19,021 research outputs found

    The secondary stress at the details of orthotropic bridge decks induced by thermal gradient under solar radiation

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    To investigate the secondary stress of orthotropic steel decks (OSD) induced by thermal gradient in steel box girders, the temperature field of the steel box girder of a self-anchored suspension bridge is measured under high environmental temperature and strong solar radiation. The vertical temperature gradient is fitted based on the measured maximum temperature difference between the roof and the floor. After establishing the sectional box girder model in ANSYS with the measured temperature applied on the box-girder surface, the temperature field in the sectional model is obtained. The temperature results on the floor beam agree well with the measured temperature, which validate the thermal analysis. Based on the simulated 24 h temperature field, the thermal stress field in the sectional box girder is first analyzed. Refined stress results are obtained based on a sub-model technology. The thermal stress time histories are determined at the four details around rib-to-floor beam (RF) connection and the cutout detail. It is found that, under strong solar radiation and high environmental temperature, the transverse temperature difference in the steel-deck box girder is not apparent, while the vertical thermal gradient is significant and can be fitted as a four-broken-line function with the maximum temperature difference lower than that of the Eurocode. Significant stress concentration appears at the details of the OSD, particularly at the cutout detail. The cutout detail will be fatigue-free if the thermal stress range resulting from the vertical temperature under solar radiation is considered, or if the stress range resulting from the truck loading is considered. The stress range at the cutout detail, which is jointly produced by the thermal effect of the vertical temperature and by the truck loading, is larger than the constant-amplitude fatigue limit and may contribute to the fatigue crack at the cutout detail

    Corrigendum: The taeniaticornis-group of genus Apanteles Foerster (Hymenoptera, Braconidae, Microgastrinae) from China with one new species. Journal of Hymenoptera Research 96: 21–31. doi: 10.3897/jhr.96.99649

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    In a paper about a new species of Apanteles (Microgastrinae)(Liu & Chen, 2023), we regret the omission of one author Jun-hua Chen in the second place of the author list who did great job in construction of the ZJUH collection for this study and the mistake in institution order and corresponding author. We provide the correct information below.Zhen Liu1, 2, Jun-hua He1, Xue-xin Chen11 Institute of Insect Sciences, Zhejiang University, Hangzhou 310058, China. 2 Zoology Key Laboratory of Hunan Higher Education, College of Life and Environmental Sciences, Hunan University of Arts and Science, Changde 415000, China

    Going Beyond Traditional Characterizations in the Age of Big Data and Network Sciences (Invited Talk)

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    What are efficient algorithms? What are network models? Big Data and Network Sciences have fundamentally challenged the traditional polynomial-time characterization of efficiency and the conventional graph-theoretical characterization of networks. More than ever before, it is not just desirable, but essential, that efficient algorithms should be scalable. In other words, their complexity should be nearly linear or sub-linear with respect to the problem size. Thus, scalability, not just polynomial-time computability, should be elevated as the central complexity notion for characterizing efficient computation. For a long time, graphs have been widely used for defining the structure of social and information networks. However, real-world network data and phenomena are much richer and more complex than what can be captured by nodes and edges. Network data are multifaceted, and thus network science requires a new theory, going beyond traditional graph theory, to capture the multifaceted data. In this talk, I discuss some aspects of these challenges. Using basic tasks in network analysis, social influence modeling, and machine learning as examples, I highlight the role of scalable algorithms and axiomatization in shaping our understanding of "effective solution concepts" in data and network sciences, which need to be both mathematically meaningful and algorithmically efficient

    Yong yu you hua zhi bei chao leng yuan zi hun he wu de guang xue ou ji jing

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    Chen, Jun = 用於優化製備超冷原子混合物的光學偶極阱 / 陳軍.Thesis M.Phil. Chinese University of Hong Kong 2014.Includes bibliographical references (leaves 109-117).Abstracts also in Chinese.Title from PDF title page (viewed on 29, November, 2016).Chen, Jun = Yong yu you hua zhi bei chao leng yuan zi hun he wu de guang xue ou ji jing / Chen Jun

    sj-pdf-1-eso-10.1177_23969873231201712 – Supplemental material for Safety and efficacy of remote ischemic conditioning for spontaneous intracerebral hemorrhage (SERIC-ICH): A multicenter, randomized, parallel-controlled clinical trial study design and protocol

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    Supplemental material, sj-pdf-1-eso-10.1177_23969873231201712 for Safety and efficacy of remote ischemic conditioning for spontaneous intracerebral hemorrhage (SERIC-ICH): A multicenter, randomized, parallel-controlled clinical trial study design and protocol by Zhen-Ni Guo, Yang Qu, Reziya Abuduxukuer, Peng Zhang, Lijuan Wang, Ying Liu, Rui-Hong Teng, Jian-Hua Gao, Feng Jin, Hai-Feng Wang, Yu Cao, Yong-Quan Xue, Jun-Feng Zhao, Magdy H Selim, Thanh N Nguyen and Yi Yang in European Stroke Journal</p

    Capturing Complementarity in Set Functions by Going Beyond Submodularity/Subadditivity

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    We introduce two new "degree of complementarity" measures: supermodular width and superadditive width. Both are formulated based on natural witnesses of complementarity. We show that both measures are robust by proving that they, respectively, characterize the gap of monotone set functions from being submodular and subadditive. Thus, they define two new hierarchies over monotone set functions, which we will refer to as Supermodular Width (SMW) hierarchy and Superadditive Width (SAW) hierarchy, with foundations - i.e. level 0 of the hierarchies - resting exactly on submodular and subadditive functions, respectively. We present a comprehensive comparative analysis of the SMW hierarchy and the Supermodular Degree (SD) hierarchy, defined by Feige and Izsak. We prove that the SMW hierarchy is strictly more expressive than the SD hierarchy: Every monotone set function of supermodular degree d has supermodular width at most d, and there exists a supermodular-width-1 function over a ground set of m elements whose supermodular degree is m-1. We show that previous results regarding approximation guarantees for welfare and constrained maximization as well as regarding the Price of Anarchy (PoA) of simple auctions can be extended without any loss from the supermodular degree to the supermodular width. We also establish almost matching information-theoretical lower bounds for these two well-studied fundamental maximization problems over set functions. The combination of these approximation and hardness results illustrate that the SMW hierarchy provides not only a natural notion of complementarity, but also an accurate characterization of "near submodularity" needed for maximization approximation. While SD and SMW hierarchies support nontrivial bounds on the PoA of simple auctions, we show that our SAW hierarchy seems to capture more intrinsic properties needed to realize the efficiency of simple auctions. So far, the SAW hierarchy provides the best dependency for the PoA of Single-bid Auction, and is nearly as competitive as the Maximum over Positive Hypergraphs (MPH) hierarchy for Simultaneous Item First Price Auction (SIA). We also provide almost tight lower bounds for the PoA of both auctions with respect to the SAW hierarchy
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