92 research outputs found

    Energy Flow in the Hadronic Final State of Diffractive and Non-Diffractive Deep-Inelastic Scattering at HERA

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    An investigation of the hadronic final state in diffractive and non--diffractive deep--inelastic electron--proton scattering at HERA is presented, where diffractive data are selected experimentally by demanding a large gap in pseudo --rapidity around the proton remnant direction. The transverse energy flow in the hadronic final state is evaluated using a set of estimators which quantify topological properties. Using available Monte Carlo QCD calculations, it is demonstrated that the final state in diffractive DIS exhibits the features expected if the interaction is interpreted as the scattering of an electron off a current quark with associated effects of perturbative QCD. A model in which deep--inelastic diffraction is taken to be the exchange of a pomeron with partonic structure is found to reproduce the measurements well. Models for deep--inelastic epep scattering, in which a sizeable diffractive contribution is present because of non--perturbative effects in the production of the hadronic final state, reproduce the general tendencies of the data but in all give a worse description.Comment: 22 pages, latex, 6 Figures appended as uuencoded fil

    A Search for Selectrons and Squarks at HERA

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    Data from electron-proton collisions at a center-of-mass energy of 300 GeV are used for a search for selectrons and squarks within the framework of the minimal supersymmetric model. The decays of selectrons and squarks into the lightest supersymmetric particle lead to final states with an electron and hadrons accompanied by large missing energy and transverse momentum. No signal is found and new bounds on the existence of these particles are derived. At 95% confidence level the excluded region extends to 65 GeV for selectron and squark masses, and to 40 GeV for the mass of the lightest supersymmetric particle.Comment: 13 pages, latex, 6 Figure

    Solubilization of Proteins in 2DE: An Outline

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    Protein solubilization for two-dimensional electrophoresis (2DE) has to break molecular interactions to separate the biological contents of the material of interest into isolated and intact polypeptides. This must be carried out in conditions compatible with the first dimension of 2DE, namely isoelectric focusing. In addition, the extraction process must enable easy removal of any nonprotein component interfering with the isoelectric focusing. The constraints brought in this process by the peculiar features of isoelectric focusing are discussed, as well as their consequences in terms of possible solutions and limits for the solubilization process

    Executive Incentive Schemes in Initial Public Offerings: The Effects of Multiple-Agency Conflicts and Corporate Governance

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    Combining a behavioral agency perspective with research on multiple-agency conflicts, this article examines factors affecting the implementation of equity-based incentive schemes in initial public offerings (IPOs). With a unique sample of U.K. IPO companies between the years 1998 and 2002, it shows that conditional (performance-related) incentive schemes are negatively associated with share ownership and board power of the IPO’s founding directors. However, the retained ownership of venture capital firms is positively associated with the probability of conditional incentive schemes. Board independence weakly effects on the toughness of executive compensation. The article’s interesting findings suggest a number of avenues for a future analysis of the governance development process in threshold firms

    PRIMARY HYPEROXALURIA TYPE-1 - GENOTYPIC AND PHENOTYPIC HETEROGENEITY

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    Primary hyperoxaluria type 1 (PH1) is an autosomal recessive disease caused by a deficiency of the liver-specific peroxisomal enzyme alanine: glyoxylate aminotransferase (AGT). The disease is notable for its extensive heterogeneity at the clinical, biochemical, enzymic and molecular genetic levels. A study of 116 PH1 patients over the past 8 years has revealed four main enzymic phenotypes: (1) absence of both AGT catalytic activity and immunoreactive AGT protein (similar to 40% of patients); (2) absence of AGT catalytic activity but presence of immunoreactive protein (similar to 16% of patients); (3) presence of both AGT catalytic activity and immunoreactive protein (similar to 41% of patients), in most of which cases the AGT is mistargeted to the mitochondria instead of the peroxisomes; and (4) a variation of the mistargeting phenotype in which AGT is equally distributed between peroxisomes and mitochondria, but in which that in the peroxisomes is aggregated into matrical core-like structures (similar to 3% of patients). Various point mutations, all occurring at conserved positions in the coding regions of the AGT gene, have been identified in these patients. The five mutations discussed in the present study, which have been found in individuals manifesting all of the four major enzymic phenotypes, account for the expressed alleles in about half of all Caucasian PH1 patients. The most common mutation found so far leads to a Gly170 --> Arg amino acid substitution. This mutation, in combination with a normally occurring Pro 11 --> Leu polymorphism, appears to be responsible for the unprecedented peroxisome-to-mitochondrion mistargeting phenotype

    Probabilistic Algorithms for the Wakeup Problem in Single-Hop Radio Networks

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    We consider the problem of waking up n processors in a completely broadcast system. We analyze this problem in both globally and locally synchronous models, with or without n being known to processors and with or without labeling of processors. The main question we answer is: how fast we can wake all the processors up with probability 1-e in each of these eight models. In [11] a logarithmic waking algorithm for the strongest set of assumptions is described, while for weaker models only linear and quadratic algorithms were obtained. We prove that in the weakest model (local synchronization, no knowledge of n or labeling) the best waking time is O(n/logn). We also show logarithmic or polylogarithmic waking algorithms for all stronger models, which in some cases gives an exponential improvement over previous results
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