Asymptotic analysis and spectrum of three anyons

The spectrum of anyons confined in harmonic oscillator potential shows both linear and nonlinear dependence on the statistical parameter. While the existence of exact linear solutions have been shown analytically, the nonlinear dependence has been arrived at by numerical and/or perturbative methods. We develop a method which shows the possibility of nonlinearly interpolating spectrum. To be specific we analyse the eigenvalue equation in various asymptotic regions for the three anyon problem.Comment: 28 pages, LaTeX, 2 Figure

Analytical Solution for MHD Casson Fluid Flow Past a Porous Linearly Stretching Surface with Wall Mass Transfer

In this analysis, MHD Casson fluid flow past a porous linearly stretching surface with wall mass transfer is studied. Using similarity transformations, the governing equations are converted to an ordinary differential equation and then solved analytically. The fluid velocity and skin friction coefficient are obtained. Our analysis reveals that the effect of increasing Casson parameter and porosity parameter is to suppress the velocity field. Keywords: Casson fluid; Stretching surface; MHD

MHD Poiseuille Flow of a Jeffrey Fluid over a Deformable Porous Layer

Poiseuille flow of a conducting Jeffrey fluid in a channel is investigated. The channel is bounded below by a finite deformable porous layer and bounded above by a stationary plate. The governing equations are solved in the free flow and porous flow regions. The expressions for the velocity field and solid displacement are obtained. The effects of the Jeffrey parameter, magnetic field parameter, viscosity parameter, the volume fraction component of the fluid on the flow velocity, displacement, mass flux and shear stress are discussed. It is found that the velocity increases with the increase in the non-Newtonian Jeffrey parameter whereas the velocity decreases with the increase in the magnetic field parameter. Keywords: MHD; Poiseuille flow; Jeffrey fluid; Porous layer; permeable bed

Dental fear in children and its relation to dental caries and gingival condition – a cross sectional study in Bangalore City, India.

Aims and objectives: The aim of this study was to determine the levels of dental fear, and its association with dental caries and gingivitis among 12 – 15 year old government high school children in Bangalore City, India. Methods: Eight government high schools were selected by simple random method from the 2 zones of Bangalore City. All the children who participated in this study were asked the single item Dental Anxiety Question to assess the dental fear and underwent oral examination for dental caries and gingivitis using decayed, missing and filled teeth (DMFT) index and Community Periodontal Index (CPI), respectively. Results: The prevalence of high dental fear among the study population was 23.4%. The mean MT was significantly associated with high fear. Highly significant correlation was found between presence of bleeding on gentle probing and high dental fear. Conclusion: High dental fear plays an important role in the oral health status of 12 to 15 year old children.&nbsp

Mhd Stagnation Point Flow of a Jeffrey Fluid Over a Stretching/Shrinking Sheet through Porous Medium

In this analysis the MHD stagnation point flow of Jeffrey fluid over a stretching/shrinking sheet through porous medium is studied. The governing partial differential equations are transformed into nonlinear ordinary differential equation using the similarity transformations and are solved shooting technique. The effects of governing parameters on the velocity, the temperature and the concentration while the skin friction coefficients, the rate of heat transfer are studied graphically. Keywords: MHD; Jeffrey fluid, stretching/shrinking sheet, Porous medium

A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders

Zero shot learning in Image Classification refers to the setting where images from some novel classes are absent in the training data but other information such as natural language descriptions or attribute vectors of the classes are available. This setting is important in the real world since one may not be able to obtain images of all the possible classes at training. While previous approaches have tried to model the relationship between the class attribute space and the image space via some kind of a transfer function in order to model the image space correspondingly to an unseen class, we take a different approach and try to generate the samples from the given attributes, using a conditional variational autoencoder, and use the generated samples for classification of the unseen classes. By extensive testing on four benchmark datasets, we show that our model outperforms the state of the art, particularly in the more realistic generalized setting, where the training classes can also appear at the test time along with the novel classes