Deuteron production and elliptic flow in relativistic heavy ion collisions

The hadronic transport model \textsc{art} is extended to include the production and annihilation of deuterons via the reactions $BB \leftrightarrow dM$, where $B$ and $M$ stand for baryons and mesons, respectively, as well as their elastic scattering with mesons and baryons in the hadronic matter. This new hadronic transport model is then used to study the transverse momentum spectrum and elliptic flow of deuterons in relativistic heavy ion collisions, with the initial hadron distributions after hadronization of produced quark-gluon plasma taken from a blast wave model. The results are compared with those measured by the PHENIX and STAR Collaborations for Au+Au collisions at $\sqrt{s_{NN}^{}} = 200$ GeV, and also with those obtained from the coalescence model based on freeze-out nucleons in the transport model.Comment: 9 pages, 10 figures, REVTeX, version to be published in Phys. Rev.

Stock Options and Chief Executive Compensation

Although stock options are commonly observed in chief executive officer (CEO) com- pensation contracts, there is theoretical controversy about whether stock options are part of the optimal contract. Using a sample of Fortune 500 companies, we solve an agency model calibrated to the company-specifc data and we find that stock options are almost always part of the optimal contract. This result is robust to alternative assumptions about the level of CEO risk-aversion and the disutility associated with their effort. In a supplementary analysis, we solve for the optimal contract when there are no restrictions on the contract space. We find that the optimal contract (which is characterized as a state-contingent payoff to the CEO) typically has option-like features over the most probable range of outcomes.Stock Options, Incentives, Agency Model

Probing Neutrino Flavor Transition Mechanism with Ultra High Energy Astrophysical Neutrinos

Observation of ultra-high energy astrophysical neutrinos and identification of their flavors have been proposed for future neutrino telescopes. The flavor ratio of astrophysical neutrinos observed on the Earth depends on both the initial flavor ratio at the source and flavor transitions taking place during propagations of these neutrinos. The flavor transition mechanisms are well-classified with our model-independent parametrization. We find a new parameter R={\phi}_e/({\phi}_{\mu} + {\phi}_{\tau}) can probe directly the flavor transition in the framework of our model-independent parametrization, without the assumption of the {\nu}_{\mu}-{\nu}_{\tau} symmetry. A few flavor transition models are employed to test our parametrization with this new observable. The observational constraints on flavor transition mechanisms by the new observable is discussed through our model-independent parametrization.Comment: 22pages, 7 figure

Watermarking FPGA Bitfile for Intellectual Property Protection

Intellectual property protection (IPP) of hardware designs is the most important requirement for many Field Programmable Gate Array (FPGA) intellectual property (IP) vendors. Digital watermarking has become an innovative technology for IPP in recent years. Existing watermarking techniques have successfully embedded watermark into IP cores. However, many of these techniques share two specific weaknesses: 1) They have extra overhead, and are likely to degrade performance of design; 2) vulnerability to removing attacks. We propose a novel watermarking technique to watermark FPGA bitfile for addressing these weaknesses. Experimental results and analysis show that the proposed technique incurs zero overhead and it is robust against removing attacks

Financial Computational Intelligence

Artificial intelligence decision support system is always a popular topic in providing the human with an optimized decision recommendation when operating under uncertainty in complex environments. The particular focus of our discussion is to compare different methods of artificial intelligence decision support systems in the investment domain – the goal of investment decision-making is to select an optimal portfolio that satisfies the investor’s objective, or, in other words, to maximize the investment returns under the constraints given by investors. In this study we apply several artificial intelligence systems like Influence Diagram (a special type of Bayesian network), Decision Tree and Neural Network to get experimental comparison analysis to help users to intelligently select the best portfoliArtificial intelligence, neural network, decision tree, bayesian network