Orbital elements of barium stars formed through a wind accretion scenario

Taking the total angular momentum conservation in place of the tangential momentum conservation, and considering the square and higher power terms of orbital eccentricity e, the changes of orbital elements of binaries are calculated for wind accretion scenario. These new equations are used to quantitatively explain the observed (e,logP) properties of normal G, K giants and barium stars. Our results reflect the evolution from G, K giant binaries to barium binaries, moreover, the barium stars with longer orbital periods P>1600 days may be formed by accreting part of the ejecta from the intrinsic AGB stars through wind accretion scenario.Comment: 7 pages, LaTex, 4 PS figures and 1 table included, accepted for publication in A &

Polarization Induced Switching Effect in Graphene Nanoribbon Edge-Defect Junction

With nonequilibrium Green's function approach combined with density functional theory, we perform an ab initio calculation to investigate transport properties of graphene nanoribbon junctions self-consistently. Tight-binding approximation is applied to model the zigzag graphene nanoribbon (ZGNR) electrodes, and its validity is confirmed by comparison with GAUSSIAN03 PBC calculation of the same system. The origin of abnormal jump points usually appearing in the transmission spectrum is explained with the detailed tight-binding ZGNR band structure. Transport property of an edge defect ZGNR junction is investigated, and the tunable tunneling current can be sensitively controlled by transverse electric fields.Comment: 18 pages, 8 figure

Photon-assisted electron transmission resonance through a quantum well with spin-orbit coupling

Using the effective-mass approximation and Floquet theory, we study the electron transmission over a quantum well in semiconductor heterostructures with Dresselhaus spin-orbit coupling and an applied oscillation field. It is demonstrated by the numerical evaluations that Dresselhaus spin-orbit coupling eliminates the spin degeneracy and leads to the splitting of asymmetric Fano-type resonance peaks in the conductivity. In turn, the splitting of Fano-type resonance induces the spin- polarization-dependent electron-current. The location and line shape of Fano-type resonance can be controlled by adjusting the oscillation frequency and the amplitude of external field as well. These interesting features may be a very useful basis for devising tunable spin filters.Comment: 10pages,4figure

Nuclear β+\beta^+/EC decays in covariant density functional theory and the impact of isoscalar proton-neutron pairing

Self-consistent proton-neutron quasiparticle random phase approximation based on the spherical nonlinear point-coupling relativistic Hartree-Bogoliubov theory is established and used to investigate the $\beta^+$/EC-decay half-lives of neutron-deficient Ar, Ca, Ti, Fe, Ni, Zn, Cd, and Sn isotopes. The isoscalar proton-neutron pairing is found to play an important role in reducing the decay half-lives, which is consistent with the same mechanism in the $\beta$ decays of neutron-rich nuclei. The experimental $\beta^+$/EC-decay half-lives can be well reproduced by a universal isoscalar proton-neutron pairing strength.Comment: 12 pages, 4 figure

Self-consistent relativistic quasiparticle random-phase approximation and its applications to charge-exchange excitations and β\beta-decay half-lives

The self-consistent quasiparticle random-phase approximation (QRPA) approach is formulated in the canonical single-nucleon basis of the relativistic Hatree-Fock-Bogoliubov (RHFB) theory. This approach is applied to study the isobaric analog states (IAS) and Gamov-Teller resonances (GTR) by taking Sn isotopes as examples. It is found that self-consistent treatment of the particle-particle residual interaction is essential to concentrate the IAS in a single peak for open-shell nuclei and the Coulomb exchange term is very important to predict the IAS energies. For the GTR, the isovector pairing can increase the calculated GTR energy, while the isoscalar pairing has an important influence on the low-lying tail of the GT transition. Furthermore, the QRPA approach is employed to predict nuclear $\beta$-decay half-lives. With an isospin-dependent pairing interaction in the isoscalar channel, the RHFB+QRPA approach almost completely reproduces the experimental $\beta$-decay half-lives for nuclei up to the Sn isotopes with half-lives smaller than one second. Large discrepancies are found for the Ni, Zn, and Ge isotopes with neutron number smaller than $50$, as well as the Sn isotopes with neutron number smaller than $82$. The potential reasons for these discrepancies are discussed in detail.Comment: 34 pages, 14 figure

Bidirectional optimization of the melting spinning process

This is the author's accepted manuscript (under the provisional title "Bi-directional optimization of the melting spinning process with an immune-enhanced neural network"). The final published article is available from the link below. Copyright 2014 @ IEEE.A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.National Nature Science Foundation of China, Ministry of Education of China, the Shanghai Committee of Science and Technology), and the Fundamental Research Funds for the Central Universities