Quark Spectral Function and Deconfinement at Nonzero Temperature

The maximum entropy method is used to compute the quark spectral function at nonzero temperature. We solve the gap equation of quantum chromodynamics (QCD) self-consistently, employing a rainbow kernel which phenomenologically models results from Dyson-Schwinger equations (DSE) and lattice QCD. We use the criterion of positivity restoration of the spectral function as a signal for deconfinement. Our calculation indicates that the critical temperature of deconfinement $T_d$ is slightly smaller than the one of chiral symmetry restoration $T_c$: $T_d\sim 94$ in the chiral limit, and $T_d\sim 96$ with physical light quark masses. Since these deviations are within the systematic error of our approach, it is reasonable to conclude that chiral symmetry restoration and deconfinement coincide at zero chemical potential

Nucleus Driven Electronic Pulsation

We derive and solve by the spectral method the equations for a neutral system of ultra-relativistic electrons that are compressed to the radius of the nucleus and subject to a driving force. This driving force can be thought of as originating from a nuclear breathing mode, a possibility we discuss in detail

Learning distance to subspace for the nearest subspace methods in high-dimensional data classification

The nearest subspace methods (NSM) are a category of classification methods widely applied to classify high-dimensional data. In this paper, we propose to improve the classification performance of NSM through learning tailored distance metrics from samples to class subspaces. The learned distance metric is termed as ‘learned distance to subspace’ (LD2S). Using LD2S in the classification rule of NSM can make the samples closer to their correct class subspaces while farther away from their wrong class subspaces. In this way, the classification task becomes easier and the classification performance of NSM can be improved. The superior classification performance of using LD2S for NSM is demonstrated on three real-world high-dimensional spectral datasets

Commodity Markets, Price Limiters and Speculative Price Dynamics

We develop a behavioral commodity market model with consumers, producers and heterogeneous speculators to characterize the nature of commodity price fluctuations and to explore the efectiveness of price stabilization schemes. Within our model, nonlinear interactions between market participants can create either bull or bear markets, or irregular price fluctuations between bulland bear markets. Both the imposition of a bottoming price level (to support producers) or a topping price level (to protect consumers) can reduce market price volatility. However, simple policy rules, such as price limiters, may have unexpected consequences in a complex environment: a minimum price level decreases the average price while a maximum price limit increases the average price. In addition, price limiters influence the price dynamics in an intricate way and may cause volatility clustering.commodity markets; price stabilization; simple limiters; technical and fundamental anaysis; bifurcation analysis; chaos control

Microscopic theory of single-electron tunneling through molecular-assembled metallic nanoparticles

We present a microscopic theory of single-electron tunneling through metallic nanoparticles connected to the electrodes through molecular bridges. It combines the theory of electron transport through molecular junctions with the description of the charging dynamics on the nanoparticles. We apply the theory to study single-electron tunneling through a gold nanoparticle connected to the gold electrodes through two representative benzene-based molecules. We calculate the background charge on the nanoparticle induced by the charge transfer between the nanoparticle and linker molecules, the capacitance and resistance of molecular junction using a first-principles based Non-Equilibrium Green's Function theory. We demonstrate the variety of transport characteristics that can be achieved through ``engineering'' of the metal-molecule interaction.Comment: To appear in Phys. Rev.

Intelligent Disaster Response via Social Media Analysis - A Survey

The success of a disaster relief and response process is largely dependent on timely and accurate information regarding the status of the disaster, the surrounding environment, and the affected people. This information is primarily provided by first responders on-site and can be enhanced by the firsthand reports posted in real-time on social media. Many tools and methods have been developed to automate disaster relief by extracting, analyzing, and visualizing actionable information from social media. However, these methods are not well integrated in the relief and response processes and the relation between the two requires exposition for further advancement. In this survey, we review the new frontier of intelligent disaster relief and response using social media, show stages of disasters which are reflected on social media, establish a connection between proposed methods based on social media and relief efforts by first responders, and outline pressing challenges and future research directions.Comment: 14 pages, 3 figures, 104 references, accepted in SIGKDD Exploration