations.
Twitter session analytics: profiling susers' short-term behavioral changes
(Springer, 2016-10-19) Kooti, Farshad; Moro, Esteban; Lerman, Kristina
Human behavior shows strong daily, weekly, and monthlypatterns. In this work, we demonstrate online behavioral changes thatoccur on a much smaller time scale: minutes, rather than days or weeks.Specifically, we study how people distribute their effort over differenttasks during periods of activity on the Twitter social platform. Wedemonstrate that later in a session on Twitter, people prefer to perform simpler tasks, such as replying and retweeting others' posts, ratherthan composing original messages, and they also tend to post shortermessages. We measure the strength of this effect empirically and statistically using mixed-effects models, and find that the first post of a sessionis up to 25 % more likely to be a composed message, and 10-20 % lesslikely to be a reply or retweet. Qualitatively, our results hold for differentpopulations of Twitter users segmented by how active and well-connectedthey are. Although our work does not resolve the mechanisms responsible for these behavioral changes, our results offer insights for improvinguser experience and engagement on online social platforms.
Nitrogen-fixing cyanobacteria are tuned for evolvability
(2018-10-18) Doldán-Martelli, Victoria; Gonzales-Moreno, Katherine; Bravo-Candel, Daniel; Muñoz-García, Javier; Ares, Saúl; Arranz, F.J.
Cyanobacteria produce a signiﬁcant fraction of the oxygen on the environment and, together with archaea, they ﬁx atmospheric nitrogen used by all other organisms. One of the ﬁrst forms of multicellular organisms on Earth are ﬁlamentous cyanobacteria, which constitutCyanobacteria produce a signiﬁcant fraction of the oxygen on the environment and, together with archaea, they ﬁx atmospheric nitrogen used by all other organisms. One of the ﬁrst forms of multicellular organisms on Earth are ﬁlamentous cyanobacteria, which constitute a paradigmatic model organism of the transition between unicellular and multicellular living forms. The genus Anabaena forms colonies with cells arranged in one-dimensional ﬁlaments; under nitrogen-limiting conditions some cells can differentiate into a nitrogen-ﬁxing heterocysts, forming regular patterns to effectively provide nitrogen for the colony. e a paradigmatic model organism of the transition between unicellular and multicellular living forms. The genus Anabaena forms colonies with cells arranged in one-dimensional ﬁlaments; under nitrogen-limiting conditions some cells can differentiate into a nitrogen-ﬁxing heterocysts, forming regular patterns to effectively provide nitrogen for the colony...
Non-locality effects in the Eden growth model
(2017-03-30) Santalla, Silvia N.; Ferreira, Silvio C.
The Eden growth model [1], originally designed to study the growth of cell colonies, is a paradigmatic example of stochastic radial growth, in which the fluctuations in the interface are described by the celebrated Kardar-Parisi-Zhang (KPZ) universality class [2]. (...)
What comes first? Social strength or common friends?
(2017-04-05) Miritello, Giovanna; Cebrián, Manuel; Moro, Esteban
Social networks are made out of strong andweak links having very different structural anddynamical properties. Social scientists have longrecognized the value of weak links in information discovery but also their relative structuralweakness that makes them more likely to decayin the future. What what features of humaninteraction build a strong tie? Here we approachthis question from an practical way by findingwhat are the properties of social interactions thatmake ties more persistent and thus stronger tomaintain social interactions in the future. Usinga large longitudinal mobile phone database webuild a predictive model of tie persistence basedon intensity, structural and temporal patternsof social interaction. While our results confirmthat structural (embeddedness) and intensity(number of calls) are correlated with tie persistence, we find that daily temporal featuresof communication events in a tie are betterand more efficient predictors for tie persistence.Specifically, although communication betweenlinks is always bursty we find that links that aremore bursty than the average are more likely todecay, signaling that the strength of the tie isnot only reflected in the intensity or topology ofthe network, but also on how we distribute intime our interactions with our relationships. Ourresults not only are important to understandthe strength of social relationships but also tounveil the entanglement between the differenttemporal scales in networks, from microscopictie burstiness to network evolution.
MemeSequencer: sparse matching for embedding image macros
(ACM, 2018-04-23) Dubey, Abhimanyu; Moro, Esteban; Cebrián, Manuel; Rahwan, Iyad
The analysis of the creation, mutation, and propagation of social media content on the Internet is an essential problem in computational social science, affecting areas ranging from marketing to political mobilization. A first step towards understanding the evolution of images online is the analysis of rapidly modifying and propagating memetic imagery or "memes". However, a pitfall in proceeding with such an investigation is the current incapability to produce a robust semantic space for such imagery, capable of understanding differences in Image Macros. In this study, we provide a first step in the systematic study of image evolution on the Internet, by proposing an algorithm based on sparse representations and deep learning to decouple various types of content in such images and produce a rich semantic embedding. We demonstrate the benefits of our approach on a variety of tasks pertaining to memes and Image Macros, such as image clustering, image retrieval, topic prediction and virality prediction, surpassing the existing methods on each. In addition to its utility on quantitative tasks, our method opens up the possibility of obtaining the first large-scale understanding of the evolution and propagation of memetic imagery.
Modelling of patA and hetF gene function in Anabaena heterocyst formation
(2018-10-18) Casanova Ferrer, Pau; Ares García, Saúl; Muñoz-García, Javier
Differentiated cell types can form patterns in filamentous cyanobacteria. Specifically the genus Anabaena has received special interest because under nitrogen-limiting conditions some of the vegetative cells differentiate into a nitrogen-fixing form called heterocyst [1]. These heterocysts cannot undergo cell division or have photosynthetic activity, but share fixed nitrogen products with the whole filament. In order to efficiently distribute the fixed nitrogen, heterocysts are arranged forming quasiregular patterns in the filament...
Interplay between columnar and smectic stability in suspensions of polydisperse colloidal platelets
(2014-04-02) Velasco, Enrique; Martínez-Ratón, Yuri
The phase behavior of a model suspension of colloidal polydisperse platelets is studied using density-functional theory. Platelets are modelled as parallel rectangular prisms of square section l(2) and height h, with length and height distributions given by different polydispersities delta(l) and delta(h). The model is intended to qualitatively represent experimental colloidal platelet suspensions at high densities with a high degree of orientational ordering. We obtain the phase behavior of the model, including nematic, smectic and columnar phases and its dependence on the two polydispersities delta(l) and delta(h). When delta(l) >; delta(h) we observe that the smectic phase stabilises first with respect to the columnar. If delta(h) >; delta(l) we observe the opposite behavior. Other more complicated cases occur, e. g. the smectic stabilises from the nematic first but then exists a first-order transition to the columnar phase. Our model assumes plate-rod symmetry, but the regions of stability of smectic and columnar phases are non-symmetric in the delta(l) - delta(h) plane due to the different dimensionality of ordering in the two phases. Microsegregation effects, i.e. different spatial distribution for different sizes within the periodic cell, take place in both phases and, in each case, is more apparent in the variable associated with ordering.
Cognitive resource allocation determines the organization of personal networks
(2020-03-04) Tamarit, Ignacio; Cuesta, José A.; Dunbar, Robin I. M.; Sánchez, Angel
The typical human personal social network contains about 150 relationships including kin, friends, and acquaintances, organized into a set of hierarchically inclusive layers of increasing size but decreasing emotional intensity. Data from a number of different sources reveal that these inclusive layers exhibit a constant scaling ratio of ∼3. While the overall size of the networks has been connected to our cognitive capacity, no mechanism explaining why the networks present a layered structure with a consistent scaling has been proposed. Here we show that the existence of a heterogeneous cost to relationships (in terms of time or cognitive investment), together with a limitation in the total capacity an individual has to invest in them, can naturally explain the existence of layers and, when the cost function is linear, explain the scaling between them. We develop a one-parameter Bayesian model that fits the empirical data remarkably well. In addition, the model predicts the existence of a contrasting regime in the case of small communities, such that the layers have an inverted structure (increasing size with increasing emotional intensity). We test the model with five communities and provide clear evidence of the existence of the two predicted regimes. Our model explains, based on first principles, the emergence of structure in the organization of personal networks and allows us to predict a rare phenomenon whose existence we confirm empirically.
Adding levels of complexity enhances robustness and evolvability in a multilevel genotype-phenotype map
(2018-01-17) Catalan, Pablo; Wagner, Andreas; Manrubia, Susanna; Cuesta, José A.
Robustness and evolvability are the main properties that account for the stability andaccessibility of phenotypes. They have been studied in a number of computationalgenotype- phenotype maps. In this contribution we study a metabolic genotypephenotypemap defined in toyLIFE, a multi-level computational model that representsa simplified cellular biology. toyLIFE includes several levels of phenotypic expression,from proteins to regulatory networks to metabolism. Our results show that toyLIFEshares many similarities with other seemingly unrelated computational genotypephenotypemaps. Thus, toyLIFE shows a high degeneracy in the mapping fromgenotypes to phenotypes, as well as a highly skewed distribution of phenotypicabundances. The neutral networks associated with abundant phenotypes are highlynavigable, and common phenotypes are close to each other in genotype space. Allof these properties are remarkable, as toyLIFE is built on a version of the HP proteinfolding model that is neither robust nor evolvable: phenotypes cannot be mutuallyaccessed through point mutations. In addition, both robustness and evolvabilityincrease with the number of genes in a genotype. Therefore, our results suggest thatadding levels of complexity to the mapping of genotypes to phenotypes and increasinggenome size enhances both these properties.
Stress vs sputtering effects in the propagation of surface ripples produced by ion-beam sputtering
(Elsevier, 2014-11) Moreno-Barrado, Ana; Cañadas Castro, Mario; Muñoz-García, Javier; Cuerno, Rodolfo
Under low energy ion irradiation, periodic features (ripples) can develop on the surfaces of semiconductor materials, with typical sizes in the nanometric range. Recently, a theory of pattern formation has been able to account for the variability with the ion/target combination of the critical angle value separating conditions on ion incidence that induce the presence or the absence of ripples. Such a theory is based in the accumulation of stress in the damaged irradiated layer and its relaxation via surface-confined viscous flow. Here we explore the role of stress, and its competition with purely erosive mechanisms, to deter-mine the sign of the velocity with which the ripple pattern moves across the target plane. Based on this theory, we discuss different situations and make specific testable predictions for the change of sign in that velocity.
Energy dependence of the ripple wavelength for ion-beam sputtering of silicon: experiments and theory
(American Institute of Physics, 2012-08-05) Cañadas Castro, Mario; Gago, Raúl; Muñoz-García, Javier; Cuerno, Rodolfo
In spite of the efforts devoted for the last 20 years to elucidating ion-beam sputtering (IBS) as an instance of surface self-organization, the classic view on the main mechanism inducing the morphological instability has been recently challenged. We report on the verification of a recent theoretical description of this nanopattern formation process for semiconducting targets, as driven by stress-induced, viscous flow of a thin amorphous layer that develops at the surface [M. Cuerno and R. Cuerno, Appl. Surf. Sci. 258, 4171 (2012)]. Through experiments on silicon as a representative case, we study the dependence of the ripple wavelength with the average ion energy, finding a linear dependence in the 0.3-1 keV range. This is explained within the viscous flow framework, taking into account the energy dependence of the number of displaced atoms generated by collision cascades in the amorphous layer, as predicted by previous models of ion-generated stress. For our analysis, we provide a systematic criterion to guarantee actual linear dynamics behavior, not affected by the onset of nonlinear effects that may influence the value of the ripple wavelength.
Alan Turing and the origins of modern Gaussian elimination
(Centro Superior de Investigaciones Científicas, 2012-10) Martínez Dopico, Froilán César
The solution of a system of linear equations is by far the most important problem in Applied Mathematics. It is important both in itself and because it is an intermediate step in many other important problems. Gaussian elimination is nowadays the standard method for solving this problem numerically on a computer and it was the first numerical algorithm to be subjected to rounding error analysis. In 1948, Alan Turing published a remarkable paper on this topic: "Rounding-off errors in matrix processes" (Quart. J. Mech. Appl. Math. 1, pp. 287-308). In this paper, Turing formulated Gaussian elimination as the matrix LU factorization and introduced the "condition number of a matrix", both of them fundamental notions of modern Numerical Analysis. In addition, Turing presented an error analysis of Gaussian elimination for general matrices that deeply influenced the spirit of the definitive analysis developed by James Wilkinson in 1961. Alan Turing's work on Gaussian elimination appears in a fascinating period for modern Numerical Analysis. Other giants of Mathematics, as John von Neumann, Herman Goldstine, and Harold Hotelling were also working in the mid-1940s on Gaussian elimination. The goal of these researchers was to find an efficient and reliable method for solving systems of linear equations in modern "automatic computers". At that time, it was not clear at all whether Gaussian elimination was a right choice or not. The purpose of this paper is to revise, at an introductory level, the contributions of Alan Turing and other authors to the error analysis of Gaussian elimination, the historical context of these contributions, and their influence on modern Numerical Analysis.
Matrix polynomials with completely prescribed eigenstructure
(Society for Industrial and Applied Mathematics, 2014-07) Terán Vergara, Fernando de; Martínez Dopico, Froilán César; Van Dooren, Paul
We present necessary and su cient conditions for the existence of a matrix polynomial when its degree, its nite and in nite elementary divisors, and its left and right minimal indices are prescribed. These conditions hold for arbitrary in nite elds and are determined mainly by the \index sum theorem", which is a fundamental relationship between the rank, the degree, the sum of all partial multiplicities, and the sum of all minimal indices of any matrix polynomial. The proof developed for the existence of such polynomial is constructive and, therefore, solves a very general inverse problem for matrix polynomials with prescribed complete eigenstructure. This result allows us to x the problem of the existence of (l)-ifications of a given matrix polynomial, as well as to determine all their possible sizes and eigenstructures.

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