Chiral expansion of the π0→γγ\pi^0\rightarrow\gamma\gamma decay width

A chiral field theory of mesons has been applied to study the contribution of the current quark masses to the $\pi^0\rightarrow\gamma\gamma$ decay width at the next leading order. $2\%$ enhancement has been predicted and there is no new parameter.Comment: 9 page

Systematic Derivation for Quadrature Oscillators Using CCCCTAs

According to 16 nullor-mirror models of the current-controlled current conveyor transconductance amplifier (CCCCTA) and using nodal admittance matrix (NAM) expansion method, three different classes of the double-mode quadrature oscillators employed CCCCTAs and two grounded capacitors are synthesized. The class I oscillators have 32 different forms, the class II oscillators have 16 different forms, and the class III oscillators have four different forms. In all, 52 quadrature oscillators using CCCCTAs are obtained. Having used canonic number of components, the circuits are easy to be integrated and the condition for oscillation and the frequency of oscillation can be tuned by tuning bias currents of the CCCCTAs. The circuit analysis and simulation results have been included to support the generation method

Classification of Arbitrary Multipartite Entangled States under Local Unitary Equivalence

We propose a practical method for finding the canonical forms of arbitrary dimensional multipartite entangled states, either pure or mixed. By extending the technique developed in one of our recent works, the canonical forms for the mixed $N$-partite entangled states are constructed where they have inherited local unitary symmetries from their corresponding $N+1$ pure state counterparts. A systematic scheme to express the local symmetries of the canonical form is also presented, which provides a feasible way of verifying the local unitary equivalence for two multipartite entangled states.Comment: 22 pages; published in J. Phys. A: Math. Theo

Excitation function of nucleon and pion elliptic flow in relativistic heavy-ion collisions

Within a relativistic transport (ART) model for heavy-ion collisions, we show that the recently observed characteristic change from out-of-plane to in-plane elliptic flow of protons in mid-central Au+Au collisions as the incident energy increases is consistent with the calculated results using a stiff nuclear equation of state (K=380 MeV). We have also studied the elliptic flow of pions and the transverse momentum dependence of both the nucleon and pion elliptic flow in order to gain further insight about the collision dynamics.Comment: 8 pages, 2 figure

Integrating clinical data from cross-sectional and longitudinal studies

Clinical trials are typically conducted over a population in order to illuminate certain characteristics of a health issue or disease process. These cross-sectional studies provide a snapshot of these disease processes over a large population but do not allow us to model the temporal nature of disease. Longitudinal studies on the other hand, are used to explore how these processes develop over time but can be expensive and time-consuming, and only cover a relatively small window within the disease process. This paper explores a technique for integrating cross-sectional and longitudinal studies to build models of disease progression

Duration of heart failure and the risk of atrial fibrillation: different mechanisms at different times?

Chronic heart failure increases the risk of atrial fibrillation (AF), with the prevalence of AF paralleling the severity of heart failure.1 Factors that underlie this increased susceptibility to AF may include electrical, structural, and neurohumoral changes.2 In AF, it is recognized that atrial electrophysiological remodelling occurs and contributes to the perpetuation of the arrhythmia, most notably the decrease of effective refractory period (ERP) which predisposes to re-entry by shortening the wavelength. Does heart failure cause similar changes in atrial electrophysiology that predispose to the arrhythmia

Macroeconomics modelling on UK GDP growth by neural computing

This paper presents multilayer neural networks used in UK gross domestic product estimation. These networks are trained by backpropagation and genetic algorithm based methods. Different from backpropagation guided by gradients of the performance, the genetic algorithm directly evaluates the performance of multiple sets of neural networks in parallel and then uses the analysed results to breed new networks that tend to be better suited to the problems in hand. It is shown that this guided evolution leads to globally optimal networks and more accurate results, with less adjustment of the algorithm needed