Competition between the BCS superconductivity and ferromagnetic spin fluctuations in MgCNi3_3

The low temperature specific heat of the superconductor MgCNi$_3$ and a non-superconductor MgC$_{0.85}$Ni$_3$ is investigated in detail. An additional contribution is observed from the data of MgCNi$_3$ but absent in MgC$_{0.85}$Ni$_3$, which is demonstrated to be insensitive to the applied magnetic field even up to 12 Tesla. A detailed discussion on its origin is then presented. By subtracting this additional contribution, the zero field specific heat of MgCNi$_3$ can be well described by the BCS theory with the gap ratio ($\Delta/k_BT_c$) determined by the previous tunneling measurements. The conventional s-wave pairing state is further proved by the magnetic field dependence of the specific heat at low temperatures and the behavior of the upper critical field.Comment: To appear in Physical Review B, 6 pages, 7 figure

Evidence for s-wave pairing from measurement on lower critical field in MgCNi3MgCNi_3

Magnetization measurements in the low field region have been carefully performed on a well-shaped cylindrical and an ellipsoidal sample of superconductor $MgCNi_3$. Data from both samples show almost the same results. The lower critical field $H_{c1}$ and the London penetration depth $\lambda$ are thus derived. It is found that the result of normalized superfluid density $\lambda^2(0)/\lambda^2(T)$ of $MgCNi_3$ can be well described by BCS prediction with the expectation for an isotropic s-wave superconductivity.Comment: To appear in Phys. Rev.

An accurate Vehicle Gasohol delivery system

Author name used in this publication: Zhan-gang YangVersion of RecordPublishe

Social learning approach in designing persuasive e-commerce recommender system model

Intention to purchase in existing online business practice is learned through observation of information display by online seller. The emergent growth of persuasive technologies currently holds a great potential in driving a positive influence towards consumer purchase behavior. But to date, there is still limited research on implementing persuasion concept into the recommender system context. Drawing upon the principle design of persuasive system, the main purpose of this study is to explore social learning advantages in creating persuasive features for E-Commerce recommender system. Based on Social Cognitive Theory, the influence of personal and environmental factors will be examined in measuring consumer purchase intention. In addition, dimensions of social learning environment are represented by observational learning theory and cognitive learning theory. From those reviews, this study assumed that social learning environment can be created based on attentiveness, retentiveness, motivational, knowledge awareness and interest evaluation cues of consumer learning factors. Furthermore, the persuasive environment of recommender system is assumed to have positive influence towards individual characteristics such as self-efficacy behavior, perceived task complexity and confused by over choice. Findings from those reviews have contributed to the development of a research model in visualizing social learning environment that can be used to develop a persuasive recommender system in E-Commerce and hence measures the impact towards consumer purchase intention

Correlations among superconductivity, structural instability, and band filling in Nb1-xB2 at the critical point x=0.2

We performed an extensive investigation on the correlations among superconductivity, structural instability and band filling in Nb1-xB2 materials. Structural measurements reveal that a notable phase transformation occurs at x=0.2, corresponding to the Fermi level (EF) in the pseudogap with the minimum total density of states (DOS) as demonstrated by the first-principles calculations. Superconductivity in Nb1-xB2 generally becomes visible in the Nb-deficient materials with x=0.2. Electron energy-loss spectroscopy (EELS) measurements on B K-edge directly demonstrated the presence of a chemical shift arising from the structural transformation. Our systematical experimental results in combination with theoretical analysis suggest that the emergence of hole states in the sigma-bands plays an important role for understanding the superconductivity and structural transition in Nb1-xB2.Comment: 16 pages, 4 figure

Partner selection in agile supply chains: A fuzzy intelligent approach

Partner selection is a fundamental issue in supply chain management as it contributes significantly to overall supply chain performance. However, such decision-making is problematic due to the need to consider both tangible and intangible factors, which cause vagueness, ambiguity and complexity. This paper proposes a new fuzzy intelligent approach for partner selection in agile supply chains by using fuzzy set theory in combination with radial basis function artificial neural network. Using these two approaches in combination enables the model to classify potential partners in the qualification phase of partner selection efficiently and effectively using very large amounts of both qualitative and quantitative data. The paper includes a worked empirical application of the model with data from 84 representative companies within the Chinese electrical components and equipment industry, to demonstrate its suitability for helping organisational decision-makers in partner selection

Integrated methodology for supplier selection: the case of a sphygmomanometer manufacturer in Taiwan

Supplier selection is a critical multi-criterion decision-making activity for suc- cessful supply chain management. This study involved developing an integrated supplier selection methodology, which is constructed using analytic network process, data envelop- ment analysis, and multiple objective particle swarm optimization. The proposed integrated methodology can account for multiple supplier selection criteria and set boundaries on weight value for multiple objective data envelopment analysis inputs and outputs. To solve the data envelopment analysis model, a new algorithm based on multiple objective particle swarm optimization is introduced, which embeds with tabu list and group mechanisms, and then, it is found to be superior to the compared algorithms in solving performance on three test functions and the illustrative case. In addition, the proposed integrated method- ology was applied to a supplier selection problem of sphygmomanometer manufacturer in Taiwan to verify its applicability of decision-making process. The results show that the methodology can be implemented as an effective decision aid for supplier selection under multiple criteria with weight restrictions