1,728 research outputs found

    Puromycin Sensitivity of Ribosomal Label after Incorporation of 14C-Labelled Amino Acids into Isolated Mitochondria from Neurospora crassa

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    Radioactive amino acids were incorporated into isolated mitochondria from Neurospora crassa. Then the mitochondrial ribosomes were isolated and submitted to density gradient centrifugation. A preferential labelling of polysomes was observed. However, when the mitochondrial suspension was treated with puromycin after amino acid incorporation, no radioactivity could be detected in either the monosomes or the polysomes. The conclusion is drawn that isolated mitochondria under these conditions do not incorporate significant amounts of amino acids into proteins of their ribosomes

    A Unifying View of Multiple Kernel Learning

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    Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different formulations of objectives and varying regularization strategies. In this paper we present a unifying general optimization criterion for multiple kernel learning and show how existing formulations are subsumed as special cases. We also derive the criterion's dual representation, which is suitable for general smooth optimization algorithms. Finally, we evaluate multiple kernel learning in this framework analytically using a Rademacher complexity bound on the generalization error and empirically in a set of experiments

    Higher leptin is associated with hypertension: the Multi-Ethnic Study of Atherosclerosis

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    Adipokines are secreted from adipose tissue, influence energy homeostasis and may contribute to the association between obesity and hypertension. Among 1897 participants enrolled in the Multi-Ethnic Study of Atherosclerosis, we examined associations between blood pressure and leptin, tumor necrosis factor-α (TNFα), resistin and total adiponectin. The mean age and body mass index (BMI) was 64.7 years and 28.1, respectively, and 50% were female. After adjustment for risk factors, a 1-s.d.-increment higher leptin level was significantly associated with higher systolic (5.0 mm Hg), diastolic (1.9), mean arterial (2.8) and pulse pressures (3.6), as well as a 34% higher odds for being hypertensive (P<0.01 for all). These associations were not materially different when the other adipokines, as well as BMI, waist circumference or waist-to-hip ratio, were additionally added to the model. Notably, the associations between leptin and hypertension were stronger in men, but were not different by race/ethnic group, BMI or smoking status. Adiponectin, resistin and TNFα were not independently associated with blood pressure or hypertension. Higher serum leptin, but not adiponectin, resistin or TNFα, is associated with higher levels of all measures of blood pressure, as well as a higher odds of hypertension, independent of risk factors, anthropometric measures and other selected adipokines

    Low-frequency characterization of quantum tunneling in flux qubits

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    We propose to investigate flux qubits by the impedance measurement technique (IMT), currently used to determine the current--phase relation in Josephson junctions. We analyze in detail the case of a high-quality tank circuit coupled to a persistent-current qubit, to which IMT was successfully applied in the classical regime. It is shown that low-frequency IMT can give considerable information about the level anticrossing, in particular the value of the tunneling amplitude. An interesting difference exists between applying the ac bias directly to the tank and indirectly via the qubit. In the latter case, a convenient way to find the degeneracy point in situ is described. Our design only involves existing technology, and its noise tolerance is quantitatively estimated to be realistic.Comment: 6 pages, 11 figures, to appear in Phys.Rev.

    Inhibition in multiclass classification

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    The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

    Inhibition in multiclass classification

    Get PDF
    The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

    Precursors of Cytochrome Oxidase in Cytochrome-Oxidase-Deficient Cells of Neurospora crassa

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    Three different cell types of Neurospora crassa deficient in cytochrome oxidase were studied: the nuclear mutant cni-1, the cytoplasmic mutant mi-1 and copper-depleted wild-type cells. * 1. The enzyme-deficient cells have retained a functioning mitochondrial protein synthesis. It accounted for 12–16% of the total protein synthesis of the cell. However, the analysis of mitochondrial translation products by gel electrophoresis revealed that different amounts of individual membrane proteins were synthesized. Especially mutant cni-1 produced large amounts of a small molecular weight translation product, which is barely detectable in wild-type. * 2. Mitochondrial preparations of cytochrome-oxidase-deficient cells were examined for precursors of cytochrome oxidase. The presence of polypeptide components of cytochrome oxidase in the mitochondria was established with specific antibodies. On the other hand, no significant amounts of heme a could be extracted. * 3. Radioactively labelled components of cytochrome oxidase were isolated by immunoprecipitation and analysed by gel electrophoresis. All three cell types contained the enzyme components 4–7, which are translated on cytoplasmic ribosomes. The mitochondrially synthesized components 1–3 were present in mi-1 mutant and in copper-depleted wild-type cells. In contrast, components 2 and 3 were not detectable in the nuclear mutant cni-1. Both relative and absolute amounts of these polypeptides in the enzyme-deficient cells were quite different from those in wild-type cells. * 4. The components of cytochrome oxidase found in the enzyme-deficient cells were tightly associated with the mitochondrial membranes. * 5. Processes, which affect and may control the production of enzyme precursors or their assembly to a functional cytochrome oxidase are discussed

    Introduction: Ambidextrous open innovation in the 4th Industrial Revolution

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    With the popularity of artificial intelligence, big data and Internet of Things, business nowadays is featured with technology advancement, open innovation and collaboration. This happens particularly in the manufacturing sectors, known as the Industrial 4.0 or the 4th Industrial Revolution. Alongside this trend, there is also a movement towards servitisation and service innovation. In the financial service sector, FinTech firms, traditional large firms, intermediaries, users and regulators are actively engaged together to develop a smart system of banking, investing and insurance service. Nevertheless, the sector is facing challenges in relation to security, trust and external disruptions. To solve this, first, this article builds an ambidextrous open innovation model with multi-dimensions, which are motivated by the arriving of the 4th Industrial Revolution. Second, this article applies the ambidextrous open innovation model with multi-dimensions to the financial sectors to validate the model basically. Third, this model is applied to several research studies to obtain additional validation of it
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