Uncovering the topology of configuration space networks

The configuration space network (CSN) of a dynamical system is an effective approach to represent the ensemble of configurations sampled during a simulation and their dynamic connectivity. To elucidate the connection between the CSN topology and the underlying free-energy landscape governing the system dynamics and thermodynamics, an analytical soluti on is provided to explain the heavy tail of the degree distribution, neighbor co nnectivity and clustering coefficient. This derivation allows to understand the universal CSN network topology observed in systems ranging from a simple quadratic well to the native state of the beta3s peptide and a 2D lattice heteropolymer. Moreover CSN are shown to fall in the general class of complex networks describe d by the fitness model.Comment: 6 figure

On the criticality of inferred models

Advanced inference techniques allow one to reconstruct the pattern of interaction from high dimensional data sets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to a phase transition. On one side, we show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher Information) is directly related to the model's susceptibility. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. On the other, this region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time-scales naturally yield models which are close to criticality.Comment: 6 pages, 2 figures, version to appear in JSTA

A simple mean field model for social interactions: dynamics, fluctuations, criticality

We study the dynamics of a spin-flip model with a mean field interaction. The system is non reversible, spacially inhomogeneous, and it is designed to model social interactions. We obtain the limiting behavior of the empirical averages in the limit of infinitely many interacting individuals, and show that phase transition occurs. Then, after having obtained the dynamics of normal fluctuations around this limit, we analize long time fluctuations for critical values of the parameters. We show that random inhomogeneities produce critical fluctuations at a shorter time scale compared to the homogeneous system.Comment: 37 pages, 2 figure

Beyond inverse Ising model: structure of the analytical solution for a class of inverse problems

I consider the problem of deriving couplings of a statistical model from measured correlations, a task which generalizes the well-known inverse Ising problem. After reminding that such problem can be mapped on the one of expressing the entropy of a system as a function of its corresponding observables, I show the conditions under which this can be done without resorting to iterative algorithms. I find that inverse problems are local (the inverse Fisher information is sparse) whenever the corresponding models have a factorized form, and the entropy can be split in a sum of small cluster contributions. I illustrate these ideas through two examples (the Ising model on a tree and the one-dimensional periodic chain with arbitrary order interaction) and support the results with numerical simulations. The extension of these methods to more general scenarios is finally discussed.Comment: 15 pages, 6 figure

Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior

Despite the availability of very detailed data on financial market, agent-based modeling is hindered by the lack of information about real trader behavior. This makes it impossible to validate agent-based models, which are thus reverse-engineering attempts. This work is a contribution to the building of a set of stylized facts about the traders themselves. Using the client database of Swissquote Bank SA, the largest on-line Swiss broker, we find empirical relationships between turnover, account values and the number of assets in which a trader is invested. A theory based on simple mean-variance portfolio optimization that crucially includes variable transaction costs is able to reproduce faithfully the observed behaviors. We finally argue that our results bring into light the collective ability of a population to construct a mean-variance portfolio that takes into account the structure of transaction costsComment: 26 pages, 9 figures, Fig. 8 fixe

Using a community-based definition of poverty for targeting poor households for premium subsidies in the context of a community health insurance in Burkina Faso

Background: One of the biggest challenges in subsidizing premiums of poor households for community health insurance is the identification and selection of these households. Generally, poverty assessments in developing countries are based on monetary terms. The household is regarded as poor if its income or consumption is lower than a predefined poverty cut-off. These measures fail to recognize the multi-dimensional character of poverty, ignoring community members? perception and understanding of poverty, leaving them voiceless and powerless in the identification process. Realizing this, the steering committee of Nouna's health insurance devised a method to involve community members to better define `perceived? poverty, using this as a key element for the poor selection. The community-identified poor were then used to effectively target premium subsidies for the insurance scheme. Methods: The study was conducted in the Nouna's Health District located in northwest Burkina Faso. Participants in each village were selected to take part in focus-group discussions (FGD) organized in 41 villages and 7 sectors of Nouna's town to discuss criteria and perceptions of poverty. The discussions were audio recorded, transcribed and analyzed in French using the software NVivo 9. Results: From the FGD on poverty and the subjective definitions and perceptions of the community members, we found that poverty was mainly seen as scarcity of basic needs, vulnerability, deprivation of capacities, powerlessness, voicelessness, indecent living conditions, and absence of social capital and community networks for support in times of need. Criteria and poverty groups as described by community members can be used to identify poor who can then be targeted for subsidies. Conclusion: Policies targeting the poorest require the establishment of effective selection strategies. These policies are well-conditioned by proper identification of the poor people. Community perceptions and criteria of poverty are grounded in reality, to better appreciate the issue. It is crucial to take these perceptions into account in undertaking community development actions which target the poor. For most community-based health insurance schemes with limited financial resources, using a community-based definition of poverty in the targeting of the poorest might be a less costly alternative

Dpp Signaling Activity Requires Pentagone to Scale with Tissue Size in the Growing Drosophila Wing Imaginal Disc

The activity of the Dpp morphogen adapts to tissue size in the growing Drosophila wing imaginal disc, and Pentagone, an important secreted feedback regulator of the Dpp pathway, is required for this adaptation

GenomegaMap: Within-Species Genome-Wide dN=dS Estimation from over 10,000 Genomes

The dN=dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters, such as dN=dS, but analyzing very large data sets poses a major statistical challenge. Here, I introduce genomegaMap for estimating within-species genome-wide variation in dN=dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: 1) It is fast no matter how large the sample size and 2) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well estimated even when genomegaMap's simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in Mycobacterium tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species

Evidence-Based Management of Hand Eczema

Hand eczema is a common skin disease with a wide variation in morphology and a complex etiology based on endogenous and exogenous factors.The diagnosis of hand eczema is based on patient history, exposure assessment, physical examination, and the results of patch testing. Management of hand eczema starts with education of the patient on the etiology of the disease, and the needed changes in behavior regarding skin care and preventive measures, and avoidance of relevant exposure factors. In many cases, medical treatment is needed for successful management of the disease; use of medication can only be successful with proper education and avoidance of relevant exposure