Thermodynamic properties and bulk viscosity near phase transition in the Z(2) and O(4) models

We investigate the thermodynamic properties including equation of state, the trace anomaly, the sound velocity and the specific heat, as well as transport properties like bulk viscosity in the Z(2) and O(4) models in the Hartree approximation of Cornwall-Jackiw-Tomboulis (CJT) formalism. We study these properties in different cases, e.g. first order phase transition, second order phase transition, crossover and the case without phase transition, and discuss the correlation between the bulk viscosity and the thermodynamic properties of the system. We find that the bulk viscosity over entropy density ratio exhibits an upward cusp at the second order phase transition, and a sharp peak at the 1st order phase transition. However, this peak becomes smooth or disappears in the case of crossover. This indicates that at RHIC, where there is no real phase transition and the system experiences a crossover, the bulk viscosity over entropy density might be small, and it will not affect too much on hadronization. We also suggest that the bulk viscosity over entropy density ratio is a better quantity than the shear viscosity over entropy density ratio to locate the critical endpoint.Comment: 19 pages, 30 figures, 1 tabl

Non-ergodic Convergence Analysis of Heavy-Ball Algorithms

In this paper, we revisit the convergence of the Heavy-ball method, and present improved convergence complexity results in the convex setting. We provide the first non-ergodic O(1/k) rate result of the Heavy-ball algorithm with constant step size for coercive objective functions. For objective functions satisfying a relaxed strongly convex condition, the linear convergence is established under weaker assumptions on the step size and inertial parameter than made in the existing literature. We extend our results to multi-block version of the algorithm with both the cyclic and stochastic update rules. In addition, our results can also be extended to decentralized optimization, where the ergodic analysis is not applicable

Modeling Chinese post-90\u272 tourism loyalty to the ex-rival state using the perceived value approach

Purpose – A recent trend in tourism research involves the study of independent Chinese tourists. Yet while post-90s or Generation Z (i.e., born in the 1990s) comprises an important share of nondomestic visitors to Taiwan and other tourist destinations, this segment of the tourist population is currently under-analyzed. As a pioneering piece of research in this area, this survey attempts to understand Chinese tourists of this cohort visiting the long-divided state. Design – This research incorporates the social dimension of perceived value in the ordinarily employed perceived-value model to better understand why Chinese post-90s would like to recommend Taiwan. Methodology – This study samples Chinese students from 12 universities located in the northern, central, southern, and western regions of Taiwan. They were investigated with the selfadministered survey which is composed of five constructs, for a total of 17 questions. Structural equation modeling was employed to analyze the collected data and testify the hypotheses. Findings – The finding provides insights in the specific tourism behaviors of this cohort and how they are found distinct from their predecessors. The emotional dimension of the post-90s’ tourismrelated perceived value is a strong determinant of their loyalty to Taiwan as a tourist destination. The prior-rival situation between both sides of the Taiwan Strait might signify that social dimension significantly predict their loyalty, through the mediator of satisfaction. Originality – This research provides important information for tourism businesses regarding place management and marketing strategies, enabling them to receive this new generation of Chinese customers

Unconventional Superconducting Symmetry in a Checkerboard Antiferromagnet

We use a renormalized mean field theory to study the Gutzwiller projected BCS states of the extended Hubbard model in the large $U$ limit, or the $t$-$t'$-$J$-$J'$ model on a two-dimensional checkerboard lattice. At small $t'/t$, the frustration due to the diagonal terms of $t'$ and $J'$ does not alter the $d_{x^2-y^2}$-wave pairing symmetry, and the negative (positive) $t'/t$ enhances (suppresses) the pairing order parameter. At large $t'/t$, the ground state has an extended s-wave symmetry. At the intermediate $t'/t$, the ground state is $d+id$ or $d+is$-wave with time reversal symmetry broken.Comment: 6 pages, 6 figure

Predicting RNA-binding residues from evolutionary information and sequence conservation

Abstract Background RNA-binding proteins (RBPs) play crucial roles in post-transcriptional control of RNA. RBPs are designed to efficiently recognize specific RNA sequences after it is derived from the DNA sequence. To satisfy diverse functional requirements, RNA binding proteins are composed of multiple blocks of RNA-binding domains (RBDs) presented in various structural arrangements to provide versatile functions. The ability to computationally predict RNA-binding residues in a RNA-binding protein can help biologists reveal important site-directed mutagenesis in wet-lab experiments. Results The proposed prediction framework named “ProteRNA” combines a SVM-based classifier with conserved residue discovery by WildSpan to identify the residues that interact with RNA in a RNA-binding protein. Although these conserved residues can be either functionally conserved residues or structurally conserved residues, they provide clues on the important residues in a protein sequence. In the independent testing dataset, ProteRNA has been able to deliver overall accuracy of 89.78%, MCC of 0.2628, F-score of 0.3075, and F0.5-score of 0.3546. Conclusions This article presents the design of a sequence-based predictor aiming to identify the RNA-binding residues in a RNA-binding protein by combining machine learning and pattern mining approaches. RNA-binding proteins have diverse functions while interacting with different categories of RNAs because these proteins are composed of multiple copies of RNA-binding domains presented in various structural arrangements to expand the functional repertoire of RNA-binding proteins. Furthermore, predicting RNA-binding residues in a RNA-binding protein can help biologists reveal important site-directed mutagenesis in wet-lab experiments.</p

Charge Ordered RVB States in the Doped Cuprates

We study charge ordered d-wave resonating valence bond states (dRVB) in the doped cuprates, and estimate the energies of these states in a generalized $t-J$ model by using a renormalized mean field theory. The long range Coulomb potential tends to modulate the charge density in favor of the charge ordered RVB state. The possible relevance to the recently observed $4 \times 4$ checkerboard patterns in tunnelling conductance in high $T_c$ cuprates is discussed.Comment: 4 pages, 4 figures, 3 table