626 research outputs found

    Green Evidence for Energy Security Transformation in China: Re- conceptualization of Energy Security and Its Implication to China’s Renewable Energy Policy Change

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    China has grown to a global large energy consumer since 1993, and surpassed the U.S. to become the top energy consumption country in 2010. Energy security is indispensable to the rapid and sustained development of China’s economy. Different from the realist geopolitics and liberalist analyzing approach, the author constructs a dynamic constructivist theoretical framework of energy security and tends to explore the unique re‐conceptualization trajectory of Chinese energy security: from self‐sufficiency security with emphasis on the internal supply (first stage) to “go abroad” supply‐oriented energy security highlighting the external expansion of sufficient energy at reasonable price (second stage), then to comprehensive energy security concept focusing on international cooperation, energy diversification, energy conservation and low‐carbon economy(third stage). Especially the transition from “decreasing energy intensity” to “reducing the carbon intensity” in the third stage has shown the conceptual shifting from the static energy security to dynamic resilience energy security. Based on the discourse and institutional analysis, the author further illustrates the profound constraints of climate change scenario to energy security in China as well as their interacting relations. Finally the author points out that the green evidence for energy security concept transformation has exerted significant impact on renewable energy policy‐making, which opening “the window of opportunity” for rapid renewable energy development in China

    Cytoplasmic tails of integrin αIIbβ3 in the regulation of integrin activation, cell adhesion and spreading

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    Integrins are major adhesion receptors for the extracellular matrix (ECM). This thesis focuses on the motifs and interactions within integrin cytoplasmic tails during integrin-mediated cell adhesion and spreading. The present study investigated the significance of the skelemin-αIIbβ3 interaction using Chinese Hamster Ovary (CHO) cells expressing wild-type or mutant αIIbβ3 receptors defective in skelemin binding. Most mutant cells displayed unimpaired adhesive capacity and spreading on immobilized fibrinogen at the early stages of cell spreading. In addition, they formed normal focal adhesions and stress fibers with no indication of impaired cell spreading. K716A and H722A mutant cells exhibited the greatest cell spreading, which was associated with enhanced p-Src activation. The K716 residue appeared to be the most important for skelemin binding in previous in vitro studies. Here, the protrusions of the leading edge of K716A cells showed strong colocalization of talin with αIIbβ3 which was associated with a loss in skelemin binding. These data suggest that the binding of skelemin to αIIbβ3 is not essential for normal cell spreading, but may act to exert contractile forces on cell spreading and coordinate the binding of talin to the membrane proximal region of integrin tails. The functional mode of peptides corresponding to the central motifs of the αIIb and αV tail, KRNRPPLEED (αIIb peptide) and KRVRPPQEEQ (αV peptide) was also investigated. Both peptides inhibited Mn2+-activated αIIbβ3 binding to soluble fibrinogen as well as the binding of αIIbβ3-expressing CHO cells to immobilized fibrinogen. Breast cancer progression has been linked to tumor cell interaction with ECM. Our αIIb and αV peptides also inhibited adhesion of two breast cancer cell lines (MDA-MB-435 and MCF7) to αV integrin ECM ligand vitronectin. Replacement of RPP with AAA significantly attenuated the inhibitory activity of the αIIb peptide. β-tubulin was identified as a potential αIIb peptide-binding partner, suggesting that microtubule cytoskeleton may participate in the regulation of integrin functions. These results provide insights into the mechanisms by which the central motifs of αIIb and αV tails regulate integrin activation and integrin-mediated cell adhesio

    Error bound of the multilevel adaptive cross approximation (MLACA)

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    An error bound of the multilevel adaptive cross approximation (MLACA 1, which is a multilevel version of the adaptive cross approximation-singular value decomposition (ACA-SVD), is rigorously derived. For compressing an off-diagonal submatrix of the method of moments MAD impedance matrix with a binary tree, the L-level MIACA includes L + 1 steps, and each step includes 2(L) ACA-SVD decompositions. If the relative Frobenius norm error of the ACA-SVD used in the MLACA is smaller than epsilon, the rigorous proof in this communication shows that the relative Frobenius norm error of the L-Ievel MLACA is smaller than (1 + epsilon)(L+1) - 1. In practical applications, the error bound of the MLACA can be approximated as epsilon(L + 1), because epsilon is always << 1. The error upper bound can he used to control the accuracy of the MLACA. To ensure an error of the L-level MLACA smaller than epsilon for different L, the ACA-SVD threshold can be set to (1 + epsilon)1/L+1 - 1, which approximately equals epsilon/(L + 1) for practical applications.Peer ReviewedPostprint (author's final draft

    Distributed Online Convex Optimization with an Aggregative Variable

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    This paper investigates distributed online convex optimization in the presence of an aggregative variable without any global/central coordinators over a multi-agent network, where each individual agent is only able to access partial information of time-varying global loss functions, thus requiring local information exchanges between neighboring agents. Motivated by many applications in reality, the considered local loss functions depend not only on their own decision variables, but also on an aggregative variable, such as the average of all decision variables. To handle this problem, an Online Distributed Gradient Tracking algorithm (O-DGT) is proposed with exact gradient information and it is shown that the dynamic regret is upper bounded by three terms: a sublinear term, a path variation term, and a gradient variation term. Meanwhile, the O-DGT algorithm is also analyzed with stochastic/noisy gradients, showing that the expected dynamic regret has the same upper bound as the exact gradient case. To our best knowledge, this paper is the first to study online convex optimization in the presence of an aggregative variable, which enjoys new characteristics in comparison with the conventional scenario without the aggregative variable. Finally, a numerical experiment is provided to corroborate the obtained theoretical results
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