Skyrmions and Hall Transport

We derive a generalized set of Ward identities that captures the effects of topological charge on Hall transport. The Ward identities follow from the 2+1 dimensional momentum algebra, which includes a central extension proportional to the topological charge density. In the presence of topological objects like Skyrmions, we observe that the central term leads to a direct relation between the thermal Hall conductivity and the topological charge density. We extend this relation to incorporate the effects of a magnetic field and an electric current. The topological charge density produces a distinct signature in the electric Hall conductivity, which is identified in existing experimental data, and yields further novel predictions. For insulating materials with translation invariance, the Hall viscosity can be directly determined from the Skyrmion density and the thermal Hall conductivity to be measured as a function of momentum.Comment: 6+1 pages including Supplemental Material. Version to appear in Physical Review Letter

Stochastic Formation of Polariton Condensates in Two Degenerate Orbital States

We explore the exciton-polariton condensation in the two degenerate orbital states. In the honeycomb lattice potential, at the third band we have two degenerate vortex-antivortex lattice states at the inequivalent K and K'-points. We have observed energetically degenerate condensates within the linewidth ~ 0.3 meV, and directly measured the vortex-antivortex lattice phase order of the order parameter. We have also observed the intensity anticorrelation between polariton condensates at the K- and K'-points. We relate this intensity anticorrelation to the dynamical feature of polariton condensates induced by the stochastic relaxation from the common particle reservoir.Comment: 5 pages, 4 figure

Algebraic order and the Berezinskii-Kosterlitz-Thouless transition in an exciton-polariton gas

We observe quasi-long range coherence in a two-dimensional condensate of exciton-polaritons. Our measurements are the first to confirm that the spatial correlation algebraically decays with a slow power-law, whose exponent quantitatively behaves as predicted by the Berezinskii-Kosterlitz-Thouless theory. The exciton-polaritons are created by non-resonant optical pumping of a micro-cavity sample with embedded GaAs quantum-wells at liquid helium temperature. Michelson interference is used to measure the coherence of the photons emitted by decaying exciton-polaritons

An evolutionary based features construction methods for data summarization approach

Coral reefs are on course to become the first ecosystem that human activity will eliminate entirely from the Earth, a leading United Nations scientist claims. It is predicted that this event will occur before the end of the present century, which means that there are children already born who will live to see a world without coral. Coral reefs are important for the immense biodiversity of their ecosystems. They contain a quarter of all marine species. This research addresses the question whether a data summarization approach can be utilized to predict the survival of Coral Reefs in Malaysia by identifying the survival factors for these Coral Reefs. A data summarization approach is proposed due to its capability to learn data stored in multiple tables. In other words, this research will discuss the application of genetic algorithm to optimize the feature construction process from the Coral Reefs data to generate input data for the data summarization method called Dynamic Aggregation of Relational Attributes (DARA). The DARA algorithm will be applied to summarize data stored in the non-target tables by clustering them into groups, where multiple records stored in non­target tables correspond to a single record i,tored in a target table. Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. These methods are proposed to improve the descriptive accuracy of the summarized data. In the process of summarizing relational data, a genetic algorithm is also applied and several feature scoring measures are evaluated in order to find the best set of relevant constructed features. In this work, we empirically compare the predictive accuracies of classification tasks based on the proposed feature construction methods and also the existing feature construction methods. The experimental results show that the predictive accuracy of classifying data that are summarized based on VLFCWS method using Total Cluster Entropy combined with Information Gain (CE-JG) as feature scoring outperforms in most cases

An intelligent categorization tool for malay research articles

Unlabeled research articles published in Malay language are becoming increas­ ingly common and available in Malaysia. Thus, the task of manually indexing these research articles is difficult and time consuming. In order to facilitate research activities that depend on research resources written in l\lalay language, these research articles must be categorized or indexed efficiently so that appro­ priate and relevant domains of knowledge can be recommended to researchers in l\falaysia. There are not many researches conducted to efficiently categorize Malay research articles. The task of categorizing Malay research articles is more complex compared to the task of categorizing English research articles due to the complexity of Malay language and thus categorizing Malay research articles represents a major contemporary challenge. Malay text documents are often represented as high-dimensional and sparse vectors, by using Malay words as features, which consist of a few thousand dimensions and a sparsity of 95 to 99% is typical. Determining the appropriate number of categories for large amount of Malay documents is also difficult and time consuming task due to the sparsity of the documents. Related documents may be grouped into different clusters, if there are too many number of categories assigned to these documents. On the other hand, unrelated documents may be clustered into the same cluster, if there are too few number of categories assigned to these documents. This research ad­dresses issues that involve improving several pre-processing processes that affect the performance of the clustering process. These pre-processing processes include stemming, part-of-speech tagging and named-entity recognition. In this work, the effects of improving all these pre-processing processes will be investigated. It is anticipated that by improving the clustering results, it will also improve the mapping of Malay and English clusters obtained from the bilingual clustering. Hence, by increasing the mapping percentage for the bilingual clusters, a more robust clustering algorithm can be developed for clustering bilingual documents. As a result, by increasing the mapping percentage for the bilingual clusters, a more robust clustering algorithm can be developed for clustering bilingual documents. In this study, a genetic algorit.hm {GA) is also proposed to be implemented in order to determine the set of terms that can be used in clustering bilingual documents with more effective

Exploring intentional medication non-adherence in patients with systemic lupus erythematosus: The role of physician-patient interactions

OBJECTIVE: Medication non-adherence contributes to worse health outcomes among SLE patients. The underlying mechanisms that drive medication non-adherence are poorly understood. The purpose of this study was to explore possible mechanisms of medication non-adherence by eliciting patient experiences. METHODS: Consented adult patients with ACR- or SLICC-classified SLE were recruited. Ten semi-structured interviews were conducted across six participants. Interviews were audio recorded, transcribed, and analysed using an iterative process. The findings were presented to an interactive public forum with SLE patients, family members and friends of patients, and health-care professionals to assess validity and for elaboration of the concepts developed. RESULTS: The following three interrelated themes emerged from the interviews. First, why do rheumatologists not know more about lupus or share what they do know with their patients? Second, why do I have to take so many drugs and why do the drugs not work? Third, if my rheumatologist cannot communicate with me, why should I follow the prescribed medication regimen? CONCLUSION: Our exploratory findings lay out a possible underlying logic by which patients might choose intentionally to engage with medication non-adherence behaviours. Patients suggested that poor communication with their rheumatologists along with a lack of validation of their symptoms contributed to them not valuing the recommendations of physicians. This also contributed to development of a cynical outlook and little belief that medication would improve their condition. Although further work is needed to validate these findings, our preliminary work suggests that interventions focusing on the development of communication skills among both patients and rheumatologists are necessary to reduce medication non-adherence