Globally Polarized Quark-gluon Plasma in Non-central A+A Collisions

Produced partons have large local relative orbital angular momentum along the direction opposite to the reaction plane in the early stage of non-central heavy-ion collisions. Parton scattering is shown to polarize quarks along the same direction due to spin-orbital coupling. Such global quark polarization will lead to many observable consequences, such as left-right asymmetry of hadron spectra, global transverse polarization of thermal photons, dileptons and hadrons. Hadrons from the decay of polarized resonances will have azimuthal asymmetry similar to the elliptic flow. Global hyperon polarization is predicted within different hadronization scenarios and can be easily tested.Comment: 4 pages in RevTex with 2 postscript figures, an erratum is added to the final published versio

Topological properties and fractal analysis of recurrence network constructed from fractional Brownian motions

Many studies have shown that we can gain additional information on time series by investigating their accompanying complex networks. In this work, we investigate the fundamental topological and fractal properties of recurrence networks constructed from fractional Brownian motions (FBMs). First, our results indicate that the constructed recurrence networks have exponential degree distributions; the relationship between $H$ and $$can be represented by a cubic polynomial function. We next focus on the motif rank distribution of recurrence networks, so that we can better understand networks at the local structure level. We find the interesting superfamily phenomenon, i.e. the recurrence networks with the same motif rank pattern being grouped into two superfamilies. Last, we numerically analyze the fractal and multifractal properties of recurrence networks. We find that the average fractal dimension$$ of recurrence networks decreases with the Hurst index $H$ of the associated FBMs, and their dependence approximately satisfies the linear formula $\approx 2 - H$. Moreover, our numerical results of multifractal analysis show that the multifractality exists in these recurrence networks, and the multifractality of these networks becomes stronger at first and then weaker when the Hurst index of the associated time series becomes larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst index $H=0.5$ possess the strongest multifractality. In addition, the dependence relationships of the average information dimension $$and the average correlation dimension$$ on the Hurst index $H$ can also be fitted well with linear functions. Our results strongly suggest that the recurrence network inherits the basic characteristic and the fractal nature of the associated FBM series.Comment: 25 pages, 1 table, 15 figures. accepted by Phys. Rev.

Exploiting Cognitive Structure for Adaptive Learning

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

Correlated Quantum Transport of Density Wave Electrons

Recently observed Aharonov-Bohm quantum interference of period h/2e in charge density wave rings strongly suggest that correlated density wave electron transport is a cooperative quantum phenomenon. The picture discussed here posits that quantum solitons nucleate and transport current above a Coulomb blockade threshold field. We propose a field-dependent tunneling matrix element and use the Schrodinger equation, viewed as an emergent classical equation as in Feynman's treatment of Josephson tunneling, to compute the evolving macrostate amplitudes, finding excellent quantitative agreement with voltage oscillations and current-voltage characteristics in NbSe3. A proposed phase diagram shows the conditions favoring soliton nucleation versus classical depinning. (Published in Phys. Rev. Lett. 108, 036404 (2012).)Comment: 9 pages, 4 figures, (5 pages & 3 figures for main article), includes Supplemental Material with 1 figure. Published version: Physical Review Letters, vol. 108, p. 036404 (2012

In situ photogalvanic acceleration of optofluidic kinetics: a new paradigm for advanced photocatalytic technologies

A multiscale-designed optofluidic reactor is demonstrated in this work, featuring an overall reaction rate constant of 1.32 s¯¹ for photocatalytic decolourization of methylene blue, which is an order of magnitude higher as compared to literature records. A novel performance-enhancement mechanism of microscale in situ photogalvanic acceleration was found to be the main reason for the superior optofluidic performance in the photocatalytic degradation of dyes as a model reaction

Gauge fields, ripples and wrinkles in graphene layers

We analyze elastic deformations of graphene sheets which lead to effective gauge fields acting on the charge carriers. Corrugations in the substrate induce stresses, which, in turn, can give rise to mechanical instabilities and the formation of wrinkles. Similar effects may take place in suspended graphene samples under tension.Comment: contribution to the special issue of Solid State Communications on graphen

Enhancement of wear properties of a polyether ether ketone polymer by incorporation of carbon and glass fibers

Some properties of polymers can be improved through the incorporation of carbon and glass fibers into the polymer matrix. In this research, the wear resistance of two polymer composites CF-polyether ether ketone (PEEK) and GF-PEEK were compared with the virgin PEEK. The wear resistance was assessed by Pin on Disk tests performed using a range of reinforced polymer pins tested against a steel disk. The influence of load, sliding velocity, counter-surface hardness, and reinforcement concentration and type, on the specific wear rate was investigated. The materials were chosen to simulate the wear experienced between a polymeric anti-extrusion ring and a steel sealing surface utilized within valves in the oil and gas industry. The average mass loss was recorded and an analysis of the variance (ANOVA) carried out to investigate the contribution of each parameter on specific wear rate. Results showed that weight percentage reinforcement and type of reinforcement material were primary contributors toward specific wear rate, with a contribution of ~70%. Secondary contributors were sliding speed (~14%) and load and steel hardness (~12%). Following the wear tests, residual stress measurements were conducted on polymer reinforced with carbon fiber. It was found that compressive residual stresses existed, and that their magnitude increased with increasing loa