Nanosensors having dipicolinic acid imprinted nanoshell for Bacillus cereus spores detection

Molecular imprinted polymers (MIPs) as a recognition element for sensors are increasingly of interest and MIP nanoclusters have started to appear in the literature. In this study, we have proposed a novel thiol ligand-capping method with polymerizable methacryloylamido-cysteine (MAC) attached to gold–silver nanoclusters, reminiscent of a self-assembled monolayer and have reconstructed surface shell by synthetic host polymers based on molecular imprinting method for recognition. In this method, methacryloylamidoantipyrine–terbium ((MAAP)₂–Tb(III)) has been used as a new metal-chelating monomer via metal coordination–chelation interactions and dipicolinic acid (DPA) which is main participant of Bacillus cereus spores used as a model. Nanoshell sensors with templates give a cavity that is selective for DPA. The DPA can simultaneously chelate to Tb(III) metal ion and fit into the shape-selective cavity. Thus, the interaction between Tb(III) ion and free coordination spheres has an effect on the binding ability of the gold–silver nanoclusters nanosensor. The binding affinity of the DPA imprinted nanoclusters has been investigated by using the Langmuir and Scatchard methods, and the respective affinity constants (K _affinity) determined were found to be 1.43 × 10⁴ and 9.1 × 10⁶ mol L^?1.     

Spectroscopic characteristics of Sm3+-doped alkali fluorophosphate glasses

Optical absorption, luminescence and lifetime measurements of Sm(3+)-doped alkali fluorophosphate glasses with molar compositions of 50(NaPO(3))(6)+10TeO(2)+20AlF(3)+19RF+1Sm(2)O(3) (R=Li, Na and K) are described. The variation of optical properties with glass composition plays a dominant role in the determination of efficient laser materials. From the experimental oscillator strengths of f-f electric dipole transitions, the phenomenological Judd-Ofelt parameters have been evaluated and are used to evaluate radiative parameters such as radiative transition probabilities (A(R)), branching ratios (beta(R)), lifetimes (tau(R)) and integrated absorption cross-section (sigma(a)) for various excited levels. The predicted values of tau(R) and beta(R) from the (4)G(5/2) excited level to its lower levels are compared with the experimentally measured values. Stimulated emission cross-sections (sigma(e)) were also determined for (4)G(5/2)-->(6)H(J) (J=5/2, 7/2, 9/2 and 11/2) emission transitions. From the emission transitions of Sm(3+) in these alkali tellurofluorophosphate glasses certain potential laser transitions have been identified.     

Flat map areal topography in Macaca mulatta based on combined MRI and histology

Flattened representations are a useful approach to represent the convoluted complex surface of the neocortex of primates and other large-brained mammals. In this study, we compared the flattened representation of neocortical areas obtained from the recently published MRI and histology atlas of the rhesus monkey brain (Saleem KS, Logothetis NK. A combined MRI and histology atlas of the rhesus monkey brain in stereotaxic coordinates. London: Academic; 2007) with other previously published maps. Our results confirm that flat map representations are advantageous due to their ease of use and that current flat maps are well comparable to each other. Some differences arise due to different distinguishing criteria and here too flat maps can help to reveal them.     

Converses of the Jensen inequality derived from the Green functions with applications in information theory

Jensen integral inequality has got much importance regarding their applications in different fields of mathematics. In this paper, two converses of Jensen integral inequality for convex function are obtained. The results are applied to establish converses of Hölder and Hermite-Hadamard inequalities as well. At the end, some useful applications in information theory of the obtained results are given. The idea used in this paper may inculcate further research.     

Minimizing nonsmooth DC functions via successive DC piecewise-affine approximations

We introduce a proximal bundle method for the numerical minimization of a nonsmooth difference-of-convex (DC) function. Exploiting some classic ideas coming from cutting-plane approaches for the convex case, we iteratively build two separate piecewise-affine approximations of the component functions, grouping the corresponding information in two separate bundles. In the bundle of the first component, only information related to points close to the current iterate are maintained, while the second bundle only refers to a global model of the corresponding component function. We combine the two convex piecewise-affine approximations, and generate a DC piecewise-affine model, which can also be seen as the pointwise maximum of several concave piecewise-affine functions. Such a nonconvex model is locally approximated by means of an auxiliary quadratic program, whose solution is used to certify approximate criticality or to generate a descent search-direction, along with a predicted reduction, that is next explored in a line-search setting. To improve the approximation properties at points that are far from the current iterate a supplementary quadratic program is also introduced to generate an alternative more promising search-direction. We discuss the main convergence issues of the line-search based proximal bundle method, and provide computational results on a set of academic benchmark test problems.     

On Hexagonal Structures in Higher Dimensional Theories

We analyze the geometrical background under which many Lie groups relevant to particle physics are endowed with a (possibly multiple) hexagonal structure. There are several groups appearing, either as special holonomy groups on the compactification process from higher dimensions, or as dynamical string gauge groups; this includes groups like SU(2), SU(3), G ₂, Spin(7), O(8) as well as E ₈ and O(32). We emphasize also the relation of these hexagonal structures with the octonion division algebra, as we expect as well eventually some role for octonions in the interpretation of symmetries in High Energy Physics.     

EXPERIMENTAL STUDY OF TURBULENT NATURAL CONVECTION IN A TALL AIR CAVITY

Abstract

This article describes an experimental study of turbulent natural convection in an air cavity with an aspect ratio of 28.6. The study provides data for the velocities and temperatures at a Rayleigh number based on cavity width of 0.83 × 10⁶, which is useful in validating computational and theoretical results. A laser Doppler anemometer was used for velocity measurements, while fine thermocouples were used for temperature measurements. Heal transfer rates and heat losses from the cell are evaluated. Further, the experimental data in the central portion of the tall cavity have been averaged to simulate an antisymmetric, Boussinesq, fully developed flow in an infinitely tall air cavity. Causes of asymmetry of the data, including radiation absorption, are also assessed.     

Current-driven electron drift solitons

The soliton formation by the current-driven drift-like wave is investigated for heavier ion (such as barium) plasma experiments planned to be performed in future. It is pointed out that the sheared flow of electrons can give rise to short scale solitary structures in the presence of stationary heavier ions. The nonlinearity appears due to convective term in the parallel equation of motion and not because of temperature gradient unlike the case of low frequency usual drift wave soliton. This higher frequency drift-like wave requires sheared flow of electrons and not the density gradient to exist.     

Nonsmooth nonconvex optimization approach to clusterwise linear regression problems

Clusterwise regression consists of finding a number of regression functions each approximating a subset of the data. In this paper, a new approach for solving the clusterwise linear regression problems is proposed based on a nonsmooth nonconvex formulation. We present an algorithm for minimizing this nonsmooth nonconvex function. This algorithm incrementally divides the whole data set into groups which can be easily approximated by one linear regression function. A special procedure is introduced to generate a good starting point for solving global optimization problems at each iteration of the incremental algorithm. Such an approach allows one to find global or near global solution to the problem when the data sets are sufficiently dense. The algorithm is compared with the multistart Späth algorithm on several publicly available data sets for regression analysis.