52,476 research outputs found

    Larkin-Ovchinnikov-Fulde-Ferrell phase in the superconductor (TMTSF)2ClO4: Theory versus experiment

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    We consider a formation of the Larkin-Ovchinnikov-Fulde-Ferrell (LOFF) phase in a quasi-one-dimensional (Q1D) conductor in a magnetic field, parallel to its conducting chains, where we take into account both the paramagnetic spin-splitting and orbital destructive effects against superconductivity. We show that, due to a relative weakness of the orbital effects in a Q1D case, the LOFF phase appears in (TMTSF)2_2ClO4_4 superconductor for real values of its Q1D band parameters. We compare our theoretical calculations with the recent experimental data by Y. Maeno's group [S. Yonezawa et al., Phys. Rev. Lett. \textbf{100}, 117002 (2008)] and show that there is a good qualitative and quantitative agreement between the theory and experimental data.Comment: 4 pages, 1 figur

    Impact of Building Information Modeling Implementation on the Acceptance of Integrated Delivery Systems: Structural Equation Modeling Analysis

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    In recent years, building information modeling (BIM) has been increasingly employed by the architecture, engineering and construction industry worldwide as a result of digital government initiatives. In spite of some promising early evidence on the benefits of BIM, the momentum of this top-down drive should build upon after-implementation empirical evidence. Through the structural equation modeling analysis of survey returns from 145 Chinese BIM-enabled projects, this research demonstrates that BIM’s degree of implementation can positively affect the acceptability of integrated project delivery (IPD) in the future via increased perception of the need for supply chain incentivization and improved communication quality enabled by BIM. Rolling out BIM on a wider scale may yield an additional benefit in lowering the barrier to the implementation of IPD systems. This finding can serve as evidential support for government mandates that require the compulsory adoption of BIM in public projects

    TIFA, an inflammatory signaling adaptor, is tumor suppressive for liver cancer.

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    TIFA (TNF receptor associated factor (TRAF)-interacting protein with a Forkhead-associated (FHA) domain), also called T2BP, was first identified using a yeast two-hybrid screening. TIFA contains a FHA domain, which directly binds phosphothreonine and phosphoserine, and a consensus TRAF6-binding motif. TIFA-mediated oligomerization and poly-ubiquitinylation of TRAF6 mediates signaling downstream of the Tumor necrosis factor alpha receptor 1 (TNFaR-I) and interleukin-1/Toll-like receptor 4 (TLR4) pathways. Examining TIFA expression in hepatocellular carcinoma (HCC) tissues microarrays, we noted marked decreases TIFA reactivity in tumor versus control samples. In agreement, we found that HCC cell lines show reduced TIFA expression levels versus normal liver controls. Reconstituting TIFA expression in HCC cell lines promoted two independent apoptosis signaling pathways: the induction of p53 and cell cycle arrest, and the activation of caspase-8 and caspase-3. In contrast, the expression of a non-oligomerizing mutant of TIFA impacted cells minimally, and suppression of TIFA expression protected cells from apoptosis. Mice bearing TIFA overexpression hepatocellular xenografts develop smaller tumors versus TIFA mutant tumors; terminal deoxynucleotidyl transferase dUTP nick end labeling staining demonstrates increased cell apoptosis, and decreased proliferation, reflecting cell cycle arrest. Interestingly, p53 has a greater role in decreased proliferation than cell death, as it appeared dispensable for TIFA-induced cell killing. The findings demonstrate a novel suppressive role of TIFA in HCC progression via promotion of cell death independent of p53

    Application of advanced technology to space automation

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    Automated operations in space provide the key to optimized mission design and data acquisition at minimum cost for the future. The results of this study strongly accentuate this statement and should provide further incentive for immediate development of specific automtion technology as defined herein. Essential automation technology requirements were identified for future programs. The study was undertaken to address the future role of automation in the space program, the potential benefits to be derived, and the technology efforts that should be directed toward obtaining these benefits

    Exploiting Cognitive Structure for Adaptive Learning

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    Adaptive learning, also known as adaptive teaching, relies on learning path recommendation, which sequentially recommends personalized learning items (e.g., lectures, exercises) to satisfy the unique needs of each learner. Although it is well known that modeling the cognitive structure including knowledge level of learners and knowledge structure (e.g., the prerequisite relations) of learning items is important for learning path recommendation, existing methods for adaptive learning often separately focus on either knowledge levels of learners or knowledge structure of learning items. To fully exploit the multifaceted cognitive structure for learning path recommendation, we propose a Cognitive Structure Enhanced framework for Adaptive Learning, named CSEAL. By viewing path recommendation as a Markov Decision Process and applying an actor-critic algorithm, CSEAL can sequentially identify the right learning items to different learners. Specifically, we first utilize a recurrent neural network to trace the evolving knowledge levels of learners at each learning step. Then, we design a navigation algorithm on the knowledge structure to ensure the logicality of learning paths, which reduces the search space in the decision process. Finally, the actor-critic algorithm is used to determine what to learn next and whose parameters are dynamically updated along the learning path. Extensive experiments on real-world data demonstrate the effectiveness and robustness of CSEAL.Comment: Accepted by KDD 2019 Research Track. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD'19

    Brans-Dicke Gravity from Entropic Viewpoint

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    We interpret the Brans-Dicke gravity from entropic viewpoint. We first apply the Verlinde's entropic formalism in the Einstein frame, then perform the conformal transformation which connects the Einstein frame to the Jordan frame. The transformed result yields the equation of motion of the Brans-Dicke theory in the Jordan frame.Comment: Title changed, minor changes to match the published versio

    The magnetic dipole transitions in the (cbˉ)(c\bar{b}) binding system

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    The magnetic dipole transitions between the vector mesons Bc∗B_c^* and their relevant pseudoscalar mesons BcB_c (BcB_c, Bc∗B_c^*, Bc(2S)B_c(2S), Bc∗(2S)B_c^*(2S), Bc(3S)B_c(3S) and Bc∗(3S)B_c^*(3S) etc, the binding states of (cbˉ)(c\bar{b}) system) of the BcB_c family are interesting. To see the `hyperfine' splitting due to spin-spin interaction is an important topic for understanding the spin-spin interaction and the spectrum of the the (cbˉ)(c\bar{b}) binding system. The knowledge about the magnetic dipole transitions is also very useful for identifying the vector boson Bc∗B_c^* mesons experimentally, whose masses are just slightly above the masses of their relevant pseudoscalar mesons BcB_c accordingly. Considering the possibility to observe the vector mesons via the transitions at Z0Z^0 factory and the potentially usages of the theoretical estimate on the transitions, we fucus our efforts on calculating the magnetic dipole transitions, i.e. precisely to calculate the rates for the transitions such as decays Bc∗→BcγB_c^*\to B_c\gamma and Bc∗→Bce+e−B_c^*\to B_c e^+e^-, and particularly work in the Behte-Salpeter framework. In the estimate, as a typical example, we carefully investigate the dependance of the rate Γ(Bc∗→Bcγ)\Gamma(B_c^*\to B_c\gamma) on the mass difference ΔM=MBc∗−MBc\Delta M=M_{B_c^*}-M_{B_c} as well.Comment: 10 pages, 2 figures, 1 tabl
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