Slow nucleic acid unzipping kinetics from sequence-defined barriers

Recent experiments on unzipping of RNA helix-loop structures by force have shown that about 40-base molecules can undergo kinetic transitions between two well-defined `open' and `closed' states, on a timescale = 1 sec [Liphardt et al., Science 297, 733-737 (2001)]. Using a simple dynamical model, we show that these phenomena result from the slow kinetics of crossing large free energy barriers which separate the open and closed conformations. The dependence of barriers on sequence along the helix, and on the size of the loop(s) is analyzed. Some DNAs and RNAs sequences that could show dynamics on different time scales, or three(or more)-state unzipping, are proposed.Comment: 8 pages Revtex, including 4 figure

Adaptive Cluster Expansion for Inferring Boltzmann Machines with Noisy Data

We introduce a procedure to infer the interactions among a set of binary variables, based on their sampled frequencies and pairwise correlations. The algorithm builds the clusters of variables contributing most to the entropy of the inferred Ising model, and rejects the small contributions due to the sampling noise. Our procedure successfully recovers benchmark Ising models even at criticality and in the low temperature phase, and is applied to neurobiological data.Comment: Accepted for publication in Physical Review Letters (2011

Large Pseudo-Counts and L2L_2-Norm Penalties Are Necessary for the Mean-Field Inference of Ising and Potts Models

Mean field (MF) approximation offers a simple, fast way to infer direct interactions between elements in a network of correlated variables, a common, computationally challenging problem with practical applications in fields ranging from physics and biology to the social sciences. However, MF methods achieve their best performance with strong regularization, well beyond Bayesian expectations, an empirical fact that is poorly understood. In this work, we study the influence of pseudo-count and $L_2$-norm regularization schemes on the quality of inferred Ising or Potts interaction networks from correlation data within the MF approximation. We argue, based on the analysis of small systems, that the optimal value of the regularization strength remains finite even if the sampling noise tends to zero, in order to correct for systematic biases introduced by the MF approximation. Our claim is corroborated by extensive numerical studies of diverse model systems and by the analytical study of the $m$-component spin model, for large but finite $m$. Additionally we find that pseudo-count regularization is robust against sampling noise, and often outperforms $L_2$-norm regularization, particularly when the underlying network of interactions is strongly heterogeneous. Much better performances are generally obtained for the Ising model than for the Potts model, for which only couplings incoming onto medium-frequency symbols are reliably inferred.Comment: 25 pages, 17 figure

Fandom from afar: identification, attachment, and consumption behaviors among United States based fans of English premier league soccer clubs.

The purpose of this study was to explore the antecedents to organizational identification among U.S.-based EPL fans and examine the relationship between these antecedents and various forms of sport consumption behavior. Specifically, this study examined the extent to which points of attachment explained variances in organizational identification and three types of sport consumption behavior – broadcast media consumption, social media consumption, and team-related merchandise purchases. Additionally, this study examined differences in points of attachment between fans of successful EPL organizations, known as the “Big Six” EPL clubs, and fans of unsuccessful EPL organizations. In contrast to most existing sport fan identification and attachment research, this study focused on distant fans, a group yet to receive significant attention in the sport management literature. This study utilized social identity theory as a conceptual foundation. Social identity theory is a socio-cognitive framework that explains the formation and behaviors of social groups. It provides the main theoretical foundation for research on organizational identification and team identification. Points of attachment represent an extension of team identification research that accounts for the potential of multiple factors to contribute toward one’s fan identification. Previous research suggests an understanding of fan identification and attachment is crucial to developing targeted marketing plans which positively influence sport consumption behaviors. To address the purpose of the study, a questionnaire was distributed to U.S.-based EPL fans through Facebook group pages organized around fan support and interactions for EPL clubs. The questionnaire contained items to assess respondent’s levels of organizational identification, attachment to various aspects of the organization, and consumption behaviors. Participant responses (n = 753) revealed attachment to fan community exhibited the strongest relationship with organizational identification and each type of sport consumption behavior. Attachment to venue also suggested positive relationships with organizational identification and sport consumption behaviors. Two new points of attachment created for this study, attachment to owner and attachment to organizational history/tradition, positively explained respondent’s frequency of merchandise purchases. Additional analysis revealed player and venue attachment held particular salience among U.S.-based fans of Big Six EPL organizations. Meanwhile, attachment to fan community, city/region, and owner displayed significantly higher ratings among U.S.-based fans of EPL organizations outside the Big Six. These results produce several theoretical and practical implications for researchers and practitioners. From a theoretical perspective, the results illuminate similarities and differences in identification and attachment among distant fan populations compared to local sport fans. Additionally, factor analyses supported a factor structure for items relating to the two new points of attachment created for this study. This sets a foundation for future researchers to utilize these points of attachment in a variety of new research contexts covering distant and local fan types. From a practical implication perspective, the results show the importance of placing the concept of fan community at the heart of marketing strategies for EPL organizations and their U.S.-based broadcast partner, NBC Sports. As information technology and high-speed internet access continue to eliminate boundaries between sport teams and fans from across the world, it will become increasingly crucial for sport organizations to understand their fan bases in distant markets. This study provides initial evidence of variables that demonstrate a significant, positive impact on organizational identification and sport consumption behaviors for a particular set of distant fans

Gender Stereotypes and Figurative Language Comprehension

The paper aims to show how and to what extent social and cultural cues influence figurative language understanding. In the first part of the paper, we argue that social-contextual knowledge is organized in “schemas” or stereotypes, which act as strong bias in speaker’s meaning comprehension. Research in Experimental Pragmatics has shown that age, gender, race and occupation stereotypes are important contextual sources of information to interpret others’ speech and provide an explanation of their behavior. In the second part of the paper, we focus on gender stereotypes and their influence on the comprehension of figurative language, to show how the social functions of figurative language are modulated by gender stereotypes. We provide then an explanation of gender stereotypical bias on figurative language in terms of possible outcomes in the social context

Exponentially hard problems are sometimes polynomial, a large deviation analysis of search algorithms for the random Satisfiability problem, and its application to stop-and-restart resolutions

A large deviation analysis of the solving complexity of random 3-Satisfiability instances slightly below threshold is presented. While finding a solution for such instances demands an exponential effort with high probability, we show that an exponentially small fraction of resolutions require a computation scaling linearly in the size of the instance only. This exponentially small probability of easy resolutions is analytically calculated, and the corresponding exponent shown to be smaller (in absolute value) than the growth exponent of the typical resolution time. Our study therefore gives some theoretical basis to heuristic stop-and-restart solving procedures, and suggests a natural cut-off (the size of the instance) for the restart.Comment: Revtex file, 4 figure

Solving satisfiability problems by fluctuations: The dynamics of stochastic local search algorithms

Stochastic local search algorithms are frequently used to numerically solve hard combinatorial optimization or decision problems. We give numerical and approximate analytical descriptions of the dynamics of such algorithms applied to random satisfiability problems. We find two different dynamical regimes, depending on the number of constraints per variable: For low constraintness, the problems are solved efficiently, i.e. in linear time. For higher constraintness, the solution times become exponential. We observe that the dynamical behavior is characterized by a fast equilibration and fluctuations around this equilibrium. If the algorithm runs long enough, an exponentially rare fluctuation towards a solution appears.Comment: 21 pages, 18 figures, revised version, to app. in PRE (2003

The dynamics of proving uncolourability of large random graphs I. Symmetric Colouring Heuristic

We study the dynamics of a backtracking procedure capable of proving uncolourability of graphs, and calculate its average running time T for sparse random graphs, as a function of the average degree c and the number of vertices N. The analysis is carried out by mapping the history of the search process onto an out-of-equilibrium (multi-dimensional) surface growth problem. The growth exponent of the average running time is quantitatively predicted, in agreement with simulations.Comment: 5 figure

Relaxation and Metastability in the RandomWalkSAT search procedure

An analysis of the average properties of a local search resolution procedure for the satisfaction of random Boolean constraints is presented. Depending on the ratio alpha of constraints per variable, resolution takes a time T_res growing linearly (T_res \sim tau(alpha) N, alpha < alpha_d) or exponentially (T_res \sim exp(N zeta(alpha)), alpha > alpha_d) with the size N of the instance. The relaxation time tau(alpha) in the linear phase is calculated through a systematic expansion scheme based on a quantum formulation of the evolution operator. For alpha > alpha_d, the system is trapped in some metastable state, and resolution occurs from escape from this state through crossing of a large barrier. An annealed calculation of the height zeta(alpha) of this barrier is proposed. The polynomial/exponentiel cross-over alpha_d is not related to the onset of clustering among solutions.Comment: 23 pages, 11 figures. A mistake in sec. IV.B has been correcte