Robust Preparation of GHZ and W States of Three Distant Atoms

Schemes to generate Greenberger-Horne-Zeilinger(GHZ) and W states of three distant atoms are proposed in this paper. The schemes use the effects of quantum statistics of indistinguishable photons emitted by the atoms inside optical cavities. The advantages of the schemes are their robustness against detection inefficiency and asynchronous emission of the photons. Moreover, in Lamb-Dicke limit, the schemes do not require simultaneous click of the detectors, this makes the schemes more realizable in experiments.Comment: 5 pages, 1 fiure. Phys. Rev. A 75, 044301 (2007

Is warrant really a derivative? Evidence from the Chinese warrant market

This paper studies the Chinese warrant market that has been developing since August 2005. Empirical evidence shows that the market prices of warrants are much higher systematically than the Black-Scholes prices with historical volatility. The prices of a warrant and its underlying asset do not support the monotonicity, perfect correlation and option redundancy properties. The cumulated delta-hedged gains for almost all expired warrants are negative. The negative gains are mainly driven by the volatility risk, and the trading values of the warrants for puts and the market risk for calls. The investors are trading some other risks in addition to the underlying risks. © 2012 Elsevier B.V. All rights reserved.postprin

Going for Gold(-Standard): Attaining Coupled Cluster Accuracy in Oxide-Supported Nanoclusters

Metal nanoclusters supported on oxide surfaces are widely-used catalysts that boasts sharply enhanced activity over their bulk, especially for the coinage metals: Au, Ag and Cu. These properties depend sensitively on the nanocluster structure, which are challenging to model with density functional theory (DFT) -- the workhorse modelling technique. Leveraging the recently developed SKZCAM protocol, we perform the first ever benchmark study of coinage metal structures on the MgO surface with coupled cluster theory [CCSD(T)] -- the gold-standard modelling technique. We investigate a comprehensive range of DFT models (exchange-correlation functional and dispersion correction) and our benchmarks reveal that none of the investigated models can accurately describe this system. We demonstrate that this arises from inadequate account of metal-metal interactions in the nanocluster and propose a high-level correction which provides reference accuracy at low cost. This forges a path towards studying larger systems, which we highlight by benchmarking Au$_{20}$ on MgO, a challenging system where DFT models have disagreed on its ground state structure.Comment: Working pape

Uncertainty sampling for action recognition via maximizing expected average precision

© 2018 International Joint Conferences on Artificial Intelligence. All right reserved. Recognizing human actions in video clips has been an important topic in computer vision. Sufficient labeled data is one of the prerequisites for the good performance of action recognition algorithms. However, while abundant videos can be collected from the Internet, categorizing each video clip is time-consuming. Active learning is one way to alleviate the labeling labor by allowing the classifier to choose the most informative unlabeled instances for manual annotation. Among various active learning algorithms, uncertainty sampling is arguably the most widely-used strategy. Conventional uncertainty sampling strategies such as entropy-based methods are usually tested under accuracy. However, in action recognition Average Precision (AP) is an acknowledged evaluation metric, which is somehow ignored in the active learning community. It is defined as the area under the precision-recall curve. In this paper, we propose a novel uncertainty sampling algorithm for action recognition using expected AP. We conduct experiments on three real-world action recognition datasets and show that our algorithm outperforms other uncertainty-based active learning algorithms

Fidelity susceptibility and long-range correlation in the Kitaev honeycomb model

We study exactly both the ground-state fidelity susceptibility and bond-bond correlation function in the Kitaev honeycomb model. Our results show that the fidelity susceptibility can be used to identify the topological phase transition from a gapped A phase with Abelian anyon excitations to a gapless B phase with non-Abelian anyon excitations. We also find that the bond-bond correlation function decays exponentially in the gapped phase, but algebraically in the gapless phase. For the former case, the correlation length is found to be $1/\xi=2\sinh^{-1}[\sqrt{2J_z -1}/(1-J_z)]$, which diverges around the critical point $J_z=(1/2)^+$.Comment: 7 pages, 6 figure

Disruption of the 37-kDa/67-kDa laminin receptor gene in bovine fetal fibroblasts

The 37-kDa/67-kDa laminin receptor (LRP/LR), also known as ribosomal protein SA (RPSA), acts as a cell surface receptor for prions and plays an important role in internalization of cellular prion protein. In this study, we knocked out the part of prion binding sites (aa 161-205) by gene targeting in the bovine fetal fibroblasts (BFF). This is the first report about disrupting the gene encoding for the prion binding site in bovine fetal fibroblasts. The heterozygous BFF are ready to be used in producing homozygous cattle, which will be applied to study the interaction between prion and the 37-kDa/67-kDa LRP/LR.Key words: Prion, PrPC, PrPSc, 37-kDa/67-kDa laminin receptor, gene targeting

Activation of JNK Signaling Mediates Connective Tissue Growth Factor Expression and Scar Formation in Corneal Wound Healing

Connective Tissue Growth Factor (CTGF) and Transforming growth factor-β1 (TGF-β1) are key growth factors in regulating corneal scarring. Although CTGF was induced by TGF-β1 and mediated many of fibroproliferative effects of TGF-β1, the signaling pathway for CTGF production in corneal scarring remains to be clarified. In the present study, we firstly investigated the effects of c-Jun N-terminal kinase (JNK) on CTGF expression induce by TGF-β1 in Telomerase-immortalized human cornea stroma fibroblasts (THSF). Then, we created penetrating corneal wound model and determined the effect of JNK in the pathogenesis of corneal scarring. TGF-β1 activated MAPK pathways in THSF cells. JNK inhibitor significantly inhibited CTGF, fibronectin and collagen I expression induced by TGF-β1 in THSF. In corneal wound healing, the JNK inhibitor significantly inhibited CTGF expression, markedly improved the architecture of corneal stroma and reduced corneal scar formation, but did not have a measurable impact on corneal wound healing in vivo. Our results indicate that JNK mediates the expression of CTGF and corneal scarring in corneal wound healing, and might be considered as specific targets of drug therapy for corneal scarring

Casein kinase 1-Like 3 is required for abscisic acid regulation of seed germination, root growth, and gene expression in Arabidopsis

The homozygous T-DNA mutant of a casein kinase 1-Like 3 (ckl3) was identified. The quantitative realtime polymerase chain reaction (QRT-PCR) results showed that CKL3 was highly expressed in flowers and roots, but less in stems, leaves and leafstalks. It was found that CKL3 gene was induced by abscisic (ABA). When grown in the presence of increasing concentration of exogenous ABA, the ckl3 mutant showed were more sensitive than wild type to the inhibition of seed germination and seedling root growth by applied ABA. In presence of all ABA, NaCl and mannitol concentrations tested, the germination percentage of ckl3 mutant seeds was lower than that of wild type. In the presence of exogenous ABA, NaCl and mannitol, wild-type seeds showed higher germination percentages than the ckl3 mutants at different stages of development. Wild type seedlings showed a reduced inhibition of root growth compared with ckl3 plants under different ABA concentration treatment. Also, compared with wild-type plants, the expressions of the ABA and abiotic stress-responsive genes including ABI1, ABI4, ABI5, ABF3, KIN1, RAB18, SOS3, and DREB1A decreased, but RD22 and RD29B increased in ckl3 mutants. Taken together, these results suggested CKL3 is required for abscisic acid regulation of seed germination, root growth and gene expression, and was involved in salt and osmotic stress response in the early development stage. This study provides important clues to casein kinase I activities in ABA signaling and plant development.Key words: Arabidopsis, casein kinase 1-like 3 (CKL3) gene, phenotype, abscisic acid (ABA) signal transduction

Heterogeneous network embedding enabling accurate disease association predictions.

BackgroundIt is significant to identificate complex biological mechanisms of various diseases in biomedical research. Recently, the growing generation of tremendous amount of data in genomics, epigenomics, metagenomics, proteomics, metabolomics, nutriomics, etc., has resulted in the rise of systematic biological means of exploring complex diseases. However, the disparity between the production of the multiple data and our capability of analyzing data has been broaden gradually. Furthermore, we observe that networks can represent many of the above-mentioned data, and founded on the vector representations learned by network embedding methods, entities which are in close proximity but at present do not actually possess direct links are very likely to be related, therefore they are promising candidate subjects for biological investigation.ResultsWe incorporate six public biological databases to construct a heterogeneous biological network containing three categories of entities (i.e., genes, diseases, miRNAs) and multiple types of edges (i.e., the known relationships). To tackle the inherent heterogeneity, we develop a heterogeneous network embedding model for mapping the network into a low dimensional vector space in which the relationships between entities are preserved well. And in order to assess the effectiveness of our method, we conduct gene-disease as well as miRNA-disease associations predictions, results of which show the superiority of our novel method over several state-of-the-arts. Furthermore, many associations predicted by our method are verified in the latest real-world dataset.ConclusionsWe propose a novel heterogeneous network embedding method which can adequately take advantage of the abundant contextual information and structures of heterogeneous network. Moreover, we illustrate the performance of the proposed method on directing studies in biology, which can assist in identifying new hypotheses in biological investigation

Quantum Dynamical Rˇ\check{R}- Matrix with Spectral Parameter from Fusion

A quantum dynamical $\check{R}$-matrix with spectral parameter is constructed by fusion procedure. This spin-1 $\check{R}$-matrix is connected with Lie algebra $so(3)$ and does not satisfy the condition of translation invariance.Comment: 6 pages, LaTeX, no figure