182 research outputs found

    Detailed Studies of Pixelated CZT Detectors Grown with the Modified Horizontal Bridgman Method

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    The detector material Cadmium Zinc Telluride (CZT), known for its high resolution over a broad energy range, is produced mainly by two methods: the Modified High-Pressure Bridgman (MHB) and the High-Pressure Bridgman (HPB) process. This study is based on MHB CZT substrates from the company Orbotech Medical Solutions Ltd. with a detector size of 2.0x2.0x0.5 cm^3, 8x8 pixels and a pitch of 2.46 mm. Former studies have emphasized only on the cathode material showing that high-work-function improve the energy resolution at lower energies. Therfore, we studied the influence of the anode material while keeping the cathode material constant. We used four different materials: Indium, Titanium, Chromium and Gold with work-functions between 4.1 eV and 5.1 eV. The low work-function materials Indium and Titanium achieved the best performance with energy resolutions: 2.0 keV (at 59 keV) and 1.9 keV (at 122 keV) for Titanium; 2.1 keV (at 59 keV) and 2.9 keV (at 122 keV) for Indium. These detectors are very competitive compared with the more expensive ones based on HPB material if one takes the large pixel pitch of 2.46 mm into account. We present a detailed comparison of our detector response with 3-D simulations, from which we determined the mobility-lifetime-products for electrons and holes. Finally, we evaluated the temperature dependency of the detector performance and mobility-lifetime-products, which is important for many applications. With decreasing temperature down to -30C the breakdown voltage increases and the electron mobility-lifetime-product decreases by about 30% over a range from 20C to -30C. This causes the energy resolution to deteriorate, but the concomitantly increasing breakdown voltage makes it possible to increase the applied bias voltage and restore the full performance.Comment: Accepted for publication in Astroparticle Physics, 25 pages, 13 figure

    A learning-based algorithm to quickly compute good primal solutions for Stochastic Integer Programs

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    We propose a novel approach using supervised learning to obtain near-optimal primal solutions for two-stage stochastic integer programming (2SIP) problems with constraints in the first and second stages. The goal of the algorithm is to predict a "representative scenario" (RS) for the problem such that, deterministically solving the 2SIP with the random realization equal to the RS, gives a near-optimal solution to the original 2SIP. Predicting an RS, instead of directly predicting a solution ensures first-stage feasibility of the solution. If the problem is known to have complete recourse, second-stage feasibility is also guaranteed. For computational testing, we learn to find an RS for a two-stage stochastic facility location problem with integer variables and linear constraints in both stages and consistently provide near-optimal solutions. Our computing times are very competitive with those of general-purpose integer programming solvers to achieve a similar solution quality

    Linear Minimax Regret Estimation of Deterministic Parameters with Bounded Data Uncertainties

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    Freezing of Spinodal Decompostion by Irreversible Chemical Growth Reaction

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    We present a description of the freezing of spinodal decomposition in systems, which contain simultaneous irreversible chemical reactions, in the hydrodynamic limit approximation. From own results we conclude, that the chemical reaction leads to an onset of spinodal decomposition also in the case of an initial system which is completely miscible and can lead to an extreme retardation of the dynamics of the spinodal decomposition, with the probability of a general freezing of this process, which can be experimetally observed in simultaneous IPN formation.Comment: 10 page

    Beyond local Nash equilibria for adversarial networks

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    Save for some special cases, current training methods for Generative Adversarial Networks (GANs) are at best guaranteed to converge to a ‘local Nash equilibrium’ (LNE). Such LNEs, however, can be arbitrarily far from an actual Nash equilibrium (NE), which implies that there are no guarantees on the quality of the found generator or classifier. This paper proposes to model GANs explicitly as finite games in mixed strategies, thereby ensuring that every LNE is an NE. We use the Parallel Nash Memory as a solution method, which is proven to monotonically converge to a resource-bounded Nash equilibrium. We empirically demonstrate that our method is less prone to typical GAN problems such as mode collapse and produces solutions that are less exploitable than those produced by GANs and MGANs

    In vitro studies on the relationship between the antioxidant activities of some berry extracts and their binding properties to serum albumin

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    The aim of this study was to investigate the possibility to use the bioactive components from cape gooseberry (Physalis peruviana), blueberry (Vaccinium corymbosum), and cranberry (Vaccinium macrocarpon) extracts as a novel source against oxidation in food supplementation. The quantitative analysis of bioactive compounds (polyphenols, flavonoids, flavanols, carotenoids, and chlorophyll) was based on radical scavenging spectrophometric assays and mass spectrometry. The total phenolic content was the highest (P < 0.05) in water extract of blueberries (46.6 ± 4.2 mg GAE/g DW). The highest antioxidant activities by 2,2-diphenyl-1-picrylhydrazyl radical scavenging assay and Cupric reducing antioxidant capacity were in water extracts of blueberries, showing 108.1 ± 7.2 and 131.1 ± 9.6 μMTE/g DW with correlation coefficients of 0.9918 and 0.9925, and by β-carotene linoleate assay at 80.1 ± 6.6 % with correlation coefficient of 0.9909, respectively. The water extracts of berries exhibited high binding properties with human serum albumin in comparison with quercetin. In conclusion, the bioactive compounds from a relatively new source of gooseberries in comparison with blueberries and cranberries have the potential as food supplementation for human health. The antioxidant and binding activities of berries depend on their bioactive compounds

    Rescaled coordinate descent methods for linear programming

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    We propose two simple polynomial-time algorithms to find a positive solution to Ax=0Ax=0 . Both algorithms iterate between coordinate descent steps similar to von Neumann’s algorithm, and rescaling steps. In both cases, either the updating step leads to a substantial decrease in the norm, or we can infer that the condition measure is small and rescale in order to improve the geometry. We also show how the algorithms can be extended to find a solution of maximum support for the system Ax=0Ax=0 , x≥0x≥0 . This is an extended abstract. The missing proofs will be provided in the full version
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