733 research outputs found

    Qualitative Research in Sport Management: Case Study as a Methodological Approach

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    This paper presents qualitative research in sport management and suggests that case study is an appropriate qualitative methodology for research and practice in sport finance. The purpose of qualitative methodology is presented along with the process of a case study. The intention of this paper, for academicians working in sport management, is twofold. The first aspect is for researchers to consider using qualitative case study methodology in instances where such practice will progress the knowledge and understanding of specific situations while invoking a deeper response to research questions. The second facet of this paper focuses on the framework of case study methodology, as applied to a research project in the field of sport finance

    A new Method for Computing One-Loop Integrals

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    We present a new program package for calculating one-loop Feynman integrals, based on a new method avoiding Feynman parametrization and the contraction due to Passarino and Veltman. The package is calculating one-, two- and three-point functions both algebraically and numerically to all tensor cases. This program is written as a package for Maple. An additional Mathematica version is planned later.Comment: 12 pages Late

    Isolation, production, purification, assay and characterization of fibrinolytic enzymes (Nattokinase, Streptokinase and Urokinase) from bacterial sources

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    Nattokinase, Streptokinase and Urokinase are novel fibrinolytic enzymes which are isolated from Bacillus subtilis, β-haemolytic Streptococci and urine sample. The fibrinolytic enzyme Nattokinase, Streptokinase and Urokinase was purified from supernatant of Bacillus subtilis, β-haemolytic Streptococci and recombinant E.coli containing short fragment genomic DNA of Pseudomonas sp. Culture broth and showed thermophilic, hydrophilic, and strong fibrinolytic activity. The optimum temperature and pH of Nattokinase, Streptokinase and Urokinase were 37-55°C and 9, 27-37°C and 7 and 55°C and 9, respectively. The molecular weight of Nattokinase, Streptokinase and Urokinase was approximately 28 kDa, 47 kDa and 34 kDa, respectively, as determined by sodium dodecyl sulfatepolyacrylamide gel electrophoresis. The caseinolytic activity of Nattokinase, Streptokinase and Urokinase were 576.73 U, 467.73 U and 785.73 U, respectively, while fibrinolytic activity achieved by fibrin plate method were 10 U, 5 U and 15 U, respectively.Key words: Anticoagulant activity, submerge fermentation, fibrinolytic enzyme activity, protein fraction precipitation, casein, serum and plasminogen plate technique, enzyme thermodynamics, haemolytic activity, enzyme screening, expression system, zymography, Edman degradation

    Mining the ESO WFI and INT WFC archives for known Near Earth Asteroids. Mega-Precovery software

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    The ESO/MPG WFI and the INT WFC wide field archives comprising 330,000 images were mined to search for serendipitous encounters of known Near Earth Asteroids (NEAs) and Potentially Hazardous Asteroids (PHAs). A total of 152 asteroids (44 PHAs and 108 other NEAs) were identified using the PRECOVERY software, their astrometry being measured on 761 images and sent to the Minor Planet Centre. Both recoveries and precoveries were reported, including prolonged orbital arcs for 18 precovered objects and 10 recoveries. We analyze all new opposition data by comparing the orbits fitted before and after including our contributions. We conclude the paper presenting Mega-Precovery, a new online service focused on data mining of many instrument archives simultaneously for one or a few given asteroids. A total of 28 instrument archives have been made available for mining using this tool, adding together about 2.5 million images forming the Mega-Archive.Comment: Accepted for publication in Astronomische Nachrichten (Sep 2012

    Cylindrical chains of water drops condensing on microstructured lubricant-infused surfaces

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    We studied the condensation of water drops on a micro-structured lubricant-infused surfaces. Hierarchical micro-prism surfaces were fabricated by soft imprinting with wet TiO2 nanoparticle paste. After hydrophobization, the patterned surfaces were infused with silicone oil as a lubricant. When cooling at high humidity (over 80%), water drops nucleate and start growing on the surface. Once they have reached a certain size, the drops at neighboring channels of the micro-prisms attract each other and spontaneously form cylindrical chains. These chains of drops align perpendicular to the prism array. The morphology and the length-to-width ratio of the chains of drops depend on the thickness of the lubricant layer. This new concept of water drop alignment on lubricant-infused surfaces offers a new route for pattern formation with condensed drops.N

    Exploration via Planning for Information about the Optimal Trajectory

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    Many potential applications of reinforcement learning (RL) are stymied by the large numbers of samples required to learn an effective policy. This is especially true when applying RL to real-world control tasks, e.g. in the sciences or robotics, where executing a policy in the environment is costly. In popular RL algorithms, agents typically explore either by adding stochasticity to a reward-maximizing policy or by attempting to gather maximal information about environment dynamics without taking the given task into account. In this work, we develop a method that allows us to plan for exploration while taking both the task and the current knowledge about the dynamics into account. The key insight to our approach is to plan an action sequence that maximizes the expected information gain about the optimal trajectory for the task at hand. We demonstrate that our method learns strong policies with 2x fewer samples than strong exploration baselines and 200x fewer samples than model free methods on a diverse set of low-to-medium dimensional control tasks in both the open-loop and closed-loop control settings.Comment: Conference paper at Neurips 2022. Code available at https://github.com/fusion-ml/trajectory-information-rl. arXiv admin note: text overlap with arXiv:2112.0524
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