2,626 research outputs found

    The Apparent Madness of Crowds: Irrational collective behavior emerging from interactions among rational agents

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    Standard economic theory assumes that agents in markets behave rationally. However, the observation of extremely large fluctuations in the price of financial assets that are not correlated to changes in their fundamental value, as well as the extreme instance of financial bubbles and crashes, imply that markets (at least occasionally) do display irrational behavior. In this paper, we briefly outline our recent work demonstrating that a market with interacting agents having bounded rationality can display price fluctuations that are {\em quantitatively} similar to those seen in real markets.Comment: 4 pages, 1 figure, to appear in Proceedings of International Workshop on "Econophysics of Stock Markets and Minority Games" (Econophys-Kolkata II), Feb 14-17, 200

    The single-finger keyboard layout problem

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    The problem of designing new keyboards layouts able to improve the typing speed of an average message has been widely considered in the literature of the Ergonomics domain. Empirical tests with users and simple optimization criteria have been used to propose new solutions. On the contrary, very few papers in Operations Research have addressed this optimization problem. In this paper we firstly resume the most relevant problems in keyboard design, enlightening the related Ergonomics aspects. Then we concentrate on keyboards that must be used witha single finger or stylus, like that of Portable Data Assistant, Smartphones and other small devices.We show that the underlying optimization problem is a generalization of the well known Quadratic Assignment Problem (QAP). We recall some of the most effective metaheuristic algorithms for QAP and we propose some non trivial extensions to the keyboard design problem. We compare the new algorithms through computational experiments with instances obtained from word lists of the English, French, Italian and Spanish languages. We provide on the web benchmark instances for each language and the best solutions we obtained

    A Location-allocation model for fog computing infrastructures

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    The trend of an ever-increasing number of geographically distributed sensors producing data for a plethora of applications, from environmental monitoring to smart cities and autonomous driving, is shifting the computing paradigm from cloud to fog. The increase in the volume of produced data makes the processing and the aggregation of information at a single remote data center unfeasible or too expensive, while latency-critical applications cannot cope with the high network delays of a remote data center. Fog computing is a preferred solution as latency-sensitive tasks can be moved closer to the sensors. Furthermore, the same fog nodes can perform data aggregation and filtering to reduce the volume of data that is forwarded to the cloud data centers, reducing the risk of network overload. In this paper, we focus on the problem of designing a fog infrastructure considering both the location of how many fog nodes are required, which nodes should be considered (from a list of potential candidates), and how to allocate data flows from sensors to fog nodes and from there to cloud data centers. To this aim, we propose and evaluate a formal model based on a multi-objective optimization problem. We thoroughly test our proposal for a wide range of parameters and exploiting a reference scenario setup taken from a realistic smart city application. We compare the performance of our proposal with other approaches to the problem available in literature, taking into account two objective functions. Our experiments demonstrate that the proposed model is viable for the design of fog infrastructure and can outperform the alternative models, with results that in several cases are close to an ideal solution

    The molecular class C acid phosphatase of Chryseobacterium meningosepticum (OlpA) is a broad-spectrum nucleotidase with preferential activity on 5'-nucleotides

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    The olpA gene of Chryseobacterium meningosepticum, encoding a molecular class C phosphatase, was cloned and expressed in Escherichia coli. The gene encodes a 29-kDa polypeptide containing an amino-terminal signal peptide typical of bacterial membrane lipoproteins. Expression in E. coli results in a functional product that mostly partitions in the outer membrane. A secreted soluble OlpA derivative (sOlpA) lacking the N-terminal cysteine residue for lipid anchoring was produced in E. coli and purified by means of two steps of ion exchange chromatography. Analysis of the kinetic parameters of sOlpA with several organic phosphoesters revealed that the enzyme was able to efficiently hydrolyze nucleotide monophosphates, with a strong preference for 5'-nucleotides and for 3'-AMP. The enzyme was also able to hydrolyze sugar phosphates and beta-glycerol phosphate, although with a lower efficiency, whereas it was apparently inactive against nucleotide di- and triphosphates, diesters, and phytate. OlpA, therefore, can be considered a broad-spectrum nucleotidase with preference for 5'-nucleotides. Its functional behaviour exhibits differences from that of the Haemophilus influenzae OMP P4 lipoprotein, revealing functional heterogeneity among phosphatases of molecular class C

    A Variational Approach for Minimizing Lennard-Jones Energies

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    A variational method for computing conformational properties of molecules with Lennard-Jones potentials for the monomer-monomer interactions is presented. The approach is tailored to deal with angular degrees of freedom, {\it rotors}, and consists in the iterative solution of a set of deterministic equations with annealing in temperature. The singular short-distance behaviour of the Lennard-Jones potential is adiabatically switched on in order to obtain stable convergence. As testbeds for the approach two distinct ensembles of molecules are used, characterized by a roughly dense-packed ore a more elongated ground state. For the latter, problems are generated from natural frequencies of occurrence of amino acids and phenomenologically determined potential parameters; they seem to represent less disorder than was previously assumed in synthetic protein studies. For the dense-packed problems in particular, the variational algorithm clearly outperforms a gradient descent method in terms of minimal energies. Although it cannot compete with a careful simulating annealing algorithm, the variational approach requires only a tiny fraction of the computer time. Issues and results when applying the method to polyelectrolytes at a finite temperature are also briefly discussed.Comment: 14 pages, uuencoded compressed postscript fil

    Delineation of the Native Basin in Continuum Models of Proteins

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    We propose two approaches for determining the native basins in off-lattice models of proteins. The first of them is based on exploring the saddle points on selected trajectories emerging from the native state. In the second approach, the basin size can be determined by monitoring random distortions in the shape of the protein around the native state. Both techniques yield the similar results. As a byproduct, a simple method to determine the folding temperature is obtained.Comment: REVTeX, 6 pages, 5 EPS figure

    Sequence Dependence of Self-Interacting Random Chains

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    We study the thermodynamic behavior of the random chain model proposed by Iori, Marinari and Parisi, and how this depends on the actual sequence of interactions along the chain. The properties of randomly chosen sequences are compared to those of designed ones, obtained through a simulated annealing procedure in sequence space. We show that the transition to the folded phase takes place at a smaller strength of the quenched disorder for designed sequences. As a result, folding can be relatively fast for these sequences.Comment: 14 pages, uuencoded compressed postscript fil
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