8,517 research outputs found

    Antifouling bastadin congeners target blue mussel phenoloxidase and complex copper(II) ions

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    Synthetically prepared congeners of spongederived bastadin derivatives such as 5,5'-dibromohemibastadin- 1 (DBHB) that suppress the settling of barnacle larvae were identified in this study as strong inhibitors of blue mussel phenoloxidase that is involved in the firm attachment of mussels to a given substrate. The IC50 value of DBHB as the most active enzyme inhibitor encountered in this study amounts to 0.84 mu M. Inhibition of phenoloxidase by DBHB is likely due to complexation of copper(II) ions from the catalytic centre of the enzyme by the a-oxo-oxime moiety of the compound as shown here for the first time by structure activity studies and by X-ray structure determination of a copper(II) complex of DBHB.Biotechnology & Applied MicrobiologyMarine & Freshwater BiologySCI(E)EI0ARTICLE61148-11581

    Corruption in bank lending to firms : do competition and information sharing matter?

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    Building on the important study by Beck, Demirguc-Kunt and Levine (2006), we examine the effects of borrower and lender competition and information sharing νia credit registries/bureaus on corruption in bank lending. Using the unique World Bank dataset of the World Business Environment Survey (WBES) covering 58 countries and information on credit registries/bureaus and bank regulation assembled by other scholars, we find (1) strong evidence that banking competition reduces lending corruption and (2) the first and robust evidence that information sharing among banks (especially via private bureaus) contributes to reducing corruption in bank lending. We also find that government- and foreign-owned firms as well as exporting firms tend to be subject to less lending corruption, objective courts and better law enforcement tend to reduce lending corruption, and private and foreign ownership of the banking industry are associated with more integrity in lending. These findings pass a number of robustness tests and they are consistent with the predictions of a Nash bargaining model

    The Gradient Model Load Balancing Method

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    A dynamic load balancing method is proposed for a class of large-diameter multiprocessor systems. The method is based on the gradient model, which entails transferring backlogged tasks to nearby idle processors according to a pressure gradient indirectly established by requests from idle processors. The algorithm is fully distributed and asynchronous. Global balance is achieved by successive refinements of many localized balances. The gradient model is formulated so as to be independent of system topology

    Simulated Performance of a Reduction-Based Multiprocessing System

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    Multiprocessing systems have the potential for increasing system speed over what is now offered by device technology. They must provide the means of generating work for the processors, getting the work to processors, and coherently collecting the results from the processors. For most applications, they should also ensure the repeatability of behavior, i.e., determinacy, speed-independence, or elimination of critical races. Determinacy can be destroyed, for example, by permitting-in separate, concurrent processes statements such as x: = x + 1 and if x = 0 then… else… , which share a common variable. Here, there may be a critical race, in that more than one global outcome is possible, depending on execution order. But by basing a multiprocessing system on functional languages, we can avoid such dangers. Our concern is the construction of multiprocessors that can be programmed in a logically transparent fashion. In other words, the programmer should not be aware of programming a multiprocessor versus a uniprocessor, except for optimizing performance for a specific configuration. This means that the programmer should not have to set up processes explicitly to achieve concurrent processing, nor be concerned with synchronizing such processes. Multiprocessor systems present unique concurrency problems. Rediflow combines disciplined von Neumann processes with a hybrid reduction and dataflow model in an effective packet-switching network

    Distributed Recovery in Applicative Systems

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    Applicative systems are promising candidates for achieving high performance computing through aggregation of processors. This paper studies the fault recovery problems in a class of applicative systems. The concept of functional checkpointing is proposed as the nucleus of a distributed recovery mechanism. This entails incrementally building a resilient structure as the evaluation of an applicative program proceeds. A simple rollback algorithm is suggested to regenerate the corrupted structure by redoing the most effective functional checkpoints. Another algorithm, which attempts to recover intermediate results, is also presented. The parent of a faulty task reproduces a functional twin of the failed task. The regenerated task inherits all offspring of the faulty task so that partial results can be salvaged

    Thermodynamical Consistent Modeling and Analysis of Nematic Liquid Crystal Flows

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    The general Ericksen-Leslie system for the flow of nematic liquid crystals is reconsidered in the non-isothermal case aiming for thermodynamically consistent models. The non-isothermal model is then investigated analytically. A fairly complete dynamic theory is developed by analyzing these systems as quasilinear parabolic evolution equations in an Lp−LqL^p-L^q-setting. First, the existence of a unique, local strong solution is proved. It is then shown that this solution extends to a global strong solution provided the initial data are close to an equilibrium or the solution is eventually bounded in the natural norm of the underlying state space. In these cases, the solution converges exponentially to an equilibrium in the natural state manifold
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