Analytic expressions for alpha particle preformation in heavy nuclei

Experimental alpha decay energies and half-lives are investigated systematically to extract alpha particle preformation in heavy nuclei. Formulas for the preformation factors are proposed that can be used to guide microscopic studies on preformation factors and perform accurate calculations of the alpha decay half-lives. There is little evidence for the existence of an island of long stability of superheavy nuclei.

Coherent classical-path description of deep tunneling

A central challenge to the semiclassical description of quantum mechanics is the quantum phenomenon of "deep" tunneling. Here we show that real time classical trajectories suffice to account correctly even for deep quantum tunneling, using a recently formulated semiclassical initial value representation series of the quantum propagator and a prefactor free semiclassical propagator. Deep quantum tunneling is effected through what we term as coherent classical paths which are composed of one or more classical trajectories that lead from reactant to product but are discontinuous along the way. The end and initial phase space points of consecutive classical trajectories contributing to the coherent path are close to each other in the sense that the distance between them is weighted by a coherent state overlap matrix element. Results are presented for thermal and energy dependent tunneling through a symmetric Eckart barrier.

Fast Haar Transform Based Feature Extraction for Face Representation and Recognition

Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications and additions, which makes the projection process computationally expensive. To tackle this problem, this paper proposes two simple-but-effective fast subspace learning and image projection methods, fast Haar transform (FHT) based principal component analysis and FHT based spectral regression discriminant analysis. The advantages of these two methods result from employing both the FHT for subspace learning and the integral vector for feature extraction. Experimental results on three face databases demonstrated their effectiveness and efficiency.

Graphical representation and the similarity of DNA primary sequences

In this article, graphical representations of DNA primary sequences were generated. Topological indices and molecular connectivity indices were calculated and used for the comparison of similarities among eight different DNA segments. The satisfactory results were achieved by this analysis.

Theoretical representation of shear and pressure influence on the phase separation behavior of PVME/PS mixture

In the framework of lattice fluid model, the Gibbs energy and equation of state are derived by introducing the energy (E-s) stored during flow for polymer blends under shear. From the calculation of the spinodal of poly(vinyl methyl ether) (PVME) and polystyrene (PS) mixtures, we have found the influence of E., an equation of state in pure component is inappreciable, but it is appreciable in the mixture. However, the effect of E, on phase separation behavior is extremely striking. In the calculation of spinodal for the PVME/PS system, a thin, long and banana miscibility gap generated by shear is seen beside the miscibility gap with lower critical solution temperature. Meanwhile, a binodal coalescence of upper and lower miscibility gaps is occurred. The three points of the three-phase equilibrium are forecasted. The shear rate dependence of cloud point temperature at a certain composition is discussed. The calculated results are acceptable compared with the experiment values obtained by Higgins et at. However, the maximum positive shift and the minimum negative shift of cloud point temperature guessed by Higgins are not obtained, Furthermore, the combining effects of pressure and shear on spinodal shift are predicted.

Representation of microscale ocean wavenumber spectrum correct to the second order

In this paper, the analytical representations of four wave source functions in high-frequency spectrum range are given on the basis of ocean wave theory and dimensional analysis, and the perturbation method is used to solve the governing equations of ocean wave high-frequency spectrum on the basis of the temporally stationary and locally homogeneous scale relations of microscale wave. The microscale ocean wavenumber spectrum correct to the second order has an explicit structure, its first order part represents the equilibrium between different source functions, and its second order part represents the contribution of microscale wave propagation.

An application of the analytic hierarchy process and fuzzy logic inference in a decision support system for forage selection

Forage selection plays a prominent role in the process of returning cultivated lands back into grasslands. The conventional method of selecting forage species can only provide attempts for problem-solving without considering the relationships among the decision factors globally. Therefore, this study is dedicated to developing a decision support system to help farmers correctly select suitable forage species for the target sites. After collecting data through a field study, we developed this decision support system. It consists of three steps: (1) the analytic hierarchy process (AHP), (2) weights determination, and (3) decision making. In the first step, six factors influencing forage growth were selected by reviewing the related references and by interviewing experts. Then a fuzzy matrix was devised to determine the weight of each factor in the second step. Finally, a gradual alternative decision support system was created to help farmers choose suitable forage species for their lands in the third step. The results showed that the AHP and fuzzy logic are useful for forage selection decision making, and the proposed system can provide accurate results in a certain area (Gansu Province) of China.

不同学习策略对改变学生物理要领错误的影响

In the field of misconceptions research, previous research was focused mainly on the effect of naive concepts on the learning of scientific concept. In this study, from the viewpoint of declarative and procedural knowledge, conceptual errors on Newtonian mechanics were studied comparatively between high-performance and low-performance students. Furthermore, the effects of self-explain learning strategies and reflective learning on the change of subjects' conceptual errors were explored. The result of experiments indicated: 1. There was significant difference in the number of conceptual errors of declarative and procedural knowledge between high-performance students and low-performance students. And Low-performance students made more conceptual errors of procedural knowledge than that of declarative knowledge. For high-performance students, there was no distinct difference between these two kinds of errors. 2. In the distribution of conceptual errors, most errors of declarative knowledge were mainly focused on the understanding of concepts of friction and acceleration. The errors of procedure knowledge most errors concentrated on the judgment of vector direction and the conceptual understanding. 3. Compared with high-performance students, the representation of conceptual declarative knowledge of low-performance students is less complex, more concrete and context bound. 4. The comparative analysis of problem-solving strategies showed: high-performance students preferred to apply analytic strategy, solving problems based on physical concepts and principles; low-performance students preferred to use context strategy, solving problem according to the literal meaning of problems, subjective and groundless presumption and wrong concepts and principles. 5. Self-explain strategies can help students correct their conceptual errors effectively. Reflective learning could help students to correct the concept errors in some degree, but the distinct effect was not observed.