Volume integrals associated with the inhomogeneous Helmholtz equation. Part 1: Ellipsoidal region

Problems of wave phenomena in fields of acoustics, electromagnetics and elasticity are often reduced to an integration of the inhomogeneous Helmholtz equation. Results are presented for volume integrals associated with the Helmholtz operator, nabla(2) to alpha(2), for the case of an ellipsoidal region. By using appropriate Taylor series expansions and multinomial theorem, these volume integrals are obtained in series form for regions r 4' and r r', where r and r' are distances from the origin to the point of observation and source, respectively. Derivatives of these integrals are easily evaluated. When the wave number approaches zero, the results reduce directly to the potentials of variable densities

Local Spin Susceptibility of the S=1/2 Kagome Lattice in ZnCu3(OD)6Cl2

We report single-crystal 2-D NMR investigation of the nearly ideal spin S=1/2 kagome lattice ZnCu3(OD)6Cl2. We successfully identify 2-D NMR signals originating from the nearest-neighbors of Cu2+ defects occupying Zn sites. From the 2-D Knight shift measurements, we demonstrate that weakly interacting Cu2+ spins at these defects cause the large Curie-Weiss enhancement toward T=0 commonly observed in the bulk susceptibility data. We estimate the intrinsic spin susceptibility of the kagome planes by subtracting defect contributions, and explore several scenarios.Comment: 4 figures; published in PR-B Rapid Communication

Transductive Multi-View Zero-Shot Learning

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Learning Multimodal Latent Attributes

Abstract—The rapid development of social media sharing has created a huge demand for automatic media classification and annotation techniques. Attribute learning has emerged as a promising paradigm for bridging the semantic gap and addressing data sparsity via transferring attribute knowledge in object recognition and relatively simple action classification. In this paper, we address the task of attribute learning for understanding multimedia data with sparse and incomplete labels. In particular we focus on videos of social group activities, which are particularly challenging and topical examples of this task because of their multi-modal content and complex and unstructured nature relative to the density of annotations. To solve this problem, we (1) introduce a concept of semi-latent attribute space, expressing user-defined and latent attributes in a unified framework, and (2) propose a novel scalable probabilistic topic model for learning multi-modal semi-latent attributes, which dramatically reduces requirements for an exhaustive accurate attribute ontology and expensive annotation effort. We show that our framework is able to exploit latent attributes to outperform contemporary approaches for addressing a variety of realistic multimedia sparse data learning tasks including: multi-task learning, learning with label noise, N-shot transfer learning and importantly zero-shot learning

Observation of Zeeman effect in topological surface state with distinct material dependence

The helical Dirac fermions on the surface of topological insulators host novel relativistic quantum phenomena in solids. Manipulating spins of topological surface state (TSS) represents an essential step towards exploring the theoretically predicted exotic states related to time reversal symmetry (TRS) breaking via magnetism or magnetic field. Understanding Zeeman effect of TSS and determining its g-factor are pivotal for such manipulations in the latter form of TRS breaking. Here, we report those direct experimental observations in Bi2Se3 and Sb2Te2Se by spectroscopic imaging scanning tunneling microscopy. The Zeeman shifting of zero mode Landau level is identified unambiguously by judiciously excluding the extrinsic influences associated with the non-linearity in the TSS band dispersion and the spatially varying potential. The g-factors of TSS in Bi2Se3 and Sb2Te2Se are determined to be 18 and -6, respectively. This remarkable material dependence opens a new route to control the spins in the TSS.Comment: main text: 17 pages, 4 figures; supplementary: 15 pages, 7 figure

A Method for Reducing the Severity of Epidemics by Allocating Vaccines According to Centrality

One long-standing question in epidemiological research is how best to allocate limited amounts of vaccine or similar preventative measures in order to minimize the severity of an epidemic. Much of the literature on the problem of vaccine allocation has focused on influenza epidemics and used mathematical models of epidemic spread to determine the effectiveness of proposed methods. Our work applies computational models of epidemics to the problem of geographically allocating a limited number of vaccines within several Texas counties. We developed a graph-based, stochastic model for epidemics that is based on the SEIR model, and tested vaccine allocation methods based on multiple centrality measures. This approach provides an alternative method for addressing the vaccine allocation problem, which can be combined with more conventional approaches to yield more effective epidemic suppression strategies. We found that allocation methods based on in-degree and inverse betweenness centralities tended to be the most effective at containing epidemics.Comment: 10 pages, accepted to ACM BCB 201

Spatially resolved characterization of InGaAs/GaAs quantum dot structures by scanning spreading resistance microscopy

Cross-sectional scanning spreading resistance microscopy (SSRM) is used to investigate stacked InGaAs/GaAs quantum dot(QD)structures with different doping schemes. Spatially resolved imaging of the QDs by SSRM is demonstrated. The SSRM contrast obtained for the QD layers is found to depend on doping in the structure. In the undoped structures both QD-layers and QDs within the layers could be resolved, while in the dopedstructures the QD layers appear more or less uniformly broadened. The origin of the SSRM contrast in the QD layer in the different samples is discussed and correlated with doping schemes.T. Hakkarainen, O. Douhéret, and S. Anand would like to acknowledge the Swedish Research Council VR for fi- nancial support and the Kurt-Alice Wallenberg KAW foundation for financing the microscope. L. Fu, H. H. Tan, and C. Jagadish would like to acknowledge the Australian Research Council ARC for financial support and Australian National Fabrication Facility ANFF for access to the facilities

Phase properties of hypergeometric states and negative hypergeometric states

We show that the three quantum states (P$\acute{o}$lya states, the generalized non-classical states related to Hahn polynomials and negative hypergeometric states) introduced recently as intermediates states which interpolate between the binomial states and negative binomial states are essentially identical. By using the Hermitial-phase-operator formalism, the phase properties of the hypergeometric states and negative hypergeometric states are studied in detail. We find that the number of peaks of phase probability distribution is one for the hypergeometric states and $M$ for the negative hypergeometric states.Comment: 7 pages, 4 figure