Dark Supersymmetry

We propose a model of Dark Supersymmetry, where a supersymmetric dark sector is coupled to the classically scale invariant non-supersymmetric Standard Model through the Higgs portal. The dark sector contains a mass scale that is protected against radiative corrections by supersymmetry, and the portal coupling mediates this scale to the Standard Model, resulting in a vacuum expectation value for the Higgs field and the usual electroweak symmetry breaking mechanism. The supersymmetric dark sector contains dark matter candidates, and we show that the observed dark matter abundance is generated for a natural choice of parameters, while avoiding the current experimental bounds on direct detection. Future experiments can probe this scenario if the dark sector mass scale is not too high.     

Structural study of TiO2 thin films by micro-Raman spectroscopy

The Raman spectroscopy method was used for structural characterization of TiO₂ thin films prepared by atomic layer deposition (ALD) and pulsed laser deposition (PLD) on fused silica and single-crystal silicon and sapphire substrates. Using ALD, anatase thin films were grown on silica and silicon substrates at temperatures 125–425 °C. At higher deposition temperatures, mixed anatase and rutile phases grew on these substrates. Post-growth annealing resulted in anatase-to-rutile phase transitions at 750 °C in the case of pure anatase films. The films that contained chlorine residues and were amorphous in their as-grown stage transformed into anatase phase at 400 °C and retained this phase even after annealing at 900 °C. On single crystal sapphire substrates, phase-pure rutile films were obtained by ALD at 425 °C and higher temperatures without additional annealing. Thin films that predominantly contained brookite phase were grown by PLD on silica substrates using rutile as a starting material.     

On some topological properties of numerical algorithms

A result quantity in a numerical algorithm is considered as a function of the input data, roundoff and truncation errors. In order to investigate this functional relationship using the methods of mathematical analysis a structural model of the numerical algorithm calledR-automaton is introduced. It is shown that the functional dependence defined by anR-automaton is a continuous rational function in a neighborhood of any data point except in a point set, the Lebesgue measure of which is zero. An effective general-purpose algorithm is presented to compute the derivative of any result quantity with respect to the individual roundoff and truncation errors. Some ways of generalizing theR-automation model without losing the results achieved are finally suggested.     

A theoretical study of filter cake washing

A problem on filter cake washing assuming a geometrical model of the pore spaces, in which axial dispersion occurs in the flow channel and mass transfer through a resistance is taking place from the cross channels to the flow channel, is solved by deriving the differential equations and the auxiliary conditions corresponding to the geometrical model and solving the mathematical problem utilizing the Laplace transform and a method for its numerical inversion that utilizes positive values of the transform variable. The numerical results are checked by comparison with asymptotic expansions and by recalculating the results utilizing other values of the transform variable. The results are presented both numerically with four significant figures and graphically.     

A regression technique to analyze the second-order nonlinear optical response of thin films

We present a new technique, based on regression analysis, to determine the second-order nonlinear optical susceptibility tensor of thin films. The technique does not require the absolute levels or phases of measured signals to be mutually calibrated. In addition it yields indicators that address the quality of theoretical models describing the sample. We use the technique to determine the susceptibility tensor of samples of a nonracemic chiral material which have very low symmetry (both chiral and anisotropic) and have many independent tensor components. The results show the importance of using detailed theoretical models that account for the linear optical properties of the sample.     

Parallelized Bayesian inversion for three-dimensional dental X-ray imaging

Diagnostic and operational tasks based on dental radiology often require three-dimensional (3-D) information that is not available in a single X-ray projection image. Comprehensive 3-D information about tissues can be obtained by computerized tomography (CT) imaging. However, in dental imaging a conventional CT scan may not be available or practical because of high radiation dose, low-resolution or the cost of the CT scanner equipment. In this paper, we consider a novel type of 3-D imaging modality for dental radiology. We consider situations in which projection images of the teeth are taken from a few sparsely distributed projection directions using the dentist's regular (digital) X-ray equipment and the 3-D X-ray attenuation function is reconstructed. A complication in these experiments is that the reconstruction of the 3-D structure based on a few projection images becomes an ill-posed inverse problem. Bayesian inversion is a well suited framework for reconstruction from such incomplete data. In Bayesian inversion, the ill-posed reconstruction problem is formulated in a well-posed probabilistic form in which a priori information is used to compensate for the incomplete information of the projection data. In this paper we propose a Bayesian method for 3-D reconstruction in dental radiology. The method is partially based on Kolehmainen et al. 2003. The prior model for dental structures consist of a weighted /spl lscr//sup 1/ and total variation (TV)-prior together with the positivity prior. The inverse problem is stated as finding the maximum a posteriori (MAP) estimate. To make the 3-D reconstruction computationally feasible, a parallelized version of an optimization algorithm is implemented for a Beowulf cluster computer. The method is tested with projection data from dental specimens and patient data. Tomosynthetic reconstructions are given as reference for the proposed method.     

Conformational fluctuations affect protein alignment in dilute liquid crystal media

The discovery of dilute liquid crystalline media to align biological macromolecules has opened many new possibilities to study protein and nucleic acid structures by NMR spectroscopy. We inspect the basic alignment phenomenon for an ensemble of protein conformations to deduce relative contributions of each member to the residual dipolar coupling signals. We find that molecular fluctuations can affect the alignment and discover a resulting emphasis of certain conformations. However, the internal fluctuations are largely uncorrelated with those of the alignment, implying that proteins have liquidlike molecular surfaces. Furthermore, we consider the implications of a dynamic bias to structure determination using data from the weak alignment method.     

Size-controlled aerosol synthesis of silver nanoparticles for plasmonic materials

Aerosol techniques were used to synthesize spherical and monodisperse silver nanoparticles for plasmonic materials. The particles were generated with an evaporation-condensation technique followed by size selection and sintering with a differential mobility analyzer and a tube furnace, respectively. Finally, the nanoparticles were collected on a glass substrate with an electrostatic precipitator. The particle size distributions were measured with a scanning mobility particle sizer and verified with a transmission electron microscope. A spectrophotometer was used to measure the optical extinction spectra of the prepared samples, which contained particles with diameters of approximately 50, 90 and 130?nm. By controlling the particle size, the dipolar peak of the localized surface plasmon resonance was tuned between wavelengths of 398 and 448?nm. In addition, quadrupolar resonances were observed at shorter wavelengths as predicted by the simplified theoretical model used to characterize the measured spectra.