Chiral geometry and rotational structure for 130^{130}Cs in the projected shell model

The projected shell model with configuration mixing for nuclear chirality is developed and applied to the observed rotational bands in the chiral nucleus $^{130}$Cs. For the chiral bands, the energy spectra and electromagnetic transition probabilities are well reproduced. The chiral geometry illustrated in the $K~plot$ and the $azithumal~plot$ is confirmed to be stable against the configuration mixing. The other rotational bands are also described in the same framework

Curie temperature dependence of magnetic properties of CoNi/Pt multilayer films

The Curie temperature of Co1¿xNix/Pt multilayer films (x = 0.5 and 0.6) has been studied as a function of CoNi and Pt layer thicknesses. Magnetic properties at room temperature are dominated by the Curie temperature. Interlayer coupling and interdiffusion are discussed as possible contributions to the thickness dependence of the Curie temperature and magnetic properties

Can Capital Mobility be Destabilizing?

In a standard two-sector neoclassical model with distortions, capital mobility can render the steady state indeterminate, in the sense that there exist infinitely many convergent paths. In the closed economy with no international capital mobility, the utility function must be linear or close to it for indeterminacy to occur, while in the open economy the shape of the utility function makes no difference. The reason is that in the no mobility case changes in aggregate investment must be matched by changes in aggregate consumption, while in the case of full capital mobility they can simply be financed by borrowing abroad. The paper provides some solid theoretical underpinnings to the concerns that de-regulating the capital account may be destabilizing.

Fundamental optical and magneto-optical constants of Co/Pt and CoNi/Pt multilayered films

A study has been made of the optical and magneto-optical properties of several Co/Pt and CoNi/Pt multilayered films that were fabricated by magnetron sputter deposition. Spectroscopic rotating analyzer ellipsometry and Kerr polarimetry were carried out to determine the fundamental optical and magneto-optical constants over the spectral range 320¿860 nm. The constants determined were the complex refractive index and the first-order magneto-optic Voigt parameter. A total of seven films were examined and excellent reproducibility was observed in the measured material constants. These have been used to discuss the spectral dependence of the figure-of-merit, for each material, associated with the detection of the polar Kerr effect

Heterogeneous network analysis on academic collaboration networks

University of Technology Sydney. Faculty of Engineering and Information Technology.Heterogeneous networks are a type of complex network model which can have multi-type objects and relationships. Nowadays, research on heterogeneous networks has been increasingly attracting interest because these networks are more advantageous in modeling real-world situations than traditional networks, that is homogenous networks, that can only have one type of object and relationship. For example, the network of Facebook has vertices including photographs, companies, movies, news and messages and different relationships among these objects. Besides that, heterogeneous networks are especially useful for representing complex abstract concepts, such as friendship and academic collaboration. Because these concepts are hard to measure directly, heterogeneous networks are able to represent these abstract concepts by concrete and measurable objects and relationships. Because of these features, heterogeneous networks are applied in many areas including social networks, the World Wide Web, research publication networks and so on. This motivates the thesis to work on network analysis in the context of heterogeneous networks. In the past, homogeneous networks were the research focus of network analysis and therefore many methods proposed by previous studies for social network analysis were designed for homogenous networks. Although heterogeneous networks can be considered as an extension of homogenous networks, most of these methods are not applicable on heterogeneous networks because these methods can only address one type of object and relationships instead of dealing with multi-type ones. In network analysis, there are three basic problems including community detection, link prediction and object ranking. These three questions are the basis of many practical questions, such as network structure extraction, recommendation systems and search engines. Community detection, also called clustering, aims to find the community structure of a network including subgroups of vertices that are closely related, which can facilitate people to understand the structure of networks. Link prediction is a task for finding links which are currently non-existent in networks but may appear in the future. Object ranking can be viewed as an object evaluation task which aims to order a set of objects based on their importance, relevance, or other user defined criteria. In addition to these three research issues, approaches for determining the number of clusters a priori is also important because it can improve the quality of community detection significantly. This thesis works on heterogeneous network and proposes a set of methods to address the four main research problems in network analysis including community detection, determining the number of clusters, link prediction and object ranking. There are four contributions in this thesis. Contribution 1 proposes a Multiple Semantic-path Clustering method which can facilitate users to achieve a desired clustering in heterogeneous networks. Contribution 2 develops a Leader Detection and Grouping Clustering method which can determine the number of clusters a priori, thereby improving the quality of clustering. Contribution 3 introduces a Network Evolution-based Link Prediction method which can improve link prediction accuracy by modeling evolution patterns of objects. Contribution 4 proposes a co-ranking method which can work on complex bipartite heterogeneous networks where one type of vertex can connect to themselves directly and indirectly. The performance of all developed methods in the thesis in terms of clustering quality, link prediction accuracy and ranking effectiveness, is evaluated in the context of a research management dataset of University of Technology, Sydney (UTS) and public bibliographic DBLP (DataBase systems and Logic Programming) dataset. Moreover, all the results of the proposed methods in this thesis are compared with state-of-the-art methods and these experimental results suggest that the proposed methods outperform these state-of-the-art methods in quantitative and qualitative analysis