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

Corporate pension plans as takeover deterrents

We use UK data to show that firms that sponsor a defined-benefit pension plan are less likely to be targeted in an acquisition and, conditional on an attempted takeover, they are less likely to be acquired. Our explanation is that the uncertainty in the value of pension liabilities is a source of risk for acquirers of the firm's shares, which works as a takeover deterrent. In support of this explanation we find that these same firms are more likely to use cash when acquiring other firms, and that the announcement of a cash acquisition is associated with positive announcement effects

Different haemodynamic (24-h ambulatory blood-pressure monitoring) and rennin-inhibiting effect of a 1 week treatment with enalapril and lisinopril

Ambulatory blood pressure and heart rate monitoring were used for comparing the antihypertensive effect of a 1-week treatment with enalapril and lisinopril 10 mg once daily (double-blind crossover placebo-controlled d y ). Twelve outpatients with mild to moderate hypertension were treated. Both drugs had a significant and identical hypotensive effect. Neither drug affected the diurnal rhythm of blood pressure or heart rate. Therefore the two drugs are equipotent antihypertensive agents. Both drugs inhibited ACE activity to a highly significant extent, but in this regard lisinopril was more effective than enalapril. However, lisinopril's greater ACE inhibition was not accompanied by a greater hypotensive effect. The clinical value of this difference is not yet established

Inferring DNA sequences from mechanical unzipping data: the large-bandwidth case

The complementary strands of DNA molecules can be separated when stretched apart by a force; the unzipping signal is correlated to the base content of the sequence but is affected by thermal and instrumental noise. We consider here the ideal case where opening events are known to a very good time resolution (very large bandwidth), and study how the sequence can be reconstructed from the unzipping data. Our approach relies on the use of statistical Bayesian inference and of Viterbi decoding algorithm. Performances are studied numerically on Monte Carlo generated data, and analytically. We show how multiple unzippings of the same molecule may be exploited to improve the quality of the prediction, and calculate analytically the number of required unzippings as a function of the bandwidth, the sequence content, the elasticity parameters of the unzipped strands

Future Scenarios for the Pampulha Region: A Geodesign Workshop

The paper describes the processes, workflow and results of a Geodesign workshop held by the authors in Belo Horizonte, Brazil in 2015. The participants were involved in the design of sustainable future alternatives for the urban district of Pampulha – an area characterized by complex conflicting interests concerning both development and landscape preservation. The scenarios were created on the basis of set objectives and priorities by six stakeholder groups, and assessed on the basis of ten evaluation systems. During the workshop, the use of a collaborative design support system (Geodesign Hub) facilitated the creation of design proposals informed by geographic context operatively enabling the application of the Steinitz’ Geodesign framework. The integration of information technologies in the planning process enabled the collaboration between the various actors involved simplifying the interactive scenario impact simulation and decision-making through real time performance analysis and quick negotiation cycles. Overall the Geodesign framework application with the Geodesign Hub platform proved to be a successful novel approach enabling to address some of the major traditional planning issues such as collaboration and negotiation in design and decision-making